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Transaction processing is of growing importance for mobile computing. Booking tickets, flight reservation, banking, ePayment, and booking holiday arrangements are just a few examples for mobile transactions. Due to temporarily disconnected situations the synchronisation and consistent transaction processing are key issues. Serializability is a too strong criteria for correctness when the semantics of a transaction is known. We introduce a transaction model that allows higher concurrency for a certain class of transactions defined by its semantic. The transaction results are ”escrow serializable” and the synchronisation mechanism is non-blocking. Experimental implementation showed higher concurrency, transaction throughput, and less resources used than common locking or optimistic protocols.
Modern web-based applications are often built as multi-tier architecture using persistence middleware. Middleware technology providers recommend the use of Optimistic Concurrency Control (OCC) mechanism to avoid the risk of blocked resources. However, most vendors of relational database management systems implement only locking schemes for concurrency control. As consequence a kind of OCC has to be implemented at client or middleware side.
A simple Row Version Verification (RVV) mechanism has been proposed to implement an OCC at client side. For performance reasons the middleware uses buffers (cache) of its own to avoid network traffic and possible disk I/O. This caching however complicates the use of RVV because the data in the middleware cache may be stale (outdated). We investigate various data access technologies, including the new Java Persistence API (JPA) and Microsoft’s LINQ technologies for their ability to use the RVV programming discipline.
The use of persistence middleware that tries to relieve the programmer from the low level transaction programming turns out to even complicate the situation in some cases.Programmed examples show how to use SQL data access patterns to solve the problem.
In this presentation the audience will be: (a) introduced to the aims and objectives of the DBTechNet initiative, (b) briefed on the DBTech EXT virtual laboratory workshops (VLW), i.e. the educational and training (E&T) content which is freely available over the internet and includes vendor-neutral hands-on laboratory training sessions on key database technology topics, and (c) informed on some of the practical problems encountered and the way they have been addressed. Last but not least, the audience will be invited to consider incorporating some or all of the DBTech EXT VLW content into their higher education (HE), vocational education and training (VET), and/or lifelong learning/training type course curricula. This will come at no cost and no commitment on behalf of the teacher/trainer; the latter is only expected to provide his/her feedback on the pedagogical value and the quality of the E&T content received/used.
Relationship Marketing (RM) presumes trust as an important antecedent for the performance of interfirm relationships. Current research is dominated by an interpersonal perspective. In this research tack, trust chiefly emerges as a result of interpersonal relationships. But multiple risks arise if customer trust rests solely on elements inextricably linked to single representatives. Hence, this paper evaluates the impact of organizational capabilities and the moderating role of customer preferences on the trust creation process. The framework presented here is tested cross-industry on 220 customers for IT solutions. The results offer significant insight into the effectiveness of individual and organizational RM strategies.
This work presents a disconnected transaction model able to cope with the increased complexity of longliving, hierarchically structured, and disconnected transactions. Wecombine an Open and Closed Nested Transaction Model with Optimistic Concurrency Control and interrelate flat transactions with the aforementioned complex nature. Despite temporary inconsistencies during a transaction’s execution our model ensures consistency.
Suppliers need to improve their relational capabilities if they are to enhance customer trust. Debate about such capabilities is dominated by an interpersonal approach. This paper provieds novel marketing options by expanding insights into alternative types of relational capabilities. Furthermore, the moderating role of customer preferences on the effectiveness of relational capabilities is evaluated.
The Third International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2011) held on January 23-27, 2011 in St. Maarten, The Netherlands Antilles, continued a series of international events covering a large spectrum of topics related to advances in fundamentals on databases, evolution of relation between databases and other domains, data base technologies and content processing, as well as specifics in applications domains databases. Advances in different technologies and domains related to databases triggered substantial improvements for content processing, information indexing, and data, process and knowledge mining. The push came from Web services, artificial intelligence, and agent technologies, as well as from the generalization of the XML adoption. High-speed communications and computations, large storage capacities, and load-balancing for distributed databases access allow new approaches for content processing with incomplete patterns, advanced ranking algorithms and advanced indexing methods. Evolution on e-business, ehealth and telemedicine, bioinformatics, finance and marketing, geographical positioning systems put pressure on database communities to push the ‘de facto’ methods to support new requirements in terms of scalability, privacy, performance, indexing, and heterogeneity of both content and technology. We take this opportunity to thank all the members of the DBKDA 2011 Technical Program Committee as well as the numerous reviewers. The creation of such a broad and high-quality conference program would not have been possible without their involvement. We also kindly thank all the authors who dedicated much of their time and efforts to contribute to the DBKDA 2011. We truly believe that, thanks to all these efforts, the final conference program consists of top quality contributions. This event could also not have been a reality without the support of many individuals, organizations, and sponsors. We are grateful to the members of the DBKDA 2011 organizing committee for their help in handling the logistics and for their work to make this professional meeting a success. We hope that DBKDA 2011 was a successful international forum for the exchange of ideas and results between academia and industry and for the promotion of progress in database research. We are convinced that the participants found the event useful and communications very open. The beautiful places of St. Maarten surely provided a pleasant environment during the conference and we hope you had a chance to visit the surroundings.
Redirected walking techniques allow people to walk in a larger virtual space than the physical extents of the laboratory. We describe two experiments conducted to investigate human sensitivity to walking on a curved path and to validate a new redirected walking technique. In a psychophysical experiment, we found that sensitivity to walking on a curved path was significantly lower for slower walking speeds (radius of 10 meters versus 22 meters). In an applied study, we investigated the influence of a velocity-dependent dynamic gain controller and an avatar controller on the average distance that participants were able to freely walk before needing to be reoriented. The mean walked distance was significantly greater in the dynamic gain controller condition, as compared to the static controller (22 meters versus 15 meters). Our results demonstrate that perceptually motivated dynamic redirected walking techniques, in combination with reorientation techniques, allow for unaided exploration of a large virtual city model.
Turning complainers into fans : towards a framework for customer services in social media channels
(2012)
In recent years, marketing scholars have invested heavily in exploring the role of social media in marketing theory and practice. One valuable strategy for using social media in marketing communication is to provide customer services in applications like Facebook or Twitter. This paper evaluates a) the concept of perceived service quality in different service channels and b) the impact customer service strategies have on customer loyalty, word of mouth communication, and cross-sell preferences. The framework presented here is tested cross-channel against data collected from the customer service department of a large telecommunication provider. The results elucidate the effectiveness of customer service strategies in different channels.
Multi-dimensional patient data, such as time varying volume data, data of different imaging modalities, surface segmentations etc. are of growing importance in the clinical routine. For many use cases, it is of major importance to replicate a certain visualization of a data set created on one machine on a different computer using different software tools. Up until now, there exists no standardized methodology for this consistent presentation. We propose an extension of the Digital Imaging und Communications in Medicine (DICOM) called “Multi dimensional Presentation State” and outline scope and first results of the standardization process.
The Fourth International Conference on Advances in Databases, Knowledge, and Data Applications [DBKDA 2012], held between February 29th and March 5th, 2012 in Saint Gilles, Reunion Island, continued a series of international events covering a large spectrum of topics related to advances in fundamentals on databases, evolution of relation between databases and other domains, data base technologies and content processing, as well as specifics in applications domains databases. Advances in different technologies and domains related to databases triggered substantial improvements for content processing, information indexing, and data, process and knowledge mining. The push came from Web services, artificial intelligence, and agent technologies, as well as from the generalization of the XML adoption. High-speed communications and computations, large storage capacities, and loadbalancing for distributed databases access allow new approaches for content processing with incomplete patterns, advanced ranking algorithms and advanced indexing methods. Evolution on e-business, e-health and telemedicine, bioinformatics, finance and marketing, geographical positioning systems put pressure on database communities to push the ‘de facto’ methods to support new requirements in terms of scalability, privacy, performance, indexing, and heterogeneity of both content and technology. We take here the opportunity to warmly thank all the members of the DBKDA 2012 Technical Program Committee, as well as the numerous reviewers. The creation of such a broad and high quality conference program would not have been possible without their involvement. We also kindly thank all the authors who dedicated much of their time and efforts to contribute to DBKDA 2012. We truly believe that, thanks to all these efforts, the final conference program consisted of top quality contributions. Also, this event could not have been a reality without the support of many individuals, organizations, and sponsors. We are grateful to the members of the DBKDA 2012 organizing committee for their help in handling the logistics and for their work to make this professional meeting a success. We hope that DBKDA 2012 was a successful international forum for the exchange of ideas and results between academia and industry and for the promotion of progress in the fields of databases, knowledge, and data applications. We are convinced that the participants found the event useful and communications very open. We also hope the attendees enjoyed the charm of Saint Gilles, Reunion Island.
When forecasting sales figures, not only the sales history but also the future price of a product will influence the sales quantity. At first sight, multivariate time series seem to be the appropriate model for this task. Nonetheless, in real life history is not always repeatable, i.e., in the case of sales history there is only one price for a product at a given time. This complicates the design of a multivariate time series. However, for some seasonal or perishable products the price is rather a function of the expiration date than of the sales history. This additional information can help to design a more accurate and causal time series model. The proposed solution uses an univariate time series model but takes the price of a product as a parameter that influences systematically the prediction based on a calculated periodicity. The price influence is computed based on historical sales data using correlation analysis and adjustable price ranges to identify products with comparable history. The periodicity is calculated based on a novel approach that is based on data folding and Pearson Correlation. Compared to other techniques this approach is easy to compute and allows to preset the price parameter for predictions and simulations. Tests with data from the Data Mining Cup 2012 as well as artificial data demonstrate better results than established sophisticated time series methods.
New storage technologies, such as Flash and Non- Volatile Memories, with fundamentally different properties are appearing. Leveraging their performance and endurance requires a redesign of existing architecture and algorithms in modern high performance databases. Multi-Version Concurrency Control (MVCC) approaches in database systems, maintain multiple timestamped versions of a tuple. Once a transaction reads a tuple the database system tracks and returns the respective version eliminating lock-requests. Hence under MVCC reads are never blocked, which leverages well the excellent read performance (high throughput, low latency) of new storage technologies. Upon tuple updates, however, established implementations of MVCC approaches (such as Snapshot Isolation) lead to multiple random writes – caused by (i) creation of the new and (ii) in-place invalidation of the old version – thus generating suboptimal access patterns for the new storage media. The combination of an append based storage manager operating with tuple granularity and snapshot isolation addresses asymmetry and in-place updates. In this paper, we highlight novel aspects of log-based storage, in multi-version database systems on new storage media. We claim that multi-versioning and append-based storage can be used to effectively address asymmetry and endurance. We identify multi-versioning as the approach to address dataplacement in complex memory hierarchies. We focus on: version handling, (physical) version placement, compression and collocation of tuple versions on Flash storage and in complex memory hierarchies. We identify possible read- and cacherelated optimizations.
"Learning by doing" in Higher Education in technical disciplines is mostly realized by hands-on labs. It challenges the exploratory aptitude and curiosity of a person. But, exploratory learning is hindered by technical situations that are not easy to establish and to verify. Technical skills are, however, mandatory for employees in this area. On the other side, theoretical concepts are often compromised by commercial products. The challenge is to contrast and reconcile theory with practice. Another challenge is to implement a self-assessment and grading scheme that keeps up with the scalability of e-learning courses. In addition, it should allow the use of different commercial products in the labs and still grade the assignment results automatically in a uniform way. In two European Union funded projects we designed, implemented, and evaluated a unique e-learning reference model, which realizes a modularized teaching concept that provides easily reproducible virtual hands-on labs. The novelty of the approach is to use software products of industrial relevance to compare with theory and to contrast different implementations. In a sample case study, we demonstrate the automated assessment for the creative database modeling and design task. Pilot applications in several European countries demonstrated that the participants gained highly sustainable competences that improved their attractiveness for employment.
Telemedicine is becoming an increasingly important approach to diagnostic, treat or prevent diseases. However, the usage of Information Communication Technologies in healthcare results in a considerable amount of data that must be efficiently and securely transmitted. Many manufacturers provide telemedicine platforms without regarding interoperability, mobility and collaboration. This paper describes a collaborative mobile telemonitoring platform that can use the IEEE 11073 and HL7 communication standards or adapt proprietary protocols. The proposed platform also covers the security and modularity aspects. Furthermore this work introduces an Android-based prototype implementation
Energy-efficiency and safety became an important factor for car manufacturers. Thus, the cars have been optimised regarding the energy consumption and safety by optimising for example the power train or the engine. Besides the optimisation of the car itself, energy-efficiency and safety can also be increased by adapting the individual driving behaviour to the current driving situation. This paper introduces a driving system, which is in development. Its goal is to optimise the driving behaviour in terms of energy-efficiency and safety by giving recommendations to the driver. For the creation of a recommendation the driving system monitors the driver and the current driving situation as well as the car using in-vehicle sensors and serial-bus systems. On the basis of the acquired data, the driving system will give individual energy-efficiency and safety recommendations in real-time. This will allow eliminating bad driving habits, while considering the driver needs.
The Fifth International Conference on Advances in Databases, Knowledge, and Data Applications [DBKDA 2013], held between January 27th- February 1st, 2013 in Seville, Spain, continued a series of international events covering a large spectrum of topics related to advances in fundamentals on databases, evolution of relation between databases and other domains, data base technologies and content processing, as well as specifics in applications domains databases. Advances in different technologies and domains related to databases triggered substantial improvements for content processing, information indexing, and data, process and knowledge mining. The push came from Web services, artificial intelligence, and agent technologies, as well as from the generalization of the XML adoption. High-speed communications and computations, large storage capacities, and loadbalancing for distributed databases access allow new approaches for content processing with incomplete patterns, advanced ranking algorithms and advanced indexing methods. Evolution on e-business, ehealth and telemedicine, bioinformatics, finance and marketing, geographical positioning systems put pressure on database communities to push the ‘de facto’ methods to support new requirements in terms of scalability, privacy, performance, indexing, and heterogeneity of both content and technology. We take here the opportunity to warmly thank all the members of the DBKDA 2013 Technical Program Committee, as well as the numerous reviewers. The creation of such a high quality conference program would not have been possible without their involvement. We also kindly thank all the authors who dedicated much of their time and efforts to contribute to DBKDA 2013. We truly believe that, thanks to all these efforts, the final conference program consisted of top quality contributions. Also, this event could not have been a reality without the support of many individuals, organizations, and sponsors. We are grateful to the members of the DBKDA 2013 organizing committee for their help in handling the logistics and for their work to make this professional meeting a success. We hope that DBKDA 2013 was a successful international forum for the exchange of ideas and results between academia and industry and for the promotion of progress in the fields of databases, knowledge and data applications. We are convinced that the participants found the event useful and communications very open. We also hope the attendees enjoyed the charm of Seville, Spain.
The workshop aims to discuss leading edge contributions to the interdisciplinary research area of ambient intelligence (AmI) applied to the domains of telemedicine and driving assistance. AmI refers to human centered environments attributed with sensors. The development of AmI in the two application domains of the workshop shares several commonalities: the extensive usage of networked devices and sensors, the design of artificial intelligence algorithms for diagnosis, including recommendation systems and qualitative reasoning or the application of mobile and wireless communication to their distributed systems. Together with the presentation of common aspects of Ambient Intelligence, a further goal of the workshop is to stimulate synergies among both application domains and present examples. The telemedicine domain can benefit from methodologies in designing complex devices, real-time conform system design, audiovisual or computer vision system design used in automotive driving assistance. Furthermore, the automotive domain can benefit from the usercentric view, biometric sensor data design, multi-user data bases for aggregation and diagnosis using big data like used in telemedicine. The German Government supports these research lines in its Hightec-Strategie under the domains “Health and Nutrition” and “Climate and Energy”. In Spain the term “Spanish Program for R&D Challenged Oriented Society – Challenge in energy safe, efficient and clean & Challenge in sustainable transport, smart and integrated” is used. Scientific contributions to the event are peer-reviewed by a suited program committee having members from Germany and Spain. The same committee is serving the JARCA workshop (Jornadas sobre Sistemas cualitativos y sus Aplicaciones en Diagnosis, Robótica e Inteligencia Ambiental - Conference on Qualitative Systems and their Applications in Diagnoses, Robotics and Ambient Intelligence) since 15 years. This workshop is sponsored by the German Academic Exchange Service (DAAD) under contract number 57070010.
When forecasting sales figures, not only the sales history but also the future price of a product will influence the sales quantity. At first sight, multivariate time series seem to be the appropriate model for this task. Nontheless, in real life history is not always repeatable, i.e. in the case of sales history there is only one price for a product at a given time. This complicates the design of a multivariate time series. However, for some seasonal or perishable products the price is rather a function of the expiration date than of the sales history. This additional information can help to design a more accurate and causal time series model. The proposed solution uses an univariate time series model but takes the price of a product as a parameter that influences systematically the prediction. The price influence is computed based on historical sales data using correlation analysis and adjustable price ranges to identify products with comparable history. Compared to other techniques this novel approach is easy to compute and allows to preset the price parameter for predictions and simulations. Tests with data from the Data Mining Cup 2012 demonstrate better results than established sophisticated time series methods.
Proceedings of the International Workshop on Mobile Networks for Biometric Data Analysis (mBiDA)
(2014)
Prevention and treatment of common and widesprea (chronic) diseases is a challenge in any modern Society and vitally important for health maintenance in aging societies. Capturing biometric data is a cornerstone for any analysis and Treatment strategy. Latest advances in sensor technology allow accurate data measurement in a non-intrusive way. In many cases, it is necessary to provide online monitoring and real-time data capturing to support patients´ prevention plans or to allow medical professionals to access the current status. Different communication standards are required to push sensor data and to store and analyze them on different (mobile) platforms. The objective of the workshop is to show new and innovative approaches dedicated to biometric data capture and analysis in a non-intrusive way maintaining mobility. Examples can be found in human centered ambient intelligence attributed with sensors or even in methodologies applied in automotive real-time conform mobile system design. The workshop´s main challenge is to focus on approaches promoting non-intrusiveness, reliable prediction algorithms and high user-acceptance. The workshop will provide overview presentations, Young researcher poster tracks, doctoral tracks and classical peer-review full paper tracks. Especially, would like to encourage students and young researchers to participate and to contribute to the workshop. Scientific contributions to the event are peer-reviewed by a suited program committee.
The impact of stress of every human being has become a serious problem. Reported impact on persons are a higher rate or health disorders like heart problems, obesity, asthma, diabetes, depressions and many others. An individual in a stressful situation has to deal with altered cognition as well as an affected decision making skill and problem solving. This could lead to a higher risk for accidents in dynamic environments such as automotive. Different papers faced the estimation as well as prediction of drivers’ stress level during driving. Another important question is not only the stress level of the driver himself, but also the influence on and of a group of other drivers in the near area. This paper proposes a system, which determines a group of drivers in a near area as clusters and it derives or computes the individual stress level. This information will be analyzed to generate a stress map, which represents a graphical view about road section with a higher stress influence. Aggregated data can be used to generate navigation routes with a lower stress influence as well as recommend driving behavior to decrease stress influenced driving as well as improve road safety.
An index in a Multi-Version DBMS (MV-DBMS) has to reflect different tuple versions of a single data item. Existing approaches follow the paradigm of logically separating the tuple version data from the data item, e.g. an index is only allowed to return at most one version of a single data item (while it may return multiple data items that match a search criteria). Hence to determine the valid (and therefore visible) tuple version of a data item, the MV-DBMS first fetches all tuple versions that match the search criteria and subsequently filters visible versions using visibility checks. This involves I/O storage accesses to tuple versions that do not have to be fetched. In this vision paper we present the Multi Version Index (MV-IDX) approach that allows index-only visibility checks which significantly reduce the amount of I/O storage accesses as well as the index maintenance overhead. The MV-IDX achieves significantly lower response times and higher transactional throughput on OLTP workloads.
The use of Wireless Sensor and Actuator Networks (WSAN) as an enabling technology for Cyber-Physical Systems has increased significantly in recent past. The challenges that arise in different application areas of Cyber- Physical Systems, in general, and in WSAN in particular, are getting the attention of academia and industry both. Since reliability issues for message delivery in wireless communication are of critical importance for certain safety related applications, it is one of the areas that has received significant focus in the research community. Additionally, the diverse needs of different applications put different demands on the lower layers in the protocol stack, thus necessitating such mechanisms in place in the lower layers which enable them to dynamically adapt. Another major issue in the realization of networked wirelessly communicating cyber-physical systems, in general, and WSAN, in particular, is the lack of approaches that tackle the reliability, configurability and application awareness issues together. One could consider tackling these issues in isolation. However, the interplay between these issues create such challenges that make the application developers spend more time on meeting these challenges, and that too not in very optimal ways, than spending their time on solving the problems related to the application being developed. Starting from some fundamental concepts, general issues and problems in cyber-physical systems, this chapter discusses such issues like energy-efficiency, application and channel-awareness for networked wirelessly communicating cyber-physical systems. Additionally, the chapter describes a middleware approach called CEACH, which is an acronym for Configurable, Energy-efficient, Application- and Channel-aware Clustering based middleware service for cyber-physical systems. The state of-the art in the area of cyberphysical systems with a special focus on communication reliability, configurability, application- and channel-awareness is described in the chapter. The chapter also describes how these features have been considered in the CEACH approach. Important node level and network level characteristics and their significance vis-àvis the design of applications for cyber physical systems is also discussed. The issue of adaptively controlling the impact of these factors vis-à-vis the application demands and network conditions is also discussed. The chapter also includes a description of Fuzzy-CEACH which is an extension of CEACH middleware service and which uses fuzzy logic principles. The fuzzy descriptors used in different stages of Fuzzy-CEACH have also been described. The fuzzy inference engine used in the Fuzzy-CEACH cluster head election process is described in detail. The Rule-Bases used by fuzzy inference engine in different stages of Fuzzy-CEACH is also included to show an insightful description of the protocol. The chapter also discusses in detail the experimental results validating the authenticity of the presented concepts in the CEACH approach. The applicability of the CEACH middleware service in different application scenarios in the domain of cyberphysical systems is also discussed. The chapter concludes by shedding light on the Publish-Subscribe mechanisms in distributed event-based systems and showing how they can make use of the CEACH middleware to reliably communicate detected events to the event-consumers or the actuators if the WSAN is modeled as a distributed event-based system.
Functionally impaired people have problems with choosing and finding the right clothing. So, they need help in their daily life to wash and manage the clothing. The goal of this work is to support the user by giving recommendations to choose the right clothing, to find the clothing and how to wash the clothing. The idea behind eKlarA is to generate a gateway based system that uses sensors to identify the clothing and their state in the clothing cycle. The clothing cycle consists of (one and more) closet, laundry basket and washing machine in one or several places. The gateway uses the information about the clothing, weather and calendar to support the user in the different steps of the clothing cycle. This allows to give more freedom to the functionally impaired people in their daily life.
Besides the optimisation of the car, energy-efficiency and safety can also be increased by optimising the driving behaviour. Based on this fact, a driving system is in development whose goal is to educate the driver in energy-efficient and safe driving. It monitors the driver, the car and the environment and gives energy-efficiency and safety relevant recommendations. However, the driving system tries not to distract or bother the driver by giving recommendations for example during stressful driving situations or when the driver is not interested in that recommendation. Therefore, the driving system monitors the stress level of the driver as well as the reaction of the driver to a given recommendation and decides whether to give a recommendation or not. This allows to suppress recommendations when needed and, thus, to increase the road safety and the user acceptance of the driving system.
Knowledge transfer is very important to our knowledge-based society and many approaches have been proposed to describe this transfer. However, these approaches take a rather abstract view on knowledge transfer, which makes implementation difficult. In order to address this issue, we introduce a layered model for knowledge transfer that structures the individual steps of knowledge transfer in more detail. This paper gives a description of the process and also an example of the application of the layered model for knowledge transfer. The example is located in the area of business process modelling. Business processes contain the important knowledge describing the procedures of the company to produce products and services. Knowledge transfer is the fundamental basis in the modelling and usage of Business processes, which makes it an interesting use case for the layered model for knowledge transfer.
Enterprise Architectures (EA) consists of many architecture elements, which stand in manifold relationships to each other. Therefore Architecture Analysis is important and very difficult for stakeholders. Due changing an architecture element has impacts on other elements different stakeholders are involved. In practice EAs are often analyzed using visualizations. This article aims at contributing to the field of visual analytics in EAM by analyzing how state of-the-art software platforms in EAM support stakeholders with respect to providing and visualizing the “right” information for decision-making tasks. We investigate the collaborative decision-making process in an experiment with master students using professional EAM tools by developing a research study and accomplishing them in a master’s level class with students.
Analysis and planning of Enterprise Architectures (EA) is a complex task for stakeholders. The change of one architecture element has impact on multiple other elements because of manifold relationships and interactions between them. The interactive cockpit approach presented in this paper supports stakeholders planning and analyzing EAs and to tackle the intrinsic complexity. This approach supplies a cockpit with multiple viewpoints to put relevant information side-by-side without losing the context combined with interaction functionality. In this paper, we develop such cockpit starting with relevant use cases, describing a potential design based on well-established foundations in EA modeling, and outline an exemplary usage scenario.
Stent graft visualization and planning tool for endovascular surgery using finite element analysis
(2014)
Purpose: A new approach to optimize stent graft selection for endovascular aortic repair is the use of finite element analysis. Once the finite element model is created and solved, a software module is needed to view the simulation results in the clinical work environment. A new tool for Interpretation of simulation results, named Medical Postprocessor, that enables comparison of different stent graft configurations and products was designed, implemented and tested. Methods Aortic endovascular stent graft ring forces and sealing states in the vessel landing zone of three different configurations were provided in a surgical planning software using the Medical Imaging Interaction Tool Kit (MITK) Software system. For data interpretation, software modules for 2D and 3D presentations were implemented. Ten surgeons evaluated the software features of the Medical Postprocessor. These surgeons performed usability tests and answered questionnaires based on their experience with the system.
Results: The Medical Postprocessor visualization system enabled vascular surgeons to determine the configuration with the highest overall fixation force in 16 ± 6 s, best proximal sealing in 56±24 s and highest proximal fixation force in 38 ± 12 s. The majority considered the multiformat data provided helpful and found the Medical Postprocessor to be an efficient decision support system for stent graft selection. The evaluation of the user interface results in an ISONORMconform user interface (113.5 points).
Conclusion: The Medical Postprocessor visualization Software tool for analyzing stent graft properties was evaluated by vascular surgeons. The results show that the software can assist the interpretation of simulation results to optimize stent graft configuration and sizing.
There are several intra-operative use cases which require the surgeon to interact with medical devices. We used the Leap Motion Controller as input device and implemented two use-cases: 2D-Interaction (e.g. advancing EPR data) and selection of a value (e.g. room illumination brightness). The gesture detection was successful and we mapped its output to several devices and systems.
Intra-operative fluoroscopy-guided assistance system for transcatheter aortic valve implantation
(2014)
A new surgical assistance system has been developed to assist the correct positioning of the AVP during transapical TAVI. The developed assistance system automatically defines the target area for implanting the AVP under live 2-D fluoroscopy guidance. Moreover, this surgical assistance system works with low levels of contrast agent for the final deployment of AVP, reducing therefore long-term negative effects, such as renal failure in the elderly and high-risk patients.
Online credit card fraud presents a significant challenge in the field of eCommerce. In 2012 alone, the total loss due to credit card fraud in the US amounted to $ 54 billion. Especially online games merchants have difficulties applying standard fraud detection algorithms to achieve timely and accurate detection. This paper describes the Special constrains of this domain and highlights the reasons why conventional algorithms are not quite effective to deal with this problem. Our suggested solution for the problem originates from the fields of feature construction joined with the field of temporal sequence data mining. We present Feature construction techniques, which are able to create discriminative features based on a sequence of transaction and are able to incorporate the time into the classification process. In addition to that, a framework is presented that allows for an automated and adaptive change of features in case the underlying pattern is changing.
Vehicles have been so far improved in terms of energy-efficiency and safety mainly by optimising the engine and the power train. However, there are opportunities to increase energy-efficiency and safety by adapting the individual driving behaviour in the given driving situation. In this paper, an improved rule match algorithm is introduced, which is used in the expert system of a human-centred driving system. The goal of the driving system is to optimise the driving behaviour in terms of energy-efficiency and safety by giving recommendations to the driver. The improved rule match algorithm checks the incoming information against the driving rules to recognise any breakings of a driving rule. The needed information is obtained by monitoring the driver, the current driving situation as well as the car, using in-vehicle sensors and serial-bus systems. On the basis of the detected broken driving rules, the expert system will create individual recommendations in terms of energy-efficiency and safety, which will allow eliminating bad driving habits, while considering the driver needs.
The recent years and especially the Internet have changed the ways in which data is stored. It is now common to store data in the form of transactions, together with ist creation time-stamp. These transactions can often be attributed to Logical units, e.g., all transactions that belong to one customer. These groups, we refer to them as data sequences, have a more complex structure than tuple-based data. This makes it more difficult to find discriminatory patterns for classification purposes. However, the complex structure potentially enables us to track behaviour and its change over the course of time. This is quite interesting, especially in the e-commerce area, in which classification of a sequence of customer actions is still a challenging task for data miners. However, before standard algorithms such as Decision Trees, Neural Nets, Naive Bayes or Bayesian Belief Networks can be applied on sequential data, preparations are required in order to capture the information stored within the sequences. Therefore, this work presents a systematic approach on how to reveal sequence patterns among data and how to construct powerful features out of the primitive sequence attributes. This is achieved by sequence aggregation and the incorporation of time dimension into the feature construction step. The proposed algorithm is described in detail and applied on a real-life data set, which demonstrates the ability of the proposed algorithm to boost the classification performance of well-known data mining algorithms for binary classification tasks.
Model-guided Therapy and Surgical Workflow Systems are two interrelated research fields, which have been developed separately in the last years. To make full use of both technologies, it is necessary to integrate them and connect them to Hospital Information Systems. We propose a framework for integration of Model-guided Therapy in Hospital Information Systems based on the Electronic Medical Record, and a taskbased Workflow Management System, which is suitable for clinical end users. Two prototypes - one based on Business Process Modeling Language, one based on the serum-board - are presented. From the experience with these prototypes, we developed a novel personalized visualization system for Surgical Workflows and Model-guided Therapy. Key challenges for further development are automated situation detection and a common communication infrastructure.
Current approaches for enterprise architecture lack analytical instruments for cyclic evaluations of business and system architectures in real business enterprise system environments. This impedes the broad use of enterprise architecture methodologies. Furthermore, the permanent evolution of systems desynchronizes quickly model representation and reality. Therefore we are introducing an approach for complementing the existing top-down approach for the creation of enterprise architecture with a bottom approach. Enterprise Architecture Analytics uses the architectural information contained in many infrastructures to provide architectural information. By applying Big Data technologies it is possible to exploit this information and to create architectural information. That means, Enterprise Architectures may be discovered, analyzed and optimized using analytics. The increased availability of architectural data also improves the possibilities to verify the compliance of Enterprise Architectures. Architectural decisions are linked to clustered architecture artifacts and categories according to a holistic EAM Reference Architecture with specific architecture metamodels. A special suited EAM Maturity Framework provides the base for systematic and analytics supported assessments of architecture capabilities.
A configuration-management-database driven approach for fabric-process specification and automation
(2014)
In this paper we describe an approach that integrates a Configuration- Management-Database into fabric-process specification and automation in order to consider different conditions regarding to cloud-services. By implementing our approach, the complexity of fabric processes gets reduced. We developed a prototype by using formal prototyping principles as research methods and integrated the Configuration-Management-Database Command into the Workflow- Management-System Activiti. We used this prototype to evaluate our approach. We implemented three different fabric-processes and show that by using our approach the complexity of these three fabric-processes gets reduced.
The recent years and especially the Internet have changed the way on how data is stored. We now often store data together with its creation time-stamp. These data sequences potentially enable us to track the change of data over time. This is quite interesting, especially in the e-commerce area, in which classification of a sequence of customer actions, is still a challenging task for data miners. However, before Standard algorithms such as Decision Trees, Neuronal Nets, Naive Bayes or Bayesian Belief Networks can be applied on sequential data, preparations need to be done in order to capture the information stored within the sequences. Therefore, this work presents a systematic approach on how to reveal sequence patterns among data and how to construct powerful features out of the primitive sequence attributes. This is achieved by sequence aggregation and the incorporation of time dimension into the Feature construction step. The proposed algorithm is described in detail and applied on a real life data set, which demonstrates the ability of the proposed algorithm to boost the classification performance of well known data mining algorithms for classification tasks.
SmartLife ecosystems are emerging as intelligent user-centered systems that will shape future trends in technology and communication. Biological metaphors of living adaptable ecosystems provide the logical foundation for self-optimizing and self-healing run-time environments for intelligent adaptable business services and related information systems with service-oriented enterprise architectures. The present research in progress work investigates mechanisms for adaptable enterprise architectures for the development of service-oriented ecosystems with integrated technologies like Semantic Technologies, Web Services, Cloud Computing and Big Data Management. With a large and diverse set of ecosystem services with different owners, our scenario of service-based SmartLife ecosystems can pose challenges in their development, and more importantly, for maintenance and software evolution. Our research explores the use of knowledge modeling using ontologies and flexible metamodels for adaptable enterprise architectures to support program comprehension for software engineers during maintenance and evolution tasks of service-based applications. Our previous reference enterprise architecture model ESARC -- Enterprise Services Architecture Reference Cube -- and the Open Group SOA Ontology was extended to support agile semantic analysis, program comprehension and software evolution for a SmartLife applications scenario. The Semantic Browser is a semantic search tool that was developed to provide knowledge-enhanced investigation capabilities for service-oriented applications and their architectures.
The Third International Conference on Data Analytics (DATA ANALYTICS 2014), held on August 24 - 28, 2014 - Rome, Italy, continued the inaugural event on fundamentals in supporting data analytics, special mechanisms and features of applying principles of data analytics, application oriented analytics, and target-area analytics.
Processing of terabytes to petabytes of data, or incorporating non-structural data and multistructured data sources and types require advanced analytics and data science mechanisms for both raw and partially-processed information. Despite considerable advancements on high performance, large storage, and high computation power, there are challenges in identifying, clustering, classifying, and interpreting of a large spectrum of information.
This thesis studies concurrency control and composition of transactions in computing environments with long living transactions where local data autonomy of transactions is indispensable. This kind of computing architecture is referred to as a Disconnected System where reads are segregated -disconnected- from writes enabling local data autonomy. Disconnecting reads from writes is inspired by Bertrand Meyer's "Command Query Separation" pattern. This thesis provides a simple yet precise definition for a Disconnected System with a focus on transaction management. Concerning concurrency control, transaction management frameworks implement a'one concurrency control mechanism fits all needs strategy'. This strategy, however, does not consider specific characteristics of data access. The thesis shows the limitations of this strategy if transaction load increases, transactions are long lived, local data autonomy is required, and serializability is aimed at isolation level. For example, in optimistic mechanisms the number of aborts suddenly increases if load increases. In pessimistic mechanisms locking causes long blocking times and is prone to deadlocks. These findings are not new and a common solution used by database vendors is to reduce the isolation. This thesis proposes the usage of a novel approach. It suggests choosing the concurrency control mechanism according to the semantics of data access of a certain data item. As a result a transaction may execute under several concurrency control mechanisms. The idea is to introduce lanes similar to a motorway where each lane is dedicated to a certain class of vehicle with the same characteristics. Whereas disconnecting reads and writes sets the traffic's direction, the semantics of data access defines the lanes. This thesis introduces four concurrency control classes capturing the semantics of data access and each of them has an associated tailored concurrency control mechanism. Class O (the optimistic class) implements a first-committer-wins strategy, class R (the reconciliation class) implements a first-n-committers-win strategy, class P (the pessimistic class) implements a first-reader-wins strategy, and class E (the escrow class) implements a first-n-readers-win strategy. In contrast to solutions that adapt the concurrency control mechanism during runtime, the idea is to classify data during the design phase of the application and adapt the classification only in certain cases at runtime. The result of the thesis is a transaction management framework called O|R|P|E. A performance study based on the TPC-C benchmark shows that O|R|P|E has a better performance and a considerably higher commit rate than other solutions. Moreover, the thesis shows that in O|R|P|E aborts are due to application specific limitations, i.e., constraint violations and not due to serialization conflicts. This is a result of considering the semantics.
Prominent theories of action recognition suggest that during the recognition of actions the physical patterns of the action is associated with only one action interpretation (e.g., a person waving his arm is recognized as waving). In contrast to this view, studies examining the visual categorization of objects show that objects are recognized in multiple ways (e.g., a VW Beetle can be recognized as a car or a beetle) and that categorization performance is based on the visual and motor movement similarity between objects. Here, we studied whether we find evidence for multiple levels of categorization for social interactions (physical interactions with another person, e.g., handshakes). To do so, we compared visual categorization of objects and social interactions (Experiments 1 and 2) in a grouping task and assessed the usefulness of motor and visual cues (Experiments 3, 4, and 5) for object and social interaction categorization. Additionally, we measured recognition performance associated with recognizing objects and social interactions at different categorization levels (Experiment 6). We found that basic level object categories were associated with a clear recognition advantage compared to subordinate recognition but basic level social interaction categories provided only a little recognition advantage. Moreover, basic level object categories were more strongly associated with similar visual and motor cues than basic level social interaction categories. The results suggest that cognitive categories underlying the recognition of objects and social interactions are associated with different performances. These results are in line with the idea that the same action can be associated with several action interpretations (e.g., a person waving his arm can be recognized as waving or greeting).
Putting actions in context: visual action adaptation aftereffects are modulated by social contexts
(2014)
The social context in which an action is embedded provides important information for the interpretation of an action. Is this social context integrated during the visual recognition of an action? We used a behavioural visual adaptation paradigm to address this question and measured participants’ perceptual bias of a test action after they were adapted to one of two adaptors (adaptation after-effect). The action adaptation after effect was measured for the same set of adaptors in two different social contexts. Our results indicate that the size of the adaptation effect varied with social context (social context modulation) although the physical appearance of the adaptors remained unchanged. Three additional experiments provided evidence that the observed social context modulation of the adaptation effect are owed to the adaptation of visual action recognition processes. We found that adaptation is critical for the social context modulation (experiment 2). Moreover, the effect is not mediated by emotional content of the action alone (experiment 3) and visual information about the action seems to be critical for the emergence of action adaptation effects (experiment 4). Taken together these results suggest that processes underlying visual action recognition are sensitive to the social context of an action.
This paper addresses the following four research questions: 1. How should customer service quality in social media channels be conceptualized on multiple levels? 2. Which aspects of customer service quality are important in enhancing customer satisfaction? 3. What outcomes are effected by customer service quality and customer satisfaction? 4. How effective are customer services delivered through social media channels (as compared to customer services delivered through other channels)?
The implementation of a web based portal QA solution will lead to a high acceptance of the staff as the usage of commonly known standard software (e.g. web browser) allows intuitive handling. In the daily use a significant simplification of the workflow and Performance enhancement can be achieved by easy access to the check documents. As the data is now saved in a database it can easily be processed and long-term trends can be displayed. Therefore possible errors can be detected much easier and earlier. By the usage of time stamps and user authentication procedures and user responsibilities are comprehensibly documented. As the software is browser based, integration into an existing software Environment is not critical. As only technical QA data is processed, no further data security measures are necessary. A certification as a medical product is not required.
Services Oriented Architectures (SOA) have emerged as a useful framework for developing interoperable, large-scale systems, typically implemented using the Web Services (WS) standards. However, the maintenance and evolution of SOA systems present many challenges. SmartLife applications are intelligent user-centered systems and a special class of SOA systems that present even greater challenges for a software maintainer. Ontologies and ontological modeling can be used to support the evolution of SOA systems. This paper describes the development of a SOA evolution ontology and its use to develop an ontological model of a SOA system. The ontology is based on a standard SOA ontology. The ontological model can be used to provide semantic and visual support for software maintainers during routine maintenance tasks. We discuss a case study to illustrate this approach, as well as the strengths and limitations.
In this work, a web-based software architecture and framework for management and diagnosis of large amounts of medical data in an ophthalmologic reading center is proposed. Data management for multi-center studies requires merging of standing data and repeatedly gathered clinical evidence such as vital signs and raw data. If ophthalmologic questions are involved the data acquisition is often provided by non-medical staff at the point of care or a study center, whereas the medical finding is mostly provided by an ophthalmologist in a specialized reading center. The study data such as participants, cohorts and measured values are administrated at a single data center for the entire study. Since a specialized reading center maintains several studies, the medical staff must learn the different data administration for the different data center. With respect to the increasing number and sizes of clinical studies, two aspects must be considered. At first, an efficient software framework is required to support the data management, processing and diagnosis by medical experts at the reading center. In the second place, this software needs a standardized user-interface that has not to be trained/taylore /adapted for each new study. Furthermore different aspects of quality and security controls have to be included. Therefore, the objective of this work is to establish a multi purpose ophthalmologic reading center, which can be connected to different data centers via configurable data interfaces in order to treat various topics simultaneously.
The Sixth International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2014), held between April 20 - 24, 2014 in Chamonix, France, continued a series of international events covering a large spectrum of topics related to advances in fundamentals on databases, evolution of relation between databases and other domains, data base technologies and content processing, as well as specifics in applications domains databases. Advances in different technologies and domains related to databases triggered substantial improvements for content processing, information indexing, and data, process and knowledge mining. The push came from Web services, artificial intelligence, and agent technologies, as well as from the generalization of the XML adoption. High-speed communications and computations, large storage capacities, and loadbalancing for distributed databases access allow new approaches for content processing with incomplete patterns, advanced ranking algorithms and advanced indexing methods. Evolution on e-business, ehealth and telemedicine, bioinformatics, finance and marketing, geographical positioning systems put pressure on database communities to push the ‘de facto’ methods to support new requirements in terms of scalability, privacy, performance, indexing, and heterogeneity of both content and technology.
This paper compares the influence a video self-avatar and a lack of a visual representation of a body have on height estimation when standing at a virtual visual cliff. A height estimation experiment was conducted using a custom augmented reality Oculus Rift hardware and software prototype also described in this paper. The results show a consistency with previous research demonstrating that the presence of a visual body influences height estimates, just as it has been shown to influence distance estimates and affordance estimates.
An operation room is a stressful work environment. Nevertheless, all involved persons have to work safely as there is no space for making mistakes. To ensure a high level of concentration and seamless interaction, all involved persons have to know their own tasks and tasks of their colleagues. The entire team must work synchronously at all times. However, the operation room (OR) is a noisy environment and the actors have to set their focus on their work. To optimize the overall workflow, a task manager supporting the team was developed. Each actor is equipped with a client terminal showing a summary of their own tasks. Moreover, a big screen displays all tasks of all actors. The architecture is a distributed system based on a communication framework that supports the interaction of all clients with the task manager. A prototype of the task manager and several clients have been developed and implemented. The system represents a proof-of-concept for further development. This paper describes the concept of the task manager.
Strategy to test mobile apps
(2014)
Nowadays the development of a mobile app implies challenges and difficulties, which have to be faced by mobile app developers. Innovations lead to a rapidly evolving mobile app market, therefore apps should be developed faster and offered in short release cycles to the market. Testing is a decisive activity within the development process that helps to improve the quality of the app. This research paper describes a strategy to test mobile apps that overcomes the challenges that mobile apps confront and permits to test the app in a structural test environment.
Many companies practice performance management in the framework of a heterogeneous, grown mix of numerous separate decisions, instruments, processes and systems and not in terms of a strategically and systematically planned management system. Due to the inefficiency of the above mentioned performance management style, a holistic and integrated approach is a key factor. Performance management must be able to meet central objectives and requirements and set the groundwork for long-term corporate success. This article presents a central approach of the conception of holistic and long-term performance management. The five equal part disciplines are illustrated and demonstrate the issue and composition complexity of a performance management due to their characteristics and combination. The objective of this article is to display and communicate the performance management issue and its context through an easily comprehensible system without following a general recipe.
Many future Services Oriented Architecture (SOA) systems may be pervasive SmartLife applications that provide real-time support for users in everyday tasks and situations. Development of such applications will be challenging, but in this position paper we argue that their ongoing maintenance may be even more so. Ontological modelling of the application may help to ease this burden, but maintainers need to understand a system at many levels, from a broad architectural perspective down to the internals of deployed components. Thus we will need consistent models that span the range of views, from business processes through system architecture to maintainable code. We provide an initial example of such a modelling approach and illustrate its application in a semantic browser to aid in software maintenance tasks.
Learning and teaching requires the transfer of knowledge from one person to another. Due to the relevance of knowledge many models have been developed for knowledge transfer. However, the process of knowledge transfer has not yet been described completely and the approaches are too vague to facilitate its implementation. This paper contributes to a better understanding of knowledge transfer to support knowledge transfer in teaching. To address this challenge, we depict a layered model for knowledge transfer. The model structures the transfer in several steps and thus identifies major influencing factors. The paper describes the knowledge transfer from one person to another step by step. An example in the area of teaching business process management illuminates the process. The main contribution of this paper is the development of a layered model and its application in teaching.
There are several intra-operative use cases which require the surgeon to interact with medical devices. I used the Leap Motion Controller as input device for three use-cases: 2D-interaction (e.g. advancing EPR data), selection of a value (e.g. room illumination brightness) and an application point and click scenario. I evaluated the Palm Mouse as the most suitable gesture solution to coordinate the mouse and advise to use the implementation using all fingers to perform a click. This small case study introduces the implementations and methods that result those recommendations.
Delivering value to customers in real-time requires companies to utilize real-time deployment of software to expose features to users faster, and to shorten the feedback loop. This allows for faster reaction and helps to ensure that the development is focused on features providing real value. Continuous delivery is a development practice where the software functionality is deployed continuously to customer environment. Although this practice has been established in some domains such as B2C mobile software, the B2B domain imposes specific challenges. This article presents a case study that is conducted in a medium-sized software company operating in the B2B domain. The objective of this study is to analyze the challenges and benefits of continuous delivery in this domain. The results suggest that technical challenges are only one part of the challenges a company encounters in this transition. The company must also address challenges related to the customer and procedures. The core challenges are caused by having multiple customers with diverse environments and unique properties, whose business depends on the software product. Some customers require to perform manual acceptance testing, while some are reluctant towards new versions. By utilizing continuous delivery, it is possible for the case company to shorten the feedback cycles, increase the reliability of new versions, and reduce the amount of resources required for deploying and testing new releases.
Software development as an experiment system : a qualitative survey on the state of the practice
(2015)
An experiment-driven approach to software product and service development is gaining increasing attention as a way to channel limited resources to the efficient creation of customer value. In this approach, software functionalities are developed incrementally and validated in continuous experiments with stakeholders such as customers and users. The experiments provide factual feedback for guiding subsequent development. Although case studies on experimentation in industry exist, the understanding of the state of the practice and the encountered obstacles is incomplete. This paper presents an interview-based qualitative survey exploring the experimentation experiences of ten software development companies. The study found that although the principles of continuous experimentation resonated with industry practitioners, the state of the practice is not yet mature. In particular, experimentation is rarely systematic and continuous. Key challenges relate to changing organizational culture, accelerating development cycle speed, and measuring customer value and product
success.
Rapid value delivery requires a company to utilize empirical evaluation of new features and products in order to avoid unnecessary product risks. This helps to make data-driven decisions and to ensure that the development is focused on features that provide real value for customers. Short feedback loops are a prerequisite as they allow for fast learning and reduced reaction times. Continuous experimentation is a development practice where the entire R&D process is guided by constantly conducting experiments and collecting feedback. Although principles of continuous experimentation have been successfully applied in domains such as game software or SAAS, it is not obvious how to transfer continuous experimentation to the business to-business domain. In this article, a case study from a medium-sized software company in the B2B domain is presented. The study objective is to analyze the challenges, benefits and organizational aspects of continuous experimentation in the B2B domain. The results suggest that technical challenges are only one part of the challenges a company encounters in this transition. The company also has to address challenges related to the customer and organizational culture. Unique properties in each customers business play a major role and need to be considered when designing experiments. Additionally, the speed by which experiments can be conducted is relative to the speed by which production deployments can be made. Finally, the article shows how the study results can be used to modify the development in the case company in a way that more feedback and data is used instead of opinions.
This is a report from a one-day fourth international workshop on "Information Systems in Distributed Environments" (ISDE), which was organized in conjunction with the OnTheMove Federated Conferences & Workshops (OTM 2014) October 29-30, 2014, Amantea, Calabria, Italy. The main focus of this event was to provide a venue for the discussion of challenges related to the development, operation, and maintenance of distributed information systems, and their creation in the context of global development projects. Further dissemination of research results will lead to an improvement of distributed information system development and deployment across the globe.
For years, agile methods are considered the most promising route toward successful software development, and a considerable number of published studies the (successful) use of agile methods and reports on the benefits companies have from adopting agile methods. Yet, since the world is not black or white, the question for what happened to the traditional models arises. Are traditional models replaced by agile methods? How is the transformation toward Agile managed, and, moreover, where did it start? With this paper we close a gap in literature by studying the general process use over time to investigate how traditional and agile methods are used. Is there coexistence or do agile methods accelerate the traditional processes’ extinction? The findings of our literature study comprise two major results: First, studies and reliable numbers on the general process model use are rare, i.e., we lack quantitative data on the actual process use and, thus, we often lack the ability to ground process-related research in practically relevant issues. Second, despite the assumed dominance of agile methods, our results clearly show that companies enact context-specific hybrid solutions in which traditional and agile development approaches are used in combination.
Software process improvement (SPI) is around for decades: frameworks are proposed, success factors are studied, and experiences have been reported. However, the sheer mass of concepts, approaches, and standards published over the years overwhelms practitioners as well as researchers. What is out there? Are there new emerging approaches? What are open issues? Still, we struggle to answer the question for what is the current state of SPI and related research? In this paper, we present initial results from a systematic mapping study to shed light on the field of SPI and to draw conclusions for future research directions. An analysis of 635 publications draws a big picture of SPI-related research of the past 25 years. Our study shows a high number of solution proposals, experience reports, and secondary studies, but only few theories. In particular, standard SPI models like CMMI and ISO/IEC 15504 are analyzed, enhanced, and evaluated for applicability, whereas these standards are critically discussed from the perspective of SPI in small-to- medium-sized companies, which leads to new specialized frameworks. Furthermore, we find a growing interest in success factors to aid companies in conducting SPI.
Entrepreneurs and small and medium enterprises usually have issues on developing new prototypes, new ideas or testing new techniques. In order to help them, in the last years, academic Software Factories, a new concept of collaboration between universities and companies have been developed. Software Factories provide a unique environment for students and companies. Students benefit from the possibility of working in a real work environment learning how to apply the state of the art of the existing techniques and showing their skills to entrepreneurs. Companies benefit from the risk-free environment where they can develop new ideas, in a protected environment. Universities finally benefit from this setup as a perfect environment for empirical studies in industrial-like environment. In this paper, we present the network of academic Software Factories in Europe, showing how companies had already benefit from existing Software Factories and reporting success stories. The results of this paper can increase the network of the factories and help other universities and companies to setup similar environment to boost the local economy.
New or adapted digital business models have huge impacts on Enterprise Architectures (EA) and require them to become more agile, flexible, and adaptable. All these changes are happening frequently and are currently not well documented. An EA consists of a lot of elements with manifold relationships between them. Thus changing the business model may have multiple impacts on other architectural elements. The EA engineering process deals with the development, change and optimization of architectural elements and their dependencies. Thus an EA provides a holistic view for both business and IT from the perspective of many stakeholders, which are involved in EA decision-making processes. Different stakeholders have specific concerns and are collaborating today in often unclear decision-making processes. In our research we are investigating information from collaborative decision-making processes to support stakeholders in taking current decisions. In addition we provide all information necessary to understand how and why decisions were taken. We are collecting the decision-related information automatically to minimize manual time intensive work as much as possible. The core contribution of our research extends a decisional metamodel, which links basic decisions with architectural elements and extends them with an associated decisional case context. Our aim is to support a new integral method for multi perspective and collaborative decision-making processes. We illustrate this by a practice-relevant decision-making scenario for Enterprise Architecture Engineering.
Information systems, which support the workflow in the clinical area, are currently limited to organizational processes. This work shows a first approach of an information system supporting all actors in the perioperative area. The first prototype and proof of concept was a task manager, giving all actors information about their task and the task of all other actors during an intervention. Based on this initial task manager, we implemented an information system based on a workflow engine controlling all processes and all information necessary for the intervention. A second part was the development of a perioperative process visualization which was developed based on a user centered approach jointly with clinicians and OR members.
We investigated the influence of body shape and pose on the perception of physical strength and social power for male virtual characters. In the first experiment, participants judged the physical strength of varying body shapes, derived from a statistical 3D body model. Based on these ratings, we determined three body shapes (weak, average, and strong) and animated them with a set of power poses for the second experiment. Participants rated how strong or powerful they perceived virtual characters of varying body shapes that were displayed in different poses. Our results show that perception of physical strength was mainly driven by the shape of the body. However, the social attribute of power was influenced by an interaction between pose and shape. Specifically, the effect of pose on power ratings was greater for weak body shapes. These results demonstrate that a character with a weak shape can be perceived as more powerful when in a high-power pose.
To evaluate the quality of a person´s sleep it is essential to identify the sleep stages and their durations. Currently, the gold standard in terms of sleep analysis is overnight polysomnography (PSG), during which several techniques like EEG (eletroencephalogram), EOG (electrooculogram), EMG (electromyogram), ECG (electrocardiogram), SpO2 (blood oxygen saturation) and for example respiratory airflow and respiratory effort are recorded. These expensive and complex procedures, applied in sleep laboratories, are invasive and unfamiliar for the subjects and it is a reason why it might have an impact on the recorded data. These are the main reasons why low-cost home diagnostic systems are likely to be advantageous. Their aim is to reach a larger population by reducing the number of parameters recorded. Nowadays, many wearable devices promise to measure sleep quality using only the ECG and body-movement signals. This work presents an android application developed in order to proof the accuracy of an algorithm published in the sleep literature. The algorithm uses ECG and body movement recordings to estimate sleep stages. The pre-recorded signals fed into the algorithm have been taken from physionet1 online database. The obtained results have been compared with those of the standard method used in PSG. The mean agreement ratios between the sleep stages REM, Wake, NREM-1, NREM-2 and NREM-3 were 38.1%, 14%, 16%, 75% and 54.3%.
A behavior marker for measuring non-technical skills of software professionals : an empirical study
(2015)
Managers recognize that software development teams need to be developed. Although technical skills are necessary, non-technical (NT) skills are equally, if not more, necessary for project success. Currently, there are no proven tools to measure the NT skills of software developers or software development teams. Behavioral markers (observable behaviors that have positive or negative impacts on individual or team performance) are successfully used by airline and medical industries to measure NT skill performance. This research developed and validated a behavior marker tool rated video clips of software development teams. The initial results show that the behavior marker tool can be reliably used with minimal training.
Real Time Charging (RTC) applications that reside in the telecommunications domain have the need for extremely fast database transactions. Today´s providers rely mostly on in-memory databases for this kind of information processing. A flexible and modular benchmark suite specifically designed for this domain provides a valuable framework to test the performance of different DB candidates. Besides a data and a load generator, the suite also includes decoupled database connectors and use case components for convenient customization and extension. Such easily produced test results can be used as guidance for choosing a subset of candidates for further tuning/testing and finally evaluating the database most suited to the chosen use cases. This is why our benchmark suite can be of value for choosing databases for RTC use cases.
In the present tutorial we perform a cross-cut analysis of database systems from the perspective of modern storage technology, namely Flash memory. We argue that neither the design of modern DBMS, nor the architecture of flash storage technologies are aligned with each other. The result is needlessly suboptimal DBMS performance and inefficient flash utilisation as well as low flash storage endurance and reliability. We showcase new DBMS approaches with improved algorithms and leaner architectures, designed to leverage the properties of modern storage technologies. We cover the area of transaction management and multi-versioning, putting a special emphasis on: (i) version organisation models and invalidation mechanisms in multi-versioning DBMS; (ii) Flash storage management especially on append-based storage in tuple granularity; (iii) Flash-friendly buffer management; as well as (iv) improvements in the searching and indexing models. Furthermore, we present our NoFTL approach to native Flash access that integrates parts of the flash-management functionality into the DBMS yielding significant performance increase and simplification of the I/O stack. In addition, we cover the basics of building large Flash storage for DBMS and revisit some of the RAID techniques and principles.
Flash SSDs are omnipresent as database storage. HDD replacement is seamless since Flash SSDs implement the same legacy hardware and software interfaces to enable backward compatibility. Yet, the price paid is high as backward compatibility masks the native behaviour, incurs significant complexity and decreases I/O performance, making it non-robust and unpredictable. Flash SSDs are black-boxes. Although DBMS have ample mechanisms to control hardware directly and utilize the performance potential of Flash memory, the legacy interfaces and black-box architecture of Flash devices prevent them from doing so.
In this paper we demonstrate NoFTL, an approach that enables native Flash access and integrates parts of the Flashmanagement functionality into the DBMS yielding significant performance increase and simplification of the I/O stack. NoFTL is implemented on real hardware based on the OpenSSD research platform. The contributions of this paper include: (i) a description of the NoFTL native Flash storage architecture; (ii) its integration in Shore-MT and (iii) performance evaluation of NoFTL on a real Flash SSD and on an on-line data-driven Flash emulator under TPCB, C,E and H workloads. The performance evaluation results indicate an improvement of at least 2.4x on real hardware over conventional Flash storage; as well as better utilisation of native Flash parallelism.
Stress is recognized as a factor of predominant disease and in the future the costs for treatment will increase. The presented approach tries to detect stress in a very basic and easy to implement way, so that the cost for the device and effort to wear it remain low. The user should benefit from the fact that the system offers an easy interface reporting the status of his body in real time. In parallel, the system provides interfaces to pass the obtained data forward for further processing and (professional) analyses, in case the user agrees. The system is designed to be used in every day’s activities and it is not restricted to laboratory use or environments. The implementation of the enhanced prototype shows that the detection of stress and the reporting can be managed using correlation plots and automatic pattern recognition even on a very light weighted microcontroller platform.
An ongoing challenge in our days is to lower the impact on the quality of life caused by dysfunctionality through individual support. With the background of an aging society and continuous increases in costs for care, a holistic solution is needed. This solution must integrate individual needs and preferences, locally available possibilities, regional conditions, professional and informal caregivers and provide the flexibility to implement future requirements. The proposed model is a result of a common initiative to overcome the major obstacles and to center a solution on individual needs caused by dysfunctionality.
Context: Companies increasingly strive to adapt to market and ecosystem changes in real time. Gauging and understanding team performance in such changing environments present a major challenge.
Objective: This paper aims to understand how software developers experience the continuous adaptation of performance in a modern, highly volatile environment using Lean and Agile software development methodology. This understanding can be used as a basis for guiding formation and maintenance of high-performing teams, to inform performance improvement initiatives, and to improve working conditions for software developers.
Method: A qualitative multiple-case study using thematic interviews was conducted with 16 experienced practitioners in five organisations.
Results: We generated a grounded theory, Performance Alignment Work, showing how software developers experience performance. We found 33 major categories of performance factors and relationships between the factors. A cross-case comparison revealed similarities and differences between different kinds and different sizes of organisations.
Conclusions: Based on our study, software teams are engaged in a constant cycle of interpreting their own performance and negotiating its alignment with other stakeholders. While differences across organisational sizes exist, a common set of performance experiences is present despite differences in context variables. Enhancing performance experiences requires integration of soft factors, such as communication, team spirit, team identity, and values, into the overall development process. Our findings suggest a view of software development and software team performance that centres around behavioural and social sciences.
Enterprise Architectures (EA) consist of a multitude of architecture elements, which relate in manifold ways to each other. As the change of a single element hence impacts various other elements, mechanisms for architecture analysis are important to stakeholders. The high number of relationships aggravates architecture analysis and makes it a complex yet important task. In practice EAs are often analyzed using visualizations. This article contributes to the field of visual analytics in enterprise architecture management (EAM) by reviewing how state-of-the-art software platforms in EAM support stakeholders with respect to providing and visualizing the “right” information for decision-making tasks. We investigate the collaborative decision-making process in an experiment with master students using professional EAM tools by developing a research study. We evaluate the students’ findings by comparing them with the experience of an enterprise architect.
An operating room is a stressful work environment. Nevertheless, all involved persons have to work safely as there is no space for mistakes. To ensure a high level of concentration and seamless interaction, all involved persons have to know their own tasks and the tasks of their colleagues. The entire team must work synchronously at all times. To optimize the overall workflow, a task manager supporting the team was developed. In parallel, a common conceptual design of a business process visualization was developed, which makes all relevant information accessible in real-time during a surgery. In this context an overview of all processes in the operating room was created and different concepts for the graphical representation of these user-dependent processes were developed. This paper describes the concept of the task manager as well as the general concept in the field of surgery.
The proposed approach applies current unsupervised clustering approaches in a different dynamic manner. Instead of taking all the data as input and finding clusters among them, the given approach clusters Holter ECG data (longterm electrocardiography data from a holter monitor) on a given interval which enables a dynamic clustering approach (DCA). Therefore advanced clustering techniques based on the well known Dynamic TimeWarping algorithm are used. Having clusters e.g. on a daily basis, clusters can be compared by defining cluster shape properties. Doing this gives a measure for variation in unsupervised cluster shapes and may reveal unknown changes in healthiness. Embedding this approach into wearable devices offers advantages over the current techniques. On the one hand users get feedback if their ECG data characteristic changes unforeseeable over time which makes early detection possible. On the other hand cluster properties like biggest or smallest cluster may help a doctor in making diagnoses or observing several patients. Further, on found clusters known processing techniques like stress detection or arrhythmia classification may be applied.
New business concepts such as Enterprise 2.0 foster the use of social software in enterprises. Especially social production significantly increases the amount of data in the context of business processes. Unfortunately, these data are still an unearthed treasure in many enterprises. Due to advances in data processing such as Big Data, the exploitation of context data becomes feasible. To provide a foundation for the methodical exploitation of context data, this paper introduces a classification, based on two classes, intrinsic and extrinsic data.
Modern enterprises reshape and transform continuously by a multitude of management processes with different perspectives. They range from business process management to IT service management and the management of the information systems. Enterprise Architecture (EA) management seeks to provide such a perspective and to align the diverse management perspectives. Therefore, EA management cannot rely on hierarchic - in a tayloristic manner designed - management processes to achieve and promote this alignment. It, conversely, has to apply bottom-up, information-centered coordination mechanisms to ensure that different management processes are aligned with each other and enterprise strategy. Social software provides such a bottom-up mechanism for providing support within EAM-processes. Consequently, challenges of EA management processes are investigated, and contributions of social software presented. A cockpit provides interactive functions and visualization methods to cope with this complexity and enable the practical use of social software in enterprise architecture management processes.
Leveraging textual information for improving decision making in the business process lifecycle
(2015)
Business process implementations fail, because requirements are elicited incompletely. At the same time, a huge amount of unstructured data is not used for decision-making during the business process lifecycle. Data from questionnaires and interviews is collected but not exploited because the effort doing so is too high. Therefore, this paper shows how to leverage textual information for improving decision making in the business process lifecycle. To do so, text mining is used for analyzing questionnaires and interviews.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change interacts with all information processes and systems that are important business enablers for the context of digitization since years. Our aim is to support flexibility and agile transformations for both business domains and related information technology and enterprise systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates collaborative decision mechanisms for adaptive digital enterprise architectures by extending original architecture reference models with state of art elements for agile architectural engineering for the digitization and collaborative architectural decision support.
Excellence in IT is both a driver and a key enabler of the digital transformation. The digital transformation changes the way we live, work, learn, communicate, and collaborate. The Internet of Things (IoT) fundamentally influences today’s digital strategies with disruptive business operating models and fast changing markets. New business information systems are integrating emerging Internet of Things infrastructures and components. With the huge diversity of Internet of Things technologies and products organizations have to leverage and extend previous Enterprise Architecture efforts to enable business value by integrating Internet of Things architectures. Both architecture engineering and management of current information systems and business models are complex and currently integrating beside the Internet of Things synergistic subjects, like Enterprise Architecture in context with services & cloud computing, semantic-based decision support through ontologies and knowledge-based systems, big data management, as well as mobility and collaboration networks. To provide adequate decision support for complex business/IT environments, we have to make transparent the impact of business and IT changes over the integral landscape of affected architectural capabilities, like directly and transitively impacted IoT-objects, business categories, processes, applications, services, platforms and infrastructures. The paper describes a new metamodel-based approach for integrating Internet of Things architectural objects, which are semi-automatically federated into a holistic Digital Enterprise Architecture environment.
Excellence in IT is a key enabler for the digital transformation of enterprises. To realize the vision of digital enterprises it is necessary to cope with changing business requirements and to align business and IT. In order to evaluate the contribution of enterprise architecture management to these goals, our paper explores the impact of various factors to the perceived benefit of EAM in enterprises. Based on literature, we build an empirical research model. It is tested with empirical data of European EAM experts using a structural equation modelling approach. It is shown that changing business requirements, IT business alignment, the complexity of information technology infrastructure as well as enterprise architecture knowledge of information technology employees are crucial impact factors to the perceived benefit of EAM in enterprises.
The Seventh International Conferences on Pervasive Patterns and Applications (PATTERNS 2015), held between March 22-27, 2015 in Nice, France, continued a series of events targeting the application of advanced patterns, at-large. In addition to support for patterns and pattern processing, special categories of patterns covering ubiquity, software, security, communications, discovery and decision were considered. It is believed that patterns play an important role on cognition, automation, and service computation and orchestration areas. Antipatterns come as a normal output as needed lessons learned.
In order to explore an image, the human eye functions like a spotlight, scanning the content from one object to the next. This visual search behavior is implemented with the help of attention control. The following work surveys the visual search behavior in "Wimmelpictures", a special type of busy pictures. The research objective is to analyze different search strategies and to work out possible differences concerning age and gender. The university experiment is carried out by an eye tracker that records the fixations and saccades of the test persons. The results indicate three forms of search strategy: based on a pattern, based on feature selection, or a mixture of both. Our data shows the search for special features of the target is the most successful. Furthermore there are no differences concerning gender but some concerning age. All age groups need more time to locate the target with an increasing number of distractors in the image. The size of the target is also relevant as a larger target is found more quickly than the smaller one.
Knowledge is an important resource, whose transfer is still not completely understood. The underlying belief of this thesis is that knowledge cannot be transferred directly from one person to another but must be converted for the transfer and therefore is subject to loss of knowledge and misunderstanding. This thesis proposes a new model for knowledge transfer and empirically evaluates this model. The model is based on the belief that knowledge must be encoded by the sender to transfer it to the receiver, who has to decode the message to obtain knowledge.
To prepare for the model this thesis provides an overview about models for knowledge transfer and factors that influence knowledge transfer. The proposed theoretical model for knowledge transfer is implemented in a prototype to demonstrate its applicability. The model describes the influence of the four layers, namely code, syntactic, semantic, and pragmatic layers, on the encoding and decoding of the message. The precise description of the influencing factors and the overlapping knowledge from sender and receiver facilitate its implementation.
The application area of the layered model for knowledge transfer was chosen to be business process modelling. Business processes incorporate an important knowledge resource of an organisation as they describe the procedures for the production of products and services. The implementation in a software prototype allows a precise description of the process by adding semantic to the simple business process modelling language used.
This thesis contributes to the body of knowledge by providing a new model for knowledge transfer, which shows the process of knowledge transfer in greater detail and highlights influencing factors. The implementation in the area of business process modelling reveals the support provided by the model. An expert evaluation indicates that the implementation of the proposed model supports knowledge transfer in business process modelling. The results of the qualitative evaluation are supported by the findings of a qualitative evaluation, performed as a quasi-experiment with a pre-test/post-test design and two experimental groups and one control group. Mann-Whitney U tests indicated that the group that used the tool that implemented the layered model performed significantly better in terms of completeness (the degree of completeness achieved in the transfer) in comparison with the group that used a standard BPM tool (Z = 3.057, p = 0.002, r = 0.59) and the control group that used pen and paper (Z = 3.859, p < 0.001, r = 0.72). The experiment indicates that the implementation of the layered model supports the creation of a business process and facilitates a more precise representation.
In recent years, the rise of the digital transformation received significant importance in Business-to-Business (B2B) research. Social media applications provide executives with a raft of new options. Consequently, interfaces to social media platforms have also been integrated into B2B salesforce applications, although very little is as yet known about their usage and general impact on B2B sales performance. This paper evaluates 1) the conceptualization of social media usage in a dyadic B2B relationship; 2) the effects of a more differentiated usage construct on customer satisfaction; 3) antecedents of social media usage on multiple levels; and 4) the effectiveness of social media usage for different types of customers. The framework presented here is tested cross-industry against data collected from dyadic buyer seller relationships in the IT service industry. The results elucidate the preconditions and the impact of social media usage strategies in B2B sales relations.
Customer services in the digital transformation: social media versus hotline channel performance
(2015)
Due to the digital transformation online service strategies have gained prominence in practice as well as in the theory of service management. This study examines the efficacy of different types of service channels in customer complaint handling. The theoretical framework, developed using complaint handling and social media literature, is tested against data collected from two different channels (hotline and social media) of a German telecommunication service provider. We contribute to the understanding of firm’s multichannel distribution strategy in two ways: a) by conceptualizing and evaluating complaint handling quality across traditional and social media channels, and b) by testing the impact of complaint handling quality on key performance outcomes like customer loyalty, positive word-of-mouth, and cross purchase intentions.
The stimulation of user engagement has received significant attention in extant research. However, the theory of antecedents for user engagement with an initial electronic word-of-mouth (eWoM) communication is relatively less developed. In an investigation of 576 unique user postings across independent Facebook (FB) communities for two German firms, we contribute to the extant knowledge on user engagement in two different ways. First, we explicate senders’ prior usage experience and the extent of their acquaintance with other community members as the two key drivers of user engagement across a product and a service community. Second, we reveal that these main effects differ according to the type of community. In service communities, experience has a stronger impact on user engagement; whereas, in product communities, acquaintance is more important.
Social media usage in business-to-business sales : conceptualization, antecedents, and outcomes
(2015)
In recent years, the rise of social media received significant importance in marketing research. Social media applications now provide executives with a raft of new options. Consequently, interfaces to social media platforms have also been integrated into Business to-Business (B2B) salesforce applications, although very little is as yet known about their usage and general impact on B2B sales performance. This paper evaluates 1) the conceptualization of social media usage in a dyadic B2B relationship; 2) the effects of a more differentiated usage construct on customer satisfaction; 3) antecedents of social media usage on multiple levels; and 4) the effectiveness of social media usage for different types of customers. The framework presented here is tested cross-industry against data collected from dyadic buyer seller relationships in the IT service industry. The results elucidate the preconditions and the impact of social media usage strategies in B2B sales relations.
In recent years, the rise of social media received significant importance in marketing research and practice. Consequently, interfaces to social media platforms have also been integrated into Business-to-Business (B2B) salesforce applications, although very little is as yet known about their usage and general impact on B2B sales performance. This paper evaluates 1) the conceptualization of social media usage in dyadic B2B relationships; 2) the effects of a more differentiated usage construct on customer satisfaction; 3) antecedents of social media usage on multiple levels; and 4) the effectiveness of social media usage for different types of cus-tomers. The framework presented here is tested cross-industry against data collected from dyadic buyer-seller relationships in the IT service industry. The results elucidate the precondi-tions and the impact of social media usage strategies in B2B sales relations.
Purpose: This paper aims to conceptualize and empirically test the determinants of service interaction quality (SIQ) as attitude, behavior and expertise of a service provider (SP). Further, the individual and simultaneous effects of SIQ and its dimensions on important marketing outcomes are tested. Design/methodology/approach – The narrative review of extant research helps formulate a conceptual model of SIQ, which is investigated using the univariate and multivariate meta-analysis.
Findings: There are interdependencies between drivers of SIQ that underlines the need to conceptualize service interaction as a dyadic phenomenon; use contemporary multilevel models, dyadic models, non-linear structural equation modeling and process studies; and study new and diverse services contexts. Meta-analysis illustrates the relative importance of the three drivers of SIQ and, in turn, their impact on consumer satisfaction and loyalty.
Research limitations/implications – The meta-analysis is based on existing research, which, unfortunately, has not examined critical services or exigency situations where SIQ is of paramount importance. Future research will be tasked with diversifying to several important domains where SIQ is a critical aspect of perceived service quality.
Practical implications: This study emphasizes that, although the expertise of an SP is important, firms would be surprised to learn that the attitude and behavior of their employees are equally important antecedents. In fact, there is a delicate balance that needs to be found; otherwise, attitudinal factors can have an overall counterproductive effect on consumer satisfaction.
Originality/value: This paper provides an empirical synthesis of SIQ and opens up interesting areas for further research.
Management nowadays is confronted by a variety of information originating from either internal or external sources. Thereby, the difficulty to focus on the relevant and company critical keyfigures information increases. In practice, information management is often a major weakness of efficient corporate management. That weakness is caused by the lack of a centralized, categorized and summarized presentation and analysis of strategy and decision-relevant information. Management cockpits, a kind of information center for managers, are an approach to meet the challenges of information management. They are a specific work environment for decision makers to get a quick and simple overview of the company’s economic situation. In the most completely equipped premises, the entire process is supported - from acquiring information, to analysis, decision-making, and communication. Use of management cockpits, a cross-functional, KPI-based and strategyoriented controlling and management process, can be successfully established in companies as well as the work of interdisciplinary management teams, which are supported. In order to provide these possibilities, the management cockpit is equipped with a range of functionalities that allow the structuring, categorization and management-adequate visualization of information along with extensive analysis and simulation options. Management cockpits, as a communication and collaboration platform, are a starting point and valuable process companion on the way to holistic and sustainable performance management.
In modern times markets are very dynamic. This situation requires agile enterprises to have the ability to react fast on market influences. Thereby an enterprise’ IT is especially affected, because new or changed business models have to be realized. However, enterprise architectures (EA) are complex structures consisting of many artifacts and relationships between them. Thus analyzing an EA becomes to a complex task for stakeholders. In addition, many stakeholders are involved in decision-making processes, because Enterprise Architecture Management (EAM) targets providing a holistic view of the enterprise. In this article we use concepts of Adaptive Case Management (ACM) to design a decision-making case consisting of a combination of different analysis techniques to support stakeholders in decision-making. We exemplify the case with a scenario of a fictive enterprise.
This paper presents a concurrency control mechanism that does not follow a ‘one concurrency control mechanism fits all needs’ strategy. With the presented mechanism a transaction runs under several concurrency control mechanisms and the appropriate one is chosen based on the accessed data. For this purpose, the data is divided into four classes based on its access type and usage (semantics). Class O (the optimistic class) implements a first-committer-wins strategy, class R (the reconciliation class) implements a first-n-committers-win strategy, class P (the pessimistic class) implements a first reader-wins strategy, and class E (the escrow class) implements a firsnreaderswin strategy. Accordingly, the model is called OjRjPjE. Under this model the TPC-C benchmark outperforms other CC mechanisms like optimistic Snapshot Isolation.
In a world with rapidly changing customer requirements and the increased role of technology, companies need more flexible systems to adapt their processes and react dynamically to changes. Adaptive Case Management (ACM) comes into consideration by providing a concept to adapt to changing business conditions. Within our research project we did a first foundational evaluation of the potential of ACM in supporting unpredictable sales processes. Based on a set of criteria we tested the concept of ACM with the open source tool Cognoscenti. The evaluation gave us the possibility to experience the concept of ACM. Hence we were able to provide a statement about the potential of ACM within the context of an unpredictable sales process, setting the path to further research and discussion of ACM in the area of sales processes.
The Seventh International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2015), held between May 24-29, 2015 in Rome, Italy, continued a series of international events covering a large spectrum of topics related to advances in fundamentals on databases, evolution of relation between databases and other domains, data base Technologies and content processing, as well as specifics in applications domains databases. Advances in different technologies and domains related to databases triggered substantial improvements for content processing, information indexing, and data, process and knowledge mining. The push came from Web services, artificial intelligence, and Agent technologies, as well as from the generalization of the XML adoption. High-speed communications and computations, large storage capacities, and loadbalancing for distributed databases access allow new approaches for content processing with incomplete patterns, advanced ranking algorithms and advanced indexing methods. Evolution on e-business, e-health and telemedicine, bioinformatics, finance and marketing, geographical positioning systems put pressure on database communities to push the ‘de facto’ methods to support new requirements in terms of scalability, privacy, performance, indexing, and heterogeneity of both content and technology.
Distraction of the driver is one of the most frequent causes for car accidents. We aim for a computational cognitive model predicting the driver’s degree of distraction during driving while performing a secondary task, such as talking with co-passengers. The secondary task might cognitively involve the driver to differing degrees depending on the topic of the conversation or the number of co-passengers. In order to detect these subtle differences in everyday driving situations, we aim to analyse in-car audio signals and combine this information with head pose and face tracking information. In the first step, we will assess driving, video and audio parameters reliably predicting cognitive distraction of the driver. These parameters will be used to train the cognitive model in estimating the degree of the driver’s distraction. In the second step, we will train and test the cognitive model during conversations of the driver with co-passengers during active driving. This paper describes the work in progress of our first experiment with preliminary results concerning driving parameters corresponding to the driver’s degree of distraction. In addition, the technical implementation of our experiment combining driving, video and audio data and first methodological results concerning the auditory analysis will be presented. The overall aim for the application of the cognitive distraction model is the development of a mobile user profile computing the individual distraction degree and being applicable also to other systems.
Small and medium-sized enterprises (SMEs) play a fundamental role in the economic system of the European Union: SMEs represent over 99 percent of all companies and provide two-thirds of the jobs in the private sector. Their innovativeness and economic success have significant influence on growth, jobs and prosperity in Europe.
Information technologies are regarded as key drivers of innovation in small and medium-sized enterprises (SME). Modern information technologies (IT) offer SMEs today many opportunities to improve their competitiveness and market position. Thus, business processes can be designed efficiently, open up new market segments and strengthen the innovation capacity significantly. However, many SMEs still have difficulties in utilizing these new technologies efficiently in order to foster process and product innovation. This is partly due to the fact that many SMEs don’t use IT Service Management and waste resources in running basic IT-functions like the maintenance of printers, software or servers.
Information Technology Service Management (ITSM) is a discipline for managing IT systems centred on the customer’s perspective of IT’s contribution to the business. Thus, by strengthening the performance of SME’s IT departments, ITSM enables process innovation (e.g. eProcurement) and product innovations (e.g. client services) can be promoted. The EU-funded project "IT Service Management for small and medium-sized Enterprises of the Danube Region" (ITSM4SME) aims to make SMEs in the Danube Region aware of the potential of ITSM, to inspire SMEs about the use of information technology and to allow IT-enabled innovations. The aims of the project have been achieved inter alia through a simplified method for IT service management for small IT organisations, practical case studies, a "do-it-yourself" service management modelling tool, an eLearning portal and by training more than 300 participants from SMEs in pilot training courses in Bulgaria, Romania and Slovenia.
Saving energy and protecting the environment became fundamental for society and politics, why several laws were enacted to increase the energy-efficiency. Furthermore, the growing number of vehicles and drivers leaded to more accidents and fatalities on the roads, why road safety became an important factor as well. Due to the increasing importance of energy-efficiency and safety, car manufacturers started to optimise the vehicle in terms of energy-effciency and safety. However, energy-efficiency and road safety can be also increased by adapting the driving behaviour to the given driving situation. This thesis presents a concept of an adaptive and rule based driving system that tries to educate the driver in energy-efficient and safe driving by showing recommendations on time. Unlike existing driving-systems, the presented driving system considers energy-efficiency and safety relevant driving rules, the individual driving behaviour and the driver condition. This allows to avoid the distraction of the driver and to increase the acceptance of the driving system, while improving the driving behaviour in terms of energy-efficiency and safety. A prototype of the driving system was developed and evaluated. The evaluation was done on a driving simulator using 42 test drivers, who tested the effect of the driving system on the driving behaviour and the effect of the adaptiveness of the driving system on the user acceptance. It has been proven during the evaluation that the energy-efficiency and safety can be increased, when the driving system was used. Furthermore, it has been proven that the user acceptance of the driving system increases when the adaptive feature was turned on. A high user acceptance of the driving system allows a steady usage of the driving system and, thus, a steady improvement of the driving behaviour in terms of energy-efficiency and safety.