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The digital transformation of the automotive industry has a significant impact on how development processes need to be organized in future. Dynamic market and technological environments require capabilities to react on changes and to learn fast. Agile methods are a promising approach to address these needs but they are not tailored to the specific characteristics of the automotive domain like product line development. Although, there have been efforts to apply agile methods in the automotive domain for many years, significant and widespread adoptions have not yet taken place. The goal of this literature review is to gain an overview and a better understanding of agile methods for embedded software development in the automotive domain, especially with respect to product line development. A mapping study was conducted to analyze the relation between agile software development, embedded software development in the automotive domain and software product line development. Three research questions were defined and 68 papers were evaluated. The study shows that agile and product line development approaches tailored for the automotive domain are not yet fully explored in the literature. Especially, literature on the combination of agile and product line development is rare. Most of the examined combinations are customizations of generic approaches or approaches stemming from other domains. Although, only few approaches for combining agile and software product line development in the automotive domain were found, these findings were valuable for identifying research gaps and provide insights into how existing approaches can be combined, extended and tailored to suit the characteristics of the automotive domain.
Scheduled flexibility and individualization of knowledge transfer in foundations of computer science
(2017)
The opening of the German higher education system for new target groups involves a heterogeneous composition of students as never before and face up the universities to new challenges. Due to different educational biographies, the students don't show a homogeneous level of knowledge. Furthermore, their access to course content and their individual learning methods are very diverse. The existing lack of knowledge and the very unequal study speed have a significant influence on the learning behavior and learning motivation. During the first semesters, the dropout rate is appreciably higher. The reform project gives an overview of a didactic restructuring from a formerly conventional teaching and learning concept to a stronger combination of digital offers, combined with classical lectures in the basic modules of computer science. The teaching content is adjusted to the individual requirements and knowledge. Students with different previous knowledge get the possibility to increase their knowledge in different levels of abstraction. The aim of the reform project has to point out the possibilities, also the challenges of the digital process in higher education. At the same time the question has to be explored, how far does an accompanied and self-directed learning in own speed and in own individual depth of knowledge have a positive impact on the motivation and on the study success of a learner.
Medical applications are becoming increasingly important in the current development of health care and therefore a crucial part of the medical industry. The work focuses on the analysis of requirements and the challenges arisen from designing mobile medical applications in relation to the user interface. The paper describes the current status in the development of mobile medical apps and illustrates the development of e-health market. The author will explain the requirements and will illustrate the hurdles and problems. He refers to the German market which is similar to the European and compares that with the market in the USA.
Context: The current situation and future scenarios of the automotive domain require a new strategy to develop high quality software in a fast pace. In the automotive domain, it is assumed that a combination of agile development practices and software product lines is beneficial, in order to be capable to handle high frequency of improvements. This assumption is based on the understanding that agile methods introduce more flexibility in short development intervals. Software product lines help to manage the high amount of variants and to improve quality by reuse of software for long term development.
Goal: This study derives a better understanding of the expected benefits for a combination. Furthermore, it identifies the automotive specific challenges that prevent the adoption of agile methods within the software product line.
Method: Survey based on 16 semi structured interviews from the automotive domain, an internal workshop with 40 participants and a discussion round on ESE congress 2016. The results are analyzed by means of thematic coding.
In this work we investigate the behavior of MIS- and Schottky-gate AlGaN/GaN HEMTs under high-power pulsestress. A special setup capable of applying pulses of constant power is used to evaluate the electro-thermal response in different operating points. For both types of devices, the time to failure was found to decrease with increasing drain-source voltage. Overall, the Schottky-gate device displays a higher pulse robustness. The pulse withstand time of the MIS-gate device is limited by the occurrence of a thermal instability at approximately 240°C while the Schottky-gate device displays a rapid increase of the gate leakage current prior to failure. The mechanism responsible for this gate current is further investigated by static and transient temperature measurements and yielded activation energies of 0.6 eV and 0.84 eV.
To assess the quality of a person’s sleep, it is essential to examine the sleep behaviour by identifying the several sleep stages, their durations and sleep cycles. The established and gold standard procedure for sleep stage scoring is overnight polysomnography (PSG) with the Rechtschaffen and Kales (R-K) method. Unfortunately, the conduct of PSG is time-consuming and unfamiliar for the subjects and might have an impact of the recorded data. To avoid the disadvantages with PSG, it is important to make further investigations in low-cost home diagnostic systems. For this intention it is necessary to find suitable bio vital parameters for classifying sleep stages without any physical impairments at the same time. Due to the promising results in several publications we want to analyse existing methods for sleep stage classification based on the parameters body movement,
heartbeat and respiration. Our aim was to find different behaviour patterns in the several sleep stages. Therefore, the average values of 15 whole-night PSG recordings -obtained from the ‘DREAMS
Subjects Database’- where analysed in the light of heartbeat, body movement and respiration with 10 different methods.
In a digitally controlled slope shaping system, reliable detection of both voltage and current slope is required to enable a closed-loop control for various power switches independent of system parameters. In most state-of-the-art works, this is realized by monitoring the absolute voltage and current values. Better accuracy at lower DC power loss is achieved by sensing techniques for a reliable passive detection, which is achieved through avoiding DC paths from the high voltage network into the sensing network. Using a high-speed analog-to-digital converter, the whole waveform of the transient derivative can be stored digitally and prepared for a predictive cycle-by-cycle regulation, without requiring high-precision digital differentiation algorithms. To gain an accurate representation of the voltage and current derivative waveforms, system parasitics are investigated and classified in three sections: (1) component parasitics, which are identified by s-parameter measurements and extraction of equivalent circuit models, (2) PCB design issues related to the sensing circuit, and (3) interconnections between adjacent boards.
The contribution of this paper is an optimized sensing network on the basis of the experimental study supporting fast transition slopes up to 100 V/ns and 1 A/ns and beyond, making the sensing technique attractive for slope shaping of fast switching devices like modern generation IGBTs, CoolMOSTM and SiC mosfets. Measurements of the optimized dv/dt and di/dt setups are demonstrated for a hard switched IGBT power stage.
This paper presents a control strategy for optimal utilization of photovoltaic (PV) generated power in conjunction with an Energy Storage System (ESS). The ESS is specifically designed to be retrofitted into existing PV systems in an end-user application. It can be attached in parallel to the PV system and connects to existing DC/AC inverters. In particular, the study covers the impact such a modification has on the output power of existing PV panels. A distinct degradation of PV output power was found due to the different power characteristics of PV panel and ESS. To overcome such degradation a novel feedback system is proposed. The feedback system continuously modifies the power characteristic of the ESS to match the PV panel and thus achieves optimal power utilization. Impact on PV and power point tracking performance is analyzed. Simulation of the proposed system is performed in MATLAB/Simulink. The results are found to be satisfactory.
The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change drive current and next 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 with more flexible enterprise information systems through adaptation and evolution of digital architectures. The present research paper investigates the continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, like microservices and the Internet of Things, as part of a new composed digital architecture. To integrate micro-granular architecture models into living architectural model versions we are extending enterprise architecture reference models by state of art elements for agile architectural engineering to support digital products, services, and processes.
In this paper we claim that a competitive analysis with new players entering a market requires a specific and systems-based analysis. System dynamics provides such an approach. We infer from our study that established premium automobile manufacturers could have identified a possible threat by a newcomer like Tesla earlier with using system dynamics. In particular, we postulate that a feedback view supports decision makers to better understand the significance of competitive information and perceive information faster and more reliably.
This paper presents a novel multi-modal CNN architecture that exploits complementary input cues in addition to sole color information. The joint model implements a mid-level fusion that allows the network to exploit cross modal interdependencies already on a medium feature-level. The benefit of the presented architecture is shown for the RGB-D image understanding task. So far, state-of-the-art RGB-D CNNs have used network weights trained on color data. In contrast, a superior initialization scheme is proposed to pre-train the depth branch of the multi-modal CNN independently. In an end-to-end training the network parameters are optimized jointly using the challenging Cityscapes dataset. In thorough experiments, the effectiveness of the proposed model is shown. Both, the RGB GoogLeNet and further RGB-D baselines are outperformed with a significant margin on two different tasks: semantic segmentation and object detection. For the latter, this paper shows how to extract object level groundtruth from the instance level annotations in Cityscapes in order to train a powerful object detector.
Characteristics of modern computing and storage technologies fundamentally differ from traditional hardware. There is a need to optimally leverage their performance, endurance and energy consumption characteristics. Therefore, existing architectures and algorithms in modern high performance database management systems have to be redesigned and advanced. Multi Version Concurrency Control (MVCC) approaches in data-base management systems maintain multiple physically independent tuple versions. Snapshot isolation approaches enable high parallelism and concurrency in workloads with almost serializable consistency level. Modern hardware technologies benefit from multi-version approaches. Indexing multi-version data on modern hardware is still an open research area. In this paper, we provide a survey of popular multi-version indexing approaches and an extended scope of high performance single-version approaches. An optimal multi-version index structure brings look-up efficiency of tuple versions, which are visible to transactions, and effort on index maintenance in balance for different workloads on modern hardware technologies.
Social networks, smart portable devices, Internet of Things (IoT) on base of technologies like analytics for big data and cloud services are emerging to support flexible connected products and agile services as the new wave of digital transformation. Biological metaphors of living and adaptable ecosystems with service-oriented enterprise architectures provide the foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems. We are extending Enterprise Architecture (EA) with mechanisms for flexible adaptation and evolution of information systems having distributed IoT and other micro-granular digital architecture to support next digitization products, services, and processes. Our aim is to support flexibility and agile transformation for both IT and business capabilities through adaptive digital enterprise architectures. The present research paper investigates additionally decision mechanisms in the context of multi-perspective explorations of enterprise services and Internet of Things architectures by extending original enterprise architecture reference models with state of art elements for architectural engineering and digitization.
This paper models the political budget cycle with stochastic differential equations. The paper highlights the development of future volatility of the budget cycle. In fact, I confirm the proposition of a less volatile budget cycle in future. Moreover, I show that this trend is even amplified due to higher transparency. These findings are new evidence in the literature on electoral cycles. I calibrate a rigorous stochastic model on public deficit-to-GDP data for several countries from 1970 to 2012.
In an exploratory study about online communication of large and medium-sized B2B companies from the German state of Baden-Württemberg, their message content communicated via websites, and their websites' appeal for international prospects has been analyzed. It revealed many basic content items absent, making the site less attractive for further exploration, and difficult or international prospects to enter into a dialog, become leads, and possible customers. The subsequent survey elicited organizational backgrounds, available resources, and objectives for online communication. It could trace deficiencies back to a lack of understanding of the importance of digital communication for lead generation, and the customer journey in general, absence of a communication strategy, lack of urgency, and lack of resources to implement desired changes and additions to communication content.
As the market penetration of alternative fuel vehicles is still uncertain, defining green design cues for their design is of specific relevance to target environmentally conscious customers. This paper is a review of the existing literature aiming at summarizing the market penetration scenarios of alternative fuel vehicles over the next years, consumer demand for sustainable materials, and present methodologies to represent characteristics of eco-friendly mobility in the interior of alternative fuel vehicles. In particular, present attempts to correlate materials with green design cues are explored. Finally, projections for the future of the field are suggested, posing enchanting research questions to further unify the field of environmentally conscious design with the domain of product personality.
Managing decentralized corporate energy systems is a challenging task for enterprises. However, the integration of energy objectives into business strategy creates difficulties resulting in inefficient decisions. To improve this, practice-proven methods such as the balanced scorecard and enterprise architecture management are transferred to the energy domain. The methods are evaluated based on a case study. Managing multi-dimensionality and high complexity are the main drivers for an effective and efficient energy management system. Both methods show a positive impact on managing decentralized corporate energy systems and are adaptable to the energy domain.
Understanding the factors that influence the accuracy of visual SLAM algorithms is very important for the future development of these algorithms. So far very few studies have done this. In this paper, a simulation model is presented and used to investigate the effect of the number of scene points tracked, the effect of the baseline length in triangulation and the influence of image point location uncertainty. It is shown that the latter is very critical, while the other all play important roles. Experiments with a well known semi-dense visual SLAM approach are also presented, when used in a monocular visual odometry mode. The experiments show that not including sensor bias and scale factor uncertainty is very detrimental to the accuracy of the simulation results.
In any autonomous driving system, the map for localization plays a vital part that is often underestimated. The map describes the world around the vehicle outside of the sensor view and is a main input into the decision making process in highly complicated scenarios. Thus there are strict requirements towards the accuracy and timeliness of the map. We present a robust and reliable approach towards crowd based mapping using a GraphSLAM framework based on radar sensors. We show on a parking lot that even in dynamically changing environments, the localization results are very accurate and reliable even in unexplored terrain without any map data. This can be achieved by collaborative map updates from multiple vehicles. To show these claims experimentally, the Joint Graph Optimization is compared to the ground truth on an industrial parking space. Mapping performance is evaluated using a dense map from a total station as reference and localization results are compared with a deeply coupled DGPS/INS system.
Incubators in multinational corporations : development of a corporate incubator operator model
(2017)
This paper analyzes the components of a corporate incubator operator model in multinational companies. Thereby, three relevant phases were identified: pre incubation, incubation, and exit. Each phase contains different criteria that represent critical success factors for a corporate incubator, which are based on theoretical findings and lessons learned from practice. During the pre-incubation phase companies should define their need for a corporate incubator, the origin of ideas and the selection criteria for incubator tenants. The actual phase of incubation refers to the incubator program, which should be flexible with respect to each tenant. Furthermore, resource allocation plays an important role during the incubator program. Exit options after a successful incubation differ according to internal ideas and external start-ups, as well as the objective of the incubator. The research is based on a comprehensive screening of existing incubator literature and a qualitative content analysis of statements from eight experts of international corporate incubators.
In the present paper we demonstrate a novel approach to handling small updates on Flash called In-Place Appends (IPA). It allows the DBMS to revisit the traditional write behavior on Flash. Instead of writing whole database pages upon an update in an out-of-place manner on Flash, we transform those small updates into update deltas and append them to a reserved area on the very same physical Flash page. In doing so we utilize the commonly ignored fact that under certain conditions Flash memories can support in-place updates to Flash pages without a preceding erase operation.
The approach was implemented under Shore-MT and evaluated on real hardware. Under standard update-intensive workloads we observed 67% less page invalidations resulting in 80% lower garbage collection overhead, which yields a 45% increase in transactional throughput, while doubling Flash longevity at the same time. The IPA outperforms In-Page Logging (IPL) by more than 50%.
We showcase a Shore-MT based prototype of the above approach, operating on real Flash hardware – the OpenSSD Flash research platform. During the demonstration we allow the users to interact with the system and gain hands on experience of its performance under different demonstration scenarios. These involve various workloads such as TPC-B, TPC-C or TATP.
In recent times, enterprises have been increasingly dealing with the use of social media in internal communication and collaboration. In particular, so-called Enterprise Social Networks (ESN) promise meaningful benefits for the nature of work in corporations. However, these platforms often suffer from poor degrees of use. This raises the question of what initiatives enterprise can launch in order to stimulate the vitality of ESN. Since the use of ESN is often voluntary, individual adoption by employees need to be examined to find an answer. Therefore, the Unified Theory of Acceptance and Use of Technology (UTAUT) model was selected for the theoretical foundation of this paper. Following a qualitative research approach, the available research provides an analysis of expert interviews on specific ESN implementation strategies and included factors. In order to extensively conceptualize and generalize these strategic considerations, we conducted an inductive coding process. The results reveal that ESN implementation strategies can be understood as a multi-level construct (individual vs. group vs. organizational level) containing different factors dependent on the degree of documentation and intensity. This research in progress describes a qualitative evaluation as a preliminary study for further quantitative analysis of an ESN adoption model.
Software and system development faces numerous challenges of rapidly changing markets. To address such challenges, companies and projects design and adopt specific development approaches by combining well-structured comprehensive methods and flexible agile practices. Yet, the number of methods and practices is large, and available studies argue that the actual process composition is carried out in a fairly ad-hoc manner. The present paper reports on a survey on hybrid software development approaches. We study which approaches are used in practice, how different approaches are combined, and what contextual factors influence the use and combination of hybrid software development approaches. Our results from 69 study participants show a variety of development approaches used and combined in practice. We show that most combinations follow a pattern in which a traditional process model serves as framework in which several fine-grained (agile) practices are plugged in. We further show that hybrid software development approaches are independent from the company size and external triggers. We conclude that such approaches are the results of a natural process evolution, which is mainly driven by experience, learning, and pragmatism.
Software startups often make assumptions about the problems and customers they are addressing as well as the market and the solutions they are developing. Testing the right assumptions early is a means to mitigate risks. Approaches such as Lean Startup foster this kind of testing by applying experimentation as part of a constant build-measure-learn feedback loop. The existing research on how software startups approach experimentation is very limited. In this study, we focus on understanding how software startups approach experimentation and identify challenges and advantages with respect to conducting experiments. To achieve this, we conducted a qualitative interview study. The initial results show that startups often spent a disproportionate amount of time focusing on creating solutions without testing critical assumptions. Main reasons are the lack of awareness, that these assumptions can be tested early and a lack of knowledge and support on how to identify, prioritize and test these assumptions. However, startups understand the need for testing risky assumptions and are open to conducting experiments.
Medical applications are becoming increasingly important in the current development of health care and therefore a crucial part of the medical industry. An essential component is the development of user interfaces for mobile medical applications. The conceptual process is crucial for the further development of the main development process. Inconsistency or errors in the conceptual phase, have a serious impact on all areas and could prevent the certification for market approval.
This paper presents a guide to support developer with this process. It was developed based on a requirement analysis of the legal requirements to publish a medical device.
Under update intensive workloads (TPC, LinkBench) small updates dominate the write behavior, e.g. 70% of all updates change less than 10 bytes across all TPC OLTP workloads. These are typically performed as in-place updates and result in random writes in page-granularity, causing major write-overhead on Flash storage, a write amplification of several hundred times and lower device longevity.
In this paper we propose an approach that transforms those small in-place updates into small update deltas that are appended to the original page. We utilize the commonly ignored fact that modern Flash memories (SLC, MLC, 3D NAND) can handle appends to already programmed physical pages by using various low-level techniques such as ISPP to avoid expensive erases and page migrations. Furthermore, we extend the traditional NSM page-layout with a delta-record area that can absorb those small updates. We propose a scheme to control the write behavior as well as the space allocation and sizing of database pages.
The proposed approach has been implemented under Shore- MT and evaluated on real Flash hardware (OpenSSD) and a Flash emulator. Compared to In-Page Logging it performs up to 62% less reads and writes and up to 74% less erases on a range of workloads. The experimental evaluation indicates: (i) significant reduction of erase operations resulting in twice the longevity of Flash devices under update-intensive workloads; (ii) 15%-60% lower read/write I/O latencies; (iii) up to 45% higher transactional throughput; (iv) 2x to 3x reduction in overall write
amplification.
Layout generators, commonly denoted as PCells (parameterized cells), play an important role in the layout design of analog ICs (integrated circuits). PCells can automatically create parts of a layout, whose properties are controlled by the PCell parameters. Any layout, whether hand-crafted or automatically generated, has to be verified against design rules using a DRC (design rule check) in order to assure proper functionality and producibility. Due to the growing complexity of today’s PCells it would be beneficial if a PCell itself could be ensured to produce DRC clean layouts for any allowed parameter values, i.e. a formal verification of the PCell’s code rather than checking all possible instances of the PCell. In this paper we demonstrate the feasibility of such a formal PCell verification for a simple NMOS transistor PCell. The set from which the parameter values can be chosen was found during the verification process.
The ability to develop and deploy high-quality software at a high speed gets increasing relevance for the comptetitiveness of car manufacturers. Agile practices have shown benefits such as faster time to market in several application domains. Therefore, it seems to be promising to carefully adopt agile practices also in the automotive domain. This article presents findings from an interview-based qualitative survey. It aims at understanding perceived forces that support agile adoption. Particularly, it focuses on embedded software development for electronic control units in the automotive domain.
First International Workshop on Hybrid dEveLopmENt Approaches in Software Systems Development
(2017)
A software process is the game plan to organize project teams and run projects. Yet, it still is a challenge to select the appropriate development approach for the respective context. A multitude of development approaches compete for the users’ favor, but there is no silver bullet serving all possible setups. Moreover, recent research as well as experience from practice shows companies utilizing different development approaches to assemble the bestfitting approach for the respective company: a more traditional process provides the basic framework to serve the organization, while project teams embody this framework with more agile (and/or lean) practices to keep their flexibility. The first HELENA workshop aims to bring together the community to discuss recent findings and to steer future work.
Pokémon Go was the first mobile Augmented Reality (AR) game that made it to the top of the download charts of mobile applications. However, very little is known about this new generation of mobile online Augmented Reality (AR) games. Existing media usage and technology acceptance theories provide limited applicability to the understanding of its users. Against this background, this research provides a comprehensive framework that incorporates findings from uses & gratification theory (U>), technology acceptance and risk research as well as flow theory. The proposed framework aims at explaining the drivers of attitudinal and intentional reactions, such as continuance in gaming or willingness to conduct in-app purchases. A survey among 642 Pokémon Go players provides insights into the psychological drivers of mobile AR games. Results show that hedonic, emotional and social benefits, and social norms drive, vice versa physical risks (but not privacy risks) hinder consumer reactions. However, the importance of these drivers differs between different forms of user behavior.
Electronic word-of-mouth (eWoM) communication plays an increasingly important role in modern business. The underlying concept of word-of-mouth (WoM) communication is well researched and has proved highly significant in respect of its impact on customers purchase behavior. However, due to the advent of digital technologies, decision-making among customers is progressively shifting to the online world. Consequently, eWoM has received a lot of attention from the academic community. As multiple research papers focus on specific facets of eWoM, there is a need to integrate current research results systematically. Thus, this paper presents a scientific literature analysis in order to determine the current state-of-the-art in the field of eWoM. Five main research areas were analyzed, supporting the need for further eWoM studies and providing a structured overview of existing results.
In this paper we build on our research in data management on native Flash storage. In particular we demonstrate the advantages of intelligent data placement strategies. To effectively manage phsical Flash space and organize the data on it, we utilize novel storage structures such as regions and groups. These are coupled to common DBMS logical structures, thus require no extra overhead for the DBA. The experimental results indicate an improvement of up to 2x, which doubles the longevity of Flash SSD. During the demonstration the audience can experience the advantages of the proposed approach on real Flash hardware.
A concept for a slope shaping gate driver IC is proposed, used to establish control over the slew rates of current and voltage during the turn-on and turn off switching transients.
It combines the high speed and linearity of a fully-integrated closed-loop analog gate driver, which is able to perform real-time regulation, with the advantages of digital control, like flexibility and parameter independency, operating in a predictive cycle-bycycle regulation. In this work, the analog gate drive integrated circuit is partitioned into functional blocks and modeled in the small-signal domain, which also includes the non-linearity of parameters. An analytical stability analysis has been performed in order to ensure full functionality of the system controlling a modern generation IGBT and a superjunction MOSFET. Major parameters of influence, such as gate resistor and summing node capacitance, are investigated to achieve stable control. The large-signal behavior, investigated by simulations of a transistor level design, verifies the correct operation of the circuit. Hence, the gate driver can be designed for robust operation.
In 2016, German car manufacturer the Audi Group (AUDI AG) was working on an expanding array of digital innovations. The goals of these innovations varied, and included strengthening customer- and employee-facing processes, digitally enhancing existing products, and developing new, potentially disruptive business models. Audi’s IT unit was critical to each of these efforts. Based on personal interviews with 11 IT- and non-IT executives at Audi, this case examines the different ways in which digitization can help to enhance and transform an organization’s processes, products, and business models. The case also highlights the challenges that arise as large companies “digitize.”
Recent digital technologies like the Internet of Things and Augmented Reality have brought IT into companies’ core products. What were previously purely physical products are becoming hybrid or digitized. Despite receiving a lot of recent attention, digitized products have only seen a slow uptake in businesses so far. In this paper, we study the challenges that keep companies from realizing the desired impacts of digitized products and the practices they employ to address these challenges. To do so, we looked at companies from a set of industries that are highly affected by digital transformation, but at the same time hesitant to move to a more digitized world: the creative industries. Based on a literature review and twelve interviews in creative industries, we developed a conceptual model that can serve as a basis for formulating testable hypotheses for further research in this area.
Digitization in the energy sector is a necessity to enable energy savings and energy efficiency potentials. Managing decentralized corporate energy systems is hindered by a non-existence. The required integration of energy objectives into business strategy creates difficulties resulting in inefficient decisions. To improve this, practice-proven methods such as Balanced Scorecard, Enterprise Architecture Management and the Value Network approach are transferred to the energy domain. The methods are evaluated based on a case study. Managing multi-dimensionality, high complexity and multiple actors are the main drivers for an effective and efficient energy management system. The underlying basis to gain the positive impacts of these methods on decentralized corporate energy systems is digitization of energy data and processes.
Digitization will require companies to fundamentally reengineer their sales processes. Adapting the concept of value selling to the digital age will enable them to deliver superior value to their customers. Specifically, social selling will provide them with an answer to the ever-increasing complexity of customer journeys. This article, based on a survey among 235 German companies, assesses the status quo and outlines opportunities. Moreover, it introduces a novel approach for developing well-grounded social selling metrics.
The third Digital Enterprise Computing Conference DEC 17 at the Herman Hollerith Center in Böblingen brings together students, researchers, and practitioners to discuss solutions, experiences, and future developments for the digital transformation. Digitization of business and IT defines the conference agenda: digital models & architecture, digital marketing, agility & innovation.
Clinical reading centers provide expertise for consistent, centralized analysis of medical data gathered in a distributed context. Accordingly, appropriate software solutions are required for the involved communication and data management processes. In this work, an analysis of general requirements and essential architectural and software design considerations for reading center information systems is provided. The identified patterns have been applied to the implementation of the reading center platform which is currently operated at the Center of Ophthalmology of the University Hospital of Tübingen.
In this paper we describe the design and development process of an electromagnetic picker for rivets. These rivets are used in a production process of leather or textile design objects like riveted waist belts or purses. The picker is designed such that it replaces conventional mechanical pickers thus avoiding mechanical wear problems and increasing the process quality. The paper illustrates the challenges in the design process of this mechatronic system. The design process was based on both simulation and experiments leading to a prototype that satisfies the requirements.
Digitization fosters the development of IT environments with many rather small structures, like Internet of Things (IoT), microservices, or mobility systems. They are needed to support flexible and agile digitized products and services. The goal is to create service-oriented enterprise architectures (EA) that are self optimizing and resilient. The present research paper investigates methods for decision-making concerning digitization architectures for Internet of Things and microservices. They are based on evolving enterprise architecture reference models and state of the art elements for architectural engineering for microgranular systems. Decision analytics in this field becomes increasingly complex and decision support, particularly for the development and evolution of sustainable enterprise architectures, is sorely needed. The challenging of the decision processes can be supported with in a more flexible and intuitive way by an architecture management cockpit.
The Ninth International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2017), held between May 21 - 25, 2017 - Barcelona, pain, 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.
Data Integration of heterogeneous data sources relies either on periodically transferring large amounts of data to a physical Data Warehouse or retrieving data from the sources on request only. The latter results in the creation of what is referred to as a virtual Data Warehouse, which is preferable when the use of the latest data is paramount. However, the downside is that it adds network traffic and suffers from performance degradation when the amount of data is high. In this paper, we propose the use of a readCheck validator to ensure the timeliness of the queried data and reduced data traffic. It is further shown that the readCheck allows transactions to update data in the data sources obeying full Atomicity, Consistency, Isolation, and Durability (ACID) properties.
The increasing number of connected mobile devices such as fitness trackers and smartphones define new data for health insurances, enabling them to gain deeper insights into the health of their customers. These additional data sources plus the trend towards an interconnected health community, including doctors, hospitals and insurers, lead to challenges regarding data filtering, organization and dissemination. First, we analyze what kind of information is relevant for a digital health insurance. Second, functional and non-functional requirements for storing and managing health data in an interconnected environment are defined. Third, we propose a data architecture for a digitized health insurance, consisting of a data model and an application architecture.
The diversity of energy prosumer types makes it difficult to create appropriate incentive mechanisms that satisfy both prosumers and energy system operators alike. Meanwhile, European energy suppliers buy guarantees of origin (GoO) which allow them to sell green energy at premium prices while in reality delivering grey energy to their customers. Blockchain technology has proven itself to be a robust paying system in which users transact money without the involvement of a third party. Blockchain tokens can be used to represent a unit of energy and, just as GoOs, be submitted to the market. This paper focuses on simulating marketplace using the ethereum blockchain and smart contracts, where prosumers can sell tokenized GoOs to consumers willing to subsidize renewable energy producers. Such markets bypass energy providers by allowing consumers to obtain tokenized GoOs directly from the producers, which in turn benefit directly from the earnings. Two market strategies where tokens are sold as GoOs have been simulated. In the Fix Price Strategy prosumers sell their tokens to the average GoO price of 2014. The Variable Price Strategy focuses on selling tokens at a price range defined by the difference between grey and green energy. The study finds that the ethereum blockchain is robust enough to functions as a platform for tokenized GoO trading. Simulation results have been compared and the results indicate that prosumers earn significantly more money by following the Variable Price
Strategy.
Condition Monitoring for mechanical systems like bearings or transmissions is often done by analysing frequency spectra obtained from accelerometers mounted to the components under observation. Although this approach gives a high amount on information about the system behaviour, the interpretation of the resulting spectra requires expert knowledge, that is, a deep understanding of the effect on condition deterioration on the measured spectra. However, an increasing number of condition monitoring applications demands other representations of the measured signals that can be easily interpreted even by non–experts. Therefore, the objective of this paper is to develop an approach for processing measured process data in order to obtain an easy to interpret measure for assessing the component condition. The main idea is to evaluate the deterioration of a component condition by computing the correlation function of current measurements with past measurements in order to detect a component condition deterioration from a change in these correlation functions. Besides the simplicity of the obtained measure, this approach opens the opportunity for integrating a model based approach as well. The developed method is tested based on a condition monitoring application in a roller chain.
This paper describes a new method for condition monitoring of a roller chain. In contrast to conventional methods, no additional accelerometers are used to measure and interpret frequency spectra but the chain condition is evaluated using an easy to interpret similarity measure based on correlation functions using the driving motor torque. An additional clustering of current data and reference measurements yields an easy to understand representation of the chain condition.
With the Internet of Things being one of the most discussed trends in the computer world lately, many organizations find themselves struggling with the great paradigm shift and thus the implementation of IoT on a strategic level. The Ignite methodoogy as a part of the Enterprise-IoT project promises to support organizations with these strategic issues as it combines best practices with expert knowledge from diverse industries helping to create a better understanding of how to transform into an IoT driven business. A framework that is introduced within the context of IoT business model development is the Bosch IoT Business Model Builder. In this study the provided framework is compared to the Osterwalder Business Model Canvas and the St. Gallen Business Model Navigator, the most commonly used and referenced frameworks according to a quantitative literature analysis.