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Software development consists to a large extend of humanbased processes with continuously increasing demands regarding interdisciplinary team work. Understanding the dynamics of software teams can be seen as highly important to successful project execution. Hence, for future project managers, knowledge about non-technical processes in teams is significant. In this paper, we present a course unit that provides an environment in which students can learn and experience the impact of group dynamics on project performance and quality. The course unit uses the Tuckman model as theoretical framework, and borrows from controlled experiments to organize and implement its practical parts in which students then experience the effects of, e.g., time pressure, resource bottlenecks, staff turnover, loss of key personnel, and other stress factors. We provide a detailed design of the course unit to allow for implementation in further software project management courses. Furthermore, we provide experiences obtained from two instances of this unit conducted in Munich and Karlskrona with 36 graduate students. We observed students building awareness of stress factors and developing counter measures to reduce impact of those factors. Moreover, students experienced what problems occur when teams work under stress and how to form a performing team despite exceptional situations.
Wasted paradise – imagining the Maldives without the garbage island of Thilafushi : Version 1.2
(2016)
To address the high level of waste production in the Maldives, the local government decided to transform the coral island of Thilafushi into an immense waste dumb in 1992. Meanwhile, each day, 330 tons of waste is ferried to Thilafushi. The policy had the positive consequence of relieving the garbage burden in Malé, the main island, and surrounding tourist atolls. However, it can also lead to serious environmental and economic damage in the long range. First, the garbage is in visual range of one of the most prominent tourist destinations. Second, if the wind blows a certain way, unfiltered fumes from burning waste travels to tourist atolls. Third, water quality can erode as hazardous waste from batteries and other toxic waste is floating in the ocean. Over time, these effects can accumulate to significantly hamper the number of tourists that travel to the Maldives – one of the state’s main sources of financial income. In our paper, we lay out the situation in more detail and translate it into a simulation model. We test different policies to propose the Maldives government how to better solve the waste problem.
Based on well-established robotic concepts of autonomous localization and navigation we present a system prototype to assist camera-based indoor navigation for human utilization implemented in the Robot Operating System (ROS). Our prototype takes advantage of state-of-the-art computer vision and robotic methods. Our system is designed for assistive indoor guidance. We employ a vibro tactile belt to serve as a guiding device to render derived motion suggestions to the user via vibration patterns. We evaluated the effectiveness of a variety of vibro-tactile feedback patterns for guidance of blindfolded users. Our prototype demonstrates that a vision-based system can support human navigation, and may also assist the visually impaired in a human-centered way.
Today the optimization of metal forming processes is done using advanced simulation tools in a virtual process, e.g. FEM-studies. The modification of the free parameters represents the different variants to be analysed. So experienced engineers may derive useful proposals in an acceptable time if good initial proposals are available. As soon as the number of free parameters growths or the total process takes long times and uses different succeeding forming steps it might be quite difficult to find promising initial ideas. In metal forming another problem has to be considered. The optimization using a series of local improvements, often called a gradient approach may find a local optimum, but this could be far away from a satisfactory solution. Therefore non-deterministic approaches, e.g. Bionic Optimization have to be used. These approaches like Evolutionary Optimization or Particle Swarm Optimization are capable to cover a large range of high dimensional optimization spaces and discover many local optima. So the chance to include the global optimum increases when using such non-deterministic methods. Unfortunately these bionic methods require large numbers of studies of different variants of the process to be optimized. The number of studies tends to increase exponentially with the number of free parameters of the forming process. As the time for one single study might be not too small as well, the total time demand will be inacceptable, taking weeks to months even if high performance computing will be used. Therefore the optimization process needs to be accelerated. Among the many ideas to reduce the time and computer power requirement Meta- and Hybrid Optimization seem to produce the most efficient results. Hybrid Optimization often consists of global searches of promising regions within the parameter space. As soon as the studies indicate that there could be a local optimum, a deterministic study tries to identify this local region. If it shows better performance than other optima found until now, it is preserved for a more detailed analysis. If it performs worse than other optima the region is excluded from further search. Meta-Optimization is often understood as the derivation of Response Surfaces of the functions of free parameters. Once there are enough studies performed, the optimization is done using the Response Surfaces as representatives e.g. for the goal and the restrictions of the optimization problem. Having found regions where interesting solutions are to be expected, the studies available up to now are used to define the Response Surfaces. In many cases low degree polynomials are used, defining their coefficients by least square methods. Both proposals Hybrid Optimization and Meta-Optimization, sometimes used in combination often help to reduce the total optimization processes by large numbers of variants to be studied. In consequence they are highly recommended when dealing with time consuming optimization studies.
Context: Companies need capabilities to evaluate the customer value of software intensive products and services. One way of systematically acquiring data on customer value is running continuous experiments as part of the overall development process. Objective: This paper investigates the first steps of transitioning towards continuous experimentation in a large company, including the challenges faced. Method: We conduct a single-case study using participant observation, interviews, and qualitative analysis of the collected data. Results: Results show that continuous experimentation was well received by the practitioners and practising experimentation helped them to enhance understanding of their product value and user needs. Although the complexities of a large multi-stakeholder business to-business (B2B) environment presented several challenges such as inaccessible users, it was possible to address impediments and integrate an experiment in an ongoing development project. Conclusion: Developing the capability for continuous experimentation in large organisations is a learning process which can be supported by a systematic introduction approach with the guidance of experts. We gained experience by introducing the approach on a small scale in a large organisation, and one of the major steps for future work is to understand how this can be scaled up to the whole development organisation.
IT environments that consist of a very large number of rather small structures like microservices, Internet of Things (IoT) components, or mobility systems are emerging to support flexible and agile products and services in the age of digital transformation. Biological metaphors of living and adaptable ecosystems with service-oriented enterprise architectures provide the foundation for self-optimizing, resilient run-time environments and distributed information systems. We are extending Enterprise Architecture (EA) methodologies and models that cover a high degree of heterogeneity and distribution to support the digital transformation and related information systems with micro-granular architectures. Our aim is to support flexibility and agile transformation for both IT and business capabilities within adaptable digital enterprise architectures. The present research paper investigates mechanisms for integrating Microservice Architectures (MSA) by extending original enterprise architecture reference models with elements for more flexible architectural metamodels and EA-mini-descriptions.
Analysis is an important part of the enterprise architecture management process. Prior to decisions regarding transformation of the enterprise architecture, the current situation and the outcomes of alternative action plans have to be analysed. Many analysis approaches have been proposed by researchers and current enterprise architecture management tools implement analysis functionalities. However, few work has been done structuring and classifying enterprise architecture analysis approaches. This paper collects and extends existing classification schemes, presenting a framework for enterprise architecture analysis classification. For evaluation, a collection of enterprise architecture analysis approaches has been classified based on this framework. As a result, the description of these approaches has been assessed, a common set of important categories for enterprise architecture analysis classification has been derived and suggestions for further development are drawn.
During the first years of their employment, the graduates are a liability to industry. The employer goes an extra mile to bridge the gap between university-exiting and profitable employment of engineering graduates. Unfortunately some cannot take this risk. Given this scenario, this paper presents a learning factory approach as a platform for the application of knowledge so as to develop the required engineering competences in South African engineering graduates before they enter the labour market. It spells out the components of a Stellenbosch University Learning Factory geared towards production of engineering graduates with the required industrial skills. It elaborates on the didactics embedded in the learning factory environment, tailor-made to produce engineers who can productively contribute to the growth of the industry upon exiting the university.
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? 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 are analyzed and evaluated for applicability, especially 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.
This summary refers to the paper Software process improvement : where is the evidence? [Ku15].
This paper was published as full research paper in the ICSSP’2015 proceedings.
Although still in the early stages of diffusion, smartwatches represent the most popular type of wearable devices. Yet, little is known why some people are more likely to adopt smartwatches than others. To deepen the understanding of underlying factors prompting adoption behavior, the authors develop a theoretical model grounded in technology acceptance and social psychology literature. Empirical results reveal perceived usefulness and visibility as important factors that drive intention. The magnitude of these antecedents is influenced by an individual’s perception of viewing smartwatches as a technology and/or as a fashion accessory. Theoretical and managerial implications are discussed.
Significant advances have been achieved in mobile robot localization and mapping in dynamic environments, however these are mostly incapable of dealing with the physical properties of automotive radar sensors. In this paper we present an accurate and robust solution to this problem, by introducing a memory efficient cluster map representation. Our approach is validated by experiments that took place on a public parking space with pedestrians, moving cars, as well as different parking configurations to provide a challenging dynamic environment. The results prove its ability to reproducibly localize our vehicle within an error margin of below 1% with respect to ground truth using only point based radar targets. A decay process enables our map representation to support local updates.
In this paper we present our work in progress on revisiting traditional DBMS mechanisms to manage space on native Flash and how it is administered by the DBA. Our observations and initial results show that: the standard logical database structures can be used for physical organization of data on native Flash; at the same time higher DBMS performance is achieved without incurring extra DBA overhead. Initial experimental evaluation indicates a 20% increase in transactional throughput under TPC-C, by performing intelligent data placement on Flash, less erase operations and thus better Flash longevity.
We present a fully automatic approach to real-time 3D face reconstruction from monocular in-the-wild videos. We use a 3D morphable face model to obtain a semi-dense shape and combine it with a fast median-based super-resolution technique to obtain a high-fidelity textured 3D face model. Our system does not need prior training and is designed to work in uncontrolled scenarios.
Preface of IDEA 2015
(2016)
An enormous amount of data in the context of business processes is stored as images. They contain valuable information for business process management. Up to now this data had to be integrated manually into the business process. By advances of capturing it is possible to extract information from an increasing number of images. Therefore, we systematically investigate the potentials of Image Mining for business process management by a literature research and an in-depth analysis of the business process lifecycle. As a first step to evaluate our research, we developed a prototype for recovering process model information from drawings using Rapidminer.
Sleep is an important aspect in life of every human being. The average sleep duration for an adult is approximately 7 h per day. Sleep is necessary to regenerate physical and psychological state of a human. A bad sleep quality has a major impact on the health status and can lead to different diseases. In this paper an approach will be presented, which uses a long-term monitoring of vital data gathered by a body sensor during the day and the night supported by mobile application connected to an analyzing system, to estimate sleep quality of its user as well as give recommendations to improve it in real-time. Actimetry and historical data will be used to improve the individual recommendations, based on common techniques used in the area of machine learning and big data analysis.
The loss contribution of a 2.3kW synchronous GaN-HEMT boost converter for an input voltage of 250V and an output voltage of 500V was analyzed. A simulation model which consists of two parts is introduced. First, a physics-based model is used to determine the switching losses. Then, a system simulation is applied to calculate the losses of the specific elements. This approach allows a fast and accurate system evaluation as required for further system optimization.
In this work, a hard- and a zero-voltage turn-on switching converter are compared. Measurements were performed to verify the simulation model, showing a good agreement. A peak efficiency of 99% was achieved for an output power of 1.4kW. Even with an output power above 400W, it was possible to obtain a system efficiency exceeding 98 %.
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 best-fitting 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 paper at hand provides insights into the HELENA study with which we aim to investigate the use of “Hybrid dEveLopmENt Approaches in software systems development”. We present the survey design and initial findings from the survey’s test runs. Furthermore, we outline the next steps towards the full survey.
Software Process Improvement (SPI) programs have been implemented, inter alia, to improve quality and speed of software development. SPI addresses many aspects ranging from individual developer skills to entire organizations. It comprises, for instance, the optimization of specific activities in the software lifecycle as well as the creation of organizational awareness and project culture. In the course of conducting a systematic mapping study on the state-of-the-art in SPI from a general perspective, we observed Software Quality Management (SQM) being of certain relevance in SPI programs. In this paper, we provide a detailed investigation of those papers from the overall systematic mapping study that were classified as addressing SPI in the context of SQM (including testing). From the main study’s result set, 92 papers were selected for an in-depth systematic review to study the contributions and to develop an initial picture of how these topics are addressed in SPI. Our findings show a fairly pragmatic contribution set in which different solutions are proposed, discussed, and evaluated. Among others, our findings indicate a certain reluctance towards standard quality or (test) maturity models and a strong focus on custom review, testing, and documentation techniques, whereas a set of five selected improvement measures is almost equally addressed.
The internet of things, enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud environments are emerging to support smart connected i.e. digital products and services and the digital transformation. Biological metaphors for living and adaptable ecosystems are currently providing the logical foundation for resilient run-time environments with serviceoriented digitization architectures and for self-optimizing intelligent business services and related distributed information systems. We are investigating mechanisms for flexible adaptation and evolution of information systems with digital architecture in the context of the ongoing digital transformation. The goal is to support flexible and agile transformations for both business and related information systems through adaptation and dynamical evolution of their digital architectures. The present research paper investigates mechanisms of decision analytics for digitization architectures, putting a spotlight to internet of things micro-granular architectures, by extending original enterprise architecture reference models with digitization architectures and their multi-perspective architectural decision management.
One of the challenges in condition monitoring systems is the residual life time prediction. This prediction is done based on statistical methods, based on physical knowledge about the considered process or a combination of these approaches. Physical knowledge of the system is a result of long-term experience of process operators. However, it can be gained as well by analyzing appropriately designed process models. The additional benefit of such models is that particular effects and their impact on the process behavior can be analyzed in detail and without plant operation in a shorter time. The current contribution developed in the framework of the research project Model Based Hierarchic Condition Monitoring presents such models for condition monitoring of roller chains. First, already existing high order dynamic models given by nonlinear differential equations of such chains are extended to incorporate effects that occur due to a deterioration of the chain condition. Then, a simple model is developed and compared to the high order model. Based on the two models the change in the process behavior due to a deterioration of the roller chain condition is analyzed to illustrate that these models can be used in future research in the above mentioned research project to better predict the residual life time of the considered roller chains.
On the way to achieving higher degrees of autonomy for vehicles in complicated, ever changing scenarios, the localization problem poses a very important role. Especially the Simultaneous Localization and Mapping (SLAM) problem has been studied greatly in the past. For an autonomous system in the real world, we present a very cost-efficient, robust and very precise localization approach based on GraphSLAM and graph optimization using radar sensors. We are able to prove on a dynamically changing parking lot layout that both mapping and localization accuracy are very high. To evaluate the performance of the mapping algorithm, a highly accurate ground truth map generated from a total station was used. Localization results are compared to a high precision DGPS/INS system. Utilizing these methods, we can show the strong performance of our algorithm.
The use of digital, IT-based components in physical products is becoming increasingly relevant in practice. Surprisingly, the strategic impact of these "digitized products" has not received a lot of attention in IS research so far. Extant papers on the topic rely on ambiguous terminology (e.g., "smart products", "cyber-physical systems", "digital product-service systems") and underlying concepts differ widely. Based on an extensive literature review, this article provides an overview of the different terms and identifies five conceptual elements that form the building blocks of digitized products in research: "hybridity" (i.e., the combination of digital and physical components), connectivity, smartness, digitized product-service bundles (servitization of digitized products), and digitized product ecosystems. The implication for practitioners is that each element comes with different managerial challenges that companies need to address when incorporating the respective element in their products. The research implication is that each conceptual element is supported by different theoretical streams.
The focus of this work lies on teaching methods for product design to stimulate novelty within a multiple disciplinary educational context. To address this issue, the different types of multiple disciplinary approach are presented by reviewing existing literature. As the initial study involved looking at the correlation between disciplines and product features, the definition of product design and its relationship with industrial design and other adjacent domains are introduced. The structure of a newly developed interdisciplinary master in product design is presented and, within this program, an educational activity fostering creativity in heterogeneous multiple disciplinary environments is described. Inspired by the approach of industrial designers to generate creative solutions, it is conceived to help product design students to flexibly adapt the problem and the solution space together through an iterative process.
In the last decades, several driving systems were developed to improve the driving behaviour in energy efficiency or safety. However, these driving systems cover either the area of energy-efficiency or safety. Furthermore, they do not consider the stress level of the driver when showing a recommendation, although stress can lead to an unsafe or inefficient driving behaviour. In this paper, an approach is presented to consider the driver stress level in a driving system for safe and energy-efficient driving behaviour. The driving system tries to suppress a recommendation when the driver is in stress in order not to stress the driver additionally with recommendations in a stressful driving situation. This can lead to an increase in the road safety and in the user acceptance of the driving system, as the driver is not getting bothered or stressed by the driving system.
The evaluation of the approach showed, that the driving system
is able to show recommendations to the driver, while also reacting
to a high stress level by suppressing recommendations in
order not to stress the driver additionally.
Influence of metallization layout on aging detector lifetime under cyclic thermo-mechanical stress
(2016)
The influence of the layout on early warning detectors in BCD technologies for metallization failure under cyclic thermo-mechanical stress was investigated. Different LDMOS transistors, with narrow or wide metal fingers and with or without embedded detectors, were used. The test structures were repeatedly stressed by pronounced self-heating until failure (a short circuit) was detected. The results show that the layout of the on-chip metallization has a large impact on the lifetime. A significant influence of the detectors on the lifetime was also observed, in our case causing a reduction of more than a factor of two, but only for the test structure with narrow metal fingers. The experimental results are explained by an efficient numerical thermo mechanical simulation approach, giving detailed insights into the strain distribution in the metal system. These results are important for aging detector design and, morever, for LDMOS on-chip metal layout in general.
Industrial hybrid systems with high pv penetration : performance, analysis and key success factors
(2016)
Since the first industrial-scale hybrid system was installed by SMA in 2012, information about the performance of several hybrid systems around the world has been monitored. This paper analyses the performance of SMA’s largest PV-Diesel hybrid system in the industrial-scale installed in Bolivia in 2014 and summarizes the lessons learned by managing this system with large-scale energy storage. The paper finally concludes with an outlook for future hybrid systems.
Increasingly volatile market conditions and manufacturing environments combined with a rising demand for highly personalized products, the emergence of new technologies like cyber-physical systems and additive manufacturing as well as an increasing cross-linking of different entities (Industrie 4.0) will result in fundamental changes of future work and logistics systems. The place of production, the logistical network and the respective production system will underlie the requirements of constant changes and therefore sources and sinks of logistical networks have to obey the versatility of (cyber-physical) production systems. To cope with the arising complexity to control and monitor changeable production and logistics systems, decentralized control systems are the mean of choice since centralized systems are pushed to their limits in this regard. This paradigm shift will affect the overall concept under which production and logistics is planned, managed and controlled and how companies interact and collaborate within the emerging value chains by using dynamic methods to generate and execute the created network and to allocate available resources to fulfill the demand for customized products. In this field of research learning factories, like the ESB Logistics Learning Factory at ESB Business School (Reutlingen University), provide a great potential as a risk free test bed to develop new methods and technical solutions, to investigate new technologies regarding their practical use and to transfer the latest state of knowledge and specific competences into the training of students and professionals. Keeping with these guiding principles ESB Business School is transferring its existing production system into a cyber-physical production system to investigate innovative solutions for the design of human-machine collaboration and technical assistance systems as wells as to develop decentralized control methods for intralogistics systems following the requirements of changeable work systems including the respective design of dynamic inbound and outbound logistic networks.
Nowadays, software development plays an important role in the entire value chain in production machine and plant engineering. An important component for rapid development of high quality software is the virtual commissioning. The real machine is described on the basis of simulation models. Therefore, the control software can be verified at an early stage using the simulation models. Since production machines are produced highly individual or in very small series, the challenge of virtual commissioning is to reduce the effort in the development of simulation models. Therefore, a systemic reuse of the simulation models and the control software for different variants of a machine is essential for an economic use. This necessarily requires a consideration of the variability which may occur between the production machines. This contribution analyzes the question of how to systematically deal with the software-related variability in the context of virtual commissioning. For this purpose, first the characteristics of the virtual commissioning and variability handling are considered. Subsequently, the requirements to a so-called variant infrastructure for virtual commissioning are analyzed and possible solutions are discussed.
For decades, Software Process Improvement (SPI) programs have been implemented, inter alia, to improve quality and speed of software development. To set up, guide, and carry out SPI projects, and to measure SPI state, impact, and success, a multitude of different SPI approaches and considerable experience are available. SPI addresses many aspects ranging from individual developer skills to entire organizations. It comprises for instance the optimization of specific activities in the software lifecycle as well as the creation of organization awareness and project culture. In the course of conducting a systematic mapping study on the state-of-the-art in SPI from a general perspective, we observed Global Software Engineering (GSE) becoming a topic of interest in recent years. Therefore, in this paper, we provide a detailed investigation of those papers from the overall systematic mapping study that were classified as addressing SPI in the context of GSE. From the main study’s result set, a set of 30 papers dealing with GSE was selected for an in-depth analysis using the systematic review instrument to study the contributions and to develop an initial picture of how GSE is considered from the perspective of SPI. Our findings show the analyzed papers delivering a substantial discussion of cultural models and how such models can be used to better address and align SPI programs with multi-national environments. Furthermore, experience is shared discussing how agile approaches can be implemented in companies working at the global scale. Finally, success factors and barriers are studied to help companies implementing SPI in a GSE context.
The limited interfaces of today's IC design environments for editing PCell parameters hinder a solid advancement towards more complex analog PCell modules. This paper presents Hierarchical Instance Parameter Editing (HIPE), a highly flexible concept for the customization of PCell sub-instances. Introducing a new type of parameter, HIPE facilitates the dynamic creation of multi-level editing forms reflecting the actual contents of a PCell instance. This approach greatly improves a PCell's ease-of-use, substantially simplifies PCell development, and allows for a hierarchical execution of parameter validation callbacks. Our HIPE implementation has been integrated into a professional PCell development tool and represents a key enabling technology for upcoming generations of high-level hierarchical PCells.
At higher frequencies the triaxial cell becomes in principle a cavity resonator which shows different resonance frequencies depending on the dimensions of the cell as well as on the size of the DUT. Above these resonance frequencies propagation of TEM waves is disturbed and measurements of screening attenuation with triaxial test method according to IEC 62153-4-15 are limited. Higher order modes respectively resonance frequencies can be suppressed by using conductive absorber material such as ferrites, nanocrystalline absorbers, magnetic absorbers or foam absorbers, placed in the Triaxial cell. With these absorbers, the frequency range of the screening attenuation measured in Triaxial cell can be extended up to several GHz.
Optimization-based design automation for analog ICs still remains behind the demands. A promising alternative is given by procedural approaches such as parameterized generators, also known as PCells. We are working on a complete analog design flow based on parameterized generators for entire circuits and corresponding layout modules. Because the conventional programming of such enhanced generators is far too complicated and costly, new methods are needed to ease their development. This paper presents gPCDS (graphical PCDS), a novel tool for a designer-oriented development of schematic module generators, integrated into a common schematic entry environment. The tool is based on PCDS (Parameterized Circuit Description Scheme), a meta-language for the creation of parametrized analog circuits. Schematic module generators are a very desirable complement to layout module generators in order to achieve a seamless schematic- driven layout design flow on module level. By facilitating a way of generator development that matches a design expert’s mentality, gPCDS contributes to close this gap in the analog design flow.
The power supply is one of the major challenges for applications like internet of things IoTs and smart home. The maintenance issue of batteries and the limited power level of energy harvesting is addressed by the integrated micro power supply presented in this paper. Connected to the 120/230 Vrms mains, which is one of the most reliable energy sources and anywhere indoor available, it provides a 3.3V DC output voltage. The micro power supply consists of a fully integrated ACDC and DCDC converter with one external low voltage SMD buffer capacitor. The micro power supply is fabricated in a low cost 0.35 μm 700 V CMOS technology and covers a die size of 7.7 mm². The use of only one external low voltage SMD capacitor, results in an extremely compact form factor. The ACDC is a direct coupled, full wave rectifier with a subsequent bipolar shunt regulator, which provides an output voltage around 17 V. The DCDC stage is a fully integrated 4:1 SC DCDC converter with an input voltage as high as 17 V and a peak efficiency of 45 %. The power supply achieves an overall output power of 3 mW, resulting in a power density of 390 μW/mm². This exceeds prior art by a factor of 11.
Gamification, the use of game elements for non-gaming purposes, may just make a huge impact on education, a contribution the world in general and South Africa in particular, desperately needs. In today’s fast-paced work environment, there is not only a severe skills shortage, but also a great need for graduates with practical knowledge - students that are not purely “book smart”. Didactic teaching habits have created an education realm in which reciting facts is more often than not what gets students to pass. Learning factories are physical, operational factories that serve as exemplary and realistic hands-on learning environments and provide an important step towards more industry-prepared graduates. Top universities around the world are establishing such environments and are showing superb results. This paper explores the potential benefit of applying gamification in such a setting to enhance the learning environment even further, and provide opportunities for training otherwise difficult to teach topics, such as shop floor management.
Context: The current transformation of automotive development towards innovation, permanent learning and adapting to changes are directing various foci on the integration of agile methods. Although, there have been efforts to apply agile methods in the automotive domain for many years, a wide-spread adoption has not yet taken place.
Goal: This study aims to gain a better understanding of the forces that prevent the adoption of agile methods.
Method: Survey based on 16 semi-structured interviews from the automotive domain. The results are analyzed by means of thematic coding.
Results: Forces that prevent agile adoption are mainly of organizational, technical and social nature and address inertia, anxiety and context factors. Key challenges in agile adoption are related to transforming organizational structures and culture, achieving faster software release cycles without loss of quality, the importance of software reuse in combination with agile practices, appropriate quality assurance measures, and the collaboration with suppliers and other disciplines such as mechanics.
Conclusion: Significant challenges are imposed by specific characteristics of the automotive domain such as high quality requirements and many interfaces to surrounding rigid and inflexible processes. Several means are identified that promise to overcome these challenges.
The paper focuses on a recently introduced paradigm for the logistic process of picking, with respect to the man-to-goods and goods-to-man concept: the robot to-goods. First the task and system architecture of the fast deployable autonomous commissioning system are described, then the economic efficiency of the system is analysed in a real business case scenario using a simplified method, which is explained and discussed. The clearly positive net present value of the investment and the short payback period obtained in the business case prove how the robot-to-goods paradigm for the commissioning process, implemented through the automation of the forklift platform, is economically attractive for small and medium size enterprises.
Nowadays there is a rich diversity of sleep monitoring systems available on the market. They promise to offer information about sleep quality of the user by recording a limited number of vital signals, mainly heart rate and body movement. Typically, fitness trackers, smart watches, smart shirts, smartphone applications or patches do not provide access to the raw sensor data. Moreover, the sleep classification algorithm and the agreement ratio with the gold standard, polysomnography (PSG) are not disclosed. Some commercial systems record and store the data on the wearable device, but the user needs to transfer and import it into specialised software applications or return it to the doctor, for clinical evaluation of the data set. Thus an immediate feedback mechanism or the possibility of remote control and supervision are lacking. Furthermore, many such systems only distinguish between sleep and wake states, or between wake, light sleep and deep sleep. It is not always clear how these stages are mapped to the four known sleep stages: REM, NREM1, NREM2, NREM3-4. [1] The goal of this research is to find a reduced complexity method to process a minimum number of bio vital signals, while providing accurate sleep classification results. The model we propose offers remote control and real time supervision capabilities, by using Internet of Things (IoT) technology. This paper focuses on the data processing method and the sleep classification logic. The body sensor network representing our data acquisition system will be described in a separate publication. Our solution showed promising results and a good potential to overcome the limitations of existing products. Further improvements will be made and subjects with different age and health conditions will be tested.
This work investigates the electro-thermal behavior and failure mechanism of a 600V depletion-mode GaN HEMT by experimental analysis and numerical thermal simulations. For this device, the positive temperature coefficient of the draingate leakage current can lead to the formation of hot spots. This localized thermal runaway which ultimately results in a breakdown of the inherent drain-gate junction is found to be the dominant cause of failure.
This paper provides an introduction to the topic of enterprise social networks (ESN) and illustrates possible applications, potentials, and challenges for future research. It outlines an analysis of research papers containing a literature overview in the field of ESN. Subsequently, single relevant research papers are analysed and further research potentials derived therefrom. This yields seven promising areas for further research: (1) user behaviour; (2) effects of ESN usage; (3) management, leadership, and governance; (4) value assessment and success measurement; (5) cultural effects, (6) architecture and design of ESN; and (7) theories, research designs and methods. This paper characterises these areas and articulates further research directions.
The superior electrical and thermal properties of silicon carbide (SiC) allow further shrinking of the active area of future power semiconductor devices. A lower boundary of the die size can be obtained from the thermal impedance required to withstand the high power dissipation during a short-circuit event. However, this implies that the power distribution is homogeneous and that no current filamentation has to be considered. Therefore, this work investigates this assumption by evaluating the stability of a SiC-MOSFET over a wide range of operation conditions by measurements up to destruction, thermal simulations, and high-temperature characterization.
In this article an energy harvesting system for measuring the wind speed starting from 2 m/s (about 2 Bft) is presented, which uses the same source for measuring and supplying power (energy autarkic). The use of the same source for measurement and power supply increases the number of potential applications since needed power is present with the measuring signal. For the case of measuring the wind velocity, one might consider applications in tunnels, tubes, pipelines, air conditioning or for controlling clogging of filters. Bluetooth Low Energy (BLE) is chosen as radio technology, since it provides the possibility to realize a unidirectional communication; requiring only a single telegram (advertising telegram) for sending the measured value. A more complex establishment of communication required by WLAN or 6LoWPAN could therefore be avoided to significantly reduce the overall energy consumption. Since the advertisement telegram does not make any provision for security or against hacking in general, a security concept is presented which includes encryption and resilience against replay attacks in a unidirectional communication system.
To facilitate the presented concepts beyond wind sensors, the system is divided into three major modules namely the generator-sensor module, the radio module and the energy management module. Whereas the first two might be changed in different applications the energy management module could be reused in many different applications. It supplies and stores the needed energy and switches power on and off in a deterministic way to ensure the radio module can operate correctly.
Analog-/Mixed-Signal (AMS) design verification is one of the most challenging and time consuming tasks of todays complex system on chip (SoC) designs. In contrast to digital system design, AMS designers have to deal with a continuous state space of conservative quantities, highly nonlinear relationships, non-functional influences, etc. enlarging the number of possibly critical scenarios to infinity. In this special session we demonstrate the verification of functional properties using simulative and formal methods. We combine different approaches including automated abstraction and refinement of mixed-level models, state-space discretization as well as affine arithmetic. To reach sufficient verification coverage with reasonable time and effort, we use enhanced simulation schemes to avoid conventional simulation drawbacks.
Efficiency in supply chain risk management (SCRM) is a major topic in industries with serial production and a complex supply chain due to limited management and financial resources. A high number of possible risk situations and intertwined processes create a more challenging environment for resource allocation. Managers cannot perform SCRM in all possible supply chain areas and hence have to decide where available resources should be utilised for highest possible risk reduction. This makes it important to quickly and systematically evaluate input and output relationships among risk mitigation actions to determine which actions are deployed first for efficient risk level reduction. This paper introduces a new SCRM method based on the failure mode and effects analysis (FMEA) in order to perform an efficiency-oriented risk action prioritisation. By considering the cost-benefit evaluation of identified risk mitigation actions for each assessed risk and by determining the implementation effort for risk mitigation actions, also considered as the cost for realising a specific risk action the method allows finding those risk and risk mitigation actions, which are most efficient for risk reduction and should be implemented first in the process of risk steering.
The efficiency impact of air-cored inductors used close to and beyond its cut-off frequency in multi-MHz converters is investigated. A method is presented to determine the converter switching frequency that causes the lowest losses in a given inductor. Influential parameters are analysed to optimize an inductor for a predefined switching frequency.
In its 100+ years of company history, IBM reinvented itself multiple times. In the last 20 years, IBM had shifted from individual products to integrated solutions and moved to become a globally integrated enterprise with standardized processes. In 2014, the expanding adoption of social, mobile, analytics, and cloud (SMAC) technologies generated excitement in the industry. IBM believed these technologies presented a huge growth opportunity. Simultaneously, management viewed SMAC technologies as disruptive forces demanding transformative changes to how IBM worked. And introducing new ways of working to 400,000 employees in 175 countries was a daunting task.
Based on personal interviews with 17 IBM business and IT executives, the case illustrates organizational challenges of introducing current technologies that even providers of these technologies face – in other words, when they “eat their own cooking.” It demonstrates the difficulties large companies face when implementing technologies that students use daily and take for granted.
Software development consists to a large extent of human-based processes with continuously increasing demands regarding interdisciplinary team work. Understanding the dynamics of software teams can be seen as highly important to successful project execution. Hence, for future project managers, knowledge about non-technical processes in teams is significant. In this paper, we present a course unit that provides an environment in which students can learn and experience the role of different communication patterns in distributed agile software development. In particular, students gain awareness about the importance of communication by experiencing the impact of limitations of communication channels and the effects on collaboration and team performance. The course unit presented uses the controlled experiment instrument to provide the basic organization of a small software project carried out in virtual teams. We provide a detailed design of the course unit to allow for implementation in further courses. Furthermore, we provide experiences obtained from implementing this course unit with 16 graduate students. We observed students struggling with technical aspects and team coordination in general, while not realizing the importance of communication channels (or their absence). Furthermore, we could show the students that lacking communication protocols impact team coordination and performance regardless of the communication channels used.