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A MATLAB toolbox was developed both for teachers performing quick experimental demonstrations during lectures and for students practicing measurement and frequency analysis procedures. The conceptual purpose was to support fundamental acoustics courses with contents defined by the DEGA recommendation 102. All implemented functions and parameters are visible at once and quickly adjustable by a GUI without submenus. A user manual is provided with explanations of how to get started and how all implemented functions can be applied. The toolbox probably still contains bugs. All users are welcome to inform the author about their experiences and proposals for improvement. In future it is planned to convert "Acoustics" to the MATLAB app designer format as Mathworks announced GUIDE to be replaced. Useful extensions would be additional tabs containing animations of sound propagation phenomena or sound fields caused by different sources.
Real estate markets are known to fluctuate. The real estate market in Stuttgart, Germany, has been booming for more than a decade: square-meter price hit top levels and real estate agents claim that market prices will continue to increase. In this paper, we test this market understanding by developing and analyzing a system dynamics model that depicts the Stuttgart real estate market. Simulating the model explains oscillating behavior arising from significant time delays and endogenous feedback structures – and not necessarily oscillating interest rates, as market experts assume. Scenarios provide insights into the system's behavior reacting to changes exogenous to the model. The first scenario tests the market development under increasing interest rates. The other scenario deals with possible effects on the real estate market if the regional automotive economy suffers from intense competition with new market players entering with alternative fuel vehicles and new technologies. With a policy run we test market structure changes to eliminate cyclical effects. The paper confirms that the business cycle in the Stuttgart real estate market arises from within the system's underlying structure, thus emphasizing the importance of understanding feedback structures.
Functionally impaired people have problems with choosing and finding the right clothing. So, they need help in their daily life to wash and manage the clothing. The goal of this work is to support the user by giving recommendations to choose the right clothing, to find the clothing and how to wash the clothing. The idea behind eKlarA is to generate a gateway based system that uses sensors to identify the clothing and their state in the clothing cycle. The clothing cycle consists of (one and more) closet, laundry basket and washing machine in one or several places. The gateway uses the information about the clothing, weather and calendar to support the user in the different steps of the clothing cycle. This allows to give more freedom to the functionally impaired people in their daily life.
Entrepreneurs and small and medium enterprises usually have issues on developing new prototypes, new ideas or testing new techniques. In order to help them, in the last years, academic Software Factories, a new concept of collaboration between universities and companies have been developed. Software Factories provide a unique environment for students and companies. Students benefit from the possibility of working in a real work environment learning how to apply the state of the art of the existing techniques and showing their skills to entrepreneurs. Companies benefit from the risk-free environment where they can develop new ideas, in a protected environment. Universities finally benefit from this setup as a perfect environment for empirical studies in industrial-like environment. In this paper, we present the network of academic Software Factories in Europe, showing how companies had already benefit from existing Software Factories and reporting success stories. The results of this paper can increase the network of the factories and help other universities and companies to setup similar environment to boost the local economy.
Today 40 Gbps is in development at IEEE 802.3bq over four pair balanced cabling. In this paper, we describe a transmission experiment of 25 Gbps enabling either a single pair transmission of 25 Gbps over a 30 meter balanced cabling channel, or a 100 Gbps transmission via a four-pair balanced channel. A scalable matrix modeling tool is introduced which allows the prediction of transmission characteristics of a channel taking mode conversion into account . We applied this tool to characterize PCB-channels including the magnetics and PCB for a four-pair 100 Gbps transmission. We evaluated prototype cables and connecting hardware for frequencies up to 2 GHz and beyond. Finally we investigated possible line encoding schemes and provide measurement results of a transmission over 30 m with a data rate of 25 Gbps per twisted pair.
Modern power transistors are able to switch at very high transition speed, which can cause EMC violations and overshoot. This is addressed by a gate driver with variable gate current, which is able to control the transition speed. The key idea is that the gate driver can influence the di/dt and dv/dt transition separately and optimize whichever transition promises the highest improvement while keeping switching losses low. To account for changes in the load current, supply voltage, etc., a control loop is required in the driver to ensure optimized switching. In this paper, an efficient control scheme for an automotive gate driver with variable output current capability is presented. The effectiveness of the control loop is demonstrated for a MOSFET bridge consisting of OptiMOS-T2™devices with a total gate charge of 39nC. This bridge setup shows dv/dt transitions between 50 to 1000ns, depending on driving current. The driver is able to switch between gate current levels of 1 to 500mA in 10/15ns (rising/falling transition). With the implemented control loop the driver is measured to significantly reduce the ringing and thereby reduce device stress and electromagnetic emissions while keeping switching losses 52% lower than with a constant current driver.
The 21st century: an era where emojis and hashtags find their way into every sentence, where taking selfies, live tweeting and mining bitcoin are the norm, and where Insta-culture dictates what we say and do. This is the era into which the digital native was born. With so many changes in every aspect of our lives, how is it that one of the most influential aspects, our education, has remained unchanged? Our education system not only fails to appeal to today’s students, but more importantly, it fails to equip them with the skills required in the 21st Century. It is thus of no surprise that industries feel graduates entering the workplace lack skills in critical thinking, problem solving and self-directed learning. AI, machine learning and big data: Tools and mechanisms we so eagerly incorporate to create smart factories yet are hesitant to use elsewhere. Gamification and games have shown great results in education and training; with most research suggesting a stronger focus on personalization and adaptation. When combined with analytics and machine learning, the potential of games is yet to be realized. A real-time adaptive game would not only always present an appropriate degree of challenge for the individual but would allow for a shift in focus from the recitation of facts, to the application of information filtered to solve the particular problem at hand. South Africa, a country faced with a severe skills gap, could benefit greatly from games. If used correctly, they may just offer a desperately needed contribution toward equipping both current and future employees with the skills needed to survive in the 21st century. This paper explores the feasibility of using such games for enhanced knowledge dissemination and the upskilling of the workforce.
Autonomous navigation is one of the main areas of research in mobile robots and intelligent connected vehicles. In this context, we are interested in presenting a general view on robotics, the progress of research, and advanced methods related to this field to improve autonomous robots’ localization. We seek to evaluate algorithms and techniques that give robots the ability to move safely and autonomously in a complex and dynamic environment. Under these constraints, we focused our work in the paper on a specific problem: to evaluate a simple, fast and light SLAM algorithm that can minimize localization errors. We presented and validated a FastSLAM 2.0 system combining scan matching and loop closure detection. To allow the robot to perceive the environment and detect objects, we have studied one of the best deep learning technique using convolutional neural networks (CNN). We validate our testing using the YOLOv3 algorithm.
Software and system development is complex and diverse, and a multitude of development approaches is used and combined with each other to address the manifold challenges companies face today. To study the current state of the practice and to build a sound understanding about the utility of different development approaches and their application to modern software system development, in 2016, we launched the HELENA initiative. This paper introduces the 2nd HELENA workshop and provides an overview of the current project state. In the workshop, six teams present initial findings from their regions, impulse talk are given, and further steps of the HELENA roadmap are discussed.
The digitization of factories will be a significant issue for the 2020s. New scenarios are emerging to increase the efficiency of production lines inside the factory, based on a new generation of robots’ collaborative functions. Manufacturers are moving towards data-driven ecosystems by leveraging product lifecycle data from connected goods. Energy-efficient communication schemes, as well as scalable data analytics, will support these various data collection scenarios. With augmented reality, new remote services are emerging that facilitate the efficient sharing of knowledge in the factory. Future communication solutions should generally ensure connectivity between the various production sites spread worldwide and new players in the value chain (e.g., suppliers, logistics) transparent, real-time, and secure. Industry 4.0 brings more intelligence and flexibility to production. Resulting in more lightweight equipment and, thus, offering better ergonomics. 5G will guarantee real-time transmissions with latencies of less than 1 ms. This will provide manufacturers with new possibilities to collect data and trigger actions automatically.
More and more power electronics applications utilize GaN transistors as they enable higher switching frequencies in comparison to conventional Si devices. Faster switching shrinks down the size of passives and enables compact solutions in applications like renewable energy, electrical cars and home appliances. GaN transistors benefit from ~10× smaller gate charge QG and gate drive voltages in the range of typically 5V vs. ~15V for Si.
An integrated synchronous buck converter with a high resolution dead time control for input voltages up to 48V and 10MHz switching frequency is presented. The benefit of an enhanced dead time control at light loads to enable zero voltage switching at both the high-side and low-side switch at low output load is studied. This way, compact multi-MHz DCDC converters can be implemented at high efficiency over a wide load current range. The concept also eliminates body diode forward conduction losses and minimizes reverse recovery losses. A dead time resolution of 125 ps is realized by an 8-bit differential delay chain. A further efficiency enhancement by soft switching at the high-side switch at light load is achieved with a voltage boost of the switching node by dead time control in forced continuous conduction mode. The monolithic converter is implemented in an 180nm high-voltage BiCMOS technology. At V IN = 48V, V OUT = 5V, 50mA load, 10MHz switching frequency and 500 nH output inductance, the efficiency is measured to be increased by 14.4% compared to a conventional predictive dead time control. A peak efficiency of 80.9% is achieved at 12V input.
In recent years, significant progress has been made on switched-capacitor DC-DC converters as they enable fully integrated on-chip power management. New converter topologies overcame the fixed input-to-output voltage limitation and achieved high efficiency at high power densities. SC converters are attractive to not only mobile handheld devices with small input and output voltages, but also for power conversion in IoE, industrial and automotive applications, etc. Such applications need to be capable of handling widely varying input voltages of more than 10V, which requires a large amount of conversion ratios. The goal is to achieve a fine granularity with the least number of flying capacitors. In [1] an SC converter was introduced that achieves these goals at low input voltage VIN ≤ 2.5V. [2] shows good efficiency up to VIN = 8V while its conversion ratio is restricted to ≤1/2 with a limited, non-equidistant number of conversion steps. A particular challenge arises with increasing input voltage as several loss mechanisms like parasitic bottom-plate losses and gate-charge losses of high-voltage transistors become of significant influence. High input voltages require supporting circuits like level shifters, auxiliary supply rails etc., which allocate additional area and add losses [2-5]. The combination of both increasing voltage and conversion ratios (VCR) lowers the efficiency and the achievable output power of SC converters. [3] and [5] use external capacitors to enable higher output power, especially for higher VIN. However, this is contradictory to the goal of a fully integrated power supply.
The presented wide-Vin step-down converter introduces a parallel-resonant converter (PRC), comprising an integrated 5-bit capacitor array and a 300 nH resonant coil, placed in parallel to a conventional buck converter. Unlike conventional resonant concepts, the implemented soft-switching control eliminates input voltage dependent losses over a wide operating range. This ensures high efficiency across a wide range of Vin= 12-48V, 100-500mA load and 5V output at up to 15MHz switching frequency. The peak efficiency of the converter is 76.3 %. Thanks to the low output current ripple, the output capacitor can be as small as 50 nF, while the inductor tolerates a larger ESR, resulting in small component size. The proposed PRC architecture is also suitable for future power electronics applications using fast-switching GaN devices.
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.
This paper presents an integrated synchronous buck converter for input voltages >12V with 10MHz switching frequency. The converter comprises a predictive dead time control with frequency compensated sampling of the switching node which does not require body diode forward conduction. A high dead time resolution of 125 ps is achieved by a differential delay chain with 8-bit resolution. This way, the efficiency of fast switching DCDC converters can be optimized by eliminating the body diode forward conduction losses, minimizing reverse recovery losses and by achieving zero voltage switching at turn off. The converter was implemented in a 180nm high-voltage BiCMOS technology. The power losses were measured to be reduced by 30%by the proposed dead time control, which results in a 6% efficiency increase at VOUT = 5V and 0.2A load. The peak efficiency is 81 %.
A 20 V, 8 MHz resonant DCDC converter with predictive control for 1 ns resolution soft-switching
(2015)
Fast switching power supplies allow to reduce the size and cost of external passive components. However, the capacitive switching losses of the power stage will increase and become the dominant part of the total losses. Therefore, resonant topologies are the known key to reduce the losses of the power stage. A power switch with an additional resonant circuit can be turned on under soft-switching conditions, ideally with zero-voltage-switching (ZVS). As conventional resonant converts are only efficient for a constant load, this paper presents a predictive regulation loop to approach soft-switching conditions under varying load and component tolerances. A sample and hold based detection circuit is utilized to control the turn-on of the power switch by a digital regulation. The proposed design was fabricated in a 180 nm high-voltage BiCMOS technology. The efficiency of the converter was measured to be increased by up to 16 % vs. worst case timing and by 13 % compared to a conventional hard-switching buck converter at 20 V input voltage and at approximately 8 MHz switching frequency.
DC-DC-converters are used in many different applications. Specifying the switching frequency is the most important parameter to calculate component costs and required space. Especially automotive applications of small brushed- or brushless dc-motors and the increasing number of DC-DC-converters have high requirements on the structual space (low box volume). This is of particular importance for automotive converters for the new 48 V board net. Multiplying the frequency by two will reduce the size of the power inductor by half at a given specification for output-voltage ripple. Smaller power inductors result in reduced losses due to smaller series resistance and parasitic capacitance. Furthermore a larger switching frequency decreases the size of the DC link capacitors. The circuit will get more idealized. However, as the switching losses increase with frequency, a DC-DC-converter can only benefit from these advantages if the switching behavior can be improved.
This paper presents an optimization method to increase switching slope and switching frequency of a 3.6 kW 3-phase step-up converter by separating the design and layout process into two parts. The first part is the power stage which carries the load current. It contains the power inductance and the drain-source-channel of the power MOSFETs. The second part is the driver circuit which contains the driver ICs, the gate resistor and the gate input impedance. While the switching slope was measured to be improved by 50 % , the switching time decreased by 20 %. Hence, the switching frequency of the step-up converter could be increased from 100 kHz to 200 kHz without loss increase. By mounting the driver ICs in a piggyback configuration in close proximity to the power stage, the parasitics could be further reduced significantly and 500 kHz switching frequency could be achieved with 97.5 % efficiency.
A 3D face modelling approach for pose-invariant face recognition in a human-robot environment
(2017)
Face analysis techniques have become a crucial component of human-machine interaction in the fields of assistive and humanoid robotics. However, the variations in head-pose that arise naturally in these environments are still a great challenge. In this paper, we present a real-time capable 3D face modelling framework for 2D in-the-wild images that is applicable for robotics. The fitting of the 3D Morphable Model is based exclusively on automatically detected landmarks. After fitting, the face can be corrected in pose and transformed back to a frontal 2D representation that is more suitable for face recognition. We conduct face recognition experiments with non-frontal images from the MUCT database and uncontrolled, in the wild images from the PaSC database, the most challenging face recognition database to date, showing an improved performance. Finally, we present our SCITOS G5 robot system, which incorporates our framework as a means of image pre-processing for face analysis.
A high-voltage replica based current sensor is presented, along with challenges and design techniques which are rarely discussed in literature so far. The performance is evaluated by detailed small signal and large signal analysis. By dedicated placing of high-voltage cascode devices, while keeping as many low-voltage devices as possible, a high gain-bandwidth product is achieved. A decoupling and biasing circuit is introduced which improves the response time of the current sensor at on/off transitions by a factor of five. The current sensor is implemented in a 180nm HV BiCMOS technology. The sensor achieves a DC loop gain of 83 dB and a gain-bandwidth product of 7 MHz. With the proposed techniques, the gain-bandwidth product is increased by a factor of six. The measurable current range is between 60mA and 1.5 A. The performance is demonstrated in a 500 kHz buck converter at an input voltage of 40V. The overall circuit concept is suitable for 100V and beyond, enabling high performance power management designs including switched mode power supplies and motor applications.
Size and cost of a switched mode power supply can be reduced by increasing the switching frequency. The maximum switching frequency and the maximum input voltage range, respectively, is limited by the minimum propagated on-time pulse, which is mainly determined by the level shifter speed. At switching frequencies above 10 MHz, a voltage conversion with an input voltage range up to 50 V and output voltages below 5 V requires an on-time of a pulse width modulated signal of less than 5 ns. This cannot be achieved with conventional level shifters. This paper presents a level shifter circuit, which controls an NMOS power FET on a high-voltage domain up to 50 V. The level shifter was implemented as part of a DCDC converter in a 180 nm BiCMOS technology. Experimental results confirm a propagation delay of 5 ns and on-time pulses of less than 3 ns. An overlapping clamping structure with low parasitic capacitances in combination with a high-speed comparator makes the level shifter also very robust against large coupling currents during high-side transitions as fast as 20 V/ns, verified by measurements. Due to the high dv/dt, capacitive coupling currents can be two orders of magnitude larger than the actual signal current. Depending on the conversion ratio, the presented level shifter enables an increase of the switching frequency for multi-MHz converters towards 100 MHz. It supports high input voltages up to 50 V and it can be applied also to other high-speed applications.
The level shifter and the floating gate supply for high-side transistors are a major challenge in high-voltage DCDC converters. This paper presents a high speed and power-efficient level shifter for voltages of up to 50V, suitable for both PMOS and NMOS power FETs. A switching node falling edge detection allows both, a sensitive and safe signal detection. This enables a robust operation during steep dv / dt transitions and a power consumption as low as 4.1 pJ per switching cycle, which is a reduction of more than 40% compared to prior art. An active clamping circuit prevents common mode displacement currents into the high-side supply. The level shifter is implemented in a 180nm BiCMOS technology. Measurements confirm a 50V 120MHz high-speed operation of the level shifter with a rising / falling propagation delay of 1.45 ns / 1.3 ns, respectively. The dv / dt robustness has been confirmed by measurements for transitions up to 6V/ ns.
Managers recognize that software development project teams need to be developed and guided. Although technical skills are necessary, non-technical (NT) skills are equally, if not more, necessary for project success. Currently, there are no proven tools to measure the NT skills of software developers or software development teams. Behavioral markers (observable behaviors that have positive or negative impacts on individual or team performance) are beginning to be successfully used by airline and medical industries to measure NT skill performance. The purpose of this research is to develop and validate the behavior marker system tool that can be used by different managers or coaches to measure the NT skills of software development individuals and teams. This paper presents an empirical study conducted at the Software Factory where users of the behavior marker tool rated video clips of software development teams. The initial results show that the behavior marker tool can be reliably used with minimal training.
This paper presents a digitally controlled boost converter IC for high output voltage and fast transient applications. Thus, it is well applicable in automotive and industrial environments. The 3V-to-6V input voltage, 6.3V output voltage, 1A boost converter IC is fabricated in a 180nm BCD technology. Digital control enables cost savings, advanced control concepts, and it is less parameter sensitive compared to common analog control. A 90 ns latency, 6-bit delay line ADC operates with a window concept, meeting high resolution requirements, e.g. in car battery applications. An output voltage live tracking is included for extending the ADC conversion window. A charge pump DAC provides high resolution, monotonicity, and short 128 ns conversion time. Further, a standard digital PI controller is enhanced by a simple but effective ΔV/Δt-intervention control. It results in 2.8x reduced output voltage deviations in case of load steps, scaling down the output capacitor value by the same factor.
How to protect the skin from getting sun burnt? The sun can damage your skin e.g. skin cancer. But the sun has a positive effect to the human. The time in sun and the intensity are key values between enjoy the sunbath and having a negative effect to the skin. A smart device like a UV flower could help you to enjoy the sunbath. It measures the UV index around you and gives this information to a smartphone app. The development steps of such a device are described in this paper. The UV flower is made of textile fabrics.
Today’s cars are characterized by many functional variants. There are many reasons for the underlying variability, from the adaptation to diverse markets to different technical aspects, which are based on a cross platform reuse of software functions. Inevitably, this variability is reflected in the model-based automotive software development. A modeling language, which is widely used for modeling embedded software in the automotive industry, is MATLAB/Simulink. There are concepts facing the high demand for a systematic handling of variability in Simulinkmodels. However, not every concept is suitable for every automotive application. In order to present a classification of concepts for modeling variability in Simulink, this paper first has to determine the relevant use cases for variant handling in modelbased automotive software development. Existing concepts for modeling variability in Simulink will then be presented before being classified in relation to the previously determined use cases.
Telemedicine is becoming an increasingly important approach to diagnostic, treat or prevent diseases. However, the usage of Information Communication Technologies in healthcare results in a considerable amount of data that must be efficiently and securely transmitted. Many manufacturers provide telemedicine platforms without regarding interoperability, mobility and collaboration. This paper describes a collaborative mobile telemonitoring platform that can use the IEEE 11073 and HL7 communication standards or adapt proprietary protocols. The proposed platform also covers the security and modularity aspects. Furthermore this work introduces an Android-based prototype implementation
The main aim of presented in this manuscript research is to compare the results of objective and subjective measurement of sleep quality for older adults (65+) in the home environment. A total amount of 73 nights was evaluated in this study. Placing under the mattress device was used to obtain objective measurement data, and a common question on perceived sleep quality was asked to collect the subjective sleep quality level. The achieved results confirm the correlation between objective and subjective measurement of sleep quality with the average standard deviation equal to 2 of 10 possible quality points.
Assistant platforms are becoming a key element for the business model of many companies. They have evolved from assistance systems that provide support when using information (or other) systems to platforms in their own. Alexa, Cortana or Siri may be used with literally thousands of services. From this background, this paper develops the notion of assistant platforms and elaborates a conceptual model that supports businesses in developing appropriate strategies. The model consists of three main building blocks, an architecture that depicts the components as well as the possible layers of an assistant platform, the mechanism that determines the value creation on assistant platforms, and the ecosystem with its network effects, which emerge from the multi-sided nature of assistant platforms. The model has been derived from a literature review and is illustrated with examples of existing assistant platforms. Its main purpose is to advance the understanding of assistant platforms and to trigger future research.
Size and cost of a switched mode power supply can be reduced by increasing the switching frequency. The maximum switching frequency and the maximum conversion ratio are limited by the duty cycle of a PWM signal. In DCDC converters, a sawtooth generator is the fundamental circuit block to generate the PWM signal. The presented PWM generator is based on two parallel, fully interleaved PWM generator stages, each containing an integrator based sawtooth generator and two 3-stage highspeed comparators. A digital multiplexing of the PWM signals of each stage eliminates the dependency of the minimum on-time on the large reset times of the sawtooth ramps. A separation of the references of the PWM comparators in both stage allows to configure the PWM generator for a DCDC converter operating in fixed frequency or in constant on-time mode, which requires an operation in a wide frequency range. The PWM generator was fabricated in an 180 nm HV BiCMOS technology, as part of a DCDC converter. Measurements confirm minimum possible ontime pulses as short as 2 ns and thus allows switching frequencies of DCDC converters of >50 MHz at small duty cycle of <10%. At moderate duty cycles switching frequencies up to 100 MHz are possible.
Many modern DBMS architectures require transferring data from storage to process it afterwards. Given the continuously increasing amounts of data, data transfers quickly become a scalability limiting factor. Near-Data Processing and smart/computational storage emerge as promising trends allowing for decoupled in-situ operation execution, data transfer reduction and better bandwidth utilization. However, not every operation is suitable for an in-situ execution and a careful placement and optimization is needed.
In this paper we present an NDP-aware cost model. It has been implemented in MySQL and evaluated with nKV. We make several observations underscoring the need for optimization.
A fast transient current-mode buckboost DC-DC converter for portable devices is presented. Running at 1 MHz the converter provides stable 3 V from a 2.7 V to 4.2 V Li-Ion battery. A small voltage under-/overshoot is achieved by fast transient techniques: (1) adaptive pulse skipping (APS) and (2) adaptive compensation capacitance (ACC). The proposed converter was implemented in a 0.25 μm CMOS technology. Load transient simulations confirm the effectiveness of APS and ACC. The improvement in voltage undershoot and response time at light-to-heavy load step (100 mA to 500 mA), are 17 % and 59 %, respectively, in boost mode and 40 % and 49 %, respectively, in buck mode. Similar results are achieved at heavy-to-light load step for overshoot and response time.
Type 1 diabetes is a chronic and a life threatening disease: an adjusted treatment and a proper management of the disease are crucial to prevent or delay the complications of diabetes. Although during the last decade the development of the artificial pancreas has presented great advances in diabetes care, the multiple daily injections therapy still represents the most widely used treatment option for type 1 diabetes. This work presents the proposal and first development stages of an application focused on guiding patients using the continuous glucose monitors and smart pens together with insulin and carbohydrates recommendations. Our proposal aims to develop a platform to integrate a series of innovative machine learning models and tools rigorously tested together with the use of the latest IoT devices to manage type 1 diabetes. The resulting system actually closes the loop, like the artificial pancreas, but in an intermittent way.
In modern times markets are very dynamic. This situation requires agile enterprises to have the ability to react fast on market influences. Thereby an enterprise’ IT is especially affected, because new or changed business models have to be realized. However, enterprise architectures (EA) are complex structures consisting of many artifacts and relationships between them. Thus analyzing an EA becomes to a complex task for stakeholders. In addition, many stakeholders are involved in decision-making processes, because Enterprise Architecture Management (EAM) targets providing a holistic view of the enterprise. In this article we use concepts of Adaptive Case Management (ACM) to design a decision-making case consisting of a combination of different analysis techniques to support stakeholders in decision-making. We exemplify the case with a scenario of a fictive enterprise.
The increasing share of renewable energy with volatile production results in higher variability of prices for electrical energy. Optimized operating schedules, e.g., for industrial units, can yield a considerable reduction of energy costs by shifting processes with high power consumption to times with low energy prices. We present a distributed control architecture for virtual power plants (VPPs) where VPP participants benefit from flexible adaptation of schedules to price forecasts while maintaining control of their operating schedule. An aggregator trades at the energy market on behalf of the participants and benefits from more detailed and reliable load profiles within the VPP.
We present a dual active bridge topology suitable for wide voltage range applications covering all combinations of 200V to 600V on the input and 20V to 60V on the output with constant power of 1kW.We employ a stepped inductance scheme to adjust the effective inductance of the converter, thus extending the efficient operation range. Using a variable switching frequency between 35 kHz and 150 kHz with operation-point-dependent limits further increases the performance of the converter. A prototype was built and the proposed changes have been compared to a fixed frequency, fixed inductance implementation. Measurements show a maximum loss reduction of 40 %, leading to a peak efficiency of 97% while maintaining constant output power over the entire working area.
In recent years, artificial intelligence (AI) has increasingly become a relevant technology for many companies. While there are a number of studies that highlight challenges and success factors in the adoption of AI, there is a lack of guidance for firms on how to approach the topic in a holistic and strategic way. The aim of this study is therefore to develop a conceptual framework for corporate AI strategy. To address this aim, a systematic literature review of a wide spectrum of AI-related research is conducted, and the results are analyzed based on an inductive coding approach. An important conclusion is that companies should consider diverse aspects when formulating an AI strategy, ranging from technological questions to corporate culture and human resources. This study contributes to knowledge by proposing a novel, comprehensive framework to foster the understanding of crucial aspects that need to be considered when using the emerging technology of AI in a corporate context.
The rapid development and growth of knowledge has resulted in a rich stream of literature on various topics. Information systems (IS) research is becoming increasingly extensive, complex, and heterogeneous. Therefore, a proper understanding and timely analysis of the existing body of knowledge are important to identify emerging topics and research gaps. Despite the advances of information technology in the context of big data, machine learning, and text mining, the implementation of systematic literature reviews (SLRs) is in most cases still a purely manual task. This might lead to serious shortcomings of SLRs in terms of quality and time. The outlined approach in this paper supports the process of SLRs with machine learning techniques. For this purpose, we develop a framework with embedded steps of text mining, cluster analysis, and network analysis to analyze and structure a large amount of research literature. Although the framework is presented using IS research as an example, it is not limited to the IS field but can also be applied to other research areas.
A wide-bandwidth galvanically isolated current sensing circuit with an integrated Rogowski coil in 180nm CMOS is presented. Exploiting the high-frequency properties of an optimized on-chip Rogowski coil, currents can be measured up to a bandwidth of 75 MHz. The analog sensor front-end comprises a two-stage integrator, which allows a chopper frequency below signal bandwidth, resulting in 2.2 mVrms output noise. An additional integrated Hall sensor extends the measurement range towards DC.
Due to their superior fast-switching performance, GaN transistors show enormous potential to enable compact power electronics in applications like renewable energy, electrical cars and home appliances by shrinking down the size of passives. However, fast switching poses challenges for the gate driver. Since GaN transistors have a low threshold voltage Vt of ~1V, an unintended driver turn-on can occur in case of a unipolar gate control as shown for a typical half-bridge in Fig. 24.2.1 (top left). This is due to coupling via the gate-drain capacitance (Miller coupling), when the low-side driver turns on, causing a peak current into the gate. This is usually tackled by applying a negative gate voltage to enhance the safety margin towards Vt, resulting in a bipolar gate-driving scheme. In many power-electronics applications GaN transistors operate in reverse conduction, carrying the inductor current during the dead time t, when the high-side and low-side switch are off (as illustrated at a high-side switch in Fig. 24.2.1, bottom left). As there is no real body diode as in silicon devices, the GaN transistor turns on in reverse operation with a voltage drop VF across the drain-source terminals (quasi-body diode behavior). As a negative gate voltage adds to VF, 63% higher reverse-conduction losses were measured for a typical GaN switch in bipolar gate-drive operation. This drawback is addressed by a three-level gate voltage (positive, 0V, negative), which at the same time provides robustness against unintended turn-on similar to the bipolar gate driver, proven in [1] for a discrete driver.
A fully passive RFID temperature sensor SoC with an accuracy of ±0.4°C (3σ) from 0°C to 125°C
(2018)
This paper presents a fully passive 13.56 MHz RFID temperature sensor system-on-chip. Its power management unit (PMU) operates over a large temperature range using a zero temperature coefficient (TC) bias source. On-chip temperature sensing is accomplished with low voltage, low power CMOS circuitry and time-domain signal processing. Two operating modes have been defined to study supply noise sensitivity: command mode and listening mode, which represent sensor operation during RFID command transfer and listening, respectively. Besides a standard readout command, a customized serial readout command is utilized to distinguish the data from both modes. In command mode, the sensor suffers from interference from the RFID command packet and outputs interference as well, while the sensor outputs no interference in listening mode. Measurements show that sensor resolution in listening mode is improved by a factor of approximately 16 compared to command mode. The chip was fabricated in a standard 0.35 µm CMOS technology and chip-on-board mounted to a tuned RFID transponder coil on an aluminium core FRA4 PCB substrate. Real-time wireless temperature sensing has been demonstrated with a commercial HF RFID reader. With a two-point calibration, the SoC achiesves a 3σ sensing accuracy of ±0.4°C from 0° C to 125° C.
A gate driver approach is presented for the reduction of turn-on losses in hard switching applications. A significant turn-on loss reduction of up to 55% has been observed for SiCMOSFETs. The gate driver approach uses a transformer which couples energy from the power path back into the gate path during switching events, providing increased gate driver current and thereby faster switching speed.
The gate driver approach was tested on a boost converter running at a switching frequency up to 300 kHz. With an input voltage of 300V and an output voltage of 600V, it was possible to reduce the converter losses by 8% at full load. Moreover, the output power range could be extended by 23% (from 2.75kW to 3.4 kW) due to the reduction of the turn-on losses.
This work presents a fully integrated GaN gate driver in a 180nm HV BCD technology that utilizes high-voltage energy storing (HVES) in an on-chip resonant LC tank, without the need of any external capacitor. It delivers up to 11nC gate charge at a 5V GaN gate, which exceeds prior art by a factor of 45-83, supporting a broad range of GaN transistor types. The stacked LC tank covers an area of only 1.44mm², which corresponds to a superior value of 7.6nC/mm².
In this paper, we address the novel EDP (Expert Design Plan) principle for procedural design automation of analog integrated circuits, which captures the knowledge-based design strategy of human circuit designers in an executable script, making it reusable. We present the EDP Player, which enables the creation and execution of EDPs for arbitrary circuits in the Cadence® Virtuoso® Design Environment. The tool provides a generic version of an instruction set, called EDPL (EDPLanguage), enabling emulation of a typical manual analog sizing flow. To automate the design of a Miller Operational Amplifier and to create variants of a Smart Power IC, several EDPs were implemented using this tool. Employing these EDPs leads to a strong reduction of design time without compromising design quality or reliability.
A generic, knowledge-based method for automatic topology selection of analog circuits in a predefined analog reuse library is presented in this paper on the OTA (Operational Transconductance Amplifier) example. Analog circuits of a given circuit class are classified in a topology tree, where each node represents a specific topology. Child nodes evolve from their parent nodes by an enhancement of the parent node’s topological structure. Topology selection is performed by a depth first-search in the topology tree starting at the root node, thus checking topologies of increasing complexity. The decisions at each node are based on solving equations or – if this is not possible – on simulations. The search ends at the first (and thus the simplest) topology which can meet the specification after an adequate circuit sizing. The advantages of the generic, tree based topology selection method presented in this paper are shown in comparison to a pool selection method and to heuristic approaches. The selection is based on an accomplished chip investigation.
We present a new methodology for automatic selection and sizing of analog circuits demonstrated on the OTA circuit class. The methodology consists of two steps: a generic topology selection method supported by a “part-sizing” process and subsequent final sizing. The circuit topologies provided by a reuse library are classified in a topology tree. The appropriate topology is selected by traversing the topology tree starting at the root node. The decision at each node is gained from the result of the part-sizing, which is in fact a node-specific set of simulations. The final sizing is a simulation-based optimization. We significantly reduce the overall simulation effort compared to a classical simulation-based optimization by combining the topology selection with the part-sizing process in the selection loop. The result is an interactive user friendly system, which eases the analog designer’s work significantly when compared to typical industrial practice in analog circuit design. The topology selection method and sizing process are implemented as a tool into a typical analog design environment. The design productivity improvement achievable by our method is shown by a comparison to other design automation approaches.
Rapidly growing population and increasing amount of shipments induced by the e-commerce are two of the main reasons for the constantly rising urban freight traffic. Cities are therefore overwhelmed by a growing stream of goods and the available infrastructure, shared between people and goods traffic, often reached its maximum capacity. Phenomena such as traffic congestion, pollution and lack of space are direct consequences of this trend and their impact on the quality of life in the city is not negligible. City administrations are keen to evaluate innovative city logistics concepts and adopt alternative solutions, to overcome the challenges posed by such a dynamic environment, constrained in existing infrastructure. In this paper, a heuristic method based on the utility analysis is presented. Thanks to a modular approach accounting for stakeholders´ requirements, possible different scenarios and available technologies, the development of new city logistic concepts is supported. The proposed method is then applied to a case study concerning the city of Reutlingen (Germany). Results are presented and a brief discussion leads to the conclusion.
This paper presents a compact 3 kW bidirectional GaN-HEMT DC/DC converter for 360V to 400-500 V. A very high efficiency has been reached by applying a zero voltage turn-on in conjunction with a negative gate-source voltage, even though normally-off HEMTs are used. Further improvements were achieved by adapting the switching frequency to the load current and output voltage, as will be explained by means of the loss contribution of the specific elements for a constant and an adaptive switching frequency. Measurements have shown a high converter efficiency exceeding 99% over a wide output power range of up to 3 kW.
This paper presents a new European initiative to support the sustainable empowerment of the ageing society. Empowerment in this context represents the capability to have a self-determined, autonomous and healthy life. The paper justifies the need of such an initiative and highlights the role that telemedicine and ambient assisted living can play in this environment.
A hybrid deep registration of MR scans to interventional ultrasound for neurosurgical guidance
(2021)
Despite the recent advances in image-guided neurosurgery, reliable and accurate estimation of the brain shift still remains one of the key challenges. In this paper, we propose an automated multimodal deformable registration method using hybrid learning-based and classical approaches to improve neurosurgical procedures. Initially, the moving and fixed images are aligned using classical affine transformation (MINC toolkit), and then the result is provided to the convolutional neural network, which predicts the deformation field using backpropagation. Subsequently, the moving image is transformed using the resultant deformation into a moved image. Our model was evaluated on two publicly available datasets: the retrospective evaluation of cerebral tumors (RESECT) and brain images of tumors for evaluation (BITE). The mean target registration errors have been reduced from 5.35 ± 4.29 to 0.99 ± 0.22 mm in the RESECT and from 4.18 ± 1.91 to 1.68 ± 0.65 mm in the BITE. Experimental results showed that our method improved the state-of-the-art in terms of both accuracy and runtime speed (170 ms on average). Hence, the proposed method provides a fast runtime for 3D MRI to intra-operative US pair in a GPU-based implementation, which shows a promise for its applicability in assisting the neurosurgical procedures compensating for brain shift.
Data governance have been relevant for companies for a long time. Yet, in the broad discussion on smart cities, research on data governance in particular is scant, even though data governance plays an essential role in an environment with multiple stakeholders, complex IT structures and heterogeneous processes. Indeed, not only can a city benefit from the existing body of knowledge on data governance, but it can also make the appropriate adjustments for its digital transformation. Therefore, this literature review aims to spark research on urban data governance by providing an initial perspective for future studies. It provides a comprehensive overview of data governance and the relevant facets embedded in this strand of research. Furthermore, it provides a fundamental basis for future research on the development of an urban data governance framework.
A TLP system with a very low characteristic impedance of 1.5 Ω and a selectable pulse length from 0.5 to 6 μs is presented. It covers the entire operation region of many power semiconductors up to 700 V and 400 A. Ist applicability is demonstrated by determining the Output characteristics for two Cool MOS devices up to destruction.
The members of the European TRIZ Campus (ETC) have been learning from and working together with many honorable members of MATRIZ Official for many years and feel very connected to the official International TRIZ Association.
To further spread the TRIZ methodology and TRIZ teaching in the European area in the past 12 months the ETC has put a lot of thought in how making TRIZ accessible to a broader audi-ence and getting more professionals in touch with the methodology was one of the focal points.
To this end, we have developed new formats such as the "Trainer Day" to support trainers on their way into practice. We have drawn up detailed quality guidelines for the teaching of the TRIZ methodology, which are intended to provide orientation for the design of training classes and docu-mentation. We strive for exchange with representatives of "neighbouring" methods such as Six sigma, Lean, DFMA and Design Thinking to indicate synergies and added value among methods and approaches of different kinds. We are testing formats for community building, in order to connect users of all places more strongly with the TRIZ methodology through communication and information of-fers. If TRIZ users feel alone in their organizations, the exchange outside their organi-zation helps them to keep up with the TRIZ methodology. Moreover, the ETC strives to increase the ability to communicate the benefits of TRIZ-usage inside organizations. We discuss, how to reach teachers and students of all age, to make them the unique way of inventive thinking accessible.
In our paper we want to give other MATRIZ Official members insights and share our experi-ences and best practices with our fellow MO members.
Enterprise Governance, Risk and Compliance (GRC) systems are key to managing risks threatening modern enterprises from many different angles. Key constituent to GRC systems is the definition of controls that are implemented on the different layers of an Enterprise Architecture (EA). As part of the compliance aspect of GRC, the effectiveness of these controls is assessed and reported to relevant management bodies within the enterprise. In this paper we present a metamodel which links controls to the affected elements of an EA and supplies a way of expressing associated assessment techniques and results. We complement the metamodel with an expository instantiation in a cockpit for control compliance applied in an international enterprise in the insurance industry.
The high system flexibility necessary for the full automation of complex and unstructured tasks leads to increased complexity, thus higher costs. On the other hand, the effectiveness and performance of such systems decrease, explaining the unfulfilled potential of robotcs in sectors such as intralogistics, where the benefits of a robotic solution rarely justify its costs. Taking the distance from the false idea that a task should be either fully automated, or fully manual, this aper presents a method for design of a lean human-robot interaction (HRI) withe the objective of the "right level of automation", where functions are divided among human and automated agends, so that the overall process gains in performances and/or costs. ... The 10 progressive steps of the method are presented and discussed with reference to their graphical tool: the House of Quality Interaction.
A millimeter-wave power amplifier concept in an advanced silicon germanium (SiGe) BiCMOS technology is presented. The goal of the concept is to investigate the impact of physical limitations of the used heterojunction bipolar transistors (HBT) on the performance of a 77 GHz power amplifier. High current behavior, collectorbase breakdown and transistor saturation can be forced with the presented design. The power amplifier is manufactured in an advanced SiGe BiCMOS technology at Infineon Technologies AG with a maximum transit frequency fT of around 250 GHz for npn HBT’s [1]. The simulation results of the power amplifier show a saturated output power of 16 dBm at a power added efficiency of 13%. The test chip is designed for a supply voltage of 3.3 V and requires a chip size of 1.448 x 0.930 mm².
The financial crisis of 2007-2010 was probably one of the greatest, most lustrous black-swan events that people of our generation(s) will experience – and at its heart, it was a dynamic phenomenon. It is stated in the vision of the System Dynamics Society that we aspire to transform society by influencing decision-making. Yet, it seems as if system dynamics did not play any significant role in this crisis: we did not examine the markets, we did not provide insights to banks, and we did not warn governments or the people. In our presentation we describe the dynamics involved in a housing bubble, and describe what made the last one different. With the insights gained from this exercise we conclude that, from a system dynamics perspective, the dimension of the financial crisis of 2007-2009 was eminently foreseeable, which will lead us to pose the following question: where were we as a field while this crisis was unfolding, why were we not active players? We present a range of potential answers to this question, hoping to provoke some reflection… and maybe some (re)action.
Model-guided Therapy and Surgical Workflow Systems are two interrelated research fields, which have been developed separately in the last years. To make full use of both technologies, it is necessary to integrate them and connect them to Hospital Information Systems. We propose a framework for integration of Model-guided Therapy in Hospital Information Systems based on the Electronic Medical Record, and a taskbased Workflow Management System, which is suitable for clinical end users. Two prototypes - one based on Business Process Modeling Language, one based on the serum-board - are presented. From the experience with these prototypes, we developed a novel personalized visualization system for Surgical Workflows and Model-guided Therapy. Key challenges for further development are automated situation detection and a common communication infrastructure.
This paper presents an approach for the implementation of a modular and scalable power electronics device for controlling electric drives in the field of electric vehicles using wide bandgap semiconductor devices. The main idea is to achieve the required output currents or voltages by connecting adequately designed hardware modules in parallel or in series. This particular design is based on the fact that the single modules generate a continuous and specified output voltage from a given dc voltage, e.g. an intermediate circuit or battery voltage. The main benefit is, that different current or voltage requirements can be satisfied based on a single module thus decreasing development and production costs. The current paper focuses on the connection in parallel of such modules. A control architecture is illustrated and a first proof of concept is given.
While several service-based maintainability metrics have been proposed in the scientific literature, reliable approaches to automatically collect these metrics are lacking. Since static analysis is complicated for decentralized and technologically diverse microservice-based systems, we propose a dynamic approach to calculate such metrics from runtime data via distributed tracing. The approach focuses on simplicity, extensibility, and broad applicability. As a first prototype, we implemented a Java application with a Zipkin integrator, 23 different metrics, and five export formats. We demonstrated the feasibility of the approach by analyzing the runtime data of an example microservice based system. During an exploratory study with six participants, 14 of the 18 services were invoked via the system’s web interface. For these services, all metrics were calculated correctly from the generated traces.
3D morphable face models are a powerful tool in computer vision. They consist of a PCA model of face shape and colour information and allow to reconstruct a 3D face from a single 2D image. 3D morphable face models are used for 3D head pose estimation, face analysis, face recognition, and, more recently, facial landmark detection and tracking. However, they are not as widely used as 2D methods - the process of building and using a 3D model is much more involved.
In this paper, we present the Surrey Face Model, a multi resolution 3D morphable model that we make available to the public for non-commercial purposes. The model contains different mesh resolution levels and landmark point annotations as well as metadata for texture remapping. Accompanying the model is a lightweight open-source C++ library designed with simplicity and ease of integration as its foremost goals. In addition to basic functionality, it contains pose estimation and face frontalisation algorithms. With the tools presented in this paper, we aim to close two gaps. First, by offering different model resolution levels and fast fitting functionality, we enable the use of a 3D Morphable Model in time-critical applications like tracking. Second, the software library makes it easy for the community to adopt the 3D morphable face model in their research, and it offers a public place for collaboration.
This paper presents a new broadband antenna for satellite communications. It describes the procedure involved in the design of a microstrip antenna array and its multi-level passive feed network that together yield circular polarization and the necessary gain to be used in an earth-satellite link. The designed antenna is notable for its large bandwidth, circular polarization, high gain and small dimensions.
A new method for the analysis of movement dependent parasitics in full custom designed MEMS sensors
(2017)
Due to the lack of sophisticated microelectromechanical systems (MEMS) component libraries, highly optimized MEMS sensors are currently designed using a polygon driven design flow. The strength of this design flow is the accurate mechanical simulation of the polygons by finite element (FE) modal analysis. The result of the FE-modal analysis is included in the system model together with the data of the (mechanical) static electrostatic analysis. However, the system model lacks the dynamic parasitic electrostatic effects, arising from the electric coupling between the wiring and the moving structures. In order to include these effects in the system model, we present a method which enables the quasi dynamic parasitic extraction with respect to in-plane movements of the sensor structures. The method is embedded in the polygon driven MEMS design flow using standard EDA tools. In order to take the influences of the fabrication process into account, such as etching process variations, the method combines the FE-modal analysis and the fabrication process simulation data. This enables the analysis of dynamic changing electrostatic parasitic effects with respect to movements of the mechanical structures. Additionally, the result can be included into the system model allowing the simulation of positive feedback of the electrostatic parasitic effects to the mechanical structures.
This paper introduces a novel placement methodology for a common-centroid (CC) pattern generator. It can be applied to various integrated circuit (IC) elements, such as transistors, capacitors, diodes, and resistors. The proposed method consists of a constructive algorithm which generates an initial, close to the optimum, solution, and an iterative algorithm which is used subsequently, if the output of constructive algorithm does not satisfy the desired criteria. The outcome of this work is an automatic CC placement algorithm for IC element arrays. Additionally, the paper presents a method for the CC arrangement evaluation. It allows for evaluating the quality of an array, and a comparison of different placement methods.
This article presents a modified method of performing power flow calculations as an alternative to pure energy-based simulations of off-grid hybrid systems. The enhancement consists in transforming the scenario-based power flow method into a discrete time-dependent algorithm with the inclusion of bus and controller dynamics.
A novel brushless excitation concept for synchronous machines with a rotating power converter is proposed in this paper. The concept does not need an auxiliary winding or any other modification to the machine structure apart from an inverter with a DC link capacitor and a controller on the rotor. The power required for the rotor excitation is provided by injecting harmonics into the stator winding. Thus, a voltage in the field coil is induced. The rotor inverter is controlled such that the alternating current charges the DC link capacitor. At the same time the inverter supplies the DC field current to the field coil. The excitation concept is first developed in theory, then presented using an analytical model and FEA, and lastly investigated with a prelimininary experimental setup.
A novel configuration of the dual active bridge (DAB) DC/DC converter is presented, enabling more efficient wide voltage range conversion at light loads. A third phase leg as well as a center tapped transformer are introduced to one side of the converter. This concept provides two different turn ratios, thus extending the zero voltage switching operation resulting in higher efficiency. A laboratory prototype was built converting an input voltage of 40V to an output voltage in the range of 350V to 650V. Measurements show a significant increase up to 20% in the efficiency for light-load operation.
This paper presents a novel emulation concept for the test of smart contracts and Distributed Ledger Technologies (DLT) in distribute control or energy economy tasks and use cases. The concept uses state of the art behavioral modeling tools such as Matlab Simulink but presents a possible way to solve the shortfall of Simulink in communicating to DLT-Nodes directly. This is solved through a middleware solution. After this, an example used in verifying the test bed is presented and the target demonstration object is described. Finally, the possible expansion of the system is discussed and presented.
Many GaN power transistors contain a PN junction between gate and the channel region close to the source. In order to maintain the on-state, current must continuously be supplied to the junction. Therefore, the commonly recommended approach uses a gate bias voltage of 12V to compensate the Miller current through a boost circuit. For the same purpose, a novel gate driving method based on an inductive feed forward has been presented. With this, stable turn-on can be achieved even for a bias voltage of only 5V. The effectiveness of this concept is demonstrated by double pulse measurements, switching currents up to 27A and a voltage of 400V. For both approaches a compact design with low source inductance is characterized. In addition to the significant reduction of the gate bias voltage and peak gate current, the new approach reduces the switching losses for load currents >23 A.
Modern power semiconductor devices have low capacitances and can therefore achieve very fast switching transients under hard-switching conditions. However, these transients are often limited by parasitic elements, especially by the source inductance and the parasitic capacitances of the power semiconductor. These limitations cannot be compensated by conventional gate drivers. To overcome this, a novel gate driver approach for power semiconductors was developed. It uses a transformer which accelerates the switching by transferring energy from the source path to the gate path.
Experimental results of the novel gate driver approach show a turn-on energy reduction of 78% (from 80 μJ down to 17 μJ) with a drain-source voltage of 500V and a drain current of 60 A. Furthermore, the efficiency improvement is demonstrated for a hard-switching boost converter. For a switching frequency of 750 kHz with an input voltage of 230V and an output voltage of 400V, it was possible to extend the output power range by 35%(from 2.3kW to 3.1 kW), due to the reduction of the turn-on losses, therefore lowering the junction temperature of the GaN-HEMT.
A novel gate driving approach to balance the transient current of parallel-connected GaN-HEMTs
(2018)
To enable higher current handling capability of GaN-based DC/DC converters, devices have to be used in parallel. However, their switching times differ, especially if their threshold voltages are not identical, which causes unbalanced device current. This paper focuses on the homogeneous distribution of turn-on switching losses of GaN-HEMTs connected in parallel. By applying a new gate driver concept, the transient current is distributed evenly. The effectiveness of this concept is demonstrated by double pulse measurements, for switching currents up to 45A and a voltage of 400V. A uniform current distribution is achieved, including a reduction of the turn-on losses by 50% compared to a conventional setup.
In contrast to IC design, MEMS design still lacks sophisticated component libraries. Therefore, the physical design of MEMS sensors is mostly done by simply drawing polygons. Hence, the sensor structure is only given as plain graphic data which hinders the identification and investigation of topology elements such as spring, anchor, mass and electrodes. In order to solve this problem, we present a rule-based recognition algorithm which identifies the architecture and the topology elements of a MEMS sensor. In addition to graphic data, the algorithm makes use of only a few marking layers, as well as net and technology information. Our approach enables RC-extraction with commercial field solvers and a subsequent synthesis of the sensor circuit. The mapping of the extracted RC-values to the topology elements of the sensor enables a detailed analysis and optimization of actual MEMS sensors.
In the upcoming years, huge benefits are expected from Artificial Intelligence (AI). However, there are also risks involved in the technology, such as accidents of autonomous vehicles or discrimination by AI-based recruitment systems. This study aims to investigate public perception of these risks, focusing on realistic risks of Narrow AI, i.e., the type of AI that is already productive today. Based on perceived risk theory, several risk scenarios are examined using data from an exploratory survey. This research shows that AI is perceived positively overall. The participants, however, do evaluate AI critically when being confronted with specific risk scenarios. Furthermore, a strong positive relationship between knowledge about AI and perceived risk could be shown. This study contributes to knowledge by advancing our understanding of the awareness and evaluation of the risks by consumers and has important implications for product development, marketing and society.
A single-phase fixed-frequency operated power factor correction circuit with reduced switching losses is proposed. The circuit uses the combination of a boost converter with an added clamp-switch, a pulse wave shaping circuit, and a standard control IC to discharge the transistor's output capacitance prior to its turn-on. In this way, a very low-complexity control circuit implementation to reduce switching losses or even achieve complete zero-voltage switching without additional sensors is possible. Moreover, this operation method is achieved at a constant switching frequency, possibly simplifying the design of the EMI filter and the converter's inductor. Experimental test results for a 100 W prototype converter are presented to validate the feasibility of the proposed operating method and corresponding circuit structure.
This work presents a spiral antenna array, which can be used in the V- and W-Band. An array equipped with Dolph-Chebychev coefficients is investigated to address issues related to the low gain and side lobe level of the radiating structure. The challenges encountered in this achievement are to provide an antenna that is not only good matched but also presents an appreciable effective bandwidth at the frequency bands of interest. Its radiation properties including the effective bandwidth and the gain are analyzed for the W-Band.
A procedural approach to automate the manual design process in analog integrated circuit design
(2018)
This paper presents a novel approach to automating the design of analog integrated circuits: (1) the Expert Design Plan (EDP), a procedural generator, and (2) the EDP Language, a high-level description language for writing an EDP. An EDP is a parameterizable, executable script, which reproduces a designer’s course of action when designing a circuit. Thus, an EDP formalizes the design expert’s knowledge-based strategy and makes it reusable. Since it is essential that an EDP represents a circuit designers’ way of thinking and working as close as possible, the designers themselves should be enabled to create the EDP. Therefore, our approach provides a input method through a domain-specific language called EDP Language (EDPL). Using this language is intuitive and requires no special training. In an exemplary implementation of our approach, a common-source amplifier is automatically sized using a set of only 10 instructions. Even in the first usage our EDP approach has appeared to be more efficient than the manual sizing process.
Motivation
In order to enable context-aware behavior of surgical assistance systems, the acquisition of various information about the current intraoperative situation is crucial. To achieve this, the complex task of situation recognition can be delegated to a specialized system. Consequently, a standardized interface is required for the seamless transfer of the recognized contextual information to the assistance systems, enabling them to adapt accordingly.
Methods
Our group analyzed four medical interface standards to determine their suitability for exchanging intraoperative contextual information. The assessment was based on a harmonized data and service model derived from the requirements of expected context-aware use cases. The Digital Imaging and Communications in Medicine (DICOM) and IEEE 11073 for Service-oriented Device Connectivity (SDC) were identified as the most appropriate standards.
Results
We specified how DICOM Unified Procedure Steps (UPS), can be used to effectively communicate contextual information. We proposed the inclusion of attributes to formalize different granularity levels of the surgical workflow.
Conclusions
DICOM UPS SOP classes can be used for the exchange of intraoperative contextual information between a situation recognition system and surgical assistance systems. This can pave the way for vendor-independent context awareness in the OR, leading to targeted assistance of the surgical team and an improvement of the surgical workflow.
DMOS transistors in integrated smart power technologies are often subject to cyclic power dissipation with substantial selfheating. This leads to repetitive thermo mechanical stress, causing fatigue of the on-chip metallization and limiting the lifetime. Hence, most designs use large devices for lower peak temperatures and thus reduced stress to avoid premature failures.
However, significantly smaller DMOS transistors are acceptable if the system reverts to a safer operating condition with lower stress when a failure is expected to occur in the near future. Hence, suitable early-warning sensors are required. This paper proposes a floating metal meander embedded between DMOS source and drain to detect an impending metallization failure. Measurement results of several variants will be presented and discussed, investigating their suitability as early warning indicators.
Documentation of clinical processes, especially in the perioperative are, is a base requirement for quality of service. Nonetheless, the documentation is a burden for the medical staff since it distracts from the clinical core process. An intuitive and user-friendly documentation system could increase documentation quality and reduce documentation workload. The optimal system solution would know what happened and the person documenting the step would need a single “confirm” button. In many cases, such a linear flow of activities is given as long as only one profession (e.g. anaestesiology, scrub nurse) is considered, but even in such cases, there might be derivations from the linear process flow and further interaction is required.
Multilevel-cell (MLC) flash is commonly deployed in today’s high density NAND memories, but low latency and high reliability requirements make it barely used in automotive embedded flash applications. This paper presents a time domain voltage sensing scheme that applies a dynamic voltage ramp at the cells’ control gate (CG) in order to achieve fast and reliable sensing suitable for automotive applications.
In analog layout design, chip floorplans are usually still handcrafted by human experts. Particularly, the nondiscrete variability of block dimensions must be exploited thereby, which is a serious challenge for optimization-based algorithmic floorplanners. This paper presents a fundamentally new automation approach based on self-organization, in which floorplan blocks can autonomously move, rotate and deform themselves to jointly let compact results emerge from a synergistic flow of interaction. Our approach is able to minimize area and wirelength, supports nonslicing floorplan structures, can consider fully variable block dimensions, accounts for a fixed rectilinear boundary, and works absolutely deterministic. The approach is innovatively different from conventional, top-down oriented floorplanning algorithms.
Sleep quality and in general, behavior in bed can be detected using a sleep state analysis. These results can help a subject to regulate sleep and recognize different sleeping disorders. In this work, a sensor grid for pressure and movement detection supporting sleep phase analysis is proposed. In comparison to the leading standard measuring system, which is Polysomnography (PSG), the system proposed in this project is a non invasive sleep monitoring device. For continuous analysis or home use, the PSG or wearable actigraphy devices tends to be uncomfortable. Besides this fact, they are also very expensive. The system represented in this work classifies respiration and body movement with only one type of sensor and also in a non invasive way. The sensor used is a pressure sensor. This sensor is low cost and can be used for commercial proposes. The system was tested by carrying out an experiment that recorded the sleep process of a subject. These recordings showed the potential for classification of breathing rate and body movements. Although previous researches show the use of pressure sensors in recognizing posture and breathing, they have been mostly used by positioning the sensors between the mattress and bedsheet. This project however, shows an innovative way to position the sensors under the mattress.
This paper presents a measurement setup and an assembly technique suitable for characterization of power semiconductor devices under very high temperature conditions exceeding 500°C. An important application of this is the experimental investigation of wide bandgap semiconductors. Measurement results are shown for a 1200V SiC MOSFET and a 650V depletion mode GaN HEMT.
A simple determination of the error voltage compensation map for motor parameter identification
(2018)
This paper proposes a new method for determining the error voltage compensation map in a parameter identification procedure of three-phase induction motors with an inverter. The compensation curve depending on the motor current is determined using a simple procedure based on given reference voltage steps and the corresponding steady state values of the stator current of the induction motor.
The cloud evolved into an attractive execution environment for parallel applications from the High Performance Computing (HPC) domain. Existing research recognized that parallel applications require architectural refactoring to benefit from cloud-specific properties (most importantly elasticity). However, architectural refactoring comes with many challenges and cannot be applied to all applications due to fundamental performance issues. Thus, during the last years, different cloud migration strategies have been considered for different classes of parallel applications. In this paper, we provide a survey on HPC cloud migration research. We investigate on the approaches applied and the parallel applications considered. Based on our findings, we identify and describe three cloud migration strategies.
Blockchain is a technology for the secure processing and verification of data transactions based on a distributed peer-to-peer network that uses cryptographic processes, consensus algorithms, and backward-linked blocks to make transactions virtually immutable. Within supply chain management, blockchain technology offer potentials in increasing supply chain transparency, visibility, automation, and efficiency. However, its complexity requires future employees to have comprehensive knowledge regarding the functionality of blockchain-based applications in order to be able to apply their benefits to scenarios in supply chain and production. Learning factories represent a suitable environment allowing learners to experience new technologies and to apply them to virtual and physical processes throughout value chains. This paper presents a concept to practically transfer knowledge about the technical functionality of blockchain technology to future engineers and software developers working within supply chains and production operations to sensitize them regarding the advantages of decentralized applications. First, the concept proposes methods to playfully convey immutable backward-linked blocks and the embedment of blockchain smart contracts. Subsequently, the students use this knowledge to develop blockchain-based application scenarios by means of an exemplary product in a learning factory environment. Finally, the developed solutions are implemented with the help of a prototypical decentralized application, which enables a holistic mapping of supply chain events.
This project aims to evaluate existing big data infrastructures for their applicability in the operating room to support medical staff with context-sensitive systems. Requirements for the system design were generated. The project compares different data mining technologies, interfaces, and software system infrastructures with a focus on their usefulness in the peri-operative setting. The lambda architecture was chosen for the proposed system design, which will provide data for both postoperative analysis and real-time support during surgery.
Context: Many companies are facing an increasingly dynamic and uncertain market environment, making traditional product roadmapping practices no longer sufficiently applicable. As a result, many companies need to adapt their product roadmapping practices for continuing to operate successfully in today’s dynamic market environment. However, transforming product roadmapping practices is a difficult process for organizations. Existing literature offers little help on how to accomplish such a process.
Objective: The objective of this paper is to present a product roadmap transformation approach for organizations to help them identify appropriate improvement actions for their roadmapping practices using an analysis of their current practices.
Method: Based on an existing assessment procedure for evaluating product roadmapping practices, the first version of a product roadmap transformation approach was developed in workshops with company experts. The approach was then given to eleven practitioners and their perceptions of the approach were gathered through interviews.
Results: The result of the study is a transformation approach consisting of a process describing what steps are necessary to adapt the currently applied product roadmapping practice to a dynamic and uncertain market environment. It also includes recommendations on how to select areas for improvement and two empirically based mapping tables. The interviews with the practitioners revealed that the product roadmap transformation approach was perceived as comprehensible, useful, and applicable. Nevertheless, we identified potential for improvements, such as a clearer presentation of some processes and the need for more improvement options in the mapping tables. In addition, minor usability issues were identified.
This paper compares the influence a video self-avatar and a lack of a visual representation of a body have on height estimation when standing at a virtual visual cliff. A height estimation experiment was conducted using a custom augmented reality Oculus Rift hardware and software prototype also described in this paper. The results show a consistency with previous research demonstrating that the presence of a visual body influences height estimates, just as it has been shown to influence distance estimates and affordance estimates.
Representing users within an immersive virtual environment is an essential functionality of a multi-person virtual reality system. Especially when communicative or collaborative tasks must be performed, there exist challenges about realistic embodying and integrating such avatar representations. A shared comprehension of local space and non-verbal communication (like gesture, posture or self-expressive cues) can support these tasks. In this paper, we introduce a novel approach to create realistic, video-texture based avatars of colocated users in real-time and integrate them in an immersive virtual environment. We show a straight forward and low-cost hard- and software solution to do so. We discuss technical design problems that arose during implementation and present a qualitative analysis on the usability of the concept from a user study, applying it to a training scenario in the automotive sector.
The demonstration project Virtual Power Plant Neckar-Alb is constructing a Virtual Power Plant (VPP) demonstration site at the Reutlingen University campus. The VPP demonstrator integrates a heterogeneous set of distributed energy resources (DERs) which are connected to control the infrastructure and an energy management system. This paper describes the components and the architecture of the demonstrator and presents strategies for demonstration of multiple optimization and control systems with different control paradigms.
In this work, a web-based software architecture and framework for management and diagnosis of large amounts of medical data in an ophthalmologic reading center is proposed. Data management for multi-center studies requires merging of standing data and repeatedly gathered clinical evidence such as vital signs and raw data. If ophthalmologic questions are involved the data acquisition is often provided by non-medical staff at the point of care or a study center, whereas the medical finding is mostly provided by an ophthalmologist in a specialized reading center. The study data such as participants, cohorts and measured values are administrated at a single data center for the entire study. Since a specialized reading center maintains several studies, the medical staff must learn the different data administration for the different data center. With respect to the increasing number and sizes of clinical studies, two aspects must be considered. At first, an efficient software framework is required to support the data management, processing and diagnosis by medical experts at the reading center. In the second place, this software needs a standardized user-interface that has not to be trained/taylore /adapted for each new study. Furthermore different aspects of quality and security controls have to be included. Therefore, the objective of this work is to establish a multi purpose ophthalmologic reading center, which can be connected to different data centers via configurable data interfaces in order to treat various topics simultaneously.
In this paper we describe an interactive web-based tool for visual analysis of Formula 1 data. A calendar-like representation provides an overview of all races on a yearly basis, either in absolute or normalized time. After selecting a dedicated race more details about this race can be explored. Furthermore it is possible to compare up to three different races. Beside visualizing details on dedicated races it is also possible to analyse driver and team performance over time. A user study was applied to get feedback about the usage of the application and decide between different visualization options.
Workflow driven support systems in the peri-operative area have the potential to optimize clinical processes and to allow new situation-adaptive support systems. We started to develop a workflow management system supporting all involved actors in the operating theatre with the goal to synchronize the tasks of the different stakeholders by giving relevant information to the right team members. Using the OMG standards BPMN, CMMN and DMN gives us the opportunity to bring established methods from other industries into the medical field. The system shows each addressed actor their information in the right place at the right time to make sure every member can execute their task in time to ensure a smooth workflow. The system has the overall view of all tasks. Accordingly, a workflow management system including the Camunda BPM workflow engine to run the models, and a middleware to connect different systems to the workflow engine and some graphical user interfaces to show necessary information or to interact with the system are used. The complete pipeline is implemented with a RESTful web service. The system is designed to include different systems like hospital information system (HIS) via the RESTful web service very easily and without loss of data. The first prototype is implemented and will be expanded.
Information systems, which support the workflow in the clinical area, are currently limited to organizational processes. This work shows a first approach of an information system supporting all actors in the perioperative area. The first prototype and proof of concept was a task manager, giving all actors information about their task and the task of all other actors during an intervention. Based on this initial task manager, we implemented an information system based on a workflow engine controlling all processes and all information necessary for the intervention. A second part was the development of a perioperative process visualization which was developed based on a user centered approach jointly with clinicians and OR members.
Lean Management hat in viele Unternehmen Einzug gehalten. Lean Konzepte stellen neue Anforderungen an die Art und Struktur der benötigten Kosteninformation, welche von traditionallen Kostenrechnungssystemen nicht unmittelbar erfüllt werden. Vertreter eines „Lean Accounting“ schlagen deshalb teils radikale Änderungen und eine Vereinfachung der Kostenrechnung vor. Der Beitrag diskutiert die Beschränkungen der traditionellen Kostenrechnung bei der Umsetzung von Lean Management und stellt ausgewählte Ansätze eines „Accounting for Lean“ vor. Die Analyse zeigt, dass Ansätze des Lean Accounting zu eng fokussiert sind und die in der Praxis vorhandene Pluralität der Kostenrechnungsfunktionen nicht adäquat abbilden können. Eine radikale Neugestaltung bestehender Kostenrechnungssysteme wird deshalb als unrealistisch und unbegründet verworfen. Der Beitrag entwickelt alternative Vorschläge, wie Konzepte des Lean Managements und die dafür benötigte Kosteninformation in traditionellen Kostenrechnungssystemen integriert werden können.