Refine
Year of publication
- 2018 (62) (remove)
Document Type
- Conference Proceeding (62) (remove)
Conference Type
- Konferenzartikel (45)
- Konferenz-Abstract (13)
- Sonstiges (3)
- Konferenz-Poster (1)
Language
- English (62) (remove)
Is part of the Bibliography
- yes (62)
Keywords
- RoboCup (3)
- 5G mobile communication (2)
- Access protocols (2)
- Decoding (2)
- Gamification (2)
- Multiuser detection (2)
- Payloads (2)
- Physical layer (2)
- access protocols (2)
- decoding (2)
- network coding (2)
- 3D-Time-of-Flight Cameras (1)
- Affective Computing (1)
- Ageing (1)
- Assistive Technologies (1)
- Atrial fibrillation (1)
- Atrioventricular delay (1)
- Augmented Reality (1)
- Batteries (1)
- Biventricular pacing (1)
- Cardiac resynchronization therapy (1)
- CoBot (1)
- Context-awareness (1)
- Deaf-Blindness (1)
- Electrochemistry (1)
- Emotion Recognition (1)
- Finite element analysis (1)
- Fractionated atrial signals (1)
- Fractionated ventricular signals (1)
- Harmonic analysis (1)
- Human-Robot Collaboration (1)
- Knowledge-based Innovation (1)
- Left atrial ECG (1)
- Left atrial delay (1)
- Left cardiac ECG (1)
- Lithium niobate (1)
- Lithium-ion battery (1)
- MEMS (1)
- MPC (1)
- Metallization (1)
- Mikrostruktur (1)
- Modelling (1)
- PV Applications, Smart PV, PV Battery Systems, PV Power Supplies (1)
- Photovoltaic (1)
- Plastizität (1)
- Rehabilitation (1)
- Roboter (1)
- Robotics (1)
- Robots (1)
- Safe Speed and Separation Monitoring. (1)
- Signal averaging ECG (1)
- Smart Grid (1)
- Smart wearables (1)
- Social Robots (1)
- Soziale Roboter (1)
- Spectral-temporal mapping (1)
- Stahl (1)
- Substrates (1)
- TRIZ (1)
- Task Analysis (1)
- Transesophageal electrocardiography (1)
- Ventricular tachycardia (1)
- Wearables (1)
- accelerometer (1)
- cloud security (1)
- cluster (1)
- cross-industry innovation (1)
- cyclic plasticity (1)
- eco-innovation (1)
- glass (1)
- gyroscope (1)
- hot work tool steel (1)
- inertial measurement unit (1)
- innovation management (1)
- laser material processing (1)
- machine learning (1)
- particle coarsening (1)
- pigment paste (1)
- printing technologies (1)
- process engineering (1)
- project-based learning (1)
- scanning electron microscope (SEM) (1)
- surface treatment (1)
- temperature dependency (1)
Institute
- Fakultät Elektrotechnik und Informationstechnik (E+I) (bis 03/2019) (32)
- Fakultät Maschinenbau und Verfahrenstechnik (M+V) (12)
- ivESK - Institut für verlässliche Embedded Systems und Kommunikationselektronik (12)
- Fakultät Medien und Informationswesen (M+I) (bis 21.04.2021) (10)
- INES - Institut für nachhaltige Energiesysteme (7)
- ACI - Affective and Cognitive Institute (4)
- Fakultät Wirtschaft (W) (4)
- CRT - Campus Research & Transfer (1)
- WLRI - Work-Life Robotics Institute (1)
- Zentrale Einrichtungen (1)
Open Access
- Closed Access (35)
- Open Access (25)
- Bronze (3)
- Closed (2)
This paper describes the Sweaty II humanoid adult size robot trying to qualify for the RoboCup 2018 adult size humanoid competition. Sweaty came 2nd in RoboCup 2017 adult size league. The main characteristics of Sweaty are described in the Team Description Paper 2017. The improvements that have been made or are planned to be implemented for RoboCup 2018 are described in this paper.
A Nonlinear FEM Model to Calculate Third-Order Harmonic and Intermodulation in TC-SAW Devices
(2018)
Nonlinearities in Temperature Compensated SAW (TC-SAW) devices in the 2 GHz range are investigated using a nonlinear finite element model by simultaneously considering both third-order intermodulation distortion (IMD3)and third harmonic (H3). In the employed perturbation approach, different contributions to the total H3, the direct and indirect contribution, are discussed. H3 and IMD3 measurements were fitted simultaneously using scaling factors for SiO 2 film and Cu electrode nonlinear material tensors in TC-SAW devices. We employ a P-Matrix simulation as intermediate step: Firstly, measurement and nonlinear P-Matrix calculations for finite devices are compared and coefficients of the P-Matrix simulation are determined. The nonlinear tensor data of the different materials involved in periodic nonlinear finite element method (FEM) computations are optimized to fit periodic P-Matrix calculations by introducing scaling factors. Thus, the contribution of different materials to the nonlinear behavior of TC-SAW devices is obtained and the role of materials is discussed.
In a Semi-autonomic cloud auditing architecture we weaved in privacy enhancing mechanisms [15] by applying the public key version of the Somewhat homomorphic encryption (SHE) scheme from [4]. It turns out that the performance of the SHE can be significantly improved by carefully deriving relevant crypto parameters from the concrete cloud auditing use cases for which the scheme serves as a privacy enhancing approach. We provide a generic algorithm for finding good SHE parameters with respect to a given use case scenario by analyzing and taking into consideration security, correctness and performance of the scheme. Also, to show the relevance of our proposed algorithms we apply it to two predominant cloud auditing use cases.
Covert- and side-channels as well as techniques to establish them in cloud computing are in focus of research for quite some time. However, not many concrete mitigation methods have been developed and even less have been adapted and concretely implemented by cloud providers. Thus, we recently conceptually proposed C 3 -Sched a CPU scheduling based approach to mitigate L2 cache covert-channels. Instead of flushing the cache on every context switch, we schedule trusted virtual machines to create noise which prevents potential covert-channels. Additionally, our approach aims on preserving performance by utilizing existing instead of artificial workload while reducing covert-channel related cache flushes to cases where not enough noise has been achieved. In this work we evaluate cache covert-channel mitigation and performance impact of our integration of C 3 -Sched in the XEN credit scheduler. Moreover, we compare it to naive solutions and more competitive approaches.
A simple measuring method for acquiring the radiation pattern of an ultrawide band Vivaldi antenna is presented. The measuring is performed by combining two identical Vivaldi antennas and some of the intrinsic properties of a stepped-frequency continue wave radar (SFCW radar) in the
range from 1.0 GHz to 6.0 GHz. A stepper-motor provided the azimuthal rotation for one of the antennas from 0 ◦ to 360 ◦. The tests have been performed within the conventional environment (laboratory / office) without using an anechoic chamber or absorbing materials. Special measuring devices have not been used either. This method has been tested with different pairs of Vivaldi antennas and it can be also used for different ones (with little or no change in the system), as long as their operational
bandwidth is within the frequency range of the SFCW radar.
Keywords — SFCW Radar, Antenna Gain Characterization,
Azimuthal Radiation Pattern
Existing ultrasonic stress evaluation methods utilize the acoustoelastic effect for bulk waves propagating in volume, which is unsuitable for a surface treated material, possessing a significant variation in material properties with depth. With knowledge of nonlinear elastic parameters – third-order elastic constants (TOEC) close to the surface of the sample, the acoustoelastic effect might be used with surface acoustic waves. This work is focused on the development of an independent method of TOEC measurement using the effect of nonlinear surface acoustic waves scattering – i.e. the effect of elastic waves interaction in a nonlinear medium.
In this paper, the possible three wave interactions of surface guided waves and bulk waves are described and formulae for the efficiency of harmonic generation and mode mixing are derived. A comparison of the efficiency of surface waves scattering in an isotropic medium for different interaction types is carried out with the help of nonlinear perturbation theory. First results for surface and bulk wave mixing with known second- and third-order elastic constants are shown.
In this paper, we establish a simple model for the exchange of messages in a vehicular network and we consider fundamental limits on the achievable data rate. For a vehicular network, the exchange of data with other nearby vehicles is particularly important for traffic safety, e.g. for collision avoidance, but also for cooperative applications like platooning. These use cases are currently addressed by standards building on IEEE 802.11p, namely ITS-G5 and DSRC (dedicated short range communication), which encounter saturation problems at high vehicle densities. For this reason, we take a step back and ask for the fundamental limits for the common data rate in a vehicular network. After defining a simple single-lane model and the corresponding capacity limits for some basic multiple- access schemes, we present results for a more realistic setting. For both scenarios, non-orthogonal multiple-access (NOMA) yields the best results.
This paper evaluates the implementation of Medium Access Control (MAC) protocols suitable for massive access connectivity in 5G multi-service networks. The access protocol extends multi-packet detection receivers based on Physical Layer Network Coding (PLNC) decoding and Coded Random Access protocols considering practical aspects to implement one-stage MAC protocols for short packet communications in mMTC services. Extensions to enhance data delivery phase in two- stage protocols are also proposed. The assessment of the access protocols is extended under system level simulations where a suitable link to system interface characterization has been taken into account.
This paper is discussing the development of a wireless Indoor Smart Gardening System with the focus on energy autonomous working. The Smart Gardening System, which is presented in this paper consists of a network of energy autonomous wireless sensor nodes which are used for monitoring important plant parameters like air temperature, soil moisture, pressure or humidity and in future to control an actuator for the plant irrigation and to measure further parameter as light and fertilizer level. Solar energy harvesting is used for powering the wireless nodes without the usage of a battery. Comparable Smart Gardening Systems are usually battery-powered. Furthermore, the overall Smart Gardening System consists of a battery powered gateway based on a Raspberry Pi 3 system, which controls the wireless nodes and collects their sensor data. The gateway is able to send the information to an internet server application and via Wi-Fi to mobile devices. Particularly the architecture of the energy autonomous wireless nodes will be considered because fully energy autonomous wireless networks could not be implemented without special concepts for the energy supply and architecture of the wireless nodes.
The economic dispatch (ED) problem is a large-scale optimization problem in electricity power grids. Its goal is to find a power output combination of all generator nodes that meet the demand of the customers at minimum operating cost. In recent years, distributed protocols have been proposed to replace the traditional centralized ED calculation for modern smart grid infrastructures with the most realistic being the one proposed by Binetti et al. (2014). However, we show that this protocol leaks private information of the generator nodes. We then propose a privacy-preserving distributed protocol that solves the ED problem. We analyze the security of our protocol and give experimental results from a prototype implementation to show the feasibility of the solution.
The CAN bus still is an important fieldbus in various domains, e.g. for in-car communication or automation applications. To counter security threats and concerns in such scenarios we design, implement, and evaluate the use of an end-to-end security concept based on the Transport Layer Security protocol. It is used to establish authenticated, integrity-checked, and confidential communication channels between field devices connected via CAN. Our performance measurements show that it is possible to use TLS at least for non time-critical applications, as well as for generic embedded networks.
The increase in households with grid connected Photovoltaic (PV) battery system poses challenge for the grid due to high PV feed-in as a result of mismatch in energy production and load demand. The purpose of this paper is to show how a Model Predictive Control (MPC) strategy could be applied to an existing grid connected household with PV battery system such that the use of battery is maximized and at the same time peaks in PV energy and load demand are reduced. The benefits of this strategy are to allow increase in PV hosting capacity and load hosting capacity of the grid without the need for external signals from the grid operator. The paper includes the optimal control problem formulation to achieve the peak shaving goals along with the experiment set up and preliminary experiment results. The goals of the experiment were to verify the hardware and software interface to implement the MPC and as well to verify the ability of the MPC to deal with the weather forecast deviation. A prediction correction has also been introduced for a short time horizon of one hour within this MPC strategy to estimate the PV output power behavior.
Uncontrollable manufacturing variations in electrical hardware circuits can be exploited as Physical Unclonable Functions (PUFs). Herein, we present a Printed Electronics (PE)-based PUF system architecture. Our proposed Differential Circuit PUF (DiffC-PUF) is a hybrid system, combining silicon-based and PE-based electronic circuits. The novel approach of the DiffC-PUF architecture is to provide a specially designed real hardware system architecture, that enables the automatic readout of interchangeable printed DiffC-PUF core circuits. The silicon-based addressing and evaluation circuit supplies and controls the printed PUF core and ensures seamless integration into silicon-based smart systems. Major objectives of our work are interconnected applications for the Internet of Things (IoT).
Vehicle-to-Everything (V2X) communication promises improvements in road safety and efficiency by enabling low-latency and reliable communication services for vehicles. Besides using Mobile Broadband (MBB), there is a need to develop Ultra Reliable Low Latency Communications (URLLC) applications with cellular networks especially when safety-related driving applications are concerned. Future cellular networks are expected to support novel latencysensitive use cases. Many applications of V2X communication, like collaborative autonomous driving requires very low latency and high reliability in order to support real-time communication between vehicles and other network elements. In this paper, we classify V2X use-cases and their requirements in order to identify cellular network technologies able to support them. The bottleneck problem of the medium access in 4G Long Term Evolution(LTE) networks is random access procedure. It is evaluated through simulations to further detail the future limitations and requirements. Limitations and improvement possibilities for next generation of cellular networks are finally detailed. Moreover, the results presented in this paper provide the limits of different parameter sets with regard to the requirements of V2X-based applications. In doing this, a starting point to migrate to Narrowband IoT (NB-IoT) or 5G - solutions is given.
The next generation cellular networks are expected to improve reliability, energy efficiency, data rate, capacity and latency. Originally, Machine Type Communication (MTC) was designed for low-bandwidth high-latency applications such as, environmental sensing, smart dustbin, etc., but there is additional demand around applications with low latency requirements, like industrial automation, driver-less cars, and so on. Improvements are required in 4G Long Term Evolution (LTE) networks towards the development of next generation cellular networks for providing very low latency and high reliability. To this end, we present an in-depth analysis of parameters that contribute to the latency in 4G networks along with a description of latency reduction techniques. We implement and validate these latency reduction techniques in the open-source network simulator (NS3) for narrowband user equipment category Cat-Ml (LTE-M) to analyze the improvements. The results presented are a step towards enabling narrowband Ultra Reliable Low Latency Communication (URLLC) networks.
The excessive control signaling in Long Term Evolution networks required for dynamic scheduling impedes the deployment of ultra-reliable low latency applications. Semi-persistent scheduling was originally designed for constant bit-rate voice applications, however, very low control overhead makes it a potential latency reduction technique in Long Term Evolution. In this paper, we investigate resource scheduling in narrowband fourth generation Long Term Evolution networks through Network Simulator (NS3) simulations. The current release of NS3 does not include a semi-persistent scheduler for Long Term Evolution module. Therefore, we developed the semi-persistent scheduling feature in NS3 to evaluate and compare the performance in terms of uplink latency. We evaluate dynamic scheduling and semi-persistent scheduling in order to analyze the impact of resource scheduling methods on up-link latency.
The Datagram Transport Layer Security (DTLS) protocol has been designed to provide end-to-end security over unreliable communication links. Where its connection establishment is concerned, DTLS copes with potential loss of protocol messages by implementing its own loss detection and retransmission scheme. However, the default scheme turns out to be suboptimal for links with high transmission error rates and low data rates, such as wireless links in electromagnetically harsh industrial environments. Therefore, in this paper, as a first step we provide an analysis of the standard DTLS handshake's performance under such adverse transmission conditions. Our studies are based on simulations that model message loss as the result of bit transmission errors. We consider several handshake variants, including endpoint authentication via pre-shared keys or certificates. As a second step, we propose and evaluate modifications to the way message loss is dealt with during the handshake, making DTLS deployable in situations which are prohibitive for default DTLS.
The Transport Layer Security (TLS) protocol is a cornerstone of secure network communication, not only for online banking, e-commerce, and social media, but also for industrial communication and cyber-physical systems. Unfortunately, implementing TLS correctly is very challenging, as becomes evident by considering the high frequency of bugfixes filed for many TLS implementations. Given the high significance of TLS, advancing the quality of implementations is a sustained pursuit. We strive to support these efforts by presenting a novel, response-distribution guided fuzzing algorithm for differential testing of black-box TLS implementations. Our algorithm generates highly diverse and mostly-valid TLS stimulation messages, which evoke more behavioral discrepancies in TLS server implementations than other algorithms. We evaluate our algorithm using 37 different TLS implementations and discuss―by means of a case study―how the resulting data allows to assess and improve not only implementations of TLS but also to identify underspecified corner cases. We introduce suspiciousness as a per-implementation metric of anomalous implementation behavior and find that more recent or bug-fixed implementations tend to have a lower suspiciousness score. Our contribution is complementary to existing tools and approaches in the area, and can help reveal implementation flaws and avoid regression. While being presented for TLS, we expect our algorithm's guidance scheme to be applicable and useful also in other contexts. Source code and data is made available for fellow researchers in order to stimulate discussions and invite others to benefit from and advance our work.
Cell lifetime diagnostics and system be-havior of stationary LFP/graphite lithium-ion batteries
(2018)
The paper describes the methodology and experimental results for revealing similarities in thermal dependencies of biases of accelerometers and gyroscopes from 250 inertial MEMS chips (MPU-9250). Temperature profiles were measured on an experimental setup with a Peltier element for temperature control. Classification of temperature curves was carried out with machine learning approach.
A perfect sensor should not have thermal dependency at all. Thus, only sensors inside the clusters with smaller dependency (smaller total temperature slopes) might be pre-selected for production of high accuracy inertial navigation modules. It was found that no unified thermal profile (“family” curve) exists for all sensors in a production batch. However, obviously, sensors might be grouped according to their parameters. Therefore, the temperature compensation profiles might be regressed for each group. 12 slope coefficients on 5 degrees temperature intervals from 0°C to +60°C were used as the features for the k-means++ clustering algorithm.
The minimum number of clusters for all sensors to be well separated from each other by bias thermal profiles in our case is 6. It was found by applying the elbow method. For each cluster a regression curve can be obtained.
Recently, the demand for scalable, efficient and accurate Indoor Positioning Systems (IPS) has seen a rising trend due to their utility in providing Location Based Services (LBS). Visible Light Communication (VLC) based IPS designs, VLC-IPS, leverage Light Emitting Diodes (LEDs) in indoor environments for localization. Among VLC-based designs, Time Difference of Arrival (TDOA) based techniques are shown to provide very low errors in the relative position of receivers. Our considered system consists of five LEDs that act as transmitters and a single receiver (photodiode or image sensor in smart phone) whose position coordinates in an indoor environment are to be determined. As a performance criterion, Cramer Rao Lower Bound (CRLB) is derived for range estimations and the impact of various factors, such as, LED transmission frequency, position of reference LED light, and the number of LED lights, on localization accuracy has been studied. Simulation results show that depending on the optimal values of these factors, location estimation on the order of few centimeters can be realistically achieved.
Modelling detailed chemistry in lithium-ion batteries: Insight into performance, ageing and safety
(2018)
Real-Time Ethernet has become the major communication technology for modern automation and industrial control systems. On the one hand, this trend increases the need for an automation-friendly security solution, as such networks can no longer be considered sufficiently isolated. On the other hand, it shows that, despite diverging requirements, the domain of Operational Technology (OT) can derive advantage from high-volume technology of the Information Technology (IT) domain. Based on these two sides of the same coin, we study the challenges and prospects of approaches to communication security in real-time Ethernet automation systems. In order to capitalize the expertise aggregated in decades of research and development, we put a special focus on the reuse of well-established security technology from the IT domain. We argue that enhancing such technology to become automation-friendly is likely to result in more robust and secure designs than greenfield designs. Because of its widespread deployment and the (to this date) nonexistence of a consistent security architecture, we use PROFINET as a showcase of our considerations. Security requirements for this technology are defined and different well-known solutions are examined according their suitability for PROFINET. Based on these findings, we elaborate the necessary adaptions for the deployment on PROFINET.
Colored glass products with various printing technologies are becoming more important in industry. The aim is to achieve individual solution in a very short delivery time. Conventional thermal treatment of burning glasses in oven for tempered color printing has predominant issues with high time consumption, energy consumption and manufacturing cost. It requires alternative process development.
This paper proposes laser process to overcome issues in conventional treatment with the latest results of tempering colored glass. Samples have been analyzed with the scanning electron microscope (SEM). Two different laser systems have been applied and the glass has been printed with black paste.
Economic growth and ecological problems have pushed industries to switch to eco-friendly technologies. However, environmental impact is still often neglected since production efficiency remains the main concern. Patent analysis in the field of process engineering shows that, on the one hand, some eco-issues appear as secondary problems of the new technologies, and on the other hand, eco-friendly solutions often show lower efficiency or performance capability. The study categorizes typical environmental problems and eco-contradictions in the field of process engineering involving solids handling and identifies underlying inventive principles that have a higher value for environmental innovation. Finally, 42 eco-innovation methods adapting TRIZ are chronologically presented and discussed.
Accelerated transformation of the society and industry through digi-talization, artificial intelligence and other emerging technologies has intensified the need for university graduates that are capable of rapidly finding breakthrough solutions to complex problems, and can successfully implement innovation con-cepts. However, there are only few universities making significant efforts to com-prehensively incorporate creative and systematic tools of TRIZ (theory of in-ventive problem solving) and KBI (knowledge-based innovation) into their de-gree structure. Engineering curricula offer little room for enhancing creativity and inventiveness by means of discipline‐specific subjects. Moreover, many ed-ucators mistakenly believe that students are either inherently creative, or will in-evitably obtain adequate problem-solving skills as a result of their university study. This paper discusses challenges of intelligent integration of TRIZ and KBI into university curricula. It advocates the need for development of standard guidelines and best-practice recommendations in order to facilitate sustainable education of ambitious, talented, and inventive specialists. Reflections of educa-tors that teach TRIZ and KBI to students from mechanical, electrical, process engineering, and business administration are presented.
The comprehensive assessment method includes 80 innovation performance parameters and 10 key indicators of innovation capability, such as innovation process performance, innovating system performance, market and customer orientation, technology orientation, creativity, leadership, communication and knowledge management, risk and cost management, innovative climate, and innovation competences. The cross-industry study identifies parameters critical for innovation success and reveals different innovation performance patterns in companies.
CONTEXT
The paper addresses the needs of medium and small businesses regarding qualification of R&D specialists in the interdisciplinary cross-industry innovation, which promises a considerable reduction of investments and R&D expenditures. The cross-industry innovation is commonly understood as identification of analogies and transfer of technologies, processes, technical solutions, working principles or business models between industrial sectors. However, engineering graduates and specialists frequently lack the advanced skills and knowledge required to run interdisciplinary innovation across the industry boundaries.
PURPOSE
The study compares the efficiency of the cross-industry innovation methods in one semester project-oriented course. It identifies the individual challenges and preferred working techniques of the students with different prior knowledge, sets of experiences, and cultural contexts, which require attention by engineering educators.
APPROACH
Two parallel one-semester courses were offered to the mechanical and process engineering students enrolled in bachelor’s and master’s degree programs at the faculty of mechanical and process engineering. The students from different years of study were working in 12 teams of 3…6 persons each on different innovation projects, spending two hours a week in the classroom and additionally on average two hours weekly on their project research. Students' feedback and self-assessments concerning gained skills, efficiency of learned tools and intermediate findings were documented, analysed, and discussed regularly along the course.
RESULTS
Analysis of numerous student projects allows to compare and to select the tools most appropriate for finding cross-industry solutions, such as thinking in analogies, web monitoring, function-oriented search, databases of technological effects and processes, special creativity techniques and others. The utilization of learned skills in practical innovation work strengthens the motivation of students and enhances their entrepreneurial competences. Suggested learning course and given recommendations help facilitate sustainable education of ambitious specialists.
CONCLUSIONS
The structured cross-industry innovation can be successfully run as a systematic process and learned in one semester course. The choice of the preferred working teqniques made by the students is affected by their prior knowledge in science, practical experience, and cultural contexts. Major outcomes of the students’ innovation projects such as feasibility, novelty and customer value of the concepts are primarily influenced by students’ engineering design skills, prior knowledge of the technologies, and industrial or business experience.
With the need for automatic control based supervisory controllers for complex energy systems, comes the need for reduced order system models representing not only the non-linear behaviour of the components but also certain unknown process dynamics like their internal control logic. At the Institute of Energy Systems Technology in Offenburg we have built a real-life microscale trigeneration plant and present in this paper a rational modelling procedure that satisfies the necessary characteristics for models to be applied in model predictive control for grid-reactive optimal scheduling of this complex energy system. These models are validated against experimental data and the efficacy of the methodology is discussed. Their application in the future for the optimal scheduling problem is also briefly motivated.
Solar irradiance prediction is vital for the power management and the cost reduction when integrating solar energy. The study is towards a ground image based solar irradiance prediction which is highly dependent on the cloud coverage. The sky images are collected by using ground based sky imager (fisheye lens). In this work, different algorithms for cloud detection being a preparation step for their segmentation are compared.
The fisheye camera has been widely studied in the field of ground based sky imagery and robot vision since it can capture a wide view of the scene at one time. However, serious image distortion is a major drawback hindering its wider use. To remedy this, this paperproposes a lens calibration and distortion correction method for detecting clouds and forecasting solar radiation. Finally, the radial distortion of the fisheye image can be corrected by incorporating the estimated calibration parameters. Experimental results validate the effectiveness of the proposed method.
This paper deals with the detection and segmentation of clouds on high-dynamic-range (HDR) images of the sky as well as the calculation of the position of the sun at any time of the year. In order to predict the movement of clouds and the radiation of the sun for a short period of time, the clouds thickness and position have to be known as precisely as possible. Consequently, the segmentation algorithm has to provide satisfactory results regardless of different weather, illumination and climatic conditions. The principle of the segmentation is based on the classification of each pixel as a cloud or as a sky. This classification is usually based on threshold methods, since these are relatively fast to implement and show a low computational burden. In order to predict if and when the sun will be covered by clouds, the position of the sun on the images has to be determined. For this purpose, the zenith and azimuth angles of the sun are determined and converted into XY coordinates.
Besides of conventional CAD systems, new, cloudbased CAD systems have also been available for some years. These CAD systems designed according to the principle of software as a service (SaaS) differ in some important features from the conventional CAD systems. Thus, these CAD systems are operated via a browser and it is not necessary to install the software on a computer. The CAD-data is stored in the cloud and not on a local computer or central server. This new approach should also facilitate the sharing and management of data. Finally, many of these new CAD systems are available as freeware for education purposes, so the universities can save license costs. The chances and risks of cloud-based systems will first be analyzed in this paper. Then two leading cloud-based CAD systems will be researched. During the process, the technical performance range these new systems offer for the product development will be initially checked and reviewed. For this purpose, various criteria are worked out and the CAD software is evaluated using these criteria. In addition, the criteria are weighted by their importance for design education. This allows one to conclude which capabilities the different CAD system offers for use in education.
Printed Electronics (PE) is a promising technology that provides mechanical flexibility and low-cost fabrication. These features make PE the key enabler for emerging applications, such as smart sensors, wearables, and Internet of Things (IoTs). Since these applications need secure communication and/or authentication, it is vital to utilize security primitives for cryptographic key and identification. Physical Unclonable Functions (PUF) have been adopted widely to provide the secure keys. In this work, we present a weak PUF based on Electrolyte-gated FETs using inorganic inkjet printed electronics. A comprehensive analysis framework including Monte Carlo simulations based on real device measurements is developed to evaluate the proposed PE-PUF. Moreover, a multi-bit PE-PUF design is proposed to optimize area usage. The analysis results show that the PE-PUF has ideal uniqueness, good reliability, and can operates at low voltage which is critical for low-power PE applications. In addition, the proposed multi-bit PE-PUF reduces the area usage around 30%.
Printed electronics offers certain technological advantages over its silicon based counterparts, such as mechanical flexibility, low process temperatures, maskless and additive manufacturing process, leading to extremely low cost manufacturing. However, to be exploited in applications such as smart sensors, Internet of Things and wearables, it is essential that the printed devices operate at low supply voltages. Electrolyte gated field effect transistors (EGFETs) using solution-processed inorganic materials which are fully printed using inkjet printers at low temperatures are very promising candidates to provide such solutions. In this paper, we discuss the technology, process, modeling, fabrication, and design aspect of circuits based on EGFETs. We show how the measurements performed in the lab can accurately be modeled in order to be integrated in the design automation tool flow in the form of a Process Design Kit (PDK). We also review some of the remaining challenges in this technology and discuss our future directions to address them.
Human-robot collaboration plays a strong role in industrial production processes. The ISO/TS 15066 defines four different methods of collaboration between humans and robots. So far, there was no robotic system available that incorporates all four collaboration methods at once. Especially for the speed and separation monitoring, there was no sensor system available that can easily be attached directly to an off-the-shelf industrial robot arm and that is capable of detecting obstacles in distances from a few millimeters up to five meters. This paper presented first results of using a 3D time-of-flight camera directly on an industrial robot arm for obstacle detection in human-robot collaboration. We attached a Visionary-T camera from SICK to the flange of a KUKA LBR iiwa 7 R800. With Matlab, we evaluated the pictures and found that it works very well for detecting obstacles in a distance range starting from 0.5 m and up to 5 m.
In public transportation, the motor pool often consists of various different vehicles bought over a duration of many years. Sometimes, they even differ within one batch bought at the same time. This poses a considerable challenge in the storage and allocation of spare parts, especially in the event of damage to a vehicle. Correctly assigning these parts before the vehicle reaches the workshop could significantly reduce both the downtime and, therefore, the actual costs for companies. In order to achieve this, the current software uses a simple probability calculation. To improve the performance, the data of specific companies was analysed, preprocessed and used with several modelling techniques to classify and, therefore, predict the spare parts to be used in the event of a faulty vehicle. We summarize our experience running through the steps of the Cross Industry Standard Process for Data Mining and compare the performance to the previously used probability. Gradient Boosting Trees turned out to be the best modeling technique for this special case.
This paper describes the use of the single-linkage hierarchical clustering method in outlier detection for manufactured metal work pieces. The main goal of the study is to group defects that occur 5 mm into a work piece from the edge, i.e., the border of the metal work piece. The goal is to remove defects outside the area of interest as outliers. According to the assumptions made for the performance criteria, the single-linkage method has achieved better results compared to other agglomeration methods.
Deafblindness is a condition that limits communication capabilities primarily to the haptic channel. In the EU-funded project SUITCEYES we design a system which allows haptic and thermal communication via soft interfaces and textiles. Based on user needs and informed by disability studies, we combine elements from smart textiles, sensors, semantic technologies, image processing, face and object recognition, machine learning, affective computing, and gamification. In this work, we present the underlying concepts and the overall design vision of the resulting assistive smart wearable.