TY - THES AB - Ultraschall-Drahtbonden ist eine Standardtechnologie im Bereich der Aufbau- und Verbindungstechnik von Leistungshalbleitermodulen. Um Prozessschritte und damit wertvolle Zeit zu sparen, sollen die Kupferdickdrähte für die Leistungshalbleiter auch für die Kontaktierung von eingespritzten Anschlusssteckern im Modulrahmen verwendet werden. Das Kontaktierungsverfahren mit diesen Drähten auf Steckern in dünnwandigen Kunststoffrahmen führt häufig zu unzureichender Bondqualität. In dieser Arbeit wird das Bonden von Anschlusssteckern experimentell und anhand von Simulationen untersucht, um die Prozessstabilität zu steigern. Zunächst wurden Experimente auf Untergründen mit hoher Steifigkeit durchgeführt, um Störgrößen von Untergrundeigenschaften zu verringern. Die gewonnenen Erkenntnisse erlaubten die Entwicklung eines Simulationsmodells für die Vorhersage der Bondqualität. Dieses basiert auf einer flächenaufgelösten Reibarbeitsbestimmung im Fügebereich unter Berücksichtigung des Ultraschallerweichungseffektes und der hierdurch entstehenden hohen Drahtverformung. Experimente an den Anschlusssteckern im Modulrahmen zeigten eine verringerte Relativverschiebung zwischen Draht und Stecker, was zu einer deutlichen Verringerung der Reibarbeit führt. Außerdem wurden verminderte Schwingamplituden des Bondwerkzeugs nachgewiesen. Dies führt zu einer weiteren Reduktion der Reibarbeit. Beide Effekte wurden mithilfe eines Mehrmassenschwingers modelliert. Die gewonnenen Erkenntnisse und die erstellten Simulationsmodelle ermöglichen die Entwicklung von Klemmvorrichtungen, welche die identifizierten Störgrößen gezielt kompensieren und so ein verlässliches Bonden der Anschlussstecker im gleichen Prozessschritt ermöglichen, in dem auch die Leistungshalbleiter kontaktiert werden. AU - Althoff, Simon ID - 41971 KW - heavy copper bonding KW - wire bonding KW - quality prediction KW - friction model KW - point-contact-element SN - 978-3-8440-8903-5 TI - Predicting the Bond Quality of Heavy Copper Wire Bonds using a Friction Model Approach VL - 15 ER - TY - JOUR AB - We study how competition between physicians affects the provision of medical care. In our theoretical model, physicians are faced with a heterogeneous patient population, in which patients systematically vary with regard to both their responsiveness to the provided quality of care and their state of health. We test the behavioral predictions derived from this model in a controlled laboratory experiment. In line with the model, we observe that competition significantly improves patient benefits as long as patients are able to respond to the quality provided. For those patients, who are not able to choose a physician, competition even decreases the patient benefit compared to a situation without competition. This decrease is in contrast to our theoretical prediction implying no change in benefits for passive patients. Deviations from patient-optimal treatment are highest for passive patients in need of a low quantity of medical services. With repetition, both, the positive effects of competition for active patients as well as the negative effects of competition for passive patients become more pronounced. Our results imply that competition can not only improve but also worsen patient outcome and that patients’ responsiveness to quality is decisive. AU - Brosig-Koch, Jeannette AU - Hehenkamp, Burkhard AU - Kokot, Johanna ID - 44092 JF - Health Economics KW - physician competition KW - patient characteristics KW - heterogeneity in quality responses KW - fee-for-service KW - laboratory experiment TI - Who benefits from quality competition in health care? A theory and a laboratory experiment on the relevance of patient characteristics ER - TY - GEN AB - We consider a model where for-profit providers compete in quality in a price-regulated market that has been opened to competition, and where the incumbent is located at the center of the market, facing high costs of relocation. The model is relevant in markets such as public health care, education and schooling, or postal services. We find that, when the regulated price is low or intermediate, the entrant strategically locates towards the corner of the market to keep the incumbent at the low monopoly quality level. For a high price, the entrant locates at the corner of the market and both providers implement higher quality compared to a monopoly. In any case, the entrant implements higher quality than the incumbent provider. Social welfare is always higher in a duopoly if the cost of quality is low. For higher cost levels welfare is non-monotonic in the price and it can be optimal to the regulator not to use its entire budget. Therefore, the welfare effect of entry depends on the price and the size of the entry cost, and the regulator should condition the decision to allow entry on an assessment of the entry cost. AU - Hehenkamp, Burkhard AU - Kaarbøe, Oddvar M. ID - 44093 KW - Quality competition KW - Price regulation KW - Location choice KW - Product differentiation TI - Price Regulation, Quality Competition and Location Choice with Costly Relocation ER - TY - JOUR AB - Brainwaves have demonstrated to be unique enough across individuals to be useful as biometrics. They also provide promising advantages over traditional means of authentication, such as resistance to external observability, revocability, and intrinsic liveness detection. However, most of the research so far has been conducted with expensive, bulky, medical-grade helmets, which offer limited applicability for everyday usage. With the aim to bring brainwave authentication and its benefits closer to real world deployment, we investigate brain biometrics with consumer devices. We conduct a comprehensive measurement experiment and user study that compare five authentication tasks on a user sample up to 10 times larger than those from previous studies, introducing three novel techniques based on cognitive semantic processing. Furthermore, we apply our analysis on high-quality open brainwave data obtained with a medical-grade headset, to assess the differences. We investigate both the performance, security, and usability of the different options and use this evidence to elicit design and research recommendations. Our results show that it is possible to achieve Equal Error Rates as low as 7.2% (a reduction between 68–72% with respect to existing approaches) based on brain responses to images with current inexpensive technology. We show that the common practice of testing authentication systems only with known attacker data is unrealistic and may lead to overly optimistic evaluations. With regard to adoption, users call for simpler devices, faster authentication, and better privacy. AU - Arias-Cabarcos, Patricia AU - Fallahi, Matin AU - Habrich, Thilo AU - Schulze, Karen AU - Becker, Christian AU - Strufe, Thorsten ID - 48063 IS - 3 JF - ACM Transactions on Privacy and Security KW - Safety KW - Risk KW - Reliability and Quality KW - General Computer Science SN - 2471-2566 TI - Performance and Usability Evaluation of Brainwave Authentication Techniques with Consumer Devices VL - 26 ER - TY - JOUR AU - Winkel, Fabian AU - Deuse-Kleinsteuber, Johannes AU - Böcker, Joachim ID - 48058 JF - IEEE Transactions on Reliability KW - Electrical and Electronic Engineering KW - Safety KW - Risk KW - Reliability and Quality SN - 0018-9529 TI - Run-to-Failure Relay Dataset for Predictive Maintenance Research With Machine Learning ER - TY - CONF AB - Quality diversity (QD) is a branch of evolutionary computation that gained increasing interest in recent years. The Map-Elites QD approach defines a feature space, i.e., a partition of the search space, and stores the best solution for each cell of this space. We study a simple QD algorithm in the context of pseudo-Boolean optimisation on the "number of ones" feature space, where the ith cell stores the best solution amongst those with a number of ones in [(i - 1)k, ik - 1]. Here k is a granularity parameter 1 {$\leq$} k {$\leq$} n+1. We give a tight bound on the expected time until all cells are covered for arbitrary fitness functions and for all k and analyse the expected optimisation time of QD on OneMax and other problems whose structure aligns favourably with the feature space. On combinatorial problems we show that QD finds a (1 - 1/e)-approximation when maximising any monotone sub-modular function with a single uniform cardinality constraint efficiently. Defining the feature space as the number of connected components of a connected graph, we show that QD finds a minimum spanning tree in expected polynomial time. AU - Bossek, Jakob AU - Sudholt, Dirk ID - 48872 KW - quality diversity KW - runtime analysis SN - 9798400701191 T2 - Proceedings of the Genetic and Evolutionary Computation Conference TI - Runtime Analysis of Quality Diversity Algorithms ER - TY - CONF AB - Manufacturing companies face the challenge of reaching required quality standards. Using optical sensors and deep learning might help. However, training deep learning algorithms require large amounts of visual training data. Using domain randomization to generate synthetic image data can alleviate this bottleneck. This paper presents the application of synthetic image training data for optical quality inspections using visual sensor technology. The results show synthetically generated training data are appropriate for visual quality inspections. AU - Gräßler, Iris AU - Hieb, Michael ID - 52816 KW - synthetic training data KW - machine vision quality gates KW - deep learning KW - automated inspection and quality control KW - production control T2 - Lectures TI - Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing ER - TY - JOUR AB - Encrypting data before sending it to the cloud ensures data confidentiality but requires the cloud to compute on encrypted data. Trusted execution environments, such as Intel SGX enclaves, promise to provide a secure environment in which data can be decrypted and then processed. However, vulnerabilities in the executed program give attackers ample opportunities to execute arbitrary code inside the enclave. This code can modify the dataflow of the program and leak secrets via SGX side channels. Fully homomorphic encryption would be an alternative to compute on encrypted data without data leaks. However, due to its high computational complexity, its applicability to general-purpose computing remains limited. Researchers have made several proposals for transforming programs to perform encrypted computations on less powerful encryption schemes. Yet current approaches do not support programs making control-flow decisions based on encrypted data. We introduce the concept of dataflow authentication (DFAuth) to enable such programs. DFAuth prevents an adversary from arbitrarily deviating from the dataflow of a program. Our technique hence offers protections against the side-channel attacks described previously. We implemented two flavors of DFAuth, a Java bytecode-to-bytecode compiler, and an SGX enclave running a small and program-independent trusted code base. We applied DFAuth to a neural network performing machine learning on sensitive medical data and a smart charging scheduler for electric vehicles. Our transformation yields a neural network with encrypted weights, which can be evaluated on encrypted inputs in \( 12.55 \,\mathrm{m}\mathrm{s} \) . Our protected scheduler is capable of updating the encrypted charging plan in approximately 1.06 seconds. AU - Fischer, Andreas AU - Fuhry, Benny AU - Kußmaul, Jörn AU - Janneck, Jonas AU - Kerschbaum, Florian AU - Bodden, Eric ID - 31844 IS - 3 JF - ACM Transactions on Privacy and Security KW - Safety KW - Risk KW - Reliability and Quality KW - General Computer Science SN - 2471-2566 TI - Computation on Encrypted Data Using Dataflow Authentication VL - 25 ER - TY - CONF AB - Generating instances of different properties is key to algorithm selection methods that differentiate between the performance of different solvers for a given combinatorial optimization problem. A wide range of methods using evolutionary computation techniques has been introduced in recent years. With this paper, we contribute to this area of research by providing a new approach based on quality diversity (QD) that is able to explore the whole feature space. QD algorithms allow to create solutions of high quality within a given feature space by splitting it up into boxes and improving solution quality within each box. We use our QD approach for the generation of TSP instances to visualize and analyze the variety of instances differentiating various TSP solvers and compare it to instances generated by established approaches from the literature. AU - Bossek, Jakob AU - Neumann, Frank ID - 48861 KW - instance features KW - instance generation KW - quality diversity KW - TSP SN - 978-1-4503-9237-2 T2 - Proceedings of the Genetic and Evolutionary Computation Conference TI - Exploring the Feature Space of TSP Instances Using Quality Diversity ER - TY - CONF AB - Recently different evolutionary computation approaches have been developed that generate sets of high quality diverse solutions for a given optimisation problem. Many studies have considered diversity 1) as a mean to explore niches in behavioural space (quality diversity) or 2) to increase the structural differences of solutions (evolutionary diversity optimisation). In this study, we introduce a co-evolutionary algorithm to simultaneously explore the two spaces for the multi-component traveling thief problem. The results show the capability of the co-evolutionary algorithm to achieve significantly higher diversity compared to the baseline evolutionary diversity algorithms from the literature. AU - Nikfarjam, Adel AU - Neumann, Aneta AU - Bossek, Jakob AU - Neumann, Frank ED - Rudolph, Günter ED - Kononova, Anna V. ED - Aguirre, Hernán ED - Kerschke, Pascal ED - Ochoa, Gabriela ED - Tu\v sar, Tea ID - 48894 KW - Co-evolutionary algorithms KW - Evolutionary diversity optimisation KW - Quality diversity KW - Traveling thief problem SN - 978-3-031-14714-2 T2 - Parallel Problem Solving from Nature (PPSN XVII) TI - Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem ER -