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 -