Methoden und Beschreibungssprachen zur Modellierung und Verifikation vonSchaltungen und Systemen: MBMV 2015 - Tagungsband, Chemnitz, 03. - 04. März 2015

Der Workshop Methoden und Beschreibungssprachen zur Modellierung und Verifikation von Schaltungen und Systemen (MBMV 2015) findet nun schon zum 18. mal statt. Ausrichter sind in diesem Jahr die Professur Schaltkreis- und Systementwurf der Technischen Universität Chemnitz und das Steinbeis-Forschungszentrum Systementwurf und Test. Der Workshop hat es sich zum Ziel gesetzt, neueste Trends, Ergebnisse und aktuelle Probleme auf dem Gebiet der Methoden zur Modellierung und Verifikation sowie der Beschreibungssprachen digitaler, analoger und Mixed-Signal-Schaltungen zu diskutieren. Er soll somit ein Forum zum Ideenaustausch sein. Weiterhin bietet der Workshop eine Plattform für den Austausch zwischen Forschung und Industrie sowie zur Pflege bestehender und zur Knüpfung neuer Kontakte. Jungen Wissenschaftlern erlaubt er, ihre Ideen und Ansätze einem breiten Publikum aus Wissenschaft und Wirtschaft zu präsentieren und im Rahmen der Veranstaltung auch fundiert zu diskutieren. Sein langjähriges Bestehen hat ihn zu einer festen Größe in vielen Veranstaltungskalendern gemacht. Traditionell sind auch die Treffen der ITGFachgruppen an den Workshop angegliedert. In diesem Jahr nutzen zwei im Rahmen der InnoProfile-Transfer-Initiative durch das Bundesministerium für Bildung und Forschung geförderte Projekte den Workshop, um in zwei eigenen Tracks ihre Forschungsergebnisse einem breiten Publikum zu präsentieren. Vertreter der Projekte Generische Plattform für Systemzuverlässigkeit und Verifikation (GPZV) und GINKO - Generische Infrastruktur zur nahtlosen energetischen Kopplung von Elektrofahrzeugen stellen Teile ihrer gegenwärtigen Arbeiten vor. Dies bereichert denWorkshop durch zusätzliche Themenschwerpunkte und bietet eine wertvolle Ergänzung zu den Beiträgen der Autoren. [... aus dem Vorwort

Quality Determination of Hydraulic Pumps with Adaptive Fuzzy Pattern Classifiers to Reduce the Risk for Quality Management

Automated production of complex assemblies such as hydraulic pumps also requires reliable detection of defects utilizing functional tests. In principle, this is a classification task in good/bad, which, however, is often not to be made sharply but should provide gradations for detailed error analysis. From this, conclusions can be drawn, for example, about the type or location of the defects, wear, or aging of components in the production chain. A high-dimensional vector of data from static or dynamic measurements including is generally available as the basis for the fault detection model. Modeling such complex nonlinear systems under various load conditions with dynamic test procedures leads to uncertainties that should also be reflected in the diagnostic model. For this, the design of the classification model (the classifier) should be largely automatic during the training phase for time and cost reasons. In addition, online updating under actual operating conditions is also often desired. These challenging goals can be met through the artificial intelligence (AI) methodology of fuzzy pattern classification. This chapter deals with the development of a fuzzy classifier for the application case of the final inspection of hydraulic axial piston pumps. The focus is on the automatic training of the classifier employing a new adaptation procedure and permanently (until termination) evaluates the resp. current classifier using performance measures. Using real experimental data, the procedure and the step-by-step adaptation results for different links between the current classification model and the new data are presented and compared

State of the Art of Laser Hardening and Cladding

In this paper an overview is given about laser surface modification processes, which are developed especially with the aim of hardness improvement for an enhanced fatigue and wear behaviour. The processes can be divided into such with and without filler material and in solid-state and melting processes. Actual work on shock hardening, transformation hardening, remelting, alloying and cladding is reviewed, where the main focus was on scientific work from the 21st century

spinfortec2022 : Tagungsband zum 14. Symposium der Sektion Sportinformatik und Sporttechnologie der Deutschen Vereinigung für Sportwissenschaft (dvs), Chemnitz 29. - 30. September 2022

Dieser Tagungsband enthält die Beiträge aller Vorträge und Posterpräsentationen des 14. Symposiums der Sektion Sportinformatik und Sporttechnologie der Deutschen Vereinigung für Sportwissenschaft (dvs) an der Technischen Universität Chemnitz (29.-30. September 2022). Mit dem Ziel, das Forschungsfeld der Sportinformatik und Sporttechnologie voranzubringen, wurden knapp 20 vierseitige Beiträge eingereicht und in den Sessions Informations- und Feedbacksysteme im Sport, Digitale Bewegung: Datenerfassung, Analyse und Algorithmen sowie Sportgeräteentwicklung: Materialien, Konstruktion, Tests vorgestellt.This conference volume contains the contributions of all oral and poster presentations of the 14th Symposium of the Section Sport Informatics and Engineering of the German Association for Sport Science (dvs) at Chemnitz University of Technology (September 29-30, 2022). With the goal of advancing the research field of sports informatics and sports technology, nearly 20 four-page papers were submitted and presented in the sessions Information and Feedback Systems in Sport, Digital Movement: Data Acquisition, Analysis and Algorithms, and Sports Equipment Development: Materials, Construction, Testing

Quality Standards for Food Products - A Particular Burden for Small Producers in Developing Countries?

This paper develops an analytical framework which structures the problem of whether, how and to what extent small producers in developing countries are disadvantaged by the increasing prevalence of food quality standards. Based on a literature review, the empirical evidence is structured and research gaps are identified. The paper finds that small and medium producers rarely comply without support from downstream actors. In case of well-educated and relatively wealthy farmers, forward integration is also found. No empirical support exists for the intuitively appealing hypothesis of a lower cost of compliance per unit of output for large producers. Zusammenfassung In diesem Papier wird ein Analyserahmen entwickelt, um die Möglichkeit und das Ausmaß der Benachteiligung von Kleinlandwirten in Entwicklungsländern durch die zunehmende Verbreitung von Qualitätsstandards für Produkte der Agrar- und Ernährungsindustrie zu strukturieren. In einer Literaturübersicht werden die Ergebnisse empirischer Studien ausgewertet und Forschungslücken identifiziert. Es wird gezeigt, dass Kleinlandwirte aufwändige Prozessstandards selten ohne die Unterstützung von Unternehmen auf nachgelagerten Stufen der Wertschöpfungskette implementieren. Die einleuchtende und weit verbreitete Hypothese, dass die Cost of Compliance per Produkteinheit für große Produzenten niedriger als für kleine Produzenten seien, wurde bisher empirisch nicht bestätigt.Quality Standards, International Trade, EUREPGAP, Certification, Small Farmers, Developing Countries, Cost of Compliance, Agribusiness, International Relations/Trade,

Perception Through Image Processing Applications for Situation Awareness

This paper introduces a concept for the perception level of situation awareness through image processing applications. The perception of the information from the environment is lacking to achieve highly autonomous vehicles. This approach mainly focuses on collecting information from the environment using camera sensors. The frames from the camera are processed using multiple image processing algorithms, outputs converted into CAN message, and sent to the expert system. CE-Box custom hardware that consists of a Raspberry Pi 3b model counted with PiCAN 2 used to implement and evaluate this approach. The goal of this paper is to provide a conceptual method to make decisions based on the extracted information from the environment using image processing algorithms

Knowledge-based Model Building with KONWERK

Modeling a real world optimization problem in a form which can be processed by a machine (computer) is usually a very difficult and complex task. Therefore, building and verifying the model is often the most time consuming part of the whole process of solving a real world problem using methods of Operations Research. Software tools, which integrate representation methods developed in the field of Artificial Intelligence (AI) and methods of OR, can facilitate and speed up the process of model development. The paper introduces the idea of knowledge based modeling as a model development and representation technique facilitating the complex process of model building. We describe the KONWERK tool-box which combines hierarchical structured knowledge representation and object oriented methodology thus providing a framework for model building and application of different optimization methods. We want the reader to form an idea of the methodology of model development and knowledge representation with KONWERK and to understand the hierarchical structure of the knowledge base. The model of the Nitra River Case is used to describe and explain the modeling and knowledge representation with KONWERK. A given multicriteria model of the Nitra River Case was reimplemented using KONWERK within about three weeks and later enlarged by implementation of additional fairness criteria

Creating, Modeling, and Visualizing Metabolic Networks

Metabolic networks combine metabolism and regulation. These complex networks are difficult to understand and create due to the diverse types of information that need to be represented. This chapter describes a suite of interlinked tools for developing, displaying, and modeling metabolic networks. The metabolic network interactions database, MetNetDB, contains information on regulatory and metabolic interactions derived from a combination of web databases and input from biologists in their area of expertise. PathBinderA mines the biological “literaturome” by searching for new interactions or supporting evidence for existing interactions in metabolic networks. Sentences from abstracts are ranked in terms of the likelihood that an interaction is described and combined with evidence provided by other sentences. FCModeler, a publicly available software package, enables the biologist to visualize and model metabolic and regulatory network maps. FCModeler aids in the development and evaluation of hypotheses, and provides a modeling framework for assessing the large amounts of data captured by high-throughput gene expression experiments

Credit risk assessment in commercial banks based on fuzzy support vector machines

Credit risk assessment plays an important role in banks credit risk management. The objective of credit assessment is to decide credit ranks, which denote the capacity of enterprises to meet their financial commitments. Traditional "one-versusone" approach has been commonly used in the multi-classification method based on Support Vector Machine (SVM). Since SVM for pattern recognition is based on binary classification, there will be unclassifiable regions when extended to multi-classification problems. Focus on this problem, a new credit risk assessment model based on fuzzy SVM is introduced in this paper that can give a reasonable classification for unclassifiable examples. Experiment results show that the fuzzy SVM method provides a better performance in generalization ability and assessment accuracy than conventional one-versus-one multi-classification approach