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31	Digitizing North Indian music: preservation and extension using multimodal sensor systems, machine learning and robotics Kapur, Ajay 24 August 2007 (has links) This dissertation describes how state of the art computer music technology can be used to digitize, analyze, preserve and extend North Indian classical music performance. Custom built controllers, influenced by the Human Computer Interaction (HCI) community, serve as new interfaces to gather musical gestures from a performing artist. Designs on how to modify a Tabla, Dholak, and Sitar with sensors and electronics are described. Experiments using wearable sensors to capture ancillary gestures of a human performer are also included. A twelve-armed solenoid-based robotic drummer was built to perform on a variety of traditional percussion instruments from around India. The dissertation also describes experimentation on interfacing a human sitar performer with the robotic drummer. Experiments include automatic tempo tracking and accompaniment methods. A framework is described for digitally transcribing performances of masters using custom designed hardware and software to aid in preservation. This work draws on knowledge from many disciplines including: music, computer science, electrical engineering, mechanical engineering and psychology. The goal is to set a paradigm on how to use technology to aid in the preservation of traditional art and culture. musical robotics indian music music technology artificial intelligence machine learning multimodal sensor systems
32	Real-time Scheduling for Data Stream Management Systems Lehner, Wolfgang, Schmidt, Sven, Legler, Thomas, Schaller, Daniel 02 June 2022 (has links) Quality-aware management of data streams is gaining more and more importance with the amount of data produced by streams growing continuously. The resources required for data stream processing depend on different factors and are limited by the environment of the data stream management system (DSMS). Thus, with a potentially unbounded amount of stream data and limited processing resources, some of the data stream processing tasks (originating from different users) may not be satisfyingly answered, and therefore, users should be enabled to negotiate a certain quality for the execution of their stream processing tasks. After the negotiation process, it is the responsibility of the Data Stream Management System to meet the quality constraints by using adequate resource reservation and scheduling techniques. Within this paper, we consider different aspects of real-time scheduling for operations within a DSMS. We propose a scheduling concept which enables us to meet certain time-dependent quality of service requirements for user-given processing tasks. Furthermore, we describe the implementation of our scheduling concept within a real-time capable data stream management system, and we give experimental results on that. info:eu-repo/classification/ddc/004 ddc:004
33	Development of Novel Wearable Sensor System Capable of Measuring and Distinguishing Between Compression and Shear Forces for Biomedical Applications Dimitrija Dusko Pecoski (8797031) 21 June 2022 (has links) <p>There are no commercially available wearable shoe in-sole sensors that are capable of measuring and distinguishing between shear and compression forces. Companies have already developed shoe sensors that simply measure pressure and make general inferences on the collected data with elaborate software [2, 3, 4, 5]. Researchers have also attempted making sensors that are capable of measuring shear forces, but they are not well suited for biomedical applications [61, 62, 63, 64]. This work focuses on the development of a novel wearable sensor system that is capable of identifying and measuring shear and compression forces through the use of capacitive sensing. Custom hardware and software tools such as materials test systems and capacitive measurement systems were developed during this work. Numerous sensor prototypes were developed, characterized, and optimized during the scope of this project. Upon analysis of the data, the best capacitive measurement system developed in this work utilized the CAV444 IC chip, whereas the use of the Arduino-derived measurement system required data filtering using median and Butterworth zero phase low pass filters. The highest dielectric constant reported from optimization experiments yielded 9.7034 (+/- 0.0801 STD) through the use of 60.2% by weight calcium copper titanate and ReoFlex-60 silicone. The experiments suggest certain sensors developed in this work feasibly measure and distinguish between shear and compressional forces. Applications for such technology focus on improving quality of life in areas such as managing diabetic ulcer formation, preventing injuries, optimizing performance for athletes and military personnel, and augmenting the scope of motion capture in biomechanical studies.</p> Biomechanical engineering Biomedical instrumentation Medical devices Circuits and systems Microelectronics Composite and hybrid materials Wearables Wearable Sensors Sensors Biomedical Engineering Mechanical Engineering Electrical Engineering Biomechanics Disease Management Diabetic Neuropathy Ulcer Prevention Athlete Injury Prevention Human Performance Optimization Motion Capture Analysis Optimization Sensor Development Capacitive Sensing Sensor Performance Characterization Dielectric Materials Composites Measurement Systems Instrumentation Mechanical Testing Materials Testing System Sensor Design Sensor Materials Sensor Manufacturing Sensor Data Analysis Custom Hardware and Software Development Sensor Systems Capacitive Sensor Modeling Biomechanical Engineering Biomedical Instrumentation Circuits and Systems Composite and Hybrid Materials Medical Devices Microelectronics and Integrated Circuits

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