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This report presents the implementation and evaluation of a computer vision problem on a Field Programmable Gate Array (FPGA). This work is based upon [5] where the feasibility of application specific image processing algorithms on a FPGA platform have been evaluated by experimental approaches. The results and conclusions of that previous work builds the starting point for the work, described in this report. The project results show considerable improvement of previous implementations in processing performance and precision. Different algorithms for detecting Binary Large OBjects (BLOBs) more precisely have been implemented. In addition, the set of input devices for acquiring image data has been extended by a Charge-Coupled Device (CCD) camera. The main goal of the designed system is to detect BLOBs in continuous video image material and compute their center points.
This work belongs to the MI6 project from the Computer Vision research group of the University of Applied Sciences Bonn-Rhein-Sieg1 . The intent is the invention of a passive tracking device for an immersive environment to improve user interaction and system usability. Therefore the detection of the users position and orientation in relation to the projection surface is required. For a reliable estimation a robust and fast computation of the BLOB's center-points is necessary. This project has covered the development of a BLOB detection system on an Altera DE2 Development and Education Board with a Cyclone II FPGA. It detects binary spatially extended objects in image material and computes their center points. Two different sources have been applied to provide image material for the processing. First, an analog composite video input, which can be attached to any compatible video device. Second, a five megapixel CCD camera, which is attached to the DE2 board. The results are transmitted on the serial interface of the DE2 board to a PC for validation of their ground truth and further processing. The evaluation compares precision and performance gain dependent on the applied computation methods and the input device, which is providing the image material.
This report presents the implementation and evaluation of a computer vision task on a Field Programmable Gate Array (FPGA). As an experimental approach for an application-specific image-processing problem it provides reliable results to measure gained performance and precision compared with similar solutions on General Purpose Processor (GPP) architectures.
The project addresses the problem of detecting Binary Large OBjects (BLOBs) in a continuous video stream. For this problem a number of different solutions exist. But most of these are realized on GPP platforms, where resolution and processing speed define the performance barrier. With the opportunity of parallelization and performance abilities like in hardware, the application of FPGAs become interesting. This work belongs to the MI6 project from the Computer Vision research group of the University of Applied Sciences Bonn-Rhein-Sieg. It address the detection of the users position and orientation in relation to the virtual environment in an Immersion Square.
The goal is to develop a light emitting device, that points from the user towards the point of interest on the projection screen. The projected light dots are used to represent the user in the virtual environment. By detecting the light dots with video cameras, the idea is to interface the position and orientation of the relative position of the user interface. Fort that the laser dots need to be arranged in a unique pattern, which requires at least five points.[29] For a reliable estimation a robust computation of the BLOB's center-points is necessary.
This project has covered the development of a BLOB detection system on a FPGA platform. It detects binary spatially extended objects in a continuous video stream and computes their center points. The results are displayed to the user and where validated for their ground truth. The evaluation compares precision and performance gain against similar approaches on GPP platforms.
Reversible logic synthesis is an emerging research topic with different application areas like low-power CMOS design, quantum- and optical computing. The key motivation behind reversible logic synthesis is the optimization of the heat dissipation problem current architectures show, by reducing it to theoretically zero [2].
This report describes the design, the implementation and the usage of a system for managing different systems for automated theorem proving and automatically generated proofs. In particular, we focus on a user-friendly web-based interface and a structure for collecting and cataloguing proofs in a uniform way. The second point hopefully helps to understand the structure of automatically generated proofs and builds a starting point for new insights for strategies for proof planning.
This report has been prepared by the SETAC Europe Scientific Task Group on Global And RegionaL Impact Categories (SETAC-Europe/STG-GARLIC) that is installed by the 2nd SETAC Europe working group on life cycle impact assessment (WIA-2). This document is background to a chapter written by the same authors under the title “Climate change, stratospheric ozone depletion, photo-oxidant formation, acidification and eutrophication” in Udo de Haes et al. (2002). The chapter summarises the work of the STG-GARLIC and aims to give a state-of-the-art review of the best available practice(s) regarding category indicators and lists of concomitant characterisation factors for climate change, stratospheric ozone depletion, photo-oxidant formation, acidification, and aquatic and terrestrial eutrophication. Backgrounds on each of the specific impact categories are given in another background report from Klöpffer and Potting (2001).
This background report provides details on a selection of general issues relevant in relation to LCA and characterisation of impact in LCA. The document starts with a short introduction of the LCA methodology and impact assessment in LCA for non LCA-experts. LCA experts, on the other hand, will usually not be familiar in-depth with scientific and political backgrounds of the specific impact categories. A review of this is given. Also the discussion is provided about the issue of the position of the category indicator in the causality chain, and into the related issue of spatial differentiation. These two issues appeared to be one of the core items for SETAC-Europe/STG-GARLIC.
This study presents the findings of a quantitative study on the use of Open Educational Resources (OER) and Open Educational Practices (OEP) in Higher Education and Adult Learning Institutions. The study is based on the results of an online survey targeted at four educational roles: educational policy makers; institutional policy makers/managers; educational professionals; and learners. The report encompasses five chapters and four annexes. Chapter I presents the survey and Chapter II discloses the main research questions and models. Chapter III characterises the universe of respondents. Chapter IV advances with a detailed survey analysis including an overview of key statistical data. Finally, Chapter V provides an exploratory in-depth analysis of some key issues: representations, attitudes and uses of OEP. The table of contents and the complete list of diagrams and tables can be found at the end of the report.
Education is widely seen as an important means of addressing both national and international problems, such as political or religious extremism, poverty, and hunger. If publicly available educational resources (OERs) shall help overcoming the educational gap, localization is one of the major issues we need to deal with. Educators as well as learners need to be supported to determine adaptation needs. This paper provides a list of possible in-fluence factors on educational scenarios which are defined as context metadata. In the given form, the list needs to be understood as an addendum for the paper entitled ‘Open Educational Resources: Education for the World?’ from Thomas richter and Maggie McPherson; It is being published in the volume 3, issue 2 of the Journal Distance Education in 2012.
This project investigated the viability of using the Microsoft Kinect in order to obtain reliable Red-Green-Blue-Depth (RGBD) information. This explored the usability of the Kinect in a variety of environments as well as its ability to detect different classes of materials and objects. This was facilitated through the implementation of Random Sample and Consensus (RANSAC) based algorithms and highly parallelized workflows in order to provide time sensitive results. We found that the Kinect provides detailed and reliable information in a time sensitive manner. Furthermore, the project results recommend usability and operational parameters for the use of the Kinect as a scientific research tool.
Machine Learning seems to offer the solution to the central problem in recommender systems: Learning to recommend interesting items from observations. However, one tends to run into similar problems each time one tries to apply out-of-the-box solutions from Machine Learning. This article relates the problem of recommendation by user modeling closely to the machine learning problem and explicates some inherent dilemmas. A few examples will illustrate specific approaches and discuss underlying assumptions on the domain or how learned hypotheses relate to requirements on the user model. The article concludes with a tentative 'checklist' that one might like to consider when thinking about to use Machine Learning in User Adaptive environments such as recommender systems.
The increasing ubiquity of Artificial Intelligence (AI) poses significant political consequences. The rapid proliferation of AI over the past decade has prompted legislators and regulators to attempt to contain AI’s technological consequences. For Germany, relevant design requirements have been expressed by the European Commission’s High-Level Expert Group on Artificial Intelligence (HLEG AI), and, at the national level, by the German government’s Data Ethics Commission (DEK) as well as the German Bundestag’s Commission of Inquiry on Artificial Intelligence (EKKI).
CASTLE is a co-design platform developed at GMD SET institute. It provides a number of design tools for configuring application specific design flows. This paper presents a walk through the CASTLE co-design environment, following the design flow of a video processing system. The design methodology and the tool usage for this real life example are described, as seen from a designers point of view. The design flow starts with a C/C++ program and gradually derives a register-transfer level description of a processor hardware, as well as the corresponding compiler for generating the processor opcode. The main results of each design step are presented and the usage of the CASTLE tools at each step is explained.
Designing consumption feedback to support sustainable behavior is an active research topic. In recent years, relevant work has suggested a variety of possible design strategies. Addressing the more recent developments in this field, this paper presents a structured literature review, providing an overview of current information design approaches and highlighting open research questions. We suggest a literature-based taxonomy of used strategies, data source and output media with a special focus on design. In particular, we analyze which visual forms are used in current research to reach the identified strategy goals. Our survey reveals that the trend is towards more complex and contextualized feedback and almost every design within sustainable HCI adopts common visualization forms. Furthermore, adopting more advanced visual forms and techniques from information visualization research is helpful when dealing with ever-increasing data sources at home. Yet so far, this combination has often been neglected in feedback design.
The problem of filtering relevant information from the huge amount of available data is tackled by using models of the user's interest in order to discriminate interesting information from un-interesting data. As a consequence, Machine Learning for User Modeling (ML4UM) has become a key technique in recent adaptive systems. This article presents the novel approach of conceptual user models which are easy to understand and which allow for the system to explain its actions to the user. We show that ILP can be applied for the task of inducing user models from even sparse feedback by mutual sample enlargement. Results are evaluated independently of domain knowledge within a clear machine learning problem definition. The whole concept presented is realized in a meta web search engine, OySTER.
Low Cost Displays
(2010)
In this paper, we provide a participatory design study of a mobile health platform for older adults that provides an integrative perspective on health data collected from different devices and apps. We illustrate the diversity and complexity of older adults’ perspectives in the context of health and technology use, the challenges which follow on for the design of mobile health platforms that support active and healthy ageing (AHA) and our approach to addressing these challenges through a participatory design (PD) process. Interviews were conducted with older adults aged 65+ in a two-month study with the goal of understanding perspectives on health and technologies for AHA support. We identified challenges and derived design ideas for a mobile health platform called “My-AHA”. For researchers in this field, the structured documentation of our procedures and results, as well as the implications derived provide valuable insights for the design of mobile health platforms for older adults.
Having multiple talkers on a bus system rises the bandwidth on this bus. To monitor the communication on a bus, tools that constantly read the bus are needed. This report shows an implementation of a monitoring system for the CAN bus utilizing the Altera DE2 development board. The Biomedical Institute of the University of New Brunswick is currently developing together with different partners a prosthetic limb device, the UNB hand. Communication in this device is done via two CAN buses, which operate at a bit-rate of 1 Mbit/s. The developed monitoring system has been completely designed in Verilog HDL. It monitors the CAN bus in real-time and allows monitoring of different modules as well as of the overall load. The calculated data is displayed on the built-in LCD and also transmitted via UART to a PC. A sample receiver programmed in C is also given. The evaluation of this system has been done by using the Microchip CAN Bus Analyzer Tool connected to the GPIO port of the development board that simulates CAN communication.
This report summarises and integrates two different tracks of research for the purpose of envisioning and preparing a joint research project proposal. Soft- and hardware systems have become increasingly complex and act "concurrently", both with respect to memory access (i.e. information flow) and computational resources (i.e. "services"). The software development metaphor of cloud-storage, cloud-computing and service-oriented design has been anticipated by artificial intelligence (AI) research at least 30 years ago (parallel and distributed computation already dates back to the 1950’s and 1970s). What is known as a "service" today is what in AI is known as the capability of an agent; and the problem of information flow and consistency has been a headstone of information processing ever since. Based on a real-world robotics application we demonstrate how an increasingly abstract description of collaborating or competing agents correspond to a set of concurrent processes.