作者:
Kashif VirkJan MadsenSystem-on-Chip Group
Computer Science & Engineering Section Department ofInformatics & Mathematical Modeling Technical University of Denmark Lyngby Denmark
Wireless sensor networks are networked embedded computersystems with stringent power, performance, cost and form-factor requirements along with numerous other constraints related to their pervasiveness and ubiquitous...
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Wireless sensor networks are networked embedded computersystems with stringent power, performance, cost and form-factor requirements along with numerous other constraints related to their pervasiveness and ubiquitousness. Therefore, only a systematic design methdology coupled with an efficient test approach can enable their conformance to design and deployment specifications. We discuss off-line, hierarchical, functional testing of complete wire- less sensor nodes containing configurable logic through a combination of FPGA-based board test and Software-Based Self-Test (SBST) techniques. The proposed functional test methodology has been applied to a COTS-based sensor node development platform and can be applied, in general, for testing all types of wireless sensor node designs.
This paper studies a Directional Antenna Multi-path Location Aided Routing (DA-MLAR) scheme with on demand transmission power support. The targeted application contexts include communications in space networks, where ...
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Recently, in service robotics area, increasing attention is being paid on interaction capability of robot for human-being as well as its task performing capability. In this paper, in particular, an automatic gesture g...
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Recently, in service robotics area, increasing attention is being paid on interaction capability of robot for human-being as well as its task performing capability. In this paper, in particular, an automatic gesture generation methodology for conversational interaction of service robots is presented toward more human-friendly human-robot interaction. From the survey on the results in the psychology field, we first categorized the target gestures into the three types of gestures, which are basic, supplementary/emphasizing, and finishing/interconnective gestures with their corresponding unit gesture components. Then, a set of mapping rules have been extracted for gesture generation based on observing human behavioral patterns during conversation, by means of morpheme decomposition and analysis. From the given text input in Korean, the proposed system tries to generate robotic gestures, which consist of the head and the arm motions, by gesture selection and motion scheduling schemes. Finally, we discuss on the effectiveness of the proposed system with the simulated motions of robot as an initial attempt to apply in a practical system.
This paper is concerned with the development of a novel color image thresholding technique using fuzzy thresholding and Dempster-Shaferpsilas theory based fusion. The color bands of a given image are fuzzified by mean...
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This paper is concerned with the development of a novel color image thresholding technique using fuzzy thresholding and Dempster-Shaferpsilas theory based fusion. The color bands of a given image are fuzzified by means of a fuzzy thresholding technique which uses an S-shape membership function and a linear index of fuzziness based fuzzy measure. The resulting fuzzy maps are used to determine the mass functions of the hypotheses representing the classes for each pixel. These hypotheses are then combined using the orthogonal sum rule of the Dempster-Shafer theory to compute the final threshold map. The results show that the proposed algorithm yields a superior performance to its counterpart methods which are based on crisp and fuzzy techniques.
This paper describes the development of a self-care support robot, developed to support elderly people with mobility problems. The Kitasap2 consists of a host computer and the physical body of a robot equipped with a ...
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This paper presents a distributed fermat-point range estimation strategy, which is important in the moving sensor localization applications. The fermat-point is defined as a point which minimizes the sum of distances ...
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This paper presents a distributed fermat-point range estimation strategy, which is important in the moving sensor localization applications. The fermat-point is defined as a point which minimizes the sum of distances from three sensors inside a triangle. This point is indeed at the triangle's center of gravity. We solve the problems of large errors and poor performance in the bounding box algorithm. We obtain two results by performance analysis for a deployed environment with 200 sensor nodes. First, when the number of sensor nodes is below 150, the mean error decreases rapidly as the node density increases, and when the number of sensor nodes exceeds 170, the mean error stays below 1%. Second, when the number of beacon nodes is below 60, the normal nodes do not have sufficient number of accurate beacon nodes to help them estimate their locations. However, when the number of beacon nodes exceeds 60, the mean error changes slightly. Simulation results indicated that the proposed algorithm for sensor position estimation is more accurate than existing algorithms and improves on existing bounding box strategies.
Sphere decoding enables maximum likelihood (ML) detection with fairly low complexity in the MIMO wireless systems, but it takes hundreds cycles at low SNR environment. This paper proposes a fast decoding algorithm to ...
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Sphere decoding enables maximum likelihood (ML) detection with fairly low complexity in the MIMO wireless systems, but it takes hundreds cycles at low SNR environment. This paper proposes a fast decoding algorithm to reduce the decoding cycles using look-ahead search. Since the proposed decoding algorithm utilizes hardware resources to add other sub-trees into the search space successively, it helps not to go down into the sub-tree that has a small value at the root node but has large values at the child nodes. Scaling and enumeration techniques are also presented, which are effective in implementing the proposed sphere decoder. As a result, the proposed decoder saves about 30% decoding cycles at the cost of small hardware overhead compared to the conventional decoder.
Case-based reasoning (CBR) uses the same technique in solving tasks that needs reference from variety of situations. It can render decision-making easier by retrieving past solutions from situations that are similar t...
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Case-based reasoning (CBR) uses the same technique in solving tasks that needs reference from variety of situations. It can render decision-making easier by retrieving past solutions from situations that are similar to the one at hand and make necessary adjustments in order to adopt them. In this paper, an ontology-based fuzzy CBR support system for ship's collision avoidance is presented to avoid the cumbersome tasks of creating a new solution each time, when a new situation is encountered. The first level of the ontology-based CBR identifies the dangerous ships and indexes the new case. The second level retrieves cases from the ontology and adapts the solution to solve for the output. The CBR's accuracy depends on the efficient retrieval of possible solutions, and the proposed algorithm improves the effectiveness of solving the similarity to a new case at hand.
In this paper we propose a methodology based on supervised automatic learning in order to classify the behaviour of generators in terms of their performance in providing primary frequency control ancillary services. T...
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In this paper we propose a methodology based on supervised automatic learning in order to classify the behaviour of generators in terms of their performance in providing primary frequency control ancillary services. The problem is posed as a time-series classification problem, and handled by using state-of- the-art supervised learning methods such as ensembles of decision trees and support-vector machines combined with several preprocessing techniques. The method was designed in the context of the Belgian system and is validated on real-life data composed of more than 600 time-series recorded on this system.
Sphere decoding enables maximum likelihood (ML) detection with lower complexity than other decoding algorithms, but it still suffers from large computational delay. This paper proposes a vertical partial Euclidean dis...
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Sphere decoding enables maximum likelihood (ML) detection with lower complexity than other decoding algorithms, but it still suffers from large computational delay. This paper proposes a vertical partial Euclidean distance (PED) computation method to reduce the critical path delay and computational resources. Since the proposed method computes ahead the PED of lower levels using upper level symbols, a high speed PED computation unit can be implemented with less hardware resources
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