An important problem in Wireless Sensor Networks (WSN) is the occurrence of failures that lead to the disconnection of parts of the network, compromising the final results achieved by the WSN operation. A way to overc...
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Errors in diagnosing the disease is a critical risk that must be faced by any person giving treatment to the hospital. Medical treatment can not always be done with perfect accuracy. Lung cancer is one of the most dea...
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Errors in diagnosing the disease is a critical risk that must be faced by any person giving treatment to the hospital. Medical treatment can not always be done with perfect accuracy. Lung cancer is one of the most deadly disease that prone to misdiagnose. In general, some practitioners tend to “read” cancer in x-ray rontgen image as tumor this could be fatal. To generate a diagnose, a general practitioner use three kind of examination i.e : patient History, Radio logic examination, phisical examination. In this paper, Gray color for image indexing and retrieval are investigated. The features are derived based on the statistical distribution of Harralick feature from image sample. By utilizing the proposed invariant features, the similarity measure between query and database images provides reliable retrieval results.
Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. However, the PSO algorithm suffers from premature convergence and high ...
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A well know problem in the Wireless Sensor Network (WSN) research area is the usage of appropriate strategies to setup the sensor nodes such that they may accomplish sensing missions. This problem refers to the select...
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Artificial Immune Systems (AISs) are composed of techniques inspired by immunology. The clonal selection principle ensures the organism adaptation to fight invading antigens by an immune response activated by the bind...
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Artificial Immune Systems (AISs) are composed of techniques inspired by immunology. The clonal selection principle ensures the organism adaptation to fight invading antigens by an immune response activated by the binding of antigens and antibodies. As an immune response can be elicited even when the binding between an antigen and an antibody is not perfect, an approximate binding might suffice, and a Fuzzy Logic mechanism might be the most appropriate mechanism to control such process. This paper presents a novel hybrid model based on concepts of Immune and Fuzzy Systems with applications to pattern recognition problems. The preliminary results obtained here suggest the proposed model is a promising pattern recognition tool.
The recent advance in SNP genotyping has made a significant contribution to reduction of the costs for large-scale genotyping. The development also has dramatically increased the size of the SNP genotype data. The inc...
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The recent advance in SNP genotyping has made a significant contribution to reduction of the costs for large-scale genotyping. The development also has dramatically increased the size of the SNP genotype data. The increase of the volume of the data, however, has posed a huge obstacle to the conventional analysis techniques that are typically vulnerable to the high-dimensionality problem. To address the issue, we propose a method that exploits two well-tested models: the document-term model and the transaction analysis model. The proposed method consists of two phases. In the first phase, we reduce the dimensions of the SNP genotype data by extracting significant SNPs through transformation of the data in lieu of the document-term model. In the second phase, we discover the association rules that signify the relations between the SNPs and the traits, through the application of the transactional analysis in the reduced-dimension genotype data. We validated the discovered rules through the literature survey. Experiments were also carried out using the HGDP panel data provided by the Foundation Jean Dausset-CEPH, which prove the validity of our new method for identifying appropriate dimensional reduction and associations of multiple SNPs and traits.
In this paper, we develop a performance modeling technique for analyzing the time varying network layer queueing behavior of multihop wireless networks with constant bit rate traffic. Our approach is a hybrid of fluid...
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In this paper, we develop a performance modeling technique for analyzing the time varying network layer queueing behavior of multihop wireless networks with constant bit rate traffic. Our approach is a hybrid of fluid flow queueing modeling and a time varying connectivity matrix. Network queues are modeled using fluid-flow based differential equation models which are solved using numerical methods, while node mobility is modeled using deterministic or stochastic modeling of adjacency matrix elements. Numerical and simulation experiments show that the new approach can provide reasonably accurate results with significant improvements in the computation time compared to standard simulation tools.
Industrial Control Systems (ICS), formerly isolated proprietary systems, are giving place to highly-connected systems, implemented using widespread operating systems and network protocols on public networks. Such stan...
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ISBN:
(纸本)9781424428328;9781424428335
Industrial Control Systems (ICS), formerly isolated proprietary systems, are giving place to highly-connected systems, implemented using widespread operating systems and network protocols on public networks. Such standardization trend opens the door to security threats previously restricted to the corporate and personal computing areas. This paper presents how the main concepts of security in conventional computing systems can be exploited in dependability aspects of ICS, and presents some considerations on how security aspects of a standard-based could be applied to a typical control board used in industrial applications involving measurement.
Local image features can provide the basis for robust and invariant recognition of objects and scenes. Therefore, compact and distinctive representations of local shape and appearance has become invaluable in modern c...
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ISBN:
(纸本)9781450300728
Local image features can provide the basis for robust and invariant recognition of objects and scenes. Therefore, compact and distinctive representations of local shape and appearance has become invaluable in modern computer vision. In this work, we study a local descriptor based on the Holder exponent, a measure of signal regularity. The proposal is to find an optimal number of dimensions for the descriptor using a genetic algorithm (GA). To guide the GA search, fitness is computed based on the performance of the descriptor when applied to standard region matching problems. This criterion is quantified using the F-Measure, derived from recall and precision analysis. Results show that it is possible to reduce the size of the canonical Holder descriptor without degrading the quality of its performance. In fact, the best descriptor found through the GA search is nearly 70% smaller and achieves similar performance on standard tests. Copyright 2010 ACM.
Meta-heuristics are efficient techniques for solving large scale optimization problems in which traditional mathematical techniques are impractical or provide sub-optimal solutions. The Shuffled Frog Leaping algorithm...
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