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A general MOPSO algorithm was applied to ZDT1-4. Bias in the archive solutions was observed in the initialisation of the archive solutions. The bias continued until simulation end because a general MOPSO algorithm does not contain any explicit way to correct bias in its archive. Pareto dominance testing was discovered to be a main contributor to the bias. Bias was also introduced by the target's problem...
The selection of products for testing Software Product Lines (SPLs) is an optimization problem. The goal is to select a possible minimum set of products that satisfies testing criteria, such as, pairwise and mutation testing. Multi-objective Evolutionary Algorithms (MOEAs) have been successfully used to solve this problem and other ones related to software development. However, the use of MOEAs demands...
In the task of hyperspectral image classification, band selection is often adopted to select a subset of informative bands to reduce the computation and storage cost. We propose a supervised band selection method which allows calculation of a discriminative weight for each band. Specifically, we consider discriminative bands as those that contribute more positive scores to a one-class classifier than...
In this paper, a novel change detection method learned from Recurrent Neural Network with transferable ability is proposed. The proposed method, which is based on an improved Long Short Term Memory (LSTM) model, aims at: 1) learning a novel change detection rule to distinguish changed regions with high accuracy; 2) analyzing a new target data with transferable ability from learned change rule; 3)...
This paper describes two new algorithms for optimising the structure of trained Evolving Connectionist System (ECoS) artificial neural networks (ANN). It also presents the results of preliminary empirical evaluations of the algorithms. While ECoS are fast and efficient constructive ANN algorithms they can lose efficiency if they are allowed to grow too large. The algorithms presented in this paper...
The paper addresses the problem of reverse engineering a function block (FB) in situations when its source code is either not available or is too complex to understand. The proposed approach builds up on a recent method for reconstructing FBs based on testing and a search-based optimization algorithm. In our work the method is augmented with candidate solution verification using the NuSMV model checker...
Pattern recognition (PR) based myoelectric hand control has become a research focus in the field of rehabilitative engineer and intelligent control. However, the state of the art method is hardly adopted for clinical use because of signal interfered by shift, fatigue and user-unfriendly of retraining. The aim of this study is to evaluate the performance of different kinds of online algorithms in classifying...
This paper deals with ABC(Artificial Bee Colony) algorithm based on bio-virus mechanism and infection at first, which is defined as VEABC(Virus Evolution Artificial Bee Colony). The VEABC is proposed based on bio-virus evolution, infection in ABC(Artificial Bee Colony) searching in continuous state, which can improve variety of ABC and convergent speed. Classic ABC is depend on three kinds of bee...
This paper deals with sentiment analysis in text documents, especially text valence detection. The proposed solution is based on Support Vector Machines classifier. This classifier was trained with huge amount of data and complex word combinations were analysed. For this purpose distributed learning on 112 processors was used. Datasets used for training and testing were automatically obtained from...
AngularJS, the new Javascript framework, with wide usage across web browsers and great expression power, comes with a shortcoming — lack of compiler optimization. Consequently it is strongly recommended that every application written in JavaScript, regardless of the used framework, should include tests that validate both its behavior and performance. This paper presents and evaluates two popular web...
This research paper deals with Reconfigurable Hardware Systems (abbreviated, RHS) that should be adapted to their environment under well-defined conditions. A reconfiguration scenario is a run-time hardware operation allowing the addition/removal of hardware components. We classify the reconfiguration scenarios into three levels: Architectural, Structural and Data Reconfiguration Levels. We propose...
Signal classification plays an important role in spectrum sensing for cognitive radios to identify and avoid interference from other wireless devices. In this paper, we study a network of cognitive radios that jointly perform signal classification via cooperation. We propose a simple but effective linear cooperation scheme to fuse pre-processed measurements collected from spatially distributed cognitive...
The design of scalar quantization for distributed binary decision in presence of an eavesdropper (Eve) is investigated. An encoder/quantizer (Alice) observes a memoryless source and communicate via a public noiseless rate-limited channel with the detector (Bob) who has also access to a correlated analog source. Bob can take advantage of both informations to perform a binary decision on the joint probability...
Tasks running in MPSoCs experience contention delays when accessing MPSoC's shared resources, complicating task timing analysis and deriving execution time bounds. Understanding the Actual Contention Delay (ACD) each task suffers due to other corunning tasks, and the particular hardware shared resources in which contention occurs, is of prominent importance to increase confidence on derived execution...
The semiconductor industry finds itself at a crossroad with the question of how to continue to drive Moore's law. The industry is exploring many avenues to drive transistor scaling as well as reduction in cost for the future nodes. Some of the popular topics for patterning advancement include EUV, DSA, EBeam direct write, and Nano-Imprint. This paper will focus on the reduction in cost brought about...
In this paper, we propose an automated technique for optimal instrumentation of multi-threaded programs for debugging and testing of concurrent data structures. We define a notion of observability that enables debuggers to trace back and locate errors through data-flow instrumentation. Observability in a concurrent program enables a debugger to extract the value of a set of desired variables through...
Modern automobiles comprise a multitude of wireless transmission systems, e.g., for mobile and car-to-x communications. The characterisation and verification of these complex systems, which connect the acquisition of information with the operational status of cars and other traffic participants and their environment, raise new and stringent requirements on reliable techniques for electromagnetic measurements...
This paper we propose a methodology of classification and prediction of chaotic time series datasets by the beauty of particle swarm optimization (PSO) in multilayer feed forward backpropagation neural network (MFFBPNN) for finding initial weights and biases of the MLFFBPNN. Designed algorithm was used for different horizons in classification and prediction to chaotic datasets by overcoming the disadvantage...
In this paper, two variants of the fractional powers of generalized Hankel-Clifford transformation defined. These transformations are extended to certain spaces of generalized functions and prove several results on inversion, uniqueness, boundedness and analyticity. The operational calculus of these transformations is developed and then applied to solve certain class of partial differential equations...
In this paper, two variants of the fractional powers of generalized Hankel-Clifford transformation defined. These transformations are extended to certain spaces of generalized functions and prove several results on inversion, uniqueness, boundedness and analyticity. The operational calculus of these transformations is developed and then applied to solve certain class of partial differential equations...
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