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One of the most important challenges in a densely wireless sensor network (WSN) with potential congestions and packet loss is dissemination of distrusted packets. In this paper we present FCCTF: Fairness Congestion Control for a disTrustful WSN using Fuzzy logic. FCCTF increases each node capability for detecting and isolating malicious nodes in order to improve packet delivery while some important...
We explore an extension of rough set theory based on probability theory. Lower and upper approximations, the basic ideas of rough set theory, are generalized by adding two parameters, denoted by alpha and beta. In our experiments, for different pairs of alpha and beta, we induced three types of rules: positive, boundary, and possible. The quality of these rules was evaluated using ten-fold cross validation...
In most of the standard Pan-sharpening methods, it is observed that color distortion appears in the final Pansharped image. In the area of image analysis in remote sensing applications, spectral information plays an important role and due to the color distortion, image analysis may get affected. In this paper, a fuzzy based hybrid multispectral image fusion method using wavelet transform is proposed...
This work presents the integration of a fuzzy method and text mining to obtain an approach that enables the text documents classification to be closer to the user needs. The aim of this work is to develop a mechanism to reduce the high dimensionality of the attribute-value matrix obtained from the documents and, with this, to manage the imprecision and uncertainty using fuzzy rules to classify text...
Automated software testing has become a fundamental requirement for several software engineering methodologies. Software development companies very often outsource the test of their products. In such cases, the hired companies sometimes have to test softwares without any access to the source code. This type of service is called black box testing, which includes presentation of some ad-hoc input to...
This paper has the purpose to present a new hybrid nature inspired metaheuristic developed based on three fundamentals pillars extremely well known: Genetic Algorithms, Game Theory and Fuzzy Systems. This new approach tries to mimic a little bit more closer how a population of individuals evolves along time, like human social evolution emphasizing the social interaction between individuals and the...
This paper examines the performance of a new Hidden Markov Model (HMM) structure used as the core of an Internet traffic classsifier and compares the results against other models present in the literature. Traffic modeling and classification find importance in many areas such as bandwidth management, traffic analysis, prediction and engineering, network planning, Quality of Service provisioning and...
This study proposes a new unsupervised approach for targets detection and classification in multispectral Magnetic Resonance (MR) images. The proposed method comprises two processes, namely Target Generation Process (TGP) and Constrained Energy Minimization (CEM). TGP is a fuzzy-set process that generates a set of potential targets from unknown information, and applies these targets to be desired...
This paper at first presents a novel approach to recognize characters, numbers or the signs under translation, scaling and rotation (TRS) from Civil Aerial Meteorological Maps by templates, which is based on a new class of moment invariants. Meanwhile, aiming to the important parameter (the range of orders for moment invariants) in it, we prove so that could decrease efficiently the errors brought...
In recent years, three-dimensional Virtual Environments developed with virtual reality and graphical computation technologies have evolved in the Web. Thus, users with different profiles, cultures and knowledge levels can access such environments remotely. In such a way, it is necessary to use an efficient interface to manage Web accesses and to actualize virtual environments to adapt them to each...
This paper proposes a methodology for a short-term bus load forecasting. This approach calculates the short-term bus load demand forecast using few aggregated models. The idea is to cluster the buses in groups with similar daily load profile and for each cluster one bus load forecasting model is adjusted. For each cluster, aggregated forecasting model is built based on the analysis of individual bus...
In traditional classification problems (single-label), patterns are associated with a single label from the set of disjoint labels (classes). When an example can simultaneously belong to more than one label, this classification problem is known as multi-label classification problem. Multi-label classification methods have been increasingly used in modern application, such as music categorization,...
From an enterprise point of view, Knowledge Management (KM) enables organizations to capture, share, and apply the collective experience and know-how (knowledge) of their staff. Up to now, little effort has been devoted to apply Artificial Intelligent techniques to KM systems. This paper proposes the application of case-based reasoning, in combination with a neural model, to develop a KM system. This...
SQL Injection attacks on web applications have become one of the most important information security concerns over the past few years. This paper presents a hybrid approach based on the Adaptive Intelligent Intrusion Detector Agent (AIIDA-SQL) for the detection of those attacks. The AIIDA-SQL agent incorporates a Case-Based Reasoning (CBR) engine which is equipped with learning and adaptation capabilities...
Gene regulatory network provides the knowledge of interaction strength among the genes in living organisms. Accurate identification of gene regulatory network is of prime interest to the researchers in recent time. Different researchers applied different optimization techniques to solve this problem. Most of these optimization techniques considers the square error between reference and simulated gene...
Particle swarm optimization (PSO) is a bioinspired technique widely used to solve real optimization problems. In the recent years, the use of Graphics Processing Units (GPU) has been proposed for some general purpose computing applications. Some PSO implementations on GPU were already proposed. The major benefit to implement the PSO for GPU is the possibility to reduce the execution time. It occurs...
The demand for cellular systems has grown in recent years and sometimes it is not an easy task to design such systems. We propose in this paper a new approach to tackle the maximum coverage problem in cellular systems using Particle Swarm Optimization (PSO). We adapted the PSO since we have associated the position of the base stations to the particles. We also developed two mechanisms to avoid overlapping...
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