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Skew is the angle the image makes with the corner of the page. Skew estimation is a preprocessing step in document image analysis. It involves two steps skew detection and skew correction. Skew estimation is needed because while scanning the document image a little skew is unavoidable. If skew is present in the document then Optical Character Recognizer (OCR) will identify the script wrongly. In this...
This paper presents a new hybrid control strategy for velocity control of an electro hydraulic servo system (EHSS) in presence of flow nonlinearities and internal friction. We employed a combination of LQR controller and fuzzy-neural network in a feedback error learning framework. In the proposed control approach, LQR controller as a classical controller is designed such that the stability is guaranteed...
Connection Manager Intelligence Agent's (CMIA) an attractive feature is use the network traffic and behavior with multi-attributes to find the best network devices and connection devices meet user habits that it possible to access various network contents everywhere at any time. In this agent, information process is thoroughly integrated into embedded system for connection manager of MeeGo or Android...
Good business decision making depends on how good information is provided. Due to this factor, the quality of data provided by transactions systems database is really important to organizations in order to produce the best solution for their company to move forward. Data Quality issues have become major problems in most enterprise systems where in some cases forced companies to stop their operations...
This paper proposes a novel fusion technique using iris-online signature biometrics at feature level space. The biometric features are extracted from the pre-processed images of iris and the dynamics of signatures. We propose different fusion schemes at feature level. In order to reduce the complexity of the fusion scheme, we adopt a binary particle swarm optimization (BPSO) procedure which allows...
The volume and diversity of documents available in today's world is increasing daily. It is therefore difficult for a single classifier to efficiently handle multi-level categorization of such a varied document space. In this paper we analyse methods to enhance the efficiency of a single classifier for two-level classification by combining it with classifiers of other types. We use the maximum significance...
In this work, we discuss how an intelligent agent learns in combinatorial auctions. It is well-known that it is NP-cpmplete problem to find the optimal allocation to maximize revenue, because this is a typical form of Set Package Problem (SPP). We apply a framework of machine learning to combinatorial auctions, and discuss how to extract intelligence about bidding behavior. We show empirical convergence...
Cuckoo Search (CS) is a meta-heuristic optimization algorithm that is inspired by breeding strategy of some cuckoo species that involves laying of eggs in the nests of other host birds. Like other population based optimization algorithms, the initial positions of the population, in the case of CS are host nests, will influence the performance of the searching. Based on this fact, we believe that the...
Many challenges are to be addressed when it comes to integrating ontologies. The common challenges are ontology mismatches. It is important for the integrated ontology to model the intended meaning and resolve all the conflicts so that it will not form a false commitment to the system. Much work has paid attention to finding similarities between ontologies. Little work has considered overcoming coverage...
The objective of condition based maintenance (CBM) is typically to determine an optimal maintenance policy to minimize the overall maintenance cost based on condition monitoring information. In Aircraft operator and the maintenance people starving to reduce the cost of aircraft maintenance. So the condition based monitoring for electromechanical control valve is very popular recently. This paper has...
Most of Intrusion Detection Systems uses all data features to detect an intrusion. Very little work addresses the importance of having a small feature subset in designing an efficient intrusion detection system. Some features are redundant and some contribute little to the intrusion detection process. Purpose of this study is to investigate the effectiveness of Rough Set Theory in identifying the...
The objective of this paper is to compare the performance of Hierarchical Soft Decision Trees and Rule based AI techniques in optimization of fuzzy outputs for the classification of epilepsy risk levels from EEG (Electroencephalogram) signals. The fuzzy pre classifier is used to classify the risk levels of epilepsy based on extracted parameters like energy, variance, peaks, sharp and spike waves,...
Body Sensor Networks (BSN) have gained interest in recent years from researches. Several promising prototypes are enabling many healthcare services. Despite of technological developments in sensing and monitoring devices, some issues related to BSN have still to be investigated. For example, information routing requires establishment of multi-hop paths which can be done considering the amount of consumed...
In this paper, we present an approach to facilitate the annotation and the retrieval of the image documents. Our approach is based on the definition and the generation of semantic rules presented via the logic of predicates. Then, we proposed the classification of these rules by a method of clustering Fuzzy C-means. For this, we used the method of co-citation to calculate the similarity measure between...
Posture language is rich in ways for individuals to express a variety of desire, feelings and thoughts. Recognizing human posture via computer is a challenging task as it involved multiple issues ranging from image, recognition algorithm and system resources. This proposed work aimed to solve viewpoint variation issue through causal topology design Hidden Markov Model (HMM) for view independent multiple...
This paper presents an innovative hybrid of Functional Networks and Support Vector Machines (FN-SVM) as an improvement over an existing Functional Networks and Type-2 Fuzzy Logic (FN-T2FL) hybrid model. The former is more promising as it combines two existing techniques that are very close in performance and well known for their computational stability and fast processing. This proposed FN-SVM hybrid...
Recent research agrees on the utility of fuzzy reasoning for the development of Decision Support Systems, which help to classify clinical data. In this context, methods or techniques for representing fuzzy terms in the form of interpretable fuzzy sets obtained from numerical data are strongly required. Typically, in medical settings, statistical data are available or can be obtained from rough data,...
Web caching is one of the most successful solutions for improving the performance of Web-based systems. In Web proxy caching, the popular Web objects that are likely to be revisited in the near future are stored on the proxy server, which plays the key roles between users and Web sites in reducing the response time of user requests and saving the network bandwidth. However, the difficulty in determining...
This paper proposes tackling the difficult course timetabling problem using a multi-agent approach. The proposed design seeks to deal with the problem using a distributed solution environment in which a mediator agent coordinates various timetabling agents that cooperate to improve a common global solution. Initial timetables provided to the multi-agent system are generated using several hybrid heuristics...
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