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Data mining is a knowledge discovery process which deals with the broad process of finding knowledge in data analyzing large storage of data in order to identify the relevant data. It is a powerful tool to uncover relationships within the data. Business intelligence (BI), is a distinctive term that refers to a lot of software applications, it is normally used to investigate a company's raw data for...
Feature selection is considered an important step for gait pattern recognition. The task of a gait classifier could be simplified by eliminating redundant and irrelevant attributes for classification. With that, the size of the feature set could be reduced and subsequently a more comprehensible analysis of the extracted patterns could be carried out. In this paper, we present a feature selection method...
The Internet has opened new interesting scenarios in the fields of e-commerce, marketing and on-line transactions. In particular, thanks to mobile technologies, customers can make purchases in a faster and cheaper way than visiting stores, and business companies can increase their sales volume due to a world-wide visibility. Moreover, online trading systems allow customers to gather all the required...
Proteins are macromolecules that have a high molecular weight, and make up, along with water, most of the composition of cells. The functions they perform are extremely important, such as the catalysis of biochemical reactions, cytoskeleton formation, and the transportation and storage of substances. With the completion of genome sequencing, protein discovery has been growing exponentially, and the...
Providing security by means of using traditional methods such as PINs, Passwords, access cards are being vulnerable to various attacks and are easily hacked by intruders or unauthorized users. The aim is to develop an efficient personal identification system to provide secure access for legitimate users which is a challenging task. In order to avoid these problems, the use of biométrie traits reliably...
In this paper, we propose the optimal parameters of local binary patterns such as type of pattern, size of blocks in the feature space and distance measure for face recognition using a genetic algorithm. The genetic algorithm is able to optimize all these parameters quickly and to improve the recognition accuracy. We provide a comparative study of three types of local binary patterns (LBP, LGP and...
Detection and delineation of Electrocardiogram has played a vital role in cardiovascular monitoring systems. The enormous database of heart beats which characterize the heart disease, uncertainity, randomness in occurrence of these beats necessitate the use of Rough set theory. Over the years Rough set theory has been effectively used for removal of uncertainties and reduction of dataset. This paper...
This paper presents a novel computer-aided multiobjective optimal design for medium-frequency (MF) transformers using NSGA genetic algorithm. The proposed methodology has the aim of reaching the best MF transformer for a given power converter topology, by optimizing transformer efficiency, weight, and also, transformer leakage and magnetizing inductances at the same time. Moreover, this work provides...
Face Recognition is among the most widely studied problems in computer vision and Pattern Recognition. Face has many advantages like permanence, accessibility and universality. It is still now not solved in literature. Several approaches are proposed to overcome with problems including; changing posed, emotional states, and illumination variation, etc. Geometric approaches which used as example distance...
This paper presents to the improvement of the Significant Matrix [1] that works along with Genetic Algorithm in feature selection of appropriate data for a decision tree structure. This work proposes the reduction of time that cut off the Genetic Algorithm's work times. The new method is proposed in the name “Significant Matrix 2” which is calculated from the relationship between categorical data...
Content-based image retrieval (CBIR) is an active research area over the past few decades. In medical applications like mammogram analysis content based image retrieval techniques helps the radiologists or physicians to access similar images from a large medical database to aid diagnosis. In this paper content-based retrieval of mammograms from DDSM database is performed using fixed, genetic algorithm...
The popular AML (Approximate Membership Localization) is the process of delivers a full coverage to the true matched substrings from single given document, but redundancies cause a low efficiency of AML process and deteriorate the performance of the real world applications using the extracted substrings. Though the results of AML are proved to be good over Approximate Membership Extraction (AME),...
Correct detection and classification of ventricular fibrillation (VF) and rapid ventricular tachycardia (VT) is of pivotal importance for an automatic external defibrillator and patient monitoring. In this paper, a VF/VT classification algorithm using a machine learning method, a support vector machine, is proposed. A total of 14 metrics were extracted from a specific window length of the electrocardiogram...
This paper presents the fusion of artificial intelligence (AI) learning algorithms that are genetic algorithms (GA) and conjugate gradient (CG) methods. Both methods are used to find the optimum weights for the hidden and output layers of feedforward artificial neural network (ANN) model. Each algorithm is presented in separate module and we proposed three different types of Dynamic Connection Strategies...
Spirometry is the most commonly performed Pulmonary Function Test (PFT) which is used to distinguish obstructive from restrictive lung diseases. This paper presents the basic system requirements for an automatic pulmonary disease classification system based on spirometric signal using a novel algorithm. The software of the system extracted features from the digitized spirogram waveform values and...
Web services composition enables the business to dynamically and seamlessly integrate business applications on the web. The performance of an overall composition is a function of its individual component services. Hence, both functional and nonfunctional properties of Web services are important when negotiating component service for a system. Automated negotiation helps speed up this process and often...
In this paper, a relevant document retrieval method is proposed for document retrieval systems with vector space models (VSM). In recent years, with the size of the database becomes extremely large, there becomes a high demanding of an accurate and fast-time document retrieval algorithm. Based on the maximum similarity criterion, a document retrieval algorithm using the discrete stochastic optimization...
This paper introduces an approach of using the genetic algorithm for orienting protein-protein interaction networks (PPIs) and discovering pathways. Biological pathways such as metabolic or signaling ones play an important role in understanding cell activities and evolution. A cost-effective method to discover such pathways is analyzing accumulated information about protein-protein interactions, which...
This paper presents a method for extracting automatically classification rules via multi-objective genetic algorithms. The paper also proposes a novel objective measure to quantify the similarity of the rules. The other objectives of the rules are average support value and accuracy. We experimentally evaluate our approach on socio-demographics and biochemistry datasets of schizophrenia patients and...
Vein recognition has been extensively studied in the past. The topology of the vein patterns allows to adopt simple representations, based on edges and their endings, which are quite similar to the fingerprint minutiae. In this paper, the Minutia Cylinder-Codes (MCC), developed for the comparison of fingerprint minutiae, are adapted to characterize vein minutiae. The algorithm adaptation requires...
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