Search results for: Neighbor relation.

Authors: Essam Al Daoud

Abstract:

This study solves a phylogeny problem by using modified wild dog pack optimization. The least squares error is considered as a cost function that needs to be minimized. Therefore, in each iteration, new distance matrices based on the constructed trees are calculated and used to select the alpha dog. To test the suggested algorithm, ten homologous genes are selected and collected from National Center for Biotechnology Information (NCBI) databanks (i.e., 16S, 18S, 28S, Cox 1, ITS1, ITS2, ETS, ATPB, Hsp90, and STN). The data are divided into three categories: 50 taxa, 100 taxa and 500 taxa. The empirical results show that the proposed algorithm is more reliable and accurate than other implemented methods.

Keywords: Least squares, neighbor joining, phylogenetic tree, wild dogpack.

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Authors: Handan Ertaş

Abstract:

The aim of the study is to determine the relationship between organizational trust level and organizational justice of Municipality officials. Correlational method has been used via descriptive survey model and Organizational Justice Perception Scale, Organizational Trust Inventory and Interpersonal Trust Scale have been applied to 353 participants who work in Konya Metropolitan Municipality and central district municipalities in the study. Frequency as statistical method, Independent Samples t test for binary groups, One Way-ANOVA analyses for multi-groups and Pearson Correlation analysis have been used to determine the relation in the data analysis process.It has been determined in the outcomes of the study that participants have high level of organizational trust, “Interpersonal Trust” is in the first place and there is a significant difference in the favor of male officials in terms of Trust on the Organization Itself and Interpersonal Trust. It has also been understood that officials in district municipalities have higher perception level in all dimensions, there is a significant difference in Trust on the Organization sub-dimension and work status is an important factor on organizational trust perception. Moreover, the study has shown that organizational justice implementations are important in raising trust of official on the organization, administrator and colleagues, and there is a parallel relation between Organizational Trust components and Organizational Trust dimensions.

Keywords: Konya, Organizational Justice, Organizational.

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

Abstract:

In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: Brain balancing, kNN, power spectral density, 3D EEG model.

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Authors: P. Jomsri

Abstract:

Currently searching through internet is very popular especially in a field of academic. A huge of educational information such as research papers are overload for user. So community-base web sites have been developed to help user search information more easily from process of customizing a web site to need each specifies user or set of user. In this paper propose to use association rule analyze the community group on research paper bookmarking. A set of design goals for community group frameworks is developed and discussed. Additionally Researcher analyzes the initial relation by using association rule discovery between the antecedent and the consequent of a rule in the groups of user for generate the idea to improve ranking search result and development recommender system.

Keywords: association rule, information retrieval, research paper bookmarking.

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Authors: Mona Taheri

Abstract:

The purpose of this research is to study the concepts of multiple Cartesian product, variety of multiple algebras and to present some examples. In the theory of multiple algebras, like other theories, deriving new things and concepts from the things and concepts available in the context is important. For example, the first were obtained from the quotient of a group modulo the equivalence relation defined by a subgroup of it. Gratzer showed that every multiple algebra can be obtained from the quotient of a universal algebra modulo a given equivalence relation. The purpose of this study is examination of multiple algebras and basic relations defined on them as well as introduction to some algebraic structures derived from multiple algebras. Among the structures obtained from multiple algebras, this article studies submultiple algebras, quotients of multiple algebras and the Cartesian product of multiple algebras.

Keywords: hypergroup, multiple algebras

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Authors: G. Murugeswari, A. Suruliandi

Abstract:

This paper proposes a rotational invariant texture feature based on the roughness property of the image for psoriasis image analysis. In this work, we have applied this feature for image classification and segmentation. The fuzzy concept is employed to overcome the imprecision of roughness. Since the psoriasis lesion is modeled by a rough surface, the feature is extended for calculating the Psoriasis Area Severity Index value. For classification and segmentation, the Nearest Neighbor algorithm is applied. We have obtained promising results for identifying affected lesions by using the roughness index and severity level estimation.

Keywords: Fuzzy texture feature, psoriasis, roughness feature, skin disease.

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Authors: Kozak K, M. Kozak, K. Stapor

Abstract:

The k-nearest neighbors (knn) is a simple but effective method of classification. In this paper we present an extended version of this technique for chemical compounds used in High Throughput Screening, where the distances of the nearest neighbors can be taken into account. Our algorithm uses kernel weight functions as guidance for the process of defining activity in screening data. Proposed kernel weight function aims to combine properties of graphical structure and molecule descriptors of screening compounds. We apply the modified knn method on several experimental data from biological screens. The experimental results confirm the effectiveness of the proposed method.

Keywords: biological screening, kernel methods, KNN, QSAR

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Authors: Xhiliola Agaraj(Shehu), Merita Murati, Valbona Gjini

Abstract:

The traditional public relations manager is usually responsible for maintaining and enhancing the reputation of the organization among key publics. While the principal focus of this effort is on support publics, it is quite clearly recognized that an organization's image has important effects on its own employees, its donors and volunteers, and its clients. The aim of paper is to define application`s aspects of public relations media and tools by nonprofit organizations in Albanian reality. Actually does used public relations media and tools, like written material, audiovisual material, organizational identity media, news, interviews and speeches, events, web sites by nonprofit organizations to attract donors? If, public relations media and tools are used, does exists a relation between public relation media and fundraising?

Keywords: Donors, Fundraising, Nonprofit Organizations, Public Relations

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Authors: Ali Dorostkar

Abstract:

In this paper, a basic schematic of fractional dimensional optimization problem is presented. As will be shown, a method is performed based on a relation between roots and tangent lines of function in fractional dimensions for an arbitrary initial point. It is shown that for each polynomial function with order N at least N tangent lines must be existed in fractional dimensions of 0 < α < N+1 which pass exactly through the all roots of the proposed function. Geometrical analysis of tangent lines in fractional dimensions is also presented to clarify more intuitively the proposed method. Results show that with an appropriate selection of fractional dimensions, we can directly find the roots. Method is presented for giving a different direction of optimization problems by the use of fractional dimensions.

Keywords: Tangent line, fractional dimension, root, optimization problem.

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Authors: Yilun Shang

Abstract:

In this paper we consider a one-dimensional random geometric graph process with the inter-nodal gaps evolving according to an exponential AR(1) process. The transition probability matrix and stationary distribution are derived for the Markov chains concerning connectivity and the number of components. We analyze the algorithm for hitting time regarding disconnectivity. In addition to dynamical properties, we also study topological properties for static snapshots. We obtain the degree distributions as well as asymptotic precise bounds and strong law of large numbers for connectivity threshold distance and the largest nearest neighbor distance amongst others. Both exact results and limit theorems are provided in this paper.

Keywords: random geometric graph, autoregressive process, degree, connectivity, Markovian, wireless network.

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Authors: Sang-Soo Kim, Seong-Bae Park, Sang-Jo Lee

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In this paper, we propose a method of resolving dependency ambiguities of Korean subordinate clauses based on Support Vector Machines (SVMs). Dependency analysis of clauses is well known to be one of the most difficult tasks in parsing sentences, especially in Korean. In order to solve this problem, we assume that the dependency relation of Korean subordinate clauses is the dependency relation among verb phrase, verb and endings in the clauses. As a result, this problem is represented as a binary classification task. In order to apply SVMs to this problem, we selected two kinds of features: static and dynamic features. The experimental results on STEP2000 corpus show that our system achieves the accuracy of 73.5%.

Keywords: Dependency analysis, subordinate clauses, binaryclassification, support vector machines.

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Authors: M. Mazhar Manzoor, Nasar.A, A. Sattar

Abstract:

In the open space of decision support system the mental impression of a manager-s decision has been the subject of large importance than the ordinary famous one, when helped by decision support system. Much of this study is an attempt to realize the relation of decision support system usage and decision outcomes that governs the system. For example, several researchers have proposed so many different models to analyze the linkage between decision support system processes and results of decision making. This study draws the important relation of manager-s mental approach with the use of decision support system. The findings of this paper are theoretical attempts to provide Decision Support System (DSS) in a way to exhibit and promote the learning in semi structured area. The proposed model shows the points of one-s learning improvements and maintains a theoretical approach in order to explore the DSS contribution in enhancing the decision forming and governing the system.

Keywords: Decision Support System , Learning Organization,

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Authors: Ahmed M. Eltohamy

Abstract:

In this paper, an experimental and numerical study was adopted to investigate the effect geogrid soil reinforcement pre-stressing on the pressure settlement relation of sand bed supporting a strip foundation. The studied parameters include foundation depth and pre-stress ratio for the cases of one and two pre-stressed reinforcement layers. The study reflected that pre-stressing of soil reinforcement resulted in a marked enhancement in reinforced bed soil stiffness compared to the reinforced soil without pre-stress. The best benefit of pre-stressing reinforcement was obtained as the overburden pressure and pre-straining ratio increase. Pre-stressing of double reinforcement topmost layers results in further enhancement of stress strain relation of bed soil.

Keywords: Geogrid reinforcement, strip footing, pre-stress, bearing capacity.

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Authors: Safak Baykal

Abstract:

The purpose of this study is analyzing the relationship between trust and social capital of people with using Social Network Analysis. In this study, two aspects of social capital will be focused: Bonding, homophilous social capital (BoSC), and Bridging, heterophilous social capital (BrSC). These two aspects diverge each other regarding to the social theories. The other concept of the study is Trust (Tr), namely interpersonal trust, willing to ascribe good intentions to and have confidence in the words and actions of other people. In this study, the sample group, 61 people, was selected from a private firm from the defense industry. The relation between BoSC/BrSC and Tr is shown by using Social Network Analysis (SNA) and statistical analysis with Likert type-questionnaire. The results of the analysis show the Cronbach’s alpha value is 0.756 and social capital values (BoSC/BrSC) is not correlated with Tr values of the people.

Keywords: Social capital, interpersonal trust, social network analysis (SNA).

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Authors: Julius Onyancha, Valentina Plekhanova

Abstract:

One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: Web log data, web user profile, user interest, noise web data learning, machine learning.

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Authors: P. Vosynek, T. Návrat, M. Peč, J. Pořízka, P. Diviš

Abstract:

Bone properties and response behavior after static or dynamic activation (loading) are still interesting topics in many fields of the science especially in the biomechanical problems such as bone loss of astronauts in space, osteoporosis, bone remodeling after fracture or remodeling after surgery (endoprosthesis and implants) and in osteointegration. This contribution deals with the relation between physiological, demineralized and deproteinized state of the turkey long bone – tibia. Three methods for comparison were used: 1) densitometry, 2) three point bending and 3) frequency analysis. The main goal of this work was to describe the decrease of the protein (collagen) or mineral of the bone with relation to the fracture in three point bending. The comparison is linked to the problem of different bone mechanical behavior in physiological and osteoporotic state.

Keywords: Bone properties, long bone, osteoporosis, response behavior.

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Authors: Imen Aouini, Lamia Ben Azzouz

Abstract:

The energy need is growing rapidly due to the population growth and the large new usage of power. Several works put considerable efforts to make the electricity grid more intelligent to reduce essentially energy consumption and provide efficiency and reliability of power systems. The Smart Grid is a complex architecture that covers critical devices and systems vulnerable to significant attacks. Hence, security is a crucial factor for the success and the wide deployment of Smart Grids. In this paper, we present security issues of the Smart Grid architecture and we highlight open issues that will make the Smart Grid security a challenging research area in the future.

Keywords: Smart grids, smart meters, home area network, neighbor area network.

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Authors: Daniel Santos, Bruno Ribeiro, Marco Amato, Antonio Fonseca

Abstract:

In this paper we discuss the behaviour of the longitudinal modes of a magnetized non collisional plasma subjected to an external electromagnetic field. We apply a semiclassical formalism, with the electrons being studied in a quantum mechanical viewpoint whereas the electromagnetic field in the classical context. We calculate the dielectric function in order to obtains the modes and found that, unlike the Bernstein modes, the presence of radiation induces oscillations around the cyclotron harmonics, which are smoothed as the energy stored in the radiation field becomes small compared to the thermal energy of the electrons. We analyze the influence of the number of photon involved in the electronic transitions between the Landau levels and how the parameters such as the external fields strength, plasma density and temperature affect the dispersion relation

Keywords: Collective oscillations, External fields, Dispersion relation.

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Authors: J. Hodna, B. Dohnalkova, V. Petranek, R. Drochytka

Abstract:

The paper is focused on the identification of limiting environmental factors of individual industrial floors on which newly developed polymer protection and repair systems with the use of secondary raw materials will be used. These mainly include floors with extreme stresses and special requirements for materials used. In relation to the environment of a particular industrial floor, it is necessary to ensure, for example, chemical stability, resistance to higher temperatures, resistance to higher mechanical stress, etc. for developed materials, which is reflected in the demands for the developed material systems. The paper describes individual environments and, in relation to them, also requirements for individual components of the developed materials and for the developed materials as a whole.

Keywords: Limits, environment, polymer, industrial floors, recycling, secondary raw material, protective system.

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Authors: Dana M. Ragab, Jasim A Ghaeb

Abstract:

The Voltage Unbalance Factor (VUF) index is recommended to evaluate system performance under unbalanced operation. However, its calculation requires complex algebra which limits its use in the field. Furthermore, one system cycle is required at least to detect unbalance using the VUF. Ideally unbalance mitigation must be performed within 10 ms for 50 Hz systems. In this work, a linear relation for VUF evaluation in three-phase electrical power system using space vector (SV) is derived. It is proposed to determine the voltage unbalance quickly and accurately and to overcome the constraints associated with the traditional methods of VUF evaluation. Aqaba-Qatrana-South Amman (AQSA) power system is considered to study the system performance under unbalanced conditions. The results show that both the complexity of calculations and the time required to evaluate VUF are reduced significantly.

Keywords: Power quality, space vector, unbalance evaluation.

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Authors: Serap Durmus

Abstract:

The aim of this paper is to exemplify the relation of architecture and philosophy over the Japanese architect Toyo Ito’s conceptual architecture. The study is practiced in ‘Architecture and Philosophy Readings’ elective course with 22 sophomore architecture students in Karadeniz Technical University Department of Architecture. It is planned as a workshop, which discusses the design philosophy of Toyo Ito’s buildings and the reflections of concept in his intellectual architecture. So, the paper contains Toyo Ito’s philosophy, his discourses and buildings and also thinking similarities with philosopher Gilles Deleuze. Thus, the workshop of course is about architecture and philosophy relationship. With this aspect, a holistic graphic representation is aimed for Toyo Ito who thinks that everything composes a whole. As a result, it can be said that architect and philosopher interaction in architecture and philosophy relation supports creative thinking. Conceptual architecture of Toyo Ito has philosophical roots and his philosophy can be read over his buildings and can be represent totally via a holistic pattern.

Keywords: Architecture, philosophy, Toyo Ito, conceptual architecture, Gilles Deleuze.

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Authors: Yih-Chuan Lin, Jung-Hong Li

Abstract:

In this paper, we propose a reversible watermarking scheme based on histogram shifting (HS) to embed watermark bits into the H.264/AVC standard videos by modifying the last nonzero level in the context adaptive variable length coding (CAVLC) domain. The proposed method collects all of the last nonzero coefficients (or called last level coefficient) of 4×4 sub-macro blocks in a macro block and utilizes predictions for the current last level from the neighbor block-s last levels to embed watermark bits. The feature of the proposed method is low computational and has the ability of reversible recovery. The experimental results have demonstrated that our proposed scheme has acceptable degradation on video quality and output bit-rate for most test videos.

Keywords: Reversible data hiding, H.264/AVC standard, CAVLC, Histogram shifting

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Authors: Sheng-Hsiu Kuo, Pao-Hsiung Chiu, Reui-Kuo Lin, Yan-Ting Lin

Abstract:

A one-step conservative level set method, combined with a global mass correction method, is developed in this study to simulate the incompressible two-phase flows. The present framework do not need to solve the conservative level set scheme at two separated steps, and the global mass can be exactly conserved. The present method is then more efficient than two-step conservative level set scheme. The dispersion-relation-preserving schemes are utilized for the advection terms. The pressure Poisson equation solver is applied to GPU computation using the pCDR library developed by National Center for High-Performance Computing, Taiwan. The SMP parallelization is used to accelerate the rest of calculations. Three benchmark problems were done for the performance evaluation. Good agreements with the referenced solutions are demonstrated for all the investigated problems.

Keywords: Conservative level set method, two-phase flow, dispersion-relation-preserving, graphics processing unit (GPU), multi-threading.

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Authors: Takayuki Konishi, Kakeru Yazawa, Mariko Kondo

Abstract:

This study examines developmental change in the production of epenthetic vowels by Japanese learners of English in relation to acquisition of L2 English speech rhythm. Seventy-two Japanese learners of English in the J-AESOP corpus were divided into lower- and higher-level learners according to their proficiency score and the frequency of vowel epenthesis. Three learners were excluded because no vowel epenthesis was observed in their utterances. The analysis of their read English speech data showed no statistical difference between lower- and higher-level learners, implying the absence of any developmental change in durations of epenthetic vowels. This result, together with the findings of previous studies, will be discussed in relation to the transfer of L1 phonology and manifestation of L2 English rhythm.

Keywords: Vowel epenthesis, Japanese learners of English, L2 speech corpus, speech rhythm.

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Authors: Nebi Gedik

Abstract:

Heart disease threatens the lives of a great number of people every year around the world. Heart issues lead to many of all deaths; therefore, early diagnosis and treatment are critical. The diagnosis of heart disease is complicated due to several factors affecting health such as high blood pressure, raised cholesterol, an irregular pulse rhythm, and more. Artificial intelligence has the potential to assist in the early detection and treatment of diseases. Improving heart failure prediction is one of the primary goals of research on heart disease risk assessment. This study aims to determine the features that provide the most successful classification prediction in detecting cardiovascular disease. The performances of each feature are compared using the K-Nearest Neighbor machine learning method. The feature that gives the most successful performance has been identified.

Keywords: Cardiovascular disease, feature extraction, supervised learning, k-NN.

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Authors: Lei Zhang, Tao Wang, Xiantong Zhen

Abstract:

Naive Bayes Nearest Neighbor (NBNN) and its variants, i,e., local NBNN and the NBNN kernels, are local feature-based classifiers that have achieved impressive performance in image classification. By exploiting instance-to-class (I2C) distances (instance means image/video in image/video classification), they avoid quantization errors of local image descriptors in the bag of words (BoW) model. However, the performances of NBNN, local NBNN and the NBNN kernels have not been validated on video analysis. In this paper, we introduce these three classifiers into human action recognition and conduct comprehensive experiments on the benchmark KTH and the realistic HMDB datasets. The results shows that those I2C based classifiers consistently outperform the SVM classifier with the BoW model.

Keywords: Instance-to-class distance, NBNN, Local NBNN, NBNN kernel.

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Authors: Ya-Hui Lee, Ching-Yi Lu, Hui-Chuan Wei

Abstract:

The purpose of this research was to explore the relation between proactive coping and well-being of middle-aged adults. We conducted survey research that with t-test, one way ANOVA, Pearson correlation and stepwise multiple regression to analyze. This research drew on a sample of 395 participants from the senior learning centers of Taiwan. The results provided the following findings: 1.The participants from different residence areas associated significant difference with proactive coping, but not with well-being. 2. The participants’ perceived of financial level associated significant difference with both proactive coping and well-being. 3. There was significant difference between participants’ income and well-being. 4. The proactive coping was positively correlated with well-being. 5. From stepwise multiple regression analysis showed that two dimensions of proactive coping had positive predictability. Finally, these results of this study can be provided as references for designing older adult educational programs in Taiwan.

Keywords: Middle-age adults, learners, proactive coping, well-being.

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Authors: Faisal Aburub, Wael Hadi

Abstract:

Data mining is the process of extracting useful or hidden information from a large database. Extracted information can be used to discover relationships among features, where data objects are grouped according to logical relationships; or to predict unseen objects to one of the predefined groups. In this paper, we aim to investigate four well-known data mining algorithms in order to predict groundwater areas in Jordan. These algorithms are Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbor (kNN) and Classification Based on Association Rule (CBA). The experimental results indicate that the SVMs algorithm outperformed other algorithms in terms of classification accuracy, precision and F1 evaluation measures using the datasets of groundwater areas that were collected from Jordanian Ministry of Water and Irrigation.

Keywords: Classification, data mining, evaluation measures, groundwater.

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Authors: Moustafa A. Bani-Hasan, Yasser M. Kadah, Fatma M. El-Hefnawi

Abstract:

An electrocardiogram (ECG) feature extraction system based on the calculation of the complex resonance frequency employing Prony-s method is developed. Prony-s method is applied on five different classes of ECG signals- arrhythmia as a finite sum of exponentials depending on the signal-s poles and the resonant complex frequencies. Those poles and resonance frequencies of the ECG signals- arrhythmia are evaluated for a large number of each arrhythmia. The ECG signals of lead II (ML II) were taken from MIT-BIH database for five different types. These are the ventricular couplet (VC), ventricular tachycardia (VT), ventricular bigeminy (VB), and ventricular fibrillation (VF) and the normal (NR). This novel method can be extended to any number of arrhythmias. Different classification techniques were tried using neural networks (NN), K nearest neighbor (KNN), linear discriminant analysis (LDA) and multi-class support vector machine (MC-SVM).

Keywords: Arrhythmias analysis, electrocardiogram, featureextraction, statistical classifiers.

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Authors: G. Lavanya Devi, Allam Appa Rao, A. Damodaram, GR Sridhar, G. Jaya Suma

Abstract:

Cluster analysis divides data into groups that are meaningful, useful, or both. Analysis of biological data is creating a new generation of epidemiologic, prognostic, diagnostic and treatment modalities. Clustering of protein sequences is one of the current research topics in the field of computer science. Linear relation is valuable in rule discovery for a given data, such as if value X goes up 1, value Y will go down 3", etc. The classical linear regression models the linear relation of two sequences perfectly. However, if we need to cluster a large repository of protein sequences into groups where sequences have strong linear relationship with each other, it is prohibitively expensive to compare sequences one by one. In this paper, we propose a new technique named General Regression Model Technique Clustering Algorithm (GRMTCA) to benignly handle the problem of linear sequences clustering. GRMT gives a measure, GR*, to tell the degree of linearity of multiple sequences without having to compare each pair of them.

Keywords: Clustering, General Regression Model, Protein Sequences, Similarity Measure.

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