Search results for: Genetic Algorithm Logistic Regression

Authors: Mohd Yusri Ibrahim

Abstract:

Although it is known that interpersonal skills are essential for personal development, the debate however continues as to how to measure those skills, especially in youths. This study was conducted to develop a measurement model of interpersonal skills by suggesting three construct namely personal, skills and relationship; six function namely self, perception, listening, conversation, emotion and conflict management; and 30 behaviours as indicators. This cross-sectional survey by questionnaires was applied in east side of peninsula of Malaysia for 150 respondents, and analyzed by structural equation modelling (SEM) by AMOS. The suggested constructs, functions and indicators were consider accepted as measurement elements by observing on regression weight for standard loading, average variance extracted (AVE) for convergent validity, square root of AVE for discriminant validity, composite reliability (CR), and at least three fit indexes for model fitness. Finally, a measurement model of interpersonal skill for youth was successfully developed.

Keywords: Interpersonal communication, interpersonal skill, youth.

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Authors: Kemalettin Eryeşil, Aykut Bedük, Mehtap Fındık

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The aim of this study is to determine the effect of strategic management implementations on the institutionalization levels. In this regard a field study has been made over 31 stone quarry enterprises in cement producing sector in Konya by using survey method. In this study, institutionalization levels of the enterprises have been evaluated regarding three dimensions: professionalization, management approach, participation in decisions and delegation of authority. According to the results of the survey, there is a highly positive and statistically significant relationship between the strategic management implementations and institutionalization levels of the enterprises. Additionally,-considering the results of regression analysis made for establishing the relationship between strategic management and institutionalization levels- it has been determined that strategic management implementations of the enterprises can be used as a variable to explain the institutionalization levels of them, and also strategic management implementations of the enterprises increase the institutionalization levels of them.

Keywords: Institutionalization, Management, Strategic Management.

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Authors: Safdar Tanweer, Abdul Mobin, Afshar Alam

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The performance and analysis of speech recognition system is illustrated in this paper. An approach to recognize the English word corresponding to digit (0-9) spoken by 2 different speakers is captured in noise free environment. For feature extraction, speech Mel frequency cepstral coefficients (MFCC) has been used which gives a set of feature vectors from recorded speech samples. Neural network model is used to enhance the recognition performance. Feed forward neural network with back propagation algorithm model is used. However other speech recognition techniques such as HMM, DTW exist. All experiments are carried out on Matlab.

Keywords: Speech Recognition, MFCC, Neural Network, classifier.

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Authors: Lijia Wang, Xuexi Huo

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This study analyzes characteristics determining member’s willingness to invest in cooperatives using ordered logit model. The data were collected in a field survey among 122 cooperative members in north-central China. The descriptive analysis of survey evidence suggests that cooperatives in China generally having poor ability to deliver the processing services related to product package, grading, and storage, performing worse in profitability, inability of providing returns to capital and obtaining agricultural loan. The regression results demonstrate that members’ farm size, their satisfaction with cooperative price preferential services, attitudes toward cooperative operational scale and development potential have statistically significant impact on willingness to invest.

Keywords: Cooperatives, investment willingness, member, ordered logit.

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: Time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder.

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Authors: Zulkufly Ramly

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This paper attempts to investigate the effect of corporate governance and shareholder monitoring mechanisms on cost of debt of Malaysian listed firms. We assess the quality of corporate governance using comprehensive corporate governance index, which consists of 139 items in six broad categories. We classify shareholder monitoring mechanisms into concentrated ownership, family, insider and government ownerships. Using panel sample from 2003 to 2007, regression results show that high corporate governance quality and concentrated ownership lower firm cost of debt. Debt issuers consider board structure and procedures, board compensation practices, accountability and audit, transparency and social and environmental activities as integral components of a good corporate governance framework.

Keywords: Corporate governance index, cost of debt, ownership structure, Malaysia.

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Authors: Saeid Saryazdi, Hossein Nezamabadi-pour

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A new blind gray-level watermarking scheme is described. In the proposed method, the host image is first divided into 4*4 non-overlapping blocks. For each block, two first AC coefficients of its Hadamard transform are then estimated using DC coefficients of its neighbor blocks. A gray-level watermark is then added into estimated values. Since embedding watermark does not change the DC coefficients, watermark extracting could be done by estimating AC coefficients and comparing them with their actual values. Several experiments are made and results suggest the robustness of the proposed algorithm.

Keywords: Digital Watermarking, Image watermarking, Information Hiden, Steganography.

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Authors: Babesse Saad, Ameddah Djameleddine

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In this paper, a learning algorithm using neuronal networks to improve the roll stability and prevent the rollover in a single unit heavy vehicle is proposed. First, LQR control to keep balanced normalized rollovers, between front and rear axles, below the unity, then a data collected from this controller is used as a training basis of a neuronal regulator. The ANN controller is thereafter applied for the nonlinear side force model, and gives satisfactory results than the LQR one.

Keywords: Rollover, single unit heavy vehicle, neural networks, nonlinear side force.

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Authors: Mahboobe Zardosht, Nasser Ghasem-Aghaee

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We propose an enhanced collaborative filtering method using Hofstede-s cultural dimensions, calculated for 111 countries. We employ 4 of these dimensions, which are correlated to the costumers- buying behavior, in order to detect users- preferences for items. In addition, several advantages of this method demonstrated for data sparseness and cold-start users, which are important challenges in collaborative filtering. We present experiments using a real dataset, Book Crossing Dataset. Experimental results shows that the proposed algorithm provide significant advantages in terms of improving recommendation quality.

Keywords: Collaborative filtering, Cross-cultural, E-commerce, Recommender systems

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Authors: Hemanth KumarA.R, Sudhakara G., Satyanarayana B.S.

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The Cluster Dimension of a network is defined as, which is the minimum cardinality of a subset S of the set of nodes having the property that for any two distinct nodes x and y, there exist the node Si, s2 (need not be distinct) in S such that ld(x,s1) — d(y, s1)1 > 1 and d(x,s2) < d(x,$) for all s E S — {s2}. In this paper, strictly non overlap¬ping clusters are constructed. The concept of LandMarks for Unique Addressing and Clustering (LMUAC) routing scheme is developed. With the help of LMUAC routing scheme, It is shown that path length (upper bound)PLN,d < PLD, Maximum memory space requirement for the networkMSLmuAc(Az) < MSEmuAc < MSH3L < MSric and Maximum Link utilization factor MLLMUAC(i=3) < MLLMUAC(z03) < M Lc

Keywords: Metric dimension, Cluster dimension, Cluster.

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Authors: Attila Vámosi, Tamás Mankovits, Dávid Huri, Imre Kocsis, Tamás Szabó

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Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. For example rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. The shape optimization problem of rubber parts led to the study of FEM based calculation processes. This type of problems was posed and investigated by several authors. In this paper the time demand of certain calculation methods are studied and the possibilities of time reduction is presented.

Keywords: Rubber bumper, data acquisition, finite element analysis, support vector regression.

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Authors: D. Prangchumpol

Abstract:

This paper is a description approach to predict incoming and outgoing data rate in network system by using association rule discover, which is one of the data mining techniques. Information of incoming and outgoing data in each times and network bandwidth are network performance parameters, which needed to solve in the traffic problem. Since congestion and data loss are important network problems. The result of this technique can predicted future network traffic. In addition, this research is useful for network routing selection and network performance improvement.

Keywords: Traffic prediction, association rule, data mining.

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Authors: A. Giniatoulline

Abstract:

A nonlinear model of the mathematical fluid dynamics which describes the motion of an incompressible viscous rotating fluid in a homogeneous gravitational field is considered. The model is a generalization of the known Navier-Stokes system with the addition of the Coriolis parameter and the equations for changeable density. An explicit algorithm for the solution is constructed, and the proof of the existence and uniqueness theorems for the strong solution of the nonlinear problem is given. For the linear case, the localization and the structure of the spectrum of inner waves are also investigated.

Keywords: Galerkin method, Navier-Stokes equations, nonlinear partial differential equations, Sobolev spaces, stratified fluid.

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Authors: R. B. Ogunrinde

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This paper presents the development, analysis and implementation of an inverse polynomial numerical method which is well suitable for solving initial value problems in first order ordinary differential equations with applications to sample problems. We also present some basic concepts and fundamental theories which are vital to the analysis of the scheme. We analyzed the consistency, convergence, and stability properties of the scheme. Numerical experiments were carried out and the results compared with the theoretical or exact solution and the algorithm was later coded using MATLAB programming language.

Keywords: Differential equations, Numerical, Initial value problem, Polynomials.

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Authors: Dariush Semnani, Javad Yekrang, Hossein Ghayoor

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Concerning the measurement of friction properties of textiles and fabrics using Kawabata Evaluation System (KES), whose output is constrained to the surface friction factor of fabric, and no other data would be generated; this research has been conducted to gain information about surface roughness regarding its surface friction factor. To assess roughness properties of light nonwovens, a 3-dimensional model of a surface has been simulated with regular sinuous waves through it as an ideal surface. A new factor was defined, namely Surface Roughness Factor, through comparing roughness properties of simulated surface and real specimens. The relation between the proposed factor and friction factor of specimens has been analyzed by regression, and results showed a meaningful correlation between them. It can be inferred that the new presented factor can be used as an acceptable criterion for evaluating the roughness properties of light nonwoven fabrics.

Keywords: Surface roughness, Nonwoven, Machine vision, Image processing.

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Authors: Igor Belykh

Abstract:

Anti-scatter grids used in radiographic imaging for the contrast enhancement leave specific artifacts. Those artifacts may be visible or may cause Moiré effect when digital image is resized on a diagnostic monitor. In this paper we propose an automated grid artifactsdetection and suppression algorithm which is still an actual problem. Grid artifacts detection is based on statistical approach in spatial domain. Grid artifacts suppression is based on Kaiser bandstop filter transfer function design and application avoiding ringing artifacts. Experimental results are discussed and concluded with description of advantages over existing approaches.

Keywords: Computed radiography, grid artifacts, image filtering.

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Authors: Jai Raj, Jito Vanualailai, Bibhya Sharma, Shonal Singh

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This paper proposes a solution to the motion planning and control problem of car-like mobile robots which is required to move safely to a designated target in a priori known workspace cluttered with swarm of boids exhibiting collective emergent behaviors. A generalized algorithm for target convergence and swarm avoidance is proposed that will work for any number of swarms. The control laws proposed in this paper also ensures practical stability of the system. The effectiveness of the proposed control laws are demonstrated via computer simulations of an emergent behavior.

Keywords: Swarm, practical stability, motion planning, emergent.

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Authors: Hataitep Wongsuwarn, Djitt Laowattana

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This paper summaries basic principles and concepts of intelligent controls, implemented in humanoid robotics as well as recent algorithms being devised for advanced control of humanoid robots. Secondly, this paper presents a new approach neuro-fuzzy system. We have included some simulating results from our computational intelligence technique that will be applied to our humanoid robot. Subsequently, we determine a relationship between joint trajectories and located forces on robot-s foot through a proposed neuro-fuzzy technique.

Keywords: Biped Robot, Computational Intelligence, Static and Dynamic Walking, Gait Synthesis, Neuro-Fuzzy System.

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Authors: G. Tamilpavai, C. Vishnuppriya

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Studying DNA (deoxyribonucleic acid) sequence is useful in biological processes and it is applied in the fields such as diagnostic and forensic research. DNA is the hereditary information in human and almost all other organisms. It is passed to their generations. Earlier stage detection of defective DNA sequence may lead to many developments in the field of Bioinformatics. Nowadays various tedious techniques are used to identify defective DNA. The proposed work is to analyze and identify the cancer-causing DNA motif in a given sequence. Initially the human DNA sequence is separated as k-mers using k-mer separation rule. The separated k-mers are clustered using Self Organizing Map (SOM). Using Levenshtein distance measure, cancer associated DNA motif is identified from the k-mer clusters. Experimental results of this work indicate the presence or absence of cancer causing DNA motif. If the cancer associated DNA motif is found in DNA, it is declared as the cancer disease causing DNA sequence. Otherwise the input human DNA is declared as normal sequence. Finally, elapsed time is calculated for finding the presence of cancer causing DNA motif using clustering formation. It is compared with normal process of finding cancer causing DNA motif. Locating cancer associated motif is easier in cluster formation process than the other one. The proposed work will be an initiative aid for finding genetic disease related research.

Keywords: Bioinformatics, cancer motif, DNA, k-mers, Levenshtein distance, SOM.

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Authors: Huey-Kuo Chen

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Travel demand forecasting including four travel choices, i.e., trip generation, trip distribution, modal split and traffic assignment constructs the core of transportation planning. In its current application, travel demand forecasting has associated with three important issues, i.e., interface inconsistencies among four travel choices, inefficiency of commonly used solution algorithms, and undesirable multiple path solutions. In this paper, each of the three issues is extensively elaborated. An ideal unified framework for the combined model consisting of the four travel choices and variable demand functions is also suggested. Then, a few remarks are provided in the end of the paper

Keywords: Travel choices, B algorithm, entropy maximization, dynamic traffic assignment.

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Authors: D. Fodorean, D.C. Popa, F. Jurca, M. Ruba

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the paper presents the optimization results for several electrical machines dedicated for powered electric wheel-chairs. The optimization, using the Hook-Jeeves algorithm, was employed based on a design approach which takes into consideration the road conditions. Also, through numerical simulations (based on finite element method), the analytical approach was validated. The optimization approach gave satisfactory results and the best suited variant was chosen for the motorization of the wheel-chair.

Keywords: electrical machines, numerical validation, optimization, electric wheel chair.

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Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

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Performance of different filtering approaches depends on modeling of dynamical system and algorithm structure. For modeling and smoothing the data the evaluation of posterior distribution in different filtering approach should be chosen carefully. In this paper different filtering approaches like filter KALMAN, EKF, UKF, EKS and smoother RTS is simulated in some trajectory tracking of path and accuracy and limitation of these approaches are explained. Then probability of model with different filters is compered and finally the effect of the noise variance to estimation is described with simulations results.

Keywords: Gaussian approximation, KALMAN smoother, Parameter estimation.

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Authors: Alexander Dao, Oscar Wambuguh

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Irritable Bowel Syndrome (IBS) is a heterogeneous functional bowel disease that is characterized by chronic visceral abdominal pain and abnormal bowel function and habits. Its multifactorial pathophysiology and mechanisms are still largely a mystery to the contemporary biomedical community, although there are many hypotheses to try to explain IBS’s presumed physiological, psychosocial, genetic, and environmental etiologies. IBS’s symptomatic presentation is varied and divided into four major subtypes: IBS-C, IBS-D, IBS-M, and IBS-U. Given its diverse presentation and unclear mechanisms, diagnosis is done through a combination of positive identification utilizing the “Rome IV Irritable Bowel Syndrome Criteria'' (Rome IV) diagnostic criteria while also excluding other potential conditions with similar symptoms. Treatment of IBS is focused on the management of symptoms using an assortment of pharmaceuticals, lifestyle changes, and dietary changes, with future potential in microbial treatment and psychotherapy as other therapy methods. Its chronic, heterogeneous nature and disruptive gastrointestinal (GI) symptoms are negatively impactful on patients’ daily lives, health systems, and society. However, with a better understanding of the gaps in knowledge and technological advances in IBS’s pathophysiology, management, and treatment options, there is optimism for the millions of people worldwide who are suffering from the debilitating effects of IBS.

Keywords: Irritable bowel syndrome, lifestyle, diet, functional gastrointestinal disorder.

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Authors: Hassan E. A. Ibrahim, Mohamed F. Serag

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In this paper, Novel method, Particle Swarm Optimization (PSO) algorithm, based technique is proposed to estimate and analyze the steady state performance of self-excited induction generator (SEIG). In this novel method the tedious job of deriving the complex coefficients of a polynomial equation and solving it, as in previous methods, is not required. By comparing the simulation results obtained by the proposed method with those obtained by the well known mathematical methods, a good agreement between these results is obtained. The comparison validates the effectiveness of the proposed technique.

Keywords: Evolution theory, MATLAB, optimization, PSO, SEIG.

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Authors: Raghav Lakhotia, Sameer Ganu, Anshul Goel, Abhishek Kumar

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In the age and times where women’s empowerment is a significant topic of discussion, we aim to analyze the potential gender diversity influence on box office revenues. The following research is carried out by collecting data from 400 Hollywood movies between the years 2014-2017 and performing regression analysis to find a correlation between the presence of female characters in movies and their return on investment (ROI). The paper finds that there is a positive relationship between the performance of the movies (its ROI) and the gender diversity i.e. the more the number of female characters, the higher the revenue generated. Another factor such as Number of Votes also has a direct impact on the revenue of the movie. The research not only takes into consideration the mere presence of women on screen but also the exchange of at least one dialogue among themselves, which is presented by the Bechdel Score of the movie.

Keywords: Bechdel, diversity, Hollywood, return on investment.

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Authors: Y. W. Chen, H. L. Fan

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Evidence shows that start-ups success is positively correlated with the launch of the first product. However, new ventures are seldom able to acquire abundant resources for new product development (NPD), which means that entrepreneurs may depend on personal creativity instead of physical investments to achieve and accelerate innovation speed. This study accentuates the role of entrepreneurial bricolage, which defined as making do by applying combinations of the resources at hand to new problems and opportunities, in the relations of creative self-efficacy and innovation speed. This study uses the multiple regression analysis to test the hypotheses in a sample of 203 start-ups operating in various creative markets in Taiwan. Results reveal that creative self-efficacy is positively and directly associated with innovation speed, whereas entrepreneurial bricolage plays a full mediator. These findings offer important theoretical and practical implications.

Keywords: Creative self-efficacy, innovation speed, entrepreneurial bricolage, new ventures.

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Authors: Xiaoou Li, Wen Yu

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Crude oil blending is an important unit operation in petroleum refining industry. A good model for the blending system is beneficial for supervision operation, prediction of the export petroleum quality and realizing model-based optimal control. Since the blending cannot follow the ideal mixing rule in practice, we propose a static neural network to approximate the blending properties. By the dead-zone approach, we propose a new robust learning algorithm and give theoretical analysis. Real data of crude oil blending is applied to illustrate the neuro modeling approach.

Keywords: Neural networks, modeling, stability, crude oil.

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Authors: Yahia I. Mohamed, Ahmed I. Marzouk, Mohamed A. Yacout

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Aim of this work was to study the genetic basis for oil accumulation in olive fruit via tracking DGAT2 (Diacylglycerol acyltransferase type-2) gene in three Egyptian Origen Olive cultivars namely Toffahi, Hamed and Maraki using molecular marker techniques and bioinformatics tools. Results illustrate that, firstly: specific genomic band of Maraki cultivars was identified as DGAT2 (Diacylglycerol acyltransferase type-2) and identical for this gene in Olea europaea with 100% of similarity. Secondly, differential genomic band of Maraki cultivars which produced from RAPD fingerprinting technique reflected predicted distinguished sequence which identified as DGAT2 (Diacylglycerol acyltransferase type-2) in Fragaria vesca subsp. Vesca with 76% of sequential similarity. Third and finally, specific genomic specific band of Hamed cultivars was identified as two fragments, 1- Olea europaea cultivar Koroneiki diacylglycerol acyltransferase type 2 mRNA, complete cds with two matches regions with 99% or 2- Predicted: Fragaria vesca subsp. vesca diacylglycerol O-acyltransferase 2-like (LOC101313050), mRNA with 86 % of similarity.

Keywords: Olea europaea, fingerprinting, Diacylglycerol acyltransferase type- 2 (DGAT2).

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Authors: Radouane Iqdour, Abdelouhab Zeroual

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The Multi-Layered Perceptron (MLP) Neural networks have been very successful in a number of signal processing applications. In this work we have studied the possibilities and the met difficulties in the application of the MLP neural networks for the prediction of daily solar radiation data. We have used the Polack-Ribière algorithm for training the neural networks. A comparison, in term of the statistical indicators, with a linear model most used in literature, is also performed, and the obtained results show that the neural networks are more efficient and gave the best results.

Keywords: Daily solar radiation, Prediction, MLP neural networks, linear model

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Authors: Sayantan Khanra, Rojers P. Joseph

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This study attempts to analyze the impact of demography and service quality on the adoption and diffusion of e-Government services in the context of India. The objective of this paper is to study the users' perception about e-Government services and investigate the key variables that are most salient to the Indian populace. At the completion of this study, a research model that would help to understand the relationship involving the demographic variables and service quality dimensions, and the willingness to adopt e-Government services is expected to be developed. Dedicated authorities, particularly those in developing economies, may use that model or its augmented versions to design and update e-Government services and promote their use among citizens. After all, enhanced public participation is required to improve efficiency, engagement and transparency in the implementation of the aforementioned services.

Keywords: Adoption and diffusion of e-Government services, demographic variables, hierarchical regression analysis, service quality dimensions.

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