Search results for: Random Forest Regression

Authors: Sabrina Gaito, Andrea Greppi, Giuliano Grossi

Abstract:

In this paper we present a technique to speed up ICA based on the idea of reducing the dimensionality of the data set preserving the quality of the results. In particular we refer to FastICA algorithm which uses the Kurtosis as statistical property to be maximized. By performing a particular Johnson-Lindenstrauss like projection of the data set, we find the minimum dimensionality reduction rate ¤ü, defined as the ratio between the size k of the reduced space and the original one d, which guarantees a narrow confidence interval of such estimator with high confidence level. The derived dimensionality reduction rate depends on a system control parameter β easily computed a priori on the basis of the observations only. Extensive simulations have been done on different sets of real world signals. They show that actually the dimensionality reduction is very high, it preserves the quality of the decomposition and impressively speeds up FastICA. On the other hand, a set of signals, on which the estimated reduction rate is greater than 1, exhibits bad decomposition results if reduced, thus validating the reliability of the parameter β. We are confident that our method will lead to a better approach to real time applications.

Keywords: Independent Component Analysis, FastICA algorithm, Higher-order statistics, Johnson-Lindenstrauss lemma.

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Authors: Z. Sakka, I. Assakkaf, T. Al-Yaqoub, J. Parol

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reliability-based methodology for the assessment and evaluation of reinforced concrete (R/C) structural elements of concrete structures is presented herein. The results of the reliability analysis and assessment for R/C structural elements were verified by the results obtained through deterministic methods. The outcomes of the reliability-based analysis were compared against currently adopted safety limits that are incorporated in the reliability indices β’s, according to international standards and codes. The methodology is based on probabilistic analysis using reliability concepts and statistics of the main random variables that are relevant to the subject matter, and for which they are to be used in the performance-function equation(s) associated with the structural elements under study. These methodology techniques can result in reliability index β, which is commonly known as the reliability index or reliability measure value that can be utilized to assess and evaluate the safety, human risk, and functionality of the structural component. Also, these methods can result in revised partial safety factor values for certain target reliability indices that can be used for the purpose of redesigning the R/C elements of the building and in which they could assist in considering some other remedial actions to improve the safety and functionality of the member.

Keywords: Concrete Structures, FORM, Monte Carlo Simulation, Structural Reliability.

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Authors: Ying-Han Pang, Andrew Teoh Beng Jin, David Ngo Chek Ling

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A cancelable palmprint authentication system proposed in this paper is specifically designed to overcome the limitations of the contemporary biometric authentication system. In this proposed system, Geometric and pseudo Zernike moments are employed as feature extractors to transform palmprint image into a lower dimensional compact feature representation. Before moment computation, wavelet transform is adopted to decompose palmprint image into lower resolution and dimensional frequency subbands. This reduces the computational load of moment calculation drastically. The generated wavelet-moment based feature representation is used to generate cancelable verification key with a set of random data. This private binary key can be canceled and replaced. Besides that, this key also possesses high data capture offset tolerance, with highly correlated bit strings for intra-class population. This property allows a clear separation of the genuine and imposter populations, as well as zero Equal Error Rate achievement, which is hardly gained in the conventional biometric based authentication system.

Keywords: Cancelable biometric authenticator, Discrete- Hashing, Moments, Palmprint.

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Authors: L. Mirtskhulava, M. Khunjgurua, N. Lomineishvili, K. Bakuria

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Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.

Keywords: Exponential distribution, conditional mean time to failure, distribution function, mathematical model, software reliability.

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Authors: César Garza

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In supervised binary classification and regression problems, it is well-known that learnability is equivalent to uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.

Keywords: Statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization.

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Authors: Laura Sapranaviciute-Zabazlajeva, Abdonas Tamosiunas, Dalia Luksiene, Dalia Virviciute

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The cardiovascular diseases (CVD) is the leading cause of death in the EU, especially in the middle aged and elderly population. Psychological wellbeing (PWB) has been linked with better cardiovascular health and survival in the elderly. The aim of the study is to evaluate associations between CVD risk and PWB in middle-aged and elderly population. 10,940 middle aged and older Lithuanians of age 45-74 years, were invited to participate in the study. A study sample was a random and stratified by gender and age. In 2006-2008 7,087 responders participated in the survey, so the response rate was 64.8%. A follow-up study was conducted from 2006 till 2015. New CVD cases and deaths from CVD were evaluated using the Kaunas population-based CVD register and death register of Kaunas. Study results revealed that good PWB predicts longer life in female participants (Log Rank = 13.7, p < 0.001). In the fully adjusted model for socio-demographic, social and CVD risk factors, hazard ratio for CVD mortality risk was lower amongst women with good PWB (HR = 0.28, 95% CI 0.11-0.72), but not significantly for men. Our study concludes, that lower CVD mortality rates is being associated with better PWB in female aged 45-74 years.

Keywords: Psychological wellbeing, cardiovascular disease, elderly.

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Authors: Sofia Stoica

Abstract:

In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices over the past five years of 10 major tech companies: Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We implemented and tested three models – a linear regressor model, a k-nearest neighbor model (KNN), and a sequential neural network – and two algorithms – Multiplicative Weight Update and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: Finance, machine learning, opening price, stock market.

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Authors: Dilavar Khan, Z. Ahmad

Abstract:

Riprap is mostly used to prevent erosion by flows down the steep slopes in river engineering. A total of 53 stability tests performed on angular riprap with a median stone size ranging from 15 to 278 mm and slope ranging from 1 to 40% are used in this study. The existing equations for the prediction of medium size of angular stones are checked for their accuracy using the available data. Predictions of median size using these equations are not satisfactory and results show deviation by more than ±20% from the observed values. A multivariable power regression analysis is performed to propose a new equation relating the median size with unit discharge, bed slope, riprap thickness and coefficient of uniformity. The proposed relationship satisfactorily predicts the median angular stone size with ±20% error. Further, the required size of the rounded stone is more than the angular stone for the same unit discharge and the ratio increases with unit discharge and also with embankment slope of the riprap.

Keywords: Angularity, Gradation, Riprap, Stabilization

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: Data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data.

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Authors: Oscar Javier Herrera, Manuel Ángel Camacho

Abstract:

This paper addresses a cutting edge method of business demand forecasting, based on an empirical probability function when the historical behavior of the data is random. Additionally, it presents error determination based on the numerical method technique ‘propagation of errors.’ The methodology was conducted characterization and process diagnostics demand planning as part of the production management, then new ways to predict its value through techniques of probability and to calculate their mistake investigated, it was tools used numerical methods. All this based on the behavior of the data. This analysis was determined considering the specific business circumstances of a company in the sector of communications, located in the city of Bogota, Colombia. In conclusion, using this application it was possible to obtain the adequate stock of the products required by the company to provide its services, helping the company reduce its service time, increase the client satisfaction rate, reduce stock which has not been in rotation for a long time, code its inventory, and plan reorder points for the replenishment of stock.

Keywords: Demand Forecasting, Empirical Distribution, Propagation of Error.

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Authors: R. P. Mahapatra, Jitendra Singh

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This paper proposes a new technique for improving the efficiency of software testing, which is based on a conventional attempt to reduce test cases that have to be tested for any given software. The approach utilizes the advantage of Regression Testing where fewer test cases would lessen time consumption of the testing as a whole. The technique also offers a means to perform test case generation automatically. Compared to one of the techniques in the literature where the tester has no option but to perform the test case generation manually, the proposed technique provides a better option. As for the test cases reduction, the technique uses simple algebraic conditions to assign fixed values to variables (Maximum, minimum and constant variables). By doing this, the variables values would be limited within a definite range, resulting in fewer numbers of possible test cases to process. The technique can also be used in program loops and arrays.

Keywords: Software Testing, Test Case Generation, Test CaseReduction

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Authors: Maryam Hsaini, Mostafa Nouri-Baygi

Abstract:

A critical problem in wireless sensor networks is limited battery and memory of nodes. Therefore, each node in the network could maintain only a subset of its neighbors to communicate with. This will increase the battery usage in the network because each packet should take more hops to reach its destination. In order to tackle these problems, spanner graphs are defined. Since each node has a small degree in a spanner graph and the distance in the graph is not much greater than its actual geographical distance, spanner graphs are suitable candidates to be used for the topology of a wireless sensor network. In this paper, we study Yao graphs and their behavior for a randomly selected set of points. We generate several random point sets and compare the properties of their Yao graphs with the complete graph. Based on our data sets, we obtain several charts demonstrating how Yao graphs behave for a set of randomly chosen point set. As the results show, the stretch factor of a Yao graph follows a normal distribution. Furthermore, the stretch factor is in average far less than the worst case stretch factor proved for Yao graphs in previous results. Furthermore, we use Yao graph for a realistic point set and study its stretch factor in real world.

Keywords: Wireless sensor network, spanner graph, Yao Graph.

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Authors: Yalçın Ozdemir

Abstract:

The purpose of this study was to examine to what extend classroom management efficacy, marital status, gender, and teaching experience predict burnout among primary school teachers. Participants of this study were 523 (345 female, 178 male) teachers who completed inventories. The results of multiple regression analysis indicated that three dimensions of teacher burnout (Emotional Exhaustion, Depersonalization, Personal Accomplishment) were affected differently from four predictor variables. Findings indicated that for the emotional exhaustion, classroom management efficacy, marital status and teaching experience; for depersonalization dimension, classroom management efficacy and marital status and finally for the personal accomplishment dimension, classroom management efficacy, gender, and teaching experience were significant predictors.

Keywords: Classroom management efficacy, teacher burnout.

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Authors: Roza Afarin, Saeed Mozaffari

Abstract:

The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: Correlation coefficients, Genetic algorithm, Image encryption, Image entropy.

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Authors: Kaushalendra K. Khadanga, Lee Hee Hyol

Abstract:

Passenger comfort has been paramount in the design of suspension systems of high speed cars. To analyze the effect of vibration on vehicle ride quality, a vertical model of a six degree of freedom railway passenger vehicle, with front and rear suspension, is built. It includes car body flexible effects and vertical rigid modes. A second order linear shaping filter is constructed to model Gaussian white noise into random rail excitation. The temporal correlation between the front and rear wheels is given by a second order Pade approximation. The complete track and the vehicle model are then designed. An active secondary suspension system based on a Linear Quadratic Gaussian (LQG) optimal control method is designed. The results show that the LQG control method reduces the vertical acceleration, pitching acceleration and vertical bending vibration of the car body as compared to the passive system.

Keywords: Active suspension, bending vibration, railway vehicle, vibration control.

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Authors: Mohammad Reza Karami Nejad

Abstract:

A hybrid learning automata-genetic algorithm (HLGA) is proposed to solve QoS routing optimization problem of next generation networks. The algorithm complements the advantages of the learning Automato Algorithm(LA) and Genetic Algorithm(GA). It firstly uses the good global search capability of LA to generate initial population needed by GA, then it uses GA to improve the Quality of Service(QoS) and acquiring the optimization tree through new algorithms for crossover and mutation operators which are an NP-Complete problem. In the proposed algorithm, the connectivity matrix of edges is used for genotype representation. Some novel heuristics are also proposed for mutation, crossover, and creation of random individuals. We evaluate the performance and efficiency of the proposed HLGA-based algorithm in comparison with other existing heuristic and GA-based algorithms by the result of simulation. Simulation results demonstrate that this paper proposed algorithm not only has the fast calculating speed and high accuracy but also can improve the efficiency in Next Generation Networks QoS routing. The proposed algorithm has overcome all of the previous algorithms in the literature.

Keywords: Routing, Quality of Service, Multicaset, Learning Automata, Genetic, Next Generation Networks.

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Authors: Javed Ahmed, M. N. Jafri, J. Ahmad, Muhammad I. Khan

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Real-time object tracking is a problem which involves extraction of critical information from complex and uncertain imagedata. In this paper, we present a comprehensive methodology to design an artificial neural network (ANN) for a real-time object tracking application. The object, which is tracked for the purpose of demonstration, is a specific airplane. However, the proposed ANN can be trained to track any other object of interest. The ANN has been simulated and tested on the training and testing datasets, as well as on a real-time streaming video. The tracking error is analyzed with post-regression analysis tool, which finds the correlation among the calculated coordinates and the correct coordinates of the object in the image. The encouraging results from the computer simulation and analysis show that the proposed ANN architecture is a good candidate solution to a real-time object tracking problem.

Keywords: Image processing, machine vision, neural networks, real-time object tracking.

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Authors: Betül Özgenç Kaya, Soner Kuslu, Sabri Çolak, Turan Çalban

Abstract:

Ulexite (Na2O.2CaO.5B2O3.16H2O) is boron mineral that is found in large quantities in the Turkey and world. In this study, the dissolution of this mineral in the disodium hydrogen phosphate solutions has been studied. Temperature, concentration, stirring speed, solid liquid ratio and particle size were selected as parameters. The experimental results were successfully correlated by linear regression using Statistica program. Dissolution curves were evaluated shrinking core models for solid-fluid systems. It was observed that increase in the reaction temperature and decrease in the solid/liquid ratio causes an increase the dissolution rate of ulexite. The activation energy was found to be 63.4 kJ/mol. The leaching of ulexite was controlled by chemical reaction.

Keywords: Disodium hydrogen phosphate, Leaching kinetics, Ulexite.

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Authors: Chengxuan Geng, Haitao E, Yijie Jiang

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According to the theory of capital structure, this paper uses principal component analysis and linear regression analysis to study the relationship between the debt characteristics of the private listed companies in Jiangsu Province and their business performance. The results show that the average debt ratio of the 29 private listed companies selected from the sample is lower. And it is found that for the sample whose debt ratio is lower than 80%, its debt ratio is negatively related to corporate performance, while for the sample whose debt ratio is beyond 80%, the relationship of debt financing and enterprise performance shows the different trends. The conclusions reflect the drawbacks may exist that the debt ratio is relatively low and having not take full advantage of debt governance effect of the private listed companies in Jiangsu Province.

Keywords: private listed companies, debt financing, business performance

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Authors: Noor A. Auzairy, Rubi Ahmad, Catherine S.F. Ho, Ros Z. Z. Sapian

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This paper is to explore the relationship and the level of stock market integration of the Asian countries, primarily concentrating on Malaysia, Thailand, Indonesia, and South Korea, with the world from January 1997 to December 2009. The degree of short-run and long-run stock market integration of those Asian countries are analyzed in order to determine the significance of series of regional and world financial crises, liberalization policies and other financial reforms in influencing the level of stock market integration. To test for cointegration, this paper applies coefficient correlation, univariate regression analyses, cointegration tests, and vector autoregressive models (VAR) by using the four Asian stock markets main indices and the MSCI World index. The empirical findings from this work reveal that there is no long-run stock market integration for the four countries and the world market. However, there is short run integration.

Keywords: Asia, integration, relationship, stock market.

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Authors: Prateep Wajeetongratana

Abstract:

The purpose of this research was to study the influence of learning efficiency on local accountants’ job performance effectiveness. This paper drew upon the survey data collected from 335 local accountants survey conducted at Nakhon Ratchasima province, Thailand. The statistics utilized in this paper included percentage, mean, standard deviation, and regression analysis. The findings revealed that the majority of samples were between 31-40 years old, married, held an undergraduate degree, and had an average income between 10,000-15,000 baht. The majority of respondents had less than five years of accounting experience and worked for local administrations. The overall learning efficiency score was in the highest level while the local accountants’ job performance effectiveness score was also in the high level. The hypothesis testing’s result disclosed that learning efficiency factors which were knowledge, Skill, and Attitude had an influence on local accountants’ job the performance effectiveness.

Keywords: Accountants, Leaning Efficiency, Performance Effectiveness.

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Authors: Mei L. Lin, Pi-Yueh Cheng

Abstract:

Classes on creativity, innovation, and entrepreneurship are becoming quite popular at universities throughout the world. However, it is not easy for business students to get involved to innovative activities, especially patent application. The present study investigated how to enhance business students- intention to participate in innovative activities and which incentives universities should consider. A 22-item research scale was used, and confirmatory factor analysis was conducted to verify its reliability and validity. Multiple regression and discriminant analyses were also conducted. The results demonstrate the effect of growth-need strength on innovative behavior and indicate that the theory of planned behavior can explain and predict business students- intention to participate in innovative activities. Additionally, the results suggest that applying our proposed model in practice would effectively strengthen business students- intentions to engage in innovative activities.

Keywords: discriminant analysis, growth need strength, innovative behavior, TPB model

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Authors: Divya Agarwal, Pushpendra S. Bharti

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Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc.

Keywords: Autonomous mobile robots, obstacle avoidance, path planning, and processing time.

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Authors: A. A. Betah

Abstract:

This research was performed to evaluate the attitudes of rural women towards education, health and work outside the home. The study was based on a random sample of 147 rural women, Kafr-Rahmaniyah village was chosen for the study because its life expectancy at birth for females, education and percentage of females in the labor force, were the highest in the district. The study data were collected from rural female respondents, using a face-to-face questionnaire. In addition, the study estimated several factors like age, main occupation, family size, monthly household income, geographic cosmopolites, and degree of social participation for rural women respondents. Using Statistical Package for the Social Sciences (SPSS), data were analyzed by non-parametric statistical methods. The main finding in this study was a significant relationship between each of the previous variables and each of rural women’s attitudes toward education, health, and work outside home. The study concluded with some recommendations. The most important element is ensuring attention to rural women’s needs, requirements and rights via raising their health awareness, education and their contributions in their society.

Keywords: Attitudes, education, health, rural women, work outside the home.

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Authors: Alireza Ghasemizad

Abstract:

In Both developed and developing countries, governments play a basic role in making policies, programs and instruments which support the development of micro, small and medium enterprises. One of the mechanisms employed to nurture small firms for more than two decades is business incubation. One of the mechanisms employed to nurture small firms for more than two decades is technology business incubation. The main aim of this research was to establish influencing factors in Technology Business Incubator's effectiveness and their explanatory model. Therefore, among 56 Technology Business Incubators in Iran, 32 active incubators were selected and by stratified random sampling, 528 start-ups were chosen. The validity of research questionnaires was determines by expert consensus, item analysis and factor analysis; and their reliability calculated by Cronbach-s alpha. Data analysis was then made through SPSS and LISREL soft wares. Both organizational procedures and entrepreneurial behaviors were the meaningful mediators. Organizational procedures with (P < .01, β =0.45) was stronger mediator for the improvement of Technology Business Incubator's effectiveness comparing to entrepreneurial behavior with (P < .01, β =0.36).

Keywords: Technology, Incubators, Effectiveness, Explanatorymodel.

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Authors: V.K. Mukhomorov

Abstract:

The solvated electron is self-trapped (polaron) owing to strong interaction with the quantum polarization field. If the electron and quantum field are strongly coupled then the collective localized state of the field and quasi-particle is formed. In such a formation the electron motion is rather intricate. On the one hand the electron oscillated within a rather deep polarization potential well and undergoes the optical transitions, and on the other, it moves together with the center of inertia of the system and participates in the thermal random walk. The problem is to separate these motions correctly, rigorously taking into account the conservation laws. This can be conveniently done using Bogolyubov-Tyablikov method of canonical transformation to the collective coordinates. This transformation removes the translational degeneracy and allows one to develop the successive approximation algorithm for the energy and wave function while simultaneously fulfilling the law of conservation of total momentum of the system. The resulting equations determine the electron transitions and depend explicitly on the translational velocity of the quasi-particle as whole. The frequency of optical transition is calculated for the solvated electron in ammonia, and an estimate is made for the thermal-induced spectral bandwidth.

Keywords: Canonical transformations, solvated electron, width of the optical spectrum.

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Authors: Jianyin Lu, Masayoshi Seike, Wei Liu, Peihong Wu, Lihua Wang, Yihua Wu, Yasuhiro Naito, Hiromu Nakajima, Yasuhiro Kouchi

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To extract the important physiological factors related to diabetes from an oral glucose tolerance test (OGTT) by mathematical modeling, highly informative but convenient protocols are required. Current models require a large number of samples and extended period of testing, which is not practical for daily use. The purpose of this study is to make model assessments possible even from a reduced number of samples taken over a relatively short period. For this purpose, test values were extrapolated using a support vector machine. A good correlation was found between reference and extrapolated values in evaluated 741 OGTTs. This result indicates that a reduction in the number of clinical test is possible through a computational approach.

Keywords: SVM regression, OGTT, diabetes, mathematical model

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Authors: Jana Aleksić, Marijana Petković

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Female population has an increasing role when it comes to purchase. Consequently, the female population has a greater role in modern marketing. Although it is thought that women buy more than men, marketing strategy was not directed specifically towards women. The thing that has changed regarding women’s role in modern marketing is the fact that the female population has a leading position when it comes to decision making in various fields and various sectors, which was not the case in the past. Marketing should be directed towards women but it should be done in the right way. Compared to men, women buy in a different way, and they look for more various advantages in the product itself, than men do. This paper aims to show the importance of the female role in the modern marketing and management and to redirect marketing in some way towards female population through new marketing strategies and management systems. Hypothesis is that women have an important role in marketing, and marketing strategy of modern society could and should be based on and directed towards female population and their tastes when it comes to purchasing. It is necessary and desirable to apply marketing strategy with a special strategy that has an emphasis on women and their purchase or in a word to apply WS- woman strategy. This research was carried out as a random sample research, where were obtained 212 valid surveys whose results serve as a basis for drawing conclusions about the research as well as to verify the formulated hypotheses. The research was carried out during 2011 and 2012. The study has shown a significant role of the female population in the marketing process.

Keywords: Marketing, management, female, purchase, strategy.

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Authors: Mohammed B. Abohedma, Milad M. Alshebani

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Recent trends in building constructions in Libya are more toward tall (high-rise) building projects. As a consequence, a better estimation of the lateral loading in the design process is becoming the focal of a safe and cost effective building industry. Byin- large, Libya is not considered a potential earthquake prone zone, making wind is the dominant design lateral loads. Current design practice in the country estimates wind speeds on a mere random bases by considering certain factor of safety to the chosen wind speed. Therefore, a need for a more accurate estimation of wind speeds in Libya was the motivation behind this study. Records of wind speed data were collected from 22 metrological stations in Libya, and were statistically analysed. The analysis of more than four decades of wind speed records suggests that the country can be divided into four zones of distinct wind speeds. A computer “survey" program was manipulated to draw design wind speeds contour map for the state of Libya. The paper presents the statistical analysis of Libya-s recorded wind speed data and proposes design wind speed values for a 50-year return period that covers the entire country.

Keywords: Ccontour map, return period, wind speed, and zone.

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Authors: Sheila Marie G. Hocson

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One of the vital developmental tasks that an individual faces during adolescence is choosing a career. Arriving at a career decision is difficult and anxious for many adolescents in the tertiary level. The main purpose of this study is to determine the factors relating to career indecision among freshmen college students as basis for the formulation of a comprehensive career counseling program for the psychological well-being of freshmen university students. The subjects were purposively selected. The Slovin-s formula was used in determining the sample size, using a 0.05 margin of error in getting the total number of samples per college and per major. The researcher made use of descriptive correlational study in determining significant factors relating to career indecision. Multiple Regression Analysis indicated that career thoughts, career decisions and vocational identity as factors related to career indecision.

Keywords: career decisions, career guidance program, career thoughts, vocational identity

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