Search results for: independent variables

Authors: Siti Kudnie Sahari, Jane Chai Hai Sing, Khairuddin Ab. Hamid

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Shrunken patterning for integrated device manufacturing requires surface cleanliness and surface smoothness in wet chemical processing [1]. It is necessary to control all process parameters perfectly especially for the common cleaning technique RCA clean (SC-1 and SC-2) [2]. In this paper the characteristic and effect of surface preparation parameters are discussed. The properties of RCA wet chemical processing in silicon technology is based on processing time, temperature, concentration and megasonic power of SC-1 and QDR. An improvement of wafer surface preparation by the enhanced variables of the wet cleaning chemical process is proposed.

Keywords: RCA, SC-1, SC-2, QDR

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Authors: Zhidong Zhang, Zhi-Chao Zhang

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This study examined the mental health and behavioral problems in early adolescence with the instrument of Achenbach System of Empirically Based Assessment (ASEBA). The purpose of the study was stratified sampling method was used to collect data from 1975 participants. Multiple regression models and hierarchical regression models were applied to examine the relations between the background variables and internalizing problems, and the ones between students’ performance and internalizing problems. The results indicated that several background variables as predictors could significantly predict the anxious/depressed problem; reading and social study scores could significantly predict the anxious/depressed problem. However the class as a hierarchical macro factor did not indicate the significant effect. In brief, the majority of these models represented that the background variables, behaviors and academic performance were significantly related to the anxious/depressed problem.

Keywords: Behavioral problems, anxious/depression problems, empirical-based assessment, hierarchical modeling.

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Authors: Rafik Djemili, Mouldi Bedda, Hocine Bourouba

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This paper proposes a novel approach that combines statistical models and support vector machines. A hybrid scheme which appropriately incorporates the advantages of both the generative and discriminant model paradigms is described and evaluated. Support vector machines (SVMs) are trained to divide the whole speakers' space into small subsets of speakers within a hierarchical tree structure. During testing a speech token is assigned to its corresponding group and evaluation using gaussian mixture models (GMMs) is then processed. Experimental results show that the proposed method can significantly improve the performance of text independent speaker identification task. We report improvements of up to 50% reduction in identification error rate compared to the baseline statistical model.

Keywords: Speaker identification, Gaussian mixture model (GMM), support vector machine (SVM), hybrid GMM/SVM.

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Authors: Fethi Soltani, Adel Almarashi, Idir Mechai

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Tikhonov regularization and reproducing kernels are the most popular approaches to solve ill-posed problems in computational mathematics and applications. And the Fourier multiplier operators are an essential tool to extend some known linear transforms in Euclidean Fourier analysis, as: Weierstrass transform, Poisson integral, Hilbert transform, Riesz transforms, Bochner-Riesz mean operators, partial Fourier integral, Riesz potential, Bessel potential, etc. Using the theory of reproducing kernels, we construct a simple and efficient representations for some class of Fourier multiplier operators Tm on the Paley-Wiener space Hh. In addition, we give an error estimate formula for the approximation and obtain some convergence results as the parameters and the independent variables approaches zero. Furthermore, using numerical quadrature integration rules to compute single and multiple integrals, we give numerical examples and we write explicitly the extremal function and the corresponding Fourier multiplier operators.

Keywords: Fourier multiplier operators, Gauss-Kronrod method of integration, Paley-Wiener space, Tikhonov regularization.

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Authors: Jianlin Li, Jizhen Li

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Transnational corporations (TNCs) are playing a major role in global R&D, not only through activities in their home countries but also increasingly abroad. However, the process of R&D offshoring is not yet discussed thoroughly. Based on in-depth case study on Agilent China Communications Operation, this paper presents a stage model for theorizing the R&D offshoring process. This stage model outlines 5 maturity levels of organization and the offshoring process: Subsidiary team, Mirror team, Independent team, Mirror sector and the Independent sector (from software engineering point of view, it is similar to the local team's capability level of maturity model). Moreover, the paper gives a detailed discussion on the relevant characteristics, as well as the ability/responsibility of transfer, priorities and the corresponding organization structure. It also gives the characteristics and key points of different level-s R&D offshoring implementation using actual team practice.

Keywords: Internationalization of R&D, R&D offshoring process, Multinational Corporations, Organization Level.

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Authors: Bahadur Singh Hathan, B. L. Prassana

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Most of the commercial gluten free products are nutritionally inferior when compared to gluten containing counterparts as manufacturers most often use the refined flours and starches. So it is possible that people on gluten free diet have low intake of fibre content. The foxtail millet flour and copra meal are gluten free and have high fibre and protein contents. The formulation of fibre rich gluten free cookies was optimized by response surface methodology considering independent process variables as proportion of Foxtail millet (Setaria italica) flour in mixed flour, fat content and guar gum. The sugar, sodium chloride, sodium bicarbonates and water were added in fixed proportion as 60, 1.0, 0.4 and 20% of mixed flour weight, respectively. Optimum formulation obtained for maximum spread ratio, fibre content, surface L-value, overall acceptability and minimum breaking strength were 80% foxtail millet flour in mixed flour, 42.8 % fat content and 0.05% guar gum.

Keywords: Copra meal flour, Fiber rich gluten-free cookies, Foxtail millet flour, Optimization

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Authors: Carolina B. Baguio

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One of the purposes of the robust method of estimation is to reduce the influence of outliers in the data, on the estimates. The outliers arise from gross errors or contamination from distributions with long tails. The trimmed mean is a robust estimate. This means that it is not sensitive to violation of distributional assumptions of the data. It is called an adaptive estimate when the trimming proportion is determined from the data rather than being fixed a “priori-. The main objective of this study is to find out the robustness properties of the adaptive trimmed means in terms of efficiency, high breakdown point and influence function. Specifically, it seeks to find out the magnitude of the trimming proportion of the adaptive trimmed mean which will yield efficient and robust estimates of the parameter for data which follow a modified Weibull distribution with parameter λ = 1/2 , where the trimming proportion is determined by a ratio of two trimmed means defined as the tail length. Secondly, the asymptotic properties of the tail length and the trimmed means are also investigated. Finally, a comparison is made on the efficiency of the adaptive trimmed means in terms of the standard deviation for the trimming proportions and when these were fixed a “priori". The asymptotic tail lengths defined as the ratio of two trimmed means and the asymptotic variances were computed by using the formulas derived. While the values of the standard deviations for the derived tail lengths for data of size 40 simulated from a Weibull distribution were computed for 100 iterations using a computer program written in Pascal language. The findings of the study revealed that the tail lengths of the Weibull distribution increase in magnitudes as the trimming proportions increase, the measure of the tail length and the adaptive trimmed mean are asymptotically independent as the number of observations n becomes very large or approaching infinity, the tail length is asymptotically distributed as the ratio of two independent normal random variables, and the asymptotic variances decrease as the trimming proportions increase. The simulation study revealed empirically that the standard error of the adaptive trimmed mean using the ratio of tail lengths is relatively smaller for different values of trimming proportions than its counterpart when the trimming proportions were fixed a 'priori'.

Keywords: Adaptive robust estimate, asymptotic efficiency, breakdown point, influence function, L-estimates, location parameter, tail length, Weibull distribution.

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Authors: Ibtisam Mahmoud Mohammed Sultan

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The present research aims at identifying the level of both emotional security and emotional competence among Tikrit University students. It also meant to know the statistically significant differences according to variables such as gender variables (m-f) and specialization variables (scientific-humanities). The research also attempts to learn what kind of relationship is there between emotional security and emotional efficiency Tikrit University students have achieved. We constructed emotional security measure which consists of 54 items as well as a measure of emotional competence consisting of 46 items. We extracted full psychometric characteristics of both scales. The research sample consisted of 600 students selected randomly and applying the scales on a basic research sample and processed statistical data using a variety of methods, including statistical measure Pearson correlation coefficient, we found a set of results as follows: Tikrit University students possess a high level of emotional security, males enjoy more emotional security than females, there is no difference between students of scientific and humanitarian specialization in variable emotional security, Tikrit University students enjoy a high level of emotional competence, females outperform males in emotional competence level, the humanitarian specialization students excel in emotional competence more than those specialized in non-humanitarian sciences. Furthermore, the research comes up with a positive correlative relationship between these two variables. Through research results, we developed a set of conclusions, proposals, and recommendations.

Keywords: Emotional security, gender variable, specialization variable, Tikrit University students.

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Authors: Lambros V. Skarlas, Grigorios N. Beligiannis, Efstratios F. Georgopoulos, Adam V. Adamopoulos

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The aim of this contribution is to present a new approach in modeling the electrical activity of the human heart. A recurrent artificial neural network is being used in order to exhibit a subset of the dynamics of the electrical behavior of the human heart. The proposed model can also be used, when integrated, as a diagnostic tool of the human heart system. What makes this approach unique is the fact that every model is being developed from physiological measurements of an individual. This kind of approach is very difficult to apply successfully in many modeling problems, because of the complexity and entropy of the free variables describing the complex system. Differences between the modeled variables and the variables of an individual, measured at specific moments, can be used for diagnostic purposes. The sensor fusion used in order to optimize the utilization of biomedical sensors is another point that this paper focuses on. Sensor fusion has been known for its advantages in applications such as control and diagnostics of mechanical and chemical processes.

Keywords: Artificial Neural Networks, Diagnostic System, Health Condition Modeling Tool, Heart Diagnostics Model, Heart Electricity Model.

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Authors: Lizbeth Puerta, Enselmina Marín

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The purpose of this research is to present a survey to be applied to professors of public universities, to identify the factors that benefit or hinder the university-industry relation. Hence, this research studies some elements that integrate the variables: Knowledge management, technology management, and technology transfer; to define the existence of a relation between these variables and the industry necessities of innovation. This study is exploratory, descriptive and non-experimental. The research question is: What is the impact of the knowledge management, the technology management, and the technology transfer, made by administrative support areas of the public universities, in the industries innovation? Thus, literature review was made to identify some elements that should be considered to design a survey that allows to obtain valid information to the study variables. After this, the survey was developed, and the Content Validity Analysis was made through the Lawshe Model. The analysis indicated that the Content Validity Index (CVI) was 0.80. Hence, it was determined that this survey presents acceptable psychometric properties to be used as an evaluation tool.

Keywords: Innovation, knowledge management, technology management, technology transfer.

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Authors: Anshu Manik, Kasthurirangan Gopalakrishnan, Siddhartha K. Khaitan

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Rutting is one of the major load-related distresses in airport flexible pavements. Rutting in paving materials develop gradually with an increasing number of load applications, usually appearing as longitudinal depressions in the wheel paths and it may be accompanied by small upheavals to the sides. Significant research has been conducted to determine the factors which affect rutting and how they can be controlled. Using the experimental design concepts, a series of tests can be conducted while varying levels of different parameters, which could be the cause for rutting in airport flexible pavements. If proper experimental design is done, the results obtained from these tests can give a better insight into the causes of rutting and the presence of interactions and synergisms among the system variables which have influence on rutting. Although traditionally, laboratory experiments are conducted in a controlled fashion to understand the statistical interaction of variables in such situations, this study is an attempt to identify the critical system variables influencing airport flexible pavement rut depth from a statistical DoE perspective using real field data from a full-scale test facility. The test results do strongly indicate that the response (rut depth) has too much noise in it and it would not allow determination of a good model. From a statistical DoE perspective, two major changes proposed for this experiment are: (1) actual replication of the tests is definitely required, (2) nuisance variables need to be identified and blocked properly. Further investigation is necessary to determine possible sources of noise in the experiment.

Keywords: Airport Pavement, Design of Experiments, Rutting, NAPTF.

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Authors: Rihab Gam, Anis Sakly, Faouzi M'sahli

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A new strategy of control is formulated for chaos synchronization of non-identical chaotic systems with different orders using the Borne and Gentina practical criterion associated with the Benrejeb canonical arrow form matrix, to drift the stability property of dynamic complex systems. The designed controller ensures that the state variables of controlled chaotic slave systems globally synchronize with the state variables of the master systems, respectively. Numerical simulations are performed to illustrate the efficiency of the proposed method.

Keywords: Synchronization, Non-identical chaotic systems, Different orders, Arrow form matrix.

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Authors: J. Cheeneebash, K. B. Lallmamode, A. Gopaul

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Throughout this paper, a relatively new technique, the Tabu search variable selection model, is elaborated showing how it can be efficiently applied within the financial world whenever researchers come across the selection of a subset of variables from a whole set of descriptive variables under analysis. In the field of financial prediction, researchers often have to select a subset of variables from a larger set to solve different type of problems such as corporate bankruptcy prediction, personal bankruptcy prediction, mortgage, credit scoring and the Arbitrage Pricing Model (APM). Consequently, to demonstrate how the method operates and to illustrate its usefulness as well as its superiority compared to other commonly used methods, the Tabu search algorithm for variable selection is compared to two main alternative search procedures namely, the stepwise regression and the maximum R 2 improvement method. The Tabu search is then implemented in finance; where it attempts to predict corporate bankruptcy by selecting the most appropriate financial ratios and thus creating its own prediction score equation. In comparison to other methods, mostly the Altman Z-Score model, the Tabu search model produces a higher success rate in predicting correctly the failure of firms or the continuous running of existing entities.

Keywords: Predicting Bankruptcy, Tabu Search

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Authors: Soon-ok Myong, Byong-soon Chun

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This paper intends to identify the ethnic Kazakhstani Koreans- political process of identity formation by exploring their narrative and practice about the state language represented in the course of their becoming the new citizens of a new independent state. The Russophone Kazakhstani Koreans- inability to speak the official language of their affiliated state is considered there as dissatisfying the basic requirement of citizens of the independent state, so that they are becoming marginalized from the public sphere. Their contradictory attitude that at once demonstrates nominal reception and practical rejection of the obligatory state language unveils a high barrier inside between their self-language and other-language. In this paper, the ethnic Korean group-s conflicting linguistic identity is not seen as a free and simple choice, but as a dynamic struggle and political process in which the subject-s past experiences and memories intersect with the external elements of pressure.

Keywords: Ethnic Kazakhstani Koreans, Soviet Korean's Russification, Linguistic Identity, Russian-Kazakh Dichotomy.

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Authors: Emmanuel Selase Asamoah, Miloslava Chovancová

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When choosing marketing strategies for international markets, one of the factors that should be considered is the cultural differences that exist among consumers in different countries. If the branding strategy has to be contextual and in tune with the culture, then the brand positioning variables has to interact, adapt and respond to the cultural variables in which the brand is operating. This study provides an overview of the relevance of culture in the development of an effective branding strategy in the international business environment. Hence, the main objective of this study is to provide a managerial framework for developing strategies for cross cultural brand management. The framework is useful because it incorporates the variables that are important in the competitiveness of fast food enterprises irrespective of their size. It provides practical, proactive and result oriented analysis that will help fast food firms augment their strategies in the international fast food markets. The proposed framework will enable managers understand the intricacies involved in branding in the global fast food industry and decrease the use of 'trial and error' when entering into unfamiliar markets.

Keywords: culture, branding strategy, marketing mix, mass customization, standardization

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Authors: Norazah Mohd Suki, Norbayah Mohd Suki

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Online shopping enables consumers to search for information and purchase products or services through direct interaction with online store. This study aims to examine the effect of Internet marketing environment, product characteristics, familiarity and confidence, and promotional offers on consumer online shopping behavior. 200 questionnaires were distributed to the respondents, who are students and staff at a public university in the Federal Territory of Labuan, Malaysia, following simple random sampling as a means of data collection. Multiple regression analysis was used as a statistical measure to determine the strength of the relationship between one dependent variable and a series of other independent variables. Results revealed that familiarity and confidence was found to greatly influence consumer online shopping behavior followed by promotional offers. A clear understanding of consumer online shopping behavior can help marketing managers predict the online shopping rate and evaluate the future growth of online commerce.

Keywords: Internet Marketing Environment, Product Characteristics, Multiple Regression Analysis, Malaysia.

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Authors: Jeffrey L. Duffany

Abstract:

An optimal solution for a large number of constraint satisfaction problems can be found using the technique of substitution and elimination of variables analogous to the technique that is used to solve systems of equations. A decision function f(A)=max(A2) is used to determine which variables to eliminate. The algorithm can be expressed in six lines and is remarkable in both its simplicity and its ability to find an optimal solution. However it is inefficient in that it needs to square the updated A matrix after each variable elimination. To overcome this inefficiency the algorithm is analyzed and it is shown that the A matrix only needs to be squared once at the first step of the algorithm and then incrementally updated for subsequent steps, resulting in significant improvement and an algorithm complexity of O(n3).

Keywords: Algorithm, complexity, constraint, np-complete.

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Authors: Jaime R. S. Fonseca

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Nevertheless the widespread application of finite mixture models in segmentation, finite mixture model selection is still an important issue. In fact, the selection of an adequate number of segments is a key issue in deriving latent segments structures and it is desirable that the selection criteria used for this end are effective. In order to select among several information criteria, which may support the selection of the correct number of segments we conduct a simulation study. In particular, this study is intended to determine which information criteria are more appropriate for mixture model selection when considering data sets with only categorical segmentation base variables. The generation of mixtures of multinomial data supports the proposed analysis. As a result, we establish a relationship between the level of measurement of segmentation variables and some (eleven) information criteria-s performance. The criterion AIC3 shows better performance (it indicates the correct number of the simulated segments- structure more often) when referring to mixtures of multinomial segmentation base variables.

Keywords: Quantitative Methods, Multivariate Data Analysis, Clustering, Finite Mixture Models, Information Theoretical Criteria, Simulation experiments.

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Authors: Abdel Hamid Ajbar, Emad Ali

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Saudi Arabia is an arid country which depends on costly desalination plants to satisfy the growing residential water demand. Prediction of water demand is usually a challenging task because the forecast model should consider variations in economic progress, climate conditions and population growth. The task is further complicated knowing that Mecca city is visited regularly by large numbers during specific months in the year due to religious occasions. In this paper, a neural networks model is proposed to handle the prediction of the monthly and yearly water demand for Mecca city, Saudi Arabia. The proposed model will be developed based on historic records of water production and estimated visitors- distribution. The driving variables for the model include annuallyvarying variables such as household income, household density, and city population, and monthly-varying variables such as expected number of visitors each month and maximum monthly temperature.

Keywords: Water demand forecast; Neural Networks model; water resources management; Saudi Arabia.

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Authors: Astiaj Khoramshahi, Hossein Ahmadi Danesh Ashtiani, Ahmad Khoshgard, Hamidreza Damghani, Leila Damghani

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Rural electrification rates are generally low in Iran and many parts of the world that lack sustainable renewable energy resources. Many homes are based on polluting solutions such as crude oil and diesel generators for lighting, heating, and charging electrical gadgets. Small-scale portable solar battery packs are accessible to the public; however, they have low capacity and are challenging to be distributed in developing countries. To design a battery-based microgrid power systems, the load profile is one of the key parameters. Additionally, the reliability of the system should be taken into account. A conventional microgrid system can be either AC or coupling DC. Both AC and DC microgrids have advantages and disadvantages depending on their application and can be either connected to the main grid or perform independently. This article proposes a tool for optimal sizing of microgrid-independent systems via respective analysis. To show such an analysis, the type of power generation, number of panels, battery capacity, microgrid size, and group of available consumers should be considered. Therefore, the optimization of different design scenarios is based on number of solar panels and super saving sources, ranges of the depth of discharges, to calculate size and estimate the overall cost. Generally, it is observed that there is an inverse relationship between the depth spectrum of discharge and the solar microgrid costs.

Keywords: Storage, super-storage, grid-independent, economic factors, microgrid.

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Authors: Birol Yildiz, Abdullah Yalama, Metin Coskun

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Many studies have shown that Artificial Neural Networks (ANN) have been widely used for forecasting financial markets, because of many financial and economic variables are nonlinear, and an ANN can model flexible linear or non-linear relationship among variables. The purpose of the study was to employ an ANN models to predict the direction of the Istanbul Stock Exchange National 100 Indices (ISE National-100). As a result of this study, the model forecast the direction of the ISE National-100 to an accuracy of 74, 51%.

Keywords: Artificial Neural Networks, Istanbul StockExchange, Non-linear Modeling.

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Authors: M. Jahangiri Lahkani, Gh. Ghassemi, N. Sohrabi, N. Rasooli

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Geometry optimizations of metal complexes of Salen(bis(Salicylidene)1,2-ethylenediamine) were carried out at HF and DFT methods employing Lanl2DZ basis set. In this work structural, energies, bond lengths and other physical properties between Mn2+,Cu2+ and Ni2+ ions coordinated by salen–type ligands are examined. All calculations were performed using Gaussian 98W program series. To investigate local aromaticities, NICS were calculated at all centers of rings. The higher the band gap indicating a higher global aromaticity. The possible binding energies have been evaluated. We have evaluated Frequencies and Zero-point energy with freq calculation. The NICS(Nucleous Independent Chemical Shift) Results show Ni(II) complexes are antiaromatic and aromaticites of Mn(II) complexes are larger than Cu(II) complexes. The energy Results show Cu(II) complexes are stability than Mn(II) and Ni(II) complexes.

Keywords: Frequency Calculation, Hartree-Fock (HF), Nucleous Independent Chemical Shift (NICS), Salen(bis(Salicylidene)1, 2-ethylenediamine).

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Authors: Swadhin Kumar Mishra, Sidhartha Panda, C. Ardil

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Multiple-Input-Multiple-Output (MIMO) is one of the most important communication techniques that allow wireless systems to achieve higher data rate. To overcome the practical difficulties in implementing Dirty Paper Coding (DPC), various suboptimal MIMO Broadcast (MIMO-BC) scheduling algorithms are employed which choose the best set of users among all the users. In this paper we discuss such a sub-optimal MIMO-BC scheduling algorithm which employs antenna selection at the receiver side. The channels for the users considered here are not Identical and Independent Distributed (IID) so that users at the receiver side do not get equal opportunity for communication. So we introduce a method of applying weights to channels of the users which are not IID in such a way that each of the users gets equal opportunity for communication. The effect of weights on overall sum-rate achieved by the system has been investigated and presented.

Keywords: Antenna selection, Identical and Independent Distributed (IID), Sum-rate capacity, Weighted sum rate.

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Authors: Mae C. Pavilario

Abstract:

This study employs a sequential explanatory mixed method. Quantitatively it investigated the profile of grade VII students. Qualitatively, the prevailing contextual variables that affect their frustration-level were sought based on their perspective and that of their parents and teachers. These students were categorized as frustration-level in reading based on the data on word list of the Philippine Informal Reading Inventory (Phil-IRI). The researcher-made reading factor instrument translated to local dialect (Hiligaynon) was subjected to cross-cultural translation to address content, semantic, technical, criterion, or conceptual equivalence, the open-ended questions, and one unstructured interview was utilized. In the profile of the 26 participants, the 12 males are categorized as grade II and grade III frustration-levels. The prevailing contextual variables are personal-“having no interest in reading”, “being ashamed and fear of having to read in front of others” for extremely high frustration level; social environmental-“having no regular reading schedule at home” for very high frustration level and personal- “having no interest in reading” for high frustration level. Kendall Tau inferential statistical tool was used to test the significant relationship in the prevailing contextual variables that affect frustration-level readers when grouped according to perspective. Result showed that significant relationship exists between students-parents perspectives; however, there is no significant relationship between students’ and teachers’, and parents’ and teachers’ perspectives. The themes in the narratives of the participants on frustration-level readers are existence of speech defects, undesirable attitude, insufficient amount of reading materials, lack of close supervision from parents, and losing time and focus on task. Intervention was designed.

Keywords: Contextual variables, frustration-level readers, perspective, inquiry.

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Authors: Nishi Bhuvandas, P. V. Timbadiya, P. L. Patel, P. D. Porey

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Recent perceived climate variability raises concerns with unprecedented hydrological phenomena and extremes. Distribution and circulation of the waters of the Earth become increasingly difficult to determine because of additional uncertainty related to anthropogenic emissions. The world wide observed changes in the large-scale hydrological cycle have been related to an increase in the observed temperature over several decades. Although the effect of change in climate on hydrology provides a general picture of possible hydrological global change, new tools and frameworks for modelling hydrological series with nonstationary characteristics at finer scales, are required for assessing climate change impacts. Of the downscaling techniques, dynamic downscaling is usually based on the use of Regional Climate Models (RCMs), which generate finer resolution output based on atmospheric physics over a region using General Circulation Model (GCM) fields as boundary conditions. However, RCMs are not expected to capture the observed spatial precipitation extremes at a fine cell scale or at a basin scale. Statistical downscaling derives a statistical or empirical relationship between the variables simulated by the GCMs, called predictors, and station-scale hydrologic variables, called predictands. The main focus of the paper is on the need for using statistical downscaling techniques for projection of local hydrometeorological variables under climate change scenarios. The projections can be then served as a means of input source to various hydrologic models to obtain streamflow, evapotranspiration, soil moisture and other hydrological variables of interest.

Keywords: Climate Change, Downscaling, GCM, RCM.

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Authors: Dinesh Kumar, C.S. Rai, Shakti Kumar

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Face Recognition has always been a fascinating research area. It has drawn the attention of many researchers because of its various potential applications such as security systems, entertainment, criminal identification etc. Many supervised and unsupervised learning techniques have been reported so far. Principal Component Analysis (PCA), Self Organizing Maps (SOM) and Independent Component Analysis (ICA) are the three techniques among many others as proposed by different researchers for Face Recognition, known as the unsupervised techniques. This paper proposes integration of the two techniques, SOM and PCA, for dimensionality reduction and feature selection. Simulation results show that, though, the individual techniques SOM and PCA itself give excellent performance but the combination of these two can also be utilized for face recognition. Experimental results also indicate that for the given face database and the classifier used, SOM performs better as compared to other unsupervised learning techniques. A comparison of two proposed methodologies of SOM, Local and Global processing, shows the superiority of the later but at the cost of more computational time.

Keywords: Face Recognition, Principal Component Analysis, Self Organizing Maps, Independent Component Analysis

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Authors: Behnaz Mohajeran, Alireza Ghaleei

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This main purpose of the study reported here was to investigate the extent to which the form of school governance (particularly decision-making) had an impact upon the effectiveness of the school with reference to parental involvement, planning and budgeting, professional development of teachers, school facilities and resources, and student outcomes. Particular attention was given to decision-making within the governance arrangements. The study was based on four case studies of high schools in New South Wales, Australia including one government school, one independent Christian community school, one independent Catholic school, and one Catholic systemic school. The focus of the research was principals, teachers, parents, and students of four schools with varying governance structures. To gain a greater insight into the issues, the researchers collected information by questionnaire, semi-structured interview, and review of school key documents. This study found that it was not so much structure but the centrality of the school Principal and the way that the Principal perceived his/her roles in relation to others that impacted most on school governance.

Keywords: governance structure, principal role, schooleffectiveness, stakeholder involvement

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Authors: Prateep Wajeetongratana

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The purpose of this research was to study the influence of accountants’ potential performance on their working process, a case study of Government Savings Banks in the northeast of Thailand. The independent variables included accounting knowledge, accounting skill, accounting value, accounting ethics, and accounting attitude, while the dependent variable included the success of the working process. A total of 155 accountants working for Government Savings Banks were selected by random sampling. A questionnaire was used as a tool for collecting data. Descriptive statistics in this research included percentage, mean, and multiple regression analyses.

The findings revealed that the majority of accountants were female with an age between 35-40 years old. Most of the respondents had an undergraduate degree with ten years of experience. Moreover, the factors of accounting knowledge, accounting skill, accounting a value and accounting ethics and accounting attitude were rated at a high level. The findings from regression analysis of observation data revealed a causal relationship in that the observation data could explain at least 51 percent of the success in the accountants’ working process.

Keywords: Influence, Potential Performance, Success, Working Process.

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Authors: V Krishnaveni, S Jayaraman, A Gunasekaran, K Ramadoss

Abstract:

The ElectroEncephaloGram (EEG) is useful for clinical diagnosis and biomedical research. EEG signals often contain strong ElectroOculoGram (EOG) artifacts produced by eye movements and eye blinks especially in EEG recorded from frontal channels. These artifacts obscure the underlying brain activity, making its visual or automated inspection difficult. The goal of ocular artifact removal is to remove ocular artifacts from the recorded EEG, leaving the underlying background signals due to brain activity. In recent times, Independent Component Analysis (ICA) algorithms have demonstrated superior potential in obtaining the least dependent source components. In this paper, the independent components are obtained by using the JADE algorithm (best separating algorithm) and are classified into either artifact component or neural component. Neural Network is used for the classification of the obtained independent components. Neural Network requires input features that exactly represent the true character of the input signals so that the neural network could classify the signals based on those key characters that differentiate between various signals. In this work, Auto Regressive (AR) coefficients are used as the input features for classification. Two neural network approaches are used to learn classification rules from EEG data. First, a Polynomial Neural Network (PNN) trained by GMDH (Group Method of Data Handling) algorithm is used and secondly, feed-forward neural network classifier trained by a standard back-propagation algorithm is used for classification and the results show that JADE-FNN performs better than JADEPNN.

Keywords: Auto Regressive (AR) Coefficients, Feed Forward Neural Network (FNN), Joint Approximation Diagonalisation of Eigen matrices (JADE) Algorithm, Polynomial Neural Network (PNN).

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Authors: Paula A. Cruise, Carvell McLeary

Abstract:

Employee turnover leads to lowered productivity, decreased morale and work quality, and psychological effects associated with employee separation and replacement. Yet, it remains unknown why talented employees willingly withdraw from organizations. This uncertainty is worsened as studies; a) priorities organizational over individual predictors resulting in restriction in range in turnover measurement; b) focus on actual rather than intended turnover thereby limiting conceptual understanding of the turnover construct and its relationship with other variables and; c) produce inconsistent findings across cultures, contexts and industries despite a clear need for a unified perspective. The current study addressed these gaps by adopting the theory of planned behavior (TPB) framework to examine socio-cognitive factors in organizational trust and individual turnover intentions among bankers and energy employees in Jamaica. In a comparative study of n=369 [n_bank= 264; male=57 (22.73%); n_energy =105; male =45 (42.86)], it was hypothesized that organizational trust was a predictor of employee turnover intention, and the effect of individual, group, cognitive and socio-affective variables varied across industry. Findings from structural equation modelling confirmed the hypothesis, with a model of both cognitive and socio-affective variables being a better fit [CMIN (χ²) = 800.067, df = 364, p ≤ .000; CFI = 0.950; RMSEA = 0.057 with 90% C.I. (0.052 - 0.062); PCLOSE = 0.016; PNFI = 0.818 in predicting turnover intention. The findings are discussed in relation to socio-cognitive components of trust models and predicting negative employee behaviors across cultures and industries.

Keywords: Context-specific organizational trust, cross-cultural psychology, theory of planned behavior, employee turnover intention.

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