• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.85-94
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• 2023

Image halftoning is a technique for varying grayscale images into two-tone binary images. Unfortunately, the static representation of an image-half toning, wherever each pixel intensity is combined by its local neighbors only, causes missing subjective problem. Also, the existing noise causes an instability criterion. In this paper an image half-toning is represented as a dynamical system for recognizing the global representation. Also, noise is reduced based on a probabilistic model. Since image half-toning is considered as 2-D matrix with a full connected pass, this structure is recognized by the dynamical system of Cellular Neural Networks (CNNs) which is defined by its template. Bayesian Rough Sets is used in exploiting the ideal CNNs construction that synthesis its dynamic. Also, Bayesian rough sets contribute to enhance the quality of the halftone image by removing noise and discovering the effective parameters in the CNNs template. The novelty of this method lies in finding a probabilistic based technique to discover the term of CNNs template and define new learning rules for CNNs internal work. A numerical experiment is conducted on image half-toning corrupted by Gaussian noise.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.421-429
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• 2022

Entrepreneurship research has focused on several factors that might affect the intention of an individual to start an enterprise. Using principles from social network theory and the entrepreneurial intention model (EI), the current research intends to investigate how social capital is formed on Social Networking Sites (SNS) and how the resulting social capital influences entrepreneurial intention. Using an online survey, 151 valid responses were received from university students. Applying partial least square structural equation modeling, positive and significant relationship was found between the SNS usage and bonding and bridging social capital. Further, it was also found that online-bonding social capital does not impact any of the three antecedents of entrepreneurial intention. On the other hand, online-bridging social capital significantly influences personal attitudes and subjective norms. It was also found that both personal attitude and perceived behavioral control significantly relate to EI, while the subjective norms do not relate significantly to EI. The paper contributes to the literature on technology-based human behavior and entrepreneurship in emerging countries, opening some areas for future research, while also providing some managerial insights. It also should be beneficial to educational institutions in understanding how the use of SNS use by students may be optimized.

• Structural Engineering and Mechanics
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• v.89 no.4
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• pp.363-374
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• 2024

Significant changes have been made to estimate the punching shear capacity for edge column-slab joints in the latest editions of most current codes. The revised equations account for axial forces as well as moments conveyed to columns from slabs, which have a substantial impact on the punching resistance of such joints. Many key design parameters, such as reinforcement-ratio, concrete strength, size-effect, and critical-section perimeter, were treated differently or even ignored in various code provisions. Consequently, wide ranges of predicted punching shear strength were detected by applying different code formulas. Therefore, it is essential to assess the various current Codes' design-equations. Because of the similarity in estimated outcomes, only the ACI, EC, and SNiP are used in this study to cover a wide range of estimation ranges from highly conservative to unconservative. This paper is devoted to analyzing the techniques in these code provisions, comparing the estimated punching resistance with available experimental data, and finally developing efficient models predicting the punching capacity of edge column-slab connections. 63 samples from past investigations were chosen for validation. To appropriately predict the punching shear, newly updated equations for ACI and SNiP are provided based on nonlinear regression analysis. The proposed equations'results match the experimental data quite well.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.359-367
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• 2022

Arabic skills are the tools by which children are prepared for the educational procedures on which their life depends. Deaf and hard of hearing students (DHH), must be able to grasp the same Arabic terms as hearing students and their different meanings in a context of different sentences less than what they are supposed to be due to their inability. However, problems arise in the same Arabic word and their different meanings in a context for (DHH) students since the way of comprehending such words does not meet the needs and circumstances of (DHH) students. Therefore, researchers introduce web-based method for Arabic words and their meanings in a context prototype that can overcome those problems. Methodology: The study sample consists of 30 (DHH) students at Al Amal City of Palestine, Gaza Region (GR). Those participants that agreed to take part in this study were recruited using a purposeful sampling method. Additionally, to examine the survey information descriptively, the Statistical Packages for social Sciences (SPSS) version 24.0 was used. A sign language teaching movie is utilized in the prototype to standardize the process and verify that Arabic vocabulary and their implications are comprehended. The Evolutionary Process Model of Prototype technique was utilized to create this system. Finding: The findings of this study show that the prototype built is workable and has the ability to help DHHS differentiate between phrases that have the same letters but distinct meanings. The findings of this study are expected to contribute to a better understanding and application of Development of Web-based Arabic Assessments for (DHH) Students in developing countries, which will help to increase the use of Development of Web-based Arabic for (HDD) students in those countries. The empirical models of Web-based Arabic for (DHH) students are established as a proof of concept for the proposed model. The results of this study are predicted to have a significant impact to the information system practitioners and to the body of knowledge.

• International Journal of Concrete Structures and Materials
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• v.9 no.2
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• pp.255-266
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• 2015

A strut-and-tie based method intended for determining the load-carrying capacity of reinforced concrete (RC) corbels is presented in this paper. In addition to the normal strut-and-tie force equilibrium requirements, the proposed model is based on secant stiffness formulation, incorporating strain compatibility and constitutive laws of cracked RC. The proposed method evaluates the load-carrying capacity as limited by the failure modes associated with nodal crushing, yielding of the longitudinal principal reinforcement, as well as crushing or splitting of the diagonal strut. Load-carrying capacity predictions obtained from the proposed analysis method are in a better agreement with corbel test results of a comprehensive database, comprising 455 test results, compiled from the available literature, than other existing models for corbels. This method is illustrated to provide more accurate estimates of behaviour and capacity than the shear-friction based approach implemented by the ACI 318-11, the strut-and-tie provisions in different codes (American, Australian, Canadian, Eurocode and New Zealand).

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.211-216
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• 2021

This study intended to test the structure of the latent factor of a subjective happiness scale and the stability of invariance across groups of students' classifications (gender and students' status). In the large, non-clinical sample (619), students completed the subjective happiness scale. The (CFA) confirmatory factor analysis was used to investigate the factor-structure of the measure, and multiple-group confirmatory factor analysis (MGCFA) model was used to test the stability of invariance across groups of students classifications. The findings of the CFA indicated support for the original one-factor model. Additional analyses of the MGCFA method support the measurement (configural, metric and strong) invariant and practical invariant components of this model. There was an invariant across gender. There was partially invariant across groups of students' statuses. The scale exists in both groups to assess the same concepts of (single and married), excluding Items 3 and 4. Given that this study is the first investigation for the structure of the subjective happiness scale.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.149-156
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• 2021

This study intended to test the structure of the latent factor of an effectiveness scale and the stability of invariance across groups of students' classifications (gender and levels of education). In the large, non-clinical sample (850), students completed the effectiveness scale. The (CFA) confirmatory factor analysis was used to investigate the factor-structure of the measure, and multiple-group confirmatory factor analysis (MGCFA) model was used to test the stability of invariance across groups of students' classifications. The findings of the CFA indicated support for the original four-factor model. Additional analyses of the MGCFA method support the measurement (configural, metric and strong) invariant and practical invariant components of this model. There was an invariant across gender. There was partially invariant across groups of levels of education. The scale exists in groups of levels of education assess the same concepts of, excluding Items 15 and 10. Given that this study is the first investigation for the structure of the effectiveness scale.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.33-40
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• 2020

The main aim of the study is to test a house pricing model by combining hedonic and asset-based pricing models. An understanding of the relationship between house pricing and its return (the rental income) helps to establish houses as a significant asset class. The model tested the relationship between house pricing (dependent variable) and the house attributes (independent variables) derived from Freeman's framework of housing attributes. This study uses a large data-set of 1,899 sample of new, high-end houses purchased between 2016 and 2019 collected from the national capital region of India (Delhi-NCR). The algorithm was built in R-Script, and stepwise multiple linear regression was used to analyze the model. The analysis of the model proves that the three significant variables, namely, carpet area, pay-off, and annual maintenance charges explain the price function. Further, the model is statistically fit. The major contribution of the study is to understand the key factors and their influence on the house pricing. The model will be helpful in risk assessment in the housing investment and enhance the chances of investment. Policy-makers can use information about the underlying valuation drivers of the house prices to stabilize the market and also in framing the tax policies.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.157-164
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• 2021

The aim of this study is to provide empirical evaluation of the accuracy of data-model fit using growing levels of invariance models. Overall model accuracy of factor solutions was evaluated by the examination of the order for testing three levels of measurement invariance (MIV) starting with configural invariance (model 0). Model testing was evaluated by the Chi-square difference test (∆𝛘²) between two groups, and root mean square error of approximation (RMSEA), comparative fit index (CFI), and Tucker-Lewis index (TLI) were used to evaluate the all-model fits. Factorial invariance result revealed that stability of the models was varying over increasing levels of measurement as a function of variable-to-factor ratio (VTF), subject-to-variable ratio (STV), and their interactions. There were invariant factor loadings and invariant intercepts among the groups indicating that measurement invariance was achieved. For VTF ratio (3:1, 6:1, and 9:1), the models started to show accuracy over levels of measurement when STV ratio was 6:1. Yet, the frequency of stability models over 1000 replications increased (from 69% to 89%) as STV ratio increased. The models showed more accuracy at or above 39:1 STV.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.317-319
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• 2022

Rich morphology language such as Arabic needs more investigation and method to improve the sentiment analysis task. Using all document parts in the process of the sentiment analysis may add some unnecessary information to the classifier. Therefore, this paper shows the ongoing work to use sentence location as a feature with Arabic sentiment analysis. Our proposed method employs a supervised sentiment classification method by enriching the feature space model with some information from the document. The experiments and evaluations that were conducted in this work show that our proposed feature in the sentiment analysis for Arabic improves the performance of the classifier compared to the baseline model.