Search results for: elastic net regression.

Authors: Babak Darvish Rouhani, Mohd Naz’ri Mahrin, Fatemeh Nikpay, Pourya Nikfard, Maryam Khanian Najafabadi

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Enterprise Architecture (EA) is a strategy that is employed by enterprises in order to align their business and Information Technology (IT). EA is managed, developed, and maintained through Enterprise Architecture Implementation Methodology (EAIM). Effectiveness of EA implementation is the degree in which EA helps to achieve the collective goals of the organization. This paper analyzes the results of a survey that aims to explore the factors that affect the effectiveness of EAIM and specifically the relationship between factors and effectiveness of the output and functionality of EA project. The exploratory factor analysis highlights a specific set of five factors: alignment, adaptiveness, support, binding, and innovation. The regression analysis shows that there is a statistically significant and positive relationship between each of the five factors and the effectiveness of EAIM. Consistent with theory and practice, the most prominent factor for developing an effective EAIM is innovation. The findings contribute to the measuring the effectiveness of EA implementation project by providing an indication of the measurement implementation approaches which is used by the Enterprise Architects, and developing an effective EAIM.

Keywords: Enterprise Architecture, Enterprise Architecture Implementation Methodology, EA, Effectiveness, Factors, Implementation Methodology.

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Authors: Mojtaba Rezaei, Elham Heydari

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This paper highlights the empirical results of analyzing the correlation between accounting information and systematic risk. This association is analyzed among financial ratios and systematic risk by considering the financial statement of 39 companies listed on the Tehran Stock Exchange (TSE) for five years (2014-2018). Financial ratios have been categorized into four groups and to describe the special features, as representative of accounting information we selected: Return on Asset (ROA), Debt Ratio (Total Debt to Total Asset), Current Ratio (current assets to current debt), Asset Turnover (Net sales to Total assets), and Total Assets. The hypotheses were tested through simple and multiple linear regression and T-student test. The findings illustrate that there is no significant relationship between accounting information and market risk. This indicates that in the selected sample, historical accounting information does not fully reflect the price of stocks.

Keywords: Accounting information, market risk, systematic risk, efficient market hypothesis, EMH, Tehran Stock Exchange, TSE.

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Authors: Yuan-Yu Chiang, Yu-Han Tseng, Chin-Chen Wen

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In the last few decades, many southeast-Asia women migrate to Taiwan by marriage, and it usually takes several years for them to acquire Taiwanese citizenship. This study investigates the relationship between their citizenship acquisition and whether they develop Taiwanese identities, and how does it affect their ethnical identity towards their original ethnics. Furthermore, the present study also explores that whether citizenship acquisition help the immigrant women to explore the host society further and make commitment to it, or the identification towards mainstream Taiwanese society is only symbolic and superficial? One hundred and ninety-two immigrant women were measured using Multigroup Ethnic Identity Measure-Revised and a global 10-point ethnic identity question. Correlation tests, t-test, and hierarchical regression were performed to answer the above questions. The results revealed that citizenship acquisition does help immigrant women to identify with Taiwanese society, but it does not affect how they identify with their own ethnics. Furthermore, the results also indicated that acquiring citizenship would not help these immigrant women become involved in deeper cultural exploration of Taiwan nor would it encourage them to make commitments to the host society.

Keywords: Immigrants, international marriage, ethnic identity, Taiwan.

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Authors: Mohamed Abdallah, Mostafa Warith, Roberto Narbaitz, Emil Petriu, Kevin Kennedy

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Heterogeneity of solid waste characteristics as well as the complex processes taking place within the landfill ecosystem motivated the implementation of soft computing methodologies such as artificial neural networks (ANN), fuzzy logic (FL), and their combination. The present work uses a hybrid ANN-FL model that employs knowledge-based FL to describe the process qualitatively and implements the learning algorithm of ANN to optimize model parameters. The model was developed to simulate and predict the landfill gas production at a given time based on operational parameters. The experimental data used were compiled from lab-scale experiment that involved various operating scenarios. The developed model was validated and statistically analyzed using F-test, linear regression between actual and predicted data, and mean squared error measures. Overall, the simulated landfill gas production rates demonstrated reasonable agreement with actual data. The discussion focused on the effect of the size of training datasets and number of training epochs.

Keywords: Adaptive neural fuzzy inference system (ANFIS), gas production, landfill

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Authors: Wen-Tsann Lin, Yung-Tsan Jou, Yih-Chuan Wu, Yuan-Du Hsiao

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The Emergency Department of a medical center in Taiwan cooperated to conduct the research. A predictive model of triage system is contracted from the contract procedure, selection of parameters to sample screening. 2,000 pieces of data needed for the patients is chosen randomly by the computer. After three categorizations of data mining (Multi-group Discriminant Analysis, Multinomial Logistic Regression, Back-propagation Neural Networks), it is found that Back-propagation Neural Networks can best distinguish the patients- extent of emergency, and the accuracy rate can reach to as high as 95.1%. The Back-propagation Neural Networks that has the highest accuracy rate is simulated into the triage acuity expert system in this research. Data mining applied to the predictive model of the triage acuity expert system can be updated regularly for both the improvement of the system and for education training, and will not be affected by subjective factors.

Keywords: Back-propagation Neural Networks, Data Mining, Emergency Department, Triage System.

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Authors: Mazila Md-Yusuf, Fauziah Mohamad Yunus, Nur Zahraatul Lail Md Supaat

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Capital structure is one of the most important financial decisions in corporate financing strategy. It involves the choice of debt and equity level in financing a company-s operations. This study aims to investigate whether the capital structure choice of Malaysian electrical and electronic manufacturing companies that are listed in the Bursa Malaysia can be explained by factors that have been found by most studies as dominant determinants of capital structure (company size, profitability, asset tangibility, liquidity and growth). Using debt ratio as the proxy for capital structure and applying pooled ordinary least square multiple regression estimation, the results showed that on average, Malaysian electrical and electronic manufacturing companies used less debt in funding their business operations. The findings also showed that size and asset tangibility has a significant positive relationship with debt level, while liquidity has a negative significant relationship with leverage.

Keywords: Capital structure, capital structure theories, leverage, manufacturing companies.

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Authors: Sumalee Lekprayura

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The purposes of this research were 1) to study consumer-based equity of luxury brands, 2) to study consumers- purchase intention for luxury brands, 3) to study direct factors affecting purchase intention towards luxury brands, and 4) to study indirect factors affecting purchase intention towards luxury brands through brand consciousness and brand equity to analyze information by descriptive statistic and hierarchical stepwise regression analysis. The findings revealed that the eight variables of the framework which were: need for uniqueness, normative susceptibility, status consumption, brand consciousness, brand awareness, perceived quality, brand association, and brand loyalty affected the purchase intention of the luxury brands (at the significance of 0.05). Brand Loyalty had the strongest direct effect while status consumption had the strongest indirect effect affecting the purchase intention towards luxury brands. Brand consciousness and brand equity had the mediators through the purchase intention of the luxury brands (at the significance of 0.05).

Keywords: Brand Consciousness, Brand Equity, Luxury Brands, Purchase intention.

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Authors: I. M. Yusuff, O. M. Oni, A. A. Aremu

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Percentage of soil-gas radon-222 concentration (²²²Rn) from soil-depths contributing to outdoor radon atmospheric level depends largely on some physical parameters of the soil. To determine its dependency in soil-depths, survey tests were carried out on soil depths and grain size particles using in-situ measurement method of soil-gas radon-222 concentration at different soil depths. The measurements were carried out with an electronic active radon detector (RAD-7) manufactured by Durridge Company USA. Radon-222 concentrations (²²²Rn) in soil-gas were measured at four different soil depths of 20, 40, 60 and 100 cm in five feasible locations. At each soil depth, soil samples were collected for grain size particle analysis using soil grasp sampler. The result showed that highest value of radon-222 concentration (24,680 ± 1960 Bqm^-3) was measured at 100 cm depth with utmost grain size particle of 17.64% while the lowest concentration (7370 ± 1139 Bqm^-3) was measured at 100 cm depth with least grain size particle of 10.75% respectively. A computational model was derived using SPSS regression package. This model could be a yardstick for prediction on soil gas radon concentration reference to soil grain size particle at different soil-depths.

Keywords: Concentration, radon, porosity, diffusion, colorectal, emanation, yardstick.

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Authors: Safaee Safiollah , Javadi Alimohammad, Javadi Maryam

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Internet access is a vital part of the modern world and an important tool in the education of our children. It is present in schools, homes and even shopping malls. Mastering the use of the internet is likely to be an important skill for those entering the job markets of the future. An internet user can be anyone he or she wants to be in an online chat room, or play thrilling and challenging games against other players from all corners of the globe. It seems at present time (or near future) for many people relationships in the real world may be neglected as those in the virtual world increase in importance. Internet is provided a fast mode of transportation caused freedom from family bonds and mixing with different cultures and new communities. This research is an attempt to study effect of Internet on Social capital. For this purpose a survey technique on the sample size amounted 168 students of Payame Noor University of Kermanshah city in country of Iran were considered. Degree of social capital is moderate. With the help of the Multi-variable Regression, variables of Iranian message attractive, Interest to internet with effect of positive and variable Creating a cordial atmosphere with negative effect be significant.

Keywords: Internet, Social Capital, social participation Social trust

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Authors: Proud Arunrangsiwed, Sarinya Kongtieng

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Teachers and university lecturers face an unsolved problem, which is students’ multitasking behaviors during class time, such as texting or playing a game. It is important to examine the most powerful predictor that can result in students’ educational performances. Meta-analysis was used to analyze the research articles, which were published with the keywords, multitasking, class performance, and texting. We selected 14 research articles published during 2008-2013 from online databases, and four articles met the predetermined inclusion criteria. Effect size of each pair of variables was used as the dependent variable. The findings revealed that the students’ expectancy and value on SNSs usages is the best significant predictor of their educational performances, followed by their motivation and ability in using SNSs, prior educational performances, usage behaviors of SNSs in class, and their personal characteristics, respectively. Future study should conduct a longitudinal design to better understand the effect of multitasking in the classroom.

Keywords: Meta-regression analysis, social networking site use, academic performance, multitasking, motivation.

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Authors: Kgatla T.E., Howard S.S, Hiss D.C.

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Prickly pear juice has received renewed attention with regard to the effects of processing and preservation on its sensory qualities (colour, taste, flavour, aroma, astringency, visual browning and overall acceptability). Juice was prepared by homogenizing fruit and treating the pulp with pectinase (Aspergillus niger). Juice treatments applied were sugar addition, acidification, heat-treatment, refrigeration, and freezing and thawing. Prickly pear pulp and juice had unique properties (low pH 3.88, soluble solids 3.68 oBrix and high titratable acidity 0.47). Sensory profiling and descriptive analyses revealed that non-treated juice had a bitter taste with high astringency whereas treated prickly pear was significantly sweeter. All treated juices had a good sensory acceptance with values approximating or exceeding 7. Regression analysis of the consumer sensory attributes for non-treated prickly pear juice indicated an overwhelming rejection, while treated prickly pear juice received overall acceptability. Thus, educed favourable sensory responses and may have positive implications for consumer acceptability.

Keywords: Consumer acceptability, descriptive test, Prickly pear juice

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Authors: Alicia Heraz, Claude Frasson

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This paper investigates how the use of machine learning techniques can significantly predict the three major dimensions of learner-s emotions (pleasure, arousal and dominance) from brainwaves. This study has adopted an experimentation in which participants were exposed to a set of pictures from the International Affective Picture System (IAPS) while their electrical brain activity was recorded with an electroencephalogram (EEG). The pictures were already rated in a previous study via the affective rating system Self-Assessment Manikin (SAM) to assess the three dimensions of pleasure, arousal, and dominance. For each picture, we took the mean of these values for all subjects used in this previous study and associated them to the recorded brainwaves of the participants in our study. Correlation and regression analyses confirmed the hypothesis that brainwave measures could significantly predict emotional dimensions. This can be very useful in the case of impassive, taciturn or disabled learners. Standard classification techniques were used to assess the reliability of the automatic detection of learners- three major dimensions from the brainwaves. We discuss the results and the pertinence of such a method to assess learner-s emotions and integrate it into a brainwavesensing Intelligent Tutoring System.

Keywords: Algorithms, brainwaves, emotional dimensions, performance.

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Authors: G. Baskar, C. Muthukumaran, S. Renganathan

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Enzymatic hydrolysis of starch from natural sources finds potential application in commercial production of alcoholic beverage and bioethanol. In this study the effect of starch concentration, temperature, time and enzyme concentration were studied and optimized for hydrolysis of cassava (Manihot esculenta) starch powder (of mesh 80/120) into glucose syrup by immobilized (using Polyacrylamide gel) a-amylase using central composite design. The experimental result on enzymatic hydrolysis of cassava starch was subjected to multiple linear regression analysis using MINITAB 14 software. Positive linear effect of starch concentration, enzyme concentration and time was observed on hydrolysis of cassava starch by a-amylase. The statistical significance of the model was validated by F-test for analysis of variance (p < 0.01). The optimum value of starch concentration temperature, time and enzyme concentration were found to be 4.5% (w/v), 45oC, 150 min, and 1% (w/v) enzyme. The maximum glucose yield at optimum condition was 5.17 mg/mL.

Keywords: Enzymatic hydrolysis, Alcoholic beverage, Centralcomposite design, Polynomial model, glucose yield.

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Authors: Ali Faal Ghayoumi, Mahmoud Dehghan Nayeri, Manouchehre Ansari, Taha Raeesi

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This study aims to investigate empirically the valuerelevance of accounting information to domestic investors in Tehran stock exchange from 1999 to 2006. During the present research impacts of two factors, including positive vs. negative earnings and the firm size are considered as well. The authors used earnings per share and annual change of earnings per share as the income statement indices, and book value of equity per share as the balance sheet index. Return and Price models through regression analysis are deployed in order to test the research hypothesis. Results depicted that accounting information is value-relevance to domestic investors in Tehran Stock Exchange according to both studied models. However, income statement information has more value-relevance than the balance sheet information. Furthermore, positive vs. negative earnings and firm size seems to have significant impact on valuerelevance of accounting information.

Keywords: Value-Relevance of Accounting Information, Iranianstock exchange, Return Model, Price Model

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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: Nopadol Burananuth

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This research was aimed to investigate (1) the relationship among local social movements, non-governmental Organization activities and state measures deployment; and (2) the effects of local social movements, non-governmental Organization activities, and state measures deployment on conflict of local people towards the Thai-Malaysian gas pipeline project. These people included 1,000 residents of the four districts in Songkhla province. The methods of data analysis consist of multiple regression analysis. The results of the analysis showed that: (1) local social movements depended on information, and mass communication; deployment of state measures depended on compromise, coordination, and mass communication; and (2) the conflict of local people depended on mobilization, negotiation, and campaigning for participation of people in the project. Thus, it is recommended that to successfully implement any government policy, consideration must be paid to the conflict of local people, mobilization, negotiation, and campaigning for people’s participation in the project.

Keywords: Conflict, NGO activities, social movements, state measures.

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Authors: B. Sabayan, A. Alidadi, S. Ebrahimi, N. M. Bakhshani

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Neuropsychological problems are more common in hemodialysis (HD) patients than in healthy individuals. The aim of this study was to investigate the effect of long term HD on memory types of HD patients. To assess the different type of memory, we used memory parts of the Persian Papers and Pencil Cognitive assessment package (PCAP) and Addenbrooke's Cognitive Examination (ACE-R). Our study included 80 HD patients of whom 39 had less than six months of HD and 41 patients and another group which had a history of HD more than six months. The population had a mean age of 51.60 years old and 27.5% of them were female. The scores of patients who have been hemodialyzed for a long time (median time of HD was up to 4 years) had lower score in anterograde, explicit, visual, recall and recognition memory (5.44±1.07, 9.49±3.472, 22.805±6.6913, 5.59±10.435, 11.02±3.190 score) than the HD patients who underwent HD for a shorter term, where the median time was 3 to 5 months (P<0.01). The regression result shows that, by increasing the HD duration, all memory types are reduced (R2=0.600, P<0.01). The present study demonstrated that HD patients who were under HD for a long time had significantly lower scores in the different types of memory. However, additional researches are needed in this area.

Keywords: Hemodialysis patients, duration of hemodialysis, memory types, Zahedan.

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Authors: Shakirat Abimbola Adesola, Shuaib Akintunde Asifat, Jelili Olalekan Amoo

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This paper presented the impact of students’ emotions on learning when receiving lectures and when taking tests. It was observed during the study that students experience different types of emotions, and this was found to have a significant effect on their academic performance. A total of 1675 students from the department of Computer Science in two Colleges of Education in South-West Nigeria took part in this study. The students were randomly selected for the research. The sample comprises of 968 males representing 58%, and 707 females representing 42%. A structured questionnaire, of Motivated Strategies for Learning Questionnaire (MSLQ) was distributed to the participants to obtain their opinions. Data gathered were analyzed using the IBM SPSS 20 to obtain ANOVA, descriptive analysis, stepwise regression, and reliability tests. The results revealed that emotion moderately shape students’ motivation and engagement in learning; and that self-regulation and self-determination do have significant impact on academic performance. It was further revealed that test anxiety has a significant correlation with academic performance.

Keywords: Motivation, self-determination, test anxiety, academic performance, academic engagement.

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Authors: Despina Galani, Anastasios Alexandridis, Antonios Stavropoulos

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The main thrust of this paper is to assess the level of disclosure in the annual reports of non-financial Greek firms and to empirically investigate the hypothesized impact of several firm characteristics on the extent of mandatory disclosure. A disclosure checklist consisting of 100 mandatory items was developed to assess the level of disclosure in the 2009 annual reports of 43 Greek companies listed at the Athens stock exchange. The association between the level of disclosure and some firm characteristics was examined using multiple linear regression analysis. The study reveals that Greek companies on general have responded adequately to the mandatory disclosure requirements of the regulatory bodies. The findings also indicate that firm size was significant positively associated with the level of disclosure. The remaining variables such as age, profitability, liquidity, and board composition were found to be insignificant in explaining the variation of mandatory disclosures. The outcome of this study is undoubtedly of great concern to the investment community at large to assist in evaluating the extent of mandatory disclosure by Greek firms and explaining the variation of disclosure in light of firm-specific characteristics.

Keywords: Mandatory disclosure, Annual report, Disclosure index

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Authors: N.Peatciyammal, B.Balachandar, M.Dinesh Kumar, K.Tamilarasan, C.Muthukumaran

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Enzymatic hydrolysis of starch from natural sources finds potential application in commercial production of alcoholic beverage and bioethanol. In this study the effect of starch concentration, temperature, time and enzyme concentration were studied and optimized for hydrolysis of Potato starch powder (of mesh 80/120) into glucose syrup by immobilized (using Sodium arginate) α-amylase using central composite design. The experimental result on enzymatic hydrolysis of Potato starch was subjected to multiple linear regression analysis using MINITAB 14 software. Positive linear effect of starch concentration, enzyme concentration and time was observed on hydrolysis of Potato starch by α-amylase. The statistical significance of the model was validated by F-test for analysis of variance (p ≤ 0.01). The optimum value of starch concentration, enzyme concentration, temperature, time and were found to be 6% (w/v), 2% (w/v), 40°C and 80min respectively. The maximum glucose yield at optimum condition was 2.34 mg/mL.

Keywords: Alcoholic beverage, Central Composite Design, Enzymatic hydrolysis, Glucose yield, Potato Starch.

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Authors: Sawcen Chebaane, Hakim Ben Othman

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This paper investigates the effect of International Financial Reporting Standards (IFRS) adoption on the frequency of earnings managements towards small positive profits. We focus on two emerging markets IFRS adopters: South Africa and Turkey. We tested our logistic regression using appropriate panelestimation techniques over a sample of 330 South African and 210 Turkish firm-year observations over the period 2002-2008. Our results document that mandatory adoption of IFRS is not associated with a reduction in earnings management towards small positive profits in emerging markets. These results contradict most of the previous findings of the studies conducted in developed countries. Based on the legal system factor, we compare the intensity of earnings management between a code law country (Turkey) and a common law country (South Africa) over the pre and post-adoption periods. Our findings show that the frequency of such earnings management practice increases significantly for the code law country.

Keywords: Civil law, common law, emerging markets, Mandatory IFRS adoption, small positive profits.

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Authors: Mohamed Moustafa Soliman, Mohamed Abd Elsalam

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Recent financial international scandals around the world have led to a number of investigations into the effectiveness of corporate governance practices and audit quality. Although evidence of corporate governance practices and audit quality exists from developed economies, very scanty studies have been conducted in Egypt where corporate governance is just evolving. Therefore, this study provides evidence on the effectiveness of corporate governance practices and audit quality from a developing country. The data for analysis are gathered from the top 50 most active companies in the Egyptian Stock Exchange, covering the three year period 2007-2009. Logistic regression was used in investigating the questions that were raised in the study. Findings from the study show that board independence; CEO duality and audit committees significantly have relationship with audit quality. The results also, indicate that institutional investor and managerial ownership have no significantly relationship with audit quality. Evidence also exist that size of the company; complexity and business leverage are important factors in audit quality for companies quoted on the Egypt Stock Exchange.

Keywords: Corporate governance, Boards of directors, corporate ownership, Audit Committees, Audit quality, and Egypt.

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Authors: A. Kumar, V. Devadas

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India has the most year-round favorable sunny conditions along with the second-highest solar irradiation in the world, the country holds the potential to become the global solar hub. The solar and wind-based generation capacity has skyrocketed in India with the successful effort of the Ministry of Renewable Energy, whereas the potential of rooftop based solar power generation has yet to be explored for proposed solar cities in India. The research aims to analyze the gap in the energy scenario in Jodhpur City and proposes interventions of solar energy generation systems as a catalyst for urban development. The research is based on the system concept which deals with simulation between the city system as a whole and its interactions between different subsystems. A system-dynamics based mathematical model is developed by identifying the control parameters using regression and correlation analysis to assess the gap in energy sector. The base model validation is done using the past 10 years timeline data collected from secondary sources. Further, energy consumption and solar energy generation-based projection are made for testing different scenarios to conclude the feasibility for maintaining the city level energy independence till 2031.

Keywords: City, consumption, energy, generation.

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Authors: A. K. Al-Othman, F. S. Al-Fares, K. M. EL-Nagger

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This paper presents a new optimization technique based on quantum computing principles to solve a security constrained power system economic dispatch problem (SCED). The proposed technique is a population-based algorithm, which uses some quantum computing elements in coding and evolving groups of potential solutions to reach the optimum following a partially directed random approach. The SCED problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Real Coded Quantum-Inspired Evolution Algorithm (RQIEA) is then applied to solve the constrained optimization formulation. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that RQIEA is very applicable for solving security constrained power system economic dispatch problem (SCED).

Keywords: State Estimation, Fuzzy Linear Regression, FuzzyLinear State Estimator (FLSE) and Measurements Uncertainty.

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Authors: Daniele Losanno, Giorgio Serino

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This paper focuses on parametric analysis of reinforced concrete structures equipped with supplemental damping braces. Practitioners still luck sufficient data for current design of damper added structures and often reduce the real model to a pure damper braced structure even if this assumption is neither realistic nor conservative. In the present study, the damping brace is modelled as made by a linear supporting brace connected in series with the viscous/hysteretic damper. Deformation capacity of existing structures is usually not adequate to undergo the design earthquake. In spite of this, additional dampers could be introduced strongly limiting structural damage to acceptable values, or in some cases, reducing frame response to elastic behavior. This work is aimed at providing useful considerations for retrofit of existing buildings by means of supplemental damping braces. The study explicitly takes into consideration variability of (a) relative frame to supporting brace stiffness, (b) dampers’ coefficient (viscous coefficient or yielding force) and (c) non-linear frame behavior. Non-linear time history analysis has been run to account for both dampers’ behavior and non-linear plastic hinges modelled by Pivot hysteretic type. Parametric analysis based on previous studies on SDOF or MDOF linear frames provide reference values for nearly optimal damping systems design. With respect to bare frame configuration, seismic response of the damper-added frame is strongly improved, limiting deformations to acceptable values far below ultimate capacity. Results of the analysis also demonstrated the beneficial effect of stiffer supporting braces, thus highlighting inadequacy of simplified pure damper models. At the same time, the effect of variable damping coefficient and yielding force has to be treated as an optimization problem.

Keywords: Brace stiffness, dissipative braces, non-linear analysis, plastic hinges, reinforced concrete.

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Authors: Fauziah Hanim Tafri, Zarinah Hamid, Ahamed Kameel Mydin Meera, Mohd Azmi Omar

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This paper examines the relationship between financial risks and profitability of the conventional and Islamic banks in Malaysia for the period between 1996 and 2005. The measures of profitability that have been used in the study are the return on equity (ROE) and return on assets (ROA) while the financial risks are credit risk, interest rate risk and liquidity risks. This study employs panel data regression analysis of Generalised Least Squares of fixed effects and random effects models. It was found that credit risk has a significant impact on ROA and ROE for the conventional as well as the Islamic banks. The relationship between interest rate risk and ROE were found to be weakly significant for the conventional banks and insignificant for the Islamic banks. The effect of interest rate risk on ROA is significant for the conventional banks. Liquidity risk was found to have an insignificant impact on both profitability measures.

Keywords: Credit risk, interest rate risk, liquidity risk, market risk, profitability.

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Authors: S. X. Sun, Q. Wang

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With the rapid development of industrialization, countries in different stages of development in the world have gradually begun to pay attention to the impact of air pollution on health and the environment. Air control in developed countries is an effective reference for air control in developing countries. Artificial intelligence and other technologies also play a positive role in the prediction of air pollution. By comparing the annual changes of pollution in London and Beijing, this paper concludes that the pollution in developed cities is relatively low and stable, while the pollution in Beijing is relatively heavy and unstable, but is clearly improving. In addition, by analyzing the changes of major pollutants in Beijing in the past eight years, it is concluded that all pollutants except O3 show a significant downward trend. In addition, all pollutants except O3 have certain correlation. For example, PM10 and PM2.5 have the greatest influence on air quality index (AQI). Python, which is commonly used by artificial intelligence, is used as the main software to establish two models, support vector machine (SVM) and linear regression. By comparing the two models under the same conditions, it is concluded that SVM has higher accuracy in pollution prediction. The results of this study provide valuable reference for pollution control and prediction in developing countries.

Keywords: Air pollution, particulate matter, AQI, correlation coefficient, air pollution prediction.

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Authors: Pisit Potjanajaruwit

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The objectives of the study were to determine the marketing mix factors that influencing tourist’s destination decision making for cultural tourism in the Chonburi province. Both quantitative and qualitative data were applied in this study. The samples of 400 cases for quantitative analysis were tourists (both Thai and foreign) who were interested in cultural tourism in the Chonburi province, and traveled to cultural sites in Chonburi and 14 representatives from provincial tourism committee of Chonburi and local tourism experts. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. The study found that Thai and foreign tourists are influenced by different important marketing mix factors. The important factors for Thai respondents were physical evidence, price, people, and place at high importance level. For foreign respondents, physical evidence, price, people, and process were high importance level, whereas, product, place and promotion were moderate importance level.

Keywords: Chonburi Province, Decision Making for cultural tourism, Marketing Mixed.

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Authors: Somdech Rungsrisawat

Abstract:

The purpose of this research is to study of consumer perception and understanding consumer buying behavior that related between satisfied and factors affecting the purchasing. Methodology can be classified between qualitative and quantitative approaches for the qualitative research were interviews from middlemen who bought organic vegetables, and middlemen related to production and marketing system. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. The result show the reason to decision buying motives is Fresh products of organic vegetables is the most significant factor on individuals’ income, with a b of –.143, t = –2.470, the price of organic vegetables is the most significant factor on individuals’ income, with a b of .176, t = 2.561, p value = .011. The results show that most people with higher income think about the organic products are expensive and have negative attitudes towards organic vegetable as individuals with low and medium income level. Therefore, household income had a significant influence on the purchasing decision.

Keywords: Consumer behaviors, Consumer perceptions, Organic Vegetable.

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Authors: L. Basha, E. Gjika

Abstract:

The exchange rate is one of the most important economic variables, especially for a small, open economy such as Albania. Its effect is noticeable on one country's competitiveness, trade and current account, inflation, wages, domestic economic activity and bank stability. This study investigates the fluctuation of Albania’s exchange rates using monthly average foreign currency, Euro (Eur) to Albanian Lek (ALL) exchange rate with a time span from January 2008 to June 2021 and the macroeconomic factors that have a significant effect on the exchange rate. Initially, the Random Forest Regression algorithm is constructed to understand the impact of economic variables in the behavior of monthly average foreign currencies exchange rates. Then the forecast of macro-economic indicators for 12 months was performed using time series models. The predicted values received are placed in the random forest model in order to obtain the average monthly forecast of Euro to Albanian Lek (ALL) exchange rate for the period July 2021 to June 2022.

Keywords: Exchange rate, Random Forest, time series, Machine Learning, forecasting.

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