Search results for: multiple stepwise regression analysis

Authors: Manan Aslam, Shafqat Rasool

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This paper attempts to examine impact of major factors affecting marketed surplus of seed cotton in district Khanewal (Punjab) using primary source of data. A representative sample of 40 cotton farmers was selected using stratified random sampling technique. The impact of major factors on marketed surplus of seed cotton growers was estimated by employing double log form of regression analysis. The value of adjusted R2 was 0.64 whereas the F-value was 10.81. The findings of analysis revealed that experience of farmers, education of farmers, area under cotton crop and distance from wholesale market were the significant variables affecting marketed surplus of cotton whereas the variables (marketing cost and sale price) showed insignificant impact. The study suggests improving prevalent marketing practices to increase volume of marketed surplus of cotton in district Khanewal.

Keywords: seed cotton, marketed surplus, double log regression analysis

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Authors: Georgios Charizanos, Haydar Demirhan, Duygu Icen

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Two of the most impactful issues in classical logistic regression are class imbalance and complete separation. These can result in model predictions heavily leaning towards the imbalanced class on the binary response variable or over-fitting issues. Fuzzy methodology offers key solutions for handling these problems. However, most studies propose the transformation of the binary responses into a continuous format limited within [0,1]. This is called the possibilistic approach within fuzzy logistic regression. Following this approach is more aligned with straightforward regression since a logit-link function is not utilized, and fuzzy probabilities are not generated. In contrast, we propose a method of fuzzifying binary response variables that allows for the use of the logit-link function; hence, a probabilistic fuzzy logistic regression model with the Monte Carlo method. The fuzzy probabilities are then classified by selecting a fuzzy threshold. Different combinations of fuzzy and crisp input, output, and coefficients are explored, aiming to understand which of these perform better under different conditions of imbalance and separation. We conduct numerical experiments using both synthetic and real datasets to demonstrate the performance of the fuzzy logistic regression framework against seven crisp machine learning methods. The proposed framework shows better performance irrespective of the degree of imbalance and presence of separation in the data, while the considered machine learning methods are significantly impacted.

Keywords: fuzzy logistic regression, fuzzy, logistic, machine learning

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Authors: Chao-xun Liu, Shi-hong Lu

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In spite of its importance to the aerospace and automobile industries, little or no attention has been devoted to the accurate modeling of the ultrasonic shot peening (USP) process. It is therefore the purpose of this study to conduct finite element analysis of the process using a realistic multiple pin impacts model with the explicit solver of ABAQUS. In this paper, we research the effect of several key parameters on the residual stress distribution within the target, including impact velocity, incident angle, friction coefficient between pins and target and impact number of times were investigated. The results reveal that the impact velocity and impact number of times have obvious effect and impacting vertically could produce the most perfect residual stress distribution. Then we compare the results with the date in USP experiment and verify the exactness of the model. The analysis of the multiple pin impacts date reveal the relationships between peening process parameters and peening quality, which are useful for identifying the parameters which need to be controlled and regulated in order to produce a more beneficial compressive residual stress distribution within the target.

Keywords: ultrasonic shot peening, finite element, multiple pins, residual stress, numerical simulation

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Authors: Dwi Wijiastutik, Tarjo, Yuni Rimawati

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The purpose of this empirical study is to analyse how to the market reaction and the conservative degree changes on the adoption of International Financial Reporting Standart (IFRS) through Jakarta Islamic Index. The study also has given others additional analysis on the profitability, capital structure and size company toward IFRS adoption. The data collection methods used in this study reveals as secondary data and deep analysis to the company’s annual report and daily price stock at yahoo finance. We analyse 40 companies listed on Jakarta Islamic Index from 2010 to 2014. The result of the study concluded that IFRS has given a different on the depth analysis to the two of variance analysis: Moderated Regression Analysis and Wilcoxon Signed Rank to test developed hypotheses. Our result on the regression analysis shows that market response and conservatism principle is not significantly after IFRS Adoption in Jakarta Islamic Index. Furthermore, in addition, analysis on profitability, capital structure, and company size show that significantly after IFRS adoption. The findings of our study help investor by showing the impact of IFRS for making decided investment.

Keywords: IFRS, earnings response coefficient, conservatism principle

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Authors: Taner Ersoz, Filiz Ersoz

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This study was designed enable application of multivariate technique in the interpretation of categorical data for measuring health care services satisfaction in Turkey. The data was collected from a total of 17726 respondents. The establishment of the sample group and collection of the data were carried out by a joint team from The Ministry of Health and Turkish Statistical Institute (Turk Stat) of Turkey. The multiple correspondence analysis (MCA) was used on the data of 2882 respondents who answered the questionnaire in full. The multiple correspondence analysis indicated that, in the evaluation of health services females, public employees, younger and more highly educated individuals were more concerned and complainant than males, private sector employees, older and less educated individuals. Overall 53 % of the respondents were pleased with the improvements in health care services in the past three years. This study demonstrates the public consciousness in health services and health care satisfaction in Turkey. It was found that most the respondents were pleased with the improvements in health care services over the past three years. Awareness of health service quality increases with education levels. Older individuals and males would appear to have lower expectancies in health services.

Keywords: multiple correspondence analysis, multivariate categorical data, health care services, health satisfaction survey

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Authors: Amir M. Shikhli, Refaat H. Abdel-Razek, Salaheddine Bendak

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Innovation is considered to be one of the key factors that influence long-term success of any company. The problem of many organizations in developing countries is trying to implement innovation without a strong basis within the organizational culture to support it. The objective of this study is to assess the effects of organizational culture on innovation in one of the biggest information technology organizations in UAE, Injazat Data System. First, an Organizational Culture Assessment Instrument (OCAI) was used as a survey and Competing Value Framework as a model to analyze the existing culture within the organization and determine its characteristics. Following that, a modified version of the Community Innovation Survey (CIS) was used to determine innovation types introduced by the organization. Then multiple linear regression analysis was used to find out the effects of existing organizational culture on innovation. Results show that existing organizational culture is composed of a combination of Hierarchy (29.4%), Clan (25.8%), Market (24.9%) and Adhocracy (19.9%). Results of the second survey show that the organization focuses on organizational innovation (26.8%) followed by market and product innovations (25.6%) and finally process innovation (22.0%). Regression analysis results reveal that for each innovation type there is a recommended combination of the four culture types. For product innovation, the combination is 47.4% Clan, 17.9% Adhocracy, 1.0% Market and 33.3% Hierarchy; for process innovation it is 19.7% Clan, 45.2% Adhocracy, 32.0% Market and 3.1% Hierarchy; for organizational innovation the combination is 5.4% Clan, 32.7% Adhocracy, 6.0% Market and 55.9% Hierarchy; and for market innovation it is 25.5% Clan, 42.6% Adhocracy, 32.6% Market and 8.4% Hierarchy. Based on these recommended combinations, this study suggests two ways to enhance the innovation culture in the organization. First, if the management decides on the innovation type to be enhanced, a comparison between the existing culture and the recommended combination of selected innovation types will lead to difference in percentages of each culture type. Then further analysis should show how to modify the existing culture to match the recommended combination. Second, if the innovation type is not selected, but the management wants to enhance innovation culture in the organization, the difference in percentages of each culture type will lead to finding out the recommended combination of culture types that gives the narrowest gap between existing culture and recommended combination.

Keywords: developing countries, organizational culture, innovation types, product innovation, process innovation, organizational innovation, marketing innovation

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Authors: Mamta Rajbhar, Sanjay K. Mohanty

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India's progress in achieving replacement level of fertility is largely contingent on fertility reduction in the state of Uttar Pradesh as it accounts 17% of India's population with a low level of development. Though the TFR in the state has declined from 5.1 in 1991 to 3.4 by 2011, it conceals large differences in fertility level across districts. Using data from multiple sources this paper tests the hypothesis that the improvement in human development significantly reduces the fertility levels in districts of Uttar Pradesh. The unit of analyses is district, and fertility estimates are derived using the reverse survival method(RSM) while human development indices(HDI) are are estimated using uniform methodology adopted by UNDP for three period. The correlation and linear regression models are used to examine the relationship of fertility change and human development indices across districts. Result show the large variation and significant change in fertility level among the districts of Uttar Pradesh. During 1991-2011, eight districts had experienced a decline of TFR by 10-20%, 30 districts by 20-30% and 32 districts had experienced decline of more than 30%. On human development aspect, 17 districts recorded increase of more than 0.170 in HDI, 18 districts in the range of 0.150-0.170, 29 districts between 0.125-0.150 and six districts in the range of 0.1-0.125 during 1991-2011. Study shows significant negative relationship between HDI and TFR. HDI alone explains 70% variation in TFR. Also, the regression coefficient of TFR and HDI has become stronger over time; from -0.524 in 1991, -0.7477 by 2001 and -0.7181 by 2010. The regression analyses indicate that 0.1 point increase in HDI value will lead to 0.78 point decline in TFR. The HDI alone explains 70% variation in TFR. Improving the HDI will certainly reduce the fertility level in the districts.

Keywords: Fertility, HDI, Uttar Pradesh

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Authors: Thi Thi Zin, Pyke Tin, Ikuo Kobayashi, Yoichiro Horii

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Today dairy farm experts and farmers have well recognized the importance of dairy cow Body Condition Score (BCS) since these scores can be used to optimize milk production, managing feeding system and as an indicator for abnormality in health even can be utilized to manage for having healthy calving times and process. In tradition, BCS measures are done by animal experts or trained technicians based on visual observations focusing on pin bones, pin, thurl and hook area, tail heads shapes, hook angles and short and long ribs. Since the traditional technique is very manual and subjective, the results can lead to different scores as well as not cost effective. Thus this paper proposes an algebraic geometric imaging approach for an automatic dairy cow BCS system. The proposed system consists of three functional modules. In the first module, significant landmarks or anatomical points from the cow image region are automatically extracted by using image processing techniques. To be specific, there are 23 anatomical points in the regions of ribs, hook bones, pin bone, thurl and tail head. These points are extracted by using block region based vertical and horizontal histogram methods. According to animal experts, the body condition scores depend mainly on the shape structure these regions. Therefore the second module will investigate some algebraic and geometric properties of the extracted anatomical points. Specifically, the second order polynomial regression is employed to a subset of anatomical points to produce the regression coefficients which are to be utilized as a part of feature vector in scoring process. In addition, the angles at thurl, pin, tail head and hook bone area are computed to extend the feature vector. Finally, in the third module, the extracted feature vectors are trained by using Markov Classification process to assign BCS for individual cows. Then the assigned BCS are revised by using multiple regression method to produce the final BCS score for dairy cows. In order to confirm the validity of proposed method, a monitoring video camera is set up at the milk rotary parlor to take top view images of cows. The proposed method extracts the key anatomical points and the corresponding feature vectors for each individual cows. Then the multiple regression calculator and Markov Chain Classification process are utilized to produce the estimated body condition score for each cow. The experimental results tested on 100 dairy cows from self-collected dataset and public bench mark dataset show very promising with accuracy of 98%.

Keywords: algebraic geometric imaging approach, body condition score, Markov classification, polynomial regression

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Authors: Suphaphon Udomluck, Pannathorn Chachvarat

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Information Communication Technology (ICT) using management is essential for effective decision making in organization. The Concerns Based Adoption Model (CBAM) was employed as the conceptual framework. The purposes of the study were to assess the situation of Information Communication Technology (ICT) using management in College of Nursing under the Praboromarajchanok Institute. The samples were multi – stage sampling of 10 colleges of nursing that participated include directors, vice directors, head of learning groups, teachers, system administrator and responsible for ICT. The total participants were 280; the instrument used were questionnaires that include 4 parts, general information, Information Communication Technology (ICT) using management, the Stage of concern Questionnaires (SoC), and the Levels of Use (LoU) ICT Questionnaires respectively. Reliability coefficients were tested; alpha coefficients were 0.967for Information Communication Technology (ICT) using management, 0.884 for SoC and 0.945 for LoU. The data were analyzed by frequency, percentage, mean, standard deviation, Pearson Product Moment Correlation and Multiple Regression. They were founded as follows: The high level overall score of Information Communication Technology (ICT) using management and issue were administration, hardware, software, and people. The overall score of the Stage of concern (SoC)ICTis at high level and the overall score of the Levels of Use (LoU) ICTis at moderate. The Information Communication Technology (ICT) using management had the positive relationship with the Stage of concern (SoC)ICTand the Levels of Use (LoU) ICT(p < .01). The results of Multiple Regression revealed that administration hardwear, software and people ware could predict SoC of ICT (18.5%) and LoU of ICT (20.8%).The factors that were significantly influenced by SoCs were people ware. The factors that were significantly influenced by LoU of ICT were administration hardware and people ware.

Keywords: information communication technology (ICT), management, the concerns-based adoption model (CBAM), stage of concern(SoC), the levels of use(LoU)

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Authors: Sungkyung Kim, Jee-Hyeon Na, Dong-Seung Kwon

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Future mobile networks following 5th generation will be characterized by one thousand times higher gains in capacity; connections for at least one hundred billion devices; user experience capable of extremely low latency and response times. To be close to the capacity requirements and higher reliability, advanced technologies have been studied, such as multiple connectivity, small cell enhancement, heterogeneous networking, and advanced interference and mobility management. This paper is focused on the multiple connectivity in heterogeneous cellular networks. We investigate the performance of coverage and user throughput in several deployment scenarios. Using the stochastic geometry approach, the SINR distributions and the coverage probabilities are derived in case of dual connection. Also, to compare the user throughput enhancement among the deployment scenarios, we calculate the spectral efficiency and discuss our results.

Keywords: heterogeneous networks, multiple connectivity, small cell enhancement, stochastic geometry

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Authors: Sergio Haram Sarmiento, Arcady Ponosov

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Based on appropriate multivariate statistical methodology, we suggest a generic framework for efficient parameter estimation for ordinary differential equations and the corresponding nonlinear models. In this framework classical linear regression strategies is refined into a nonlinear regression by a locally linear modelling technique (known as metamodelling). The approach identifies those latent variables of the given model that accumulate most information about it among all approximations of the same dimension. The method is applied to several benchmark problems, in particular, to the so-called ”power-law systems”, being non-linear differential equations typically used in Biochemical System Theory.

Keywords: principal component analysis, generalized law of mass action, parameter estimation, metamodels

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Authors: Taksina Bunbut

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Personality and grooming are vital for creating professionalism and safety image for all staffs in the airline industry. Airline Business Program also has an aim to educate students through the subject Personality Development and Grooming in order to elevate the quality of students to meet standard requirements of the airline industry. However, students agree that there are many difficulties that cause unsuccessful learning experience in this subject. The research is to study problems that can afflict students from getting good results in the classroom. Furthermore, exploring possible solutions to overcome challenges are also included in this study. The research sample consists of 140 students who attended the class of Personality Development and Grooming. The employed research instrument is a questionnaire. Statistic for data analysis is t-test and Multiple Regression Analysis. The result found that although students are satisfied with teaching and learning of this subject, they considered that teaching in English and teaching topics in social etiquette in different cultures are difficult for them to understand.

Keywords: personality development, grooming, Airline Business Program, soft skill

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Authors: Ammar Asma, Bouafia Nabiha, Ghammam Rim, Ezzi Olfa, Ben Cheikh Asma, Mahjoub Mohamed, Helali Radhia, Sma Nesrine, Chouchène Imed, Boussarsar Hamadi, Njah Mansour

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Background: Central venous catheter associated infections (CVC-AI) are among the serious hospital-acquired infections. The aims of this study are to determine the incidence of CVC-AI, and their risk factors among patients followed in a Tunisian medical intensive care unit (ICU). Materials / Methods: A prospective cohort study conducted between September 15th, 2015 and November 15th, 2016 in an 8-bed medical ICU including all patients admitted for more than 48h. CVC-AI were defined according to CDC of ATLANTA criteria. The enrollment was based on clinical and laboratory diagnosis of CVC-AI. For all subjects, age, sex, underlying diseases, SAPS II score, ICU length of stay, exposure to CVC (number of CVC placed, site of insertion and duration catheterization) were recorded. Risk factors were analyzed by conditional stepwise logistic regression. The p-value of < 0.05 was considered significant. Results: Among 192 eligible patients, 144 patients (75%) had a central venous catheter. Twenty-eight patients (19.4%) had developed CVC-AI with density rate incidence 20.02/1000 CVC-days. Among these infections, 60.7% (n=17) were systemic CVC-AI (with negative blood culture), and 35.7% (n=10) were bloodstream CVC-AI. The mean SAPS II of patients with CVC-AI was 32.76 14.48; their mean Charlson index was 1.77 1.55, their mean duration of catheterization was 15.46 10.81 days and the mean duration of one central line was 5.8+/-3.72 days. Gram-negative bacteria was determined in 53.5 % of CVC-AI (n= 15) dominated by multi-drug resistant Acinetobacter baumani (n=7). Staphylococci were isolated in 3 CVC-AI. Fourteen (50%) patients with CVC-AI died. Univariate analysis identified men (p=0.034), the referral from another hospital department (p=0.03), tobacco (p=0.006), duration of sedation (p=0.003) and the duration of catheterization (p=0), as possible risk factors of CVC-AI. Multivariate analysis showed that independent factors of CVC-AI were, male sex; OR= 5.73, IC 95% [2; 16.46], p=0.001, Ramsay score; OR= 1.57, IC 95% [1.036; 2.38], p=0.033, and duration of catheterization; OR=1.093, IC 95% [1.035; 1.15], p=0.001. Conclusion: In a monocenter cohort, CVC-AI had a high density and is associated with poor outcome. Identifying the risk factors is necessary to find solutions for this major health problem.

Keywords: central venous catheter associated infection, intensive care unit, prospective cohort studies, risk factors

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Authors: Amornchai Challcharoenwattana, Chanathip Pharino

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Rising amount of MSW every day, maximizing material diversions from landfills via recycling is a prefer method to land dumping. Characteristic of Thai MSW is classified as 40 -60 per cent compostable wastes while potentially recyclable materials in waste streams are composed of plastics, papers, glasses, and metals. However, rate of material recovery from MSW, excluding composting or biogas generation, in Thailand is still low. Thailand’s recycling rate in 2010 was only 20.5 per cent. Central government as well as local governments in Thailand have tried to curb this problem by charging some of MSW management fees at the users. However, the fee is often too low to promote MSW minimization. The objective of this paper is to identify levels of willingness-to-pay (WTP) for MSW recycling in different social structures with expected outcome of sustainable MSW managements for different town settlements to maximize MSW recycling pertaining to each town’s potential. The method of eliciting WTP is a payment card. The questionnaire was deployed using online survey during December 2012. Responses were categorized into respondents living in Bangkok, living in other municipality areas, or outside municipality area. The responses were analysed using descriptive statistics, and multiple linear regression analysis to identify relationships and factors that could influence high or low WTP. During the survey period, there were 168 filled questionnaires from total 689 visits. However, only 96 questionnaires could be usable. Among respondents in the usable questionnaires, 36 respondents lived in within the boundary of Bangkok Metropolitan Administration while 45 respondents lived in the chartered areas that were classified as other municipality but not in BMA. Most of respondents were well-off as 75 respondents reported positive monthly cash flow (77.32%), 15 respondents reported neutral monthly cash flow (15.46%) while 7 respondent reported negative monthly cash flow (7.22%). For WTP data including WTP of 0 baht with valid responses, ranking from the highest means of WTP to the lowest WTP of respondents by geographical locations for good MSW management were Bangkok (196 baht/month), municipalities (154 baht/month), and non-urbanized towns (111 baht/month). In-depth analysis was conducted to analyse whether there are additional room for further increase of MSW management fees from the current payment that each correspondent is currently paying. The result from multiple-regression analysis suggested that the following factors could impacts the increase or decrease of WTP: incomes, age, and gender. Overall, the outcome of this study suggests that survey respondents are likely to support improvement of MSW treatments that are not solely relying on landfilling technique. Recommendations for further studies are to obtain larger sample sizes in order to improve statistical powers and to provide better accuracy of WTP study.

Keywords: MSW, willingness to pay, payment card, waste seperation

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Authors: Paul Han, Jun-Geol Baek

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In the flat panel display industry, the scheduler and dispatching system to meet production target quantities and the deadline of production are the major production management system which controls each facility production order and distribution of WIP (Work in Process). In dispatching system, delivery time is a key factor for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors and a forecasting model of delivery time. Of survival analysis techniques to select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the Accelerated Failure Time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the Mean Square Error (MSE) criteria, the AFT model decreased by 33.8% compared to the existing prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing a delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.

Keywords: delivery time, survival analysis, Cox PH model, accelerated failure time model

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Authors: Ali A. Abdollahi

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During the last several decades, scientists have consistently applied Multiple Criteria Decision-Making methods in making decisions about multi-faceted, complicated subjects. While making such decisions and in order to achieve more accurate evaluations, they have regularly used a variety of criteria instead of applying just one Optimum Evaluation Criterion. The method presented here utilizes both ‘quantity’ and ‘quality’ to assess the function of the Multiple-Criteria method. Applying Data envelopment analysis (DEA), weighted aggregated sum product assessment (WASPAS), Weighted Sum Approach (WSA), Analytic Network Process (ANP), and Charnes, Cooper, Rhodes (CCR) methods, we have analyzed thirteen parks in Kerman city. It further indicates that the functions of WASPAS and WSA are compatible with each other, but also that their deviation from DEA is extensive. Finally, the results for the CCR technique do not match the results of the DEA technique. Our study indicates that the ANP method, with the average rate of 1/51, ranks closest to the DEA method, which has an average rate of 1/49.

Keywords: multiple criteria decision making, Data envelopment analysis (DEA), Charnes Cooper Rhodes (CCR), Weighted Sum Approach (WSA)

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Authors: Azam Mohammadbagheri, Bahram Fathi

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DEA has become a very popular method of performance measure, but it still suffers from some shortcomings. One of these shortcomings is the issue of having multiple optimal solutions to weights for efficient DMUs. The cross efficiency evaluation as an extension of DEA is proposed to avoid this problem. Lam (2010) is also proposed a mixed-integer linear programming formulation based on linear discriminate analysis and super efficiency method (MILP model) to avoid having multiple optimal solutions to weights. In this study, we modified MILP model to determine more suitable weight sets and also evaluate the energy efficiency of MENA countries as an application of the proposed model.

Keywords: data envelopment analysis, discriminate analysis, cross efficiency, MILP model

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Authors: Mina Adel Shokry Fahim, Jūratė Sužiedelytė Visockienė

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With the growing concern over air pollution (AP), it is clear that this has gained more prominence than ever before. The level of consciousness has increased and a sense of knowledge now has to be forwarded as a duty by those enlightened enough to disseminate it to others. This realisation often comes after an understanding of how poor air quality indices (AQI) damage human health. The study focuses on assessing air pollution prediction models specifically for Lithuania, addressing a substantial need for empirical research within the region. Concentrating on Vilnius, it specifically examines particulate matter concentrations 10 micrometers or less in diameter (PM10). Utilizing Gaussian Process Regression (GPR) and Regression Tree Ensemble, and Regression Tree methodologies, predictive forecasting models are validated and tested using hourly data from January 2020 to December 2022. The study explores the classification of AP data into anthropogenic and natural sources, the impact of AP on human health, and its connection to cardiovascular diseases. The study revealed varying levels of accuracy among the models, with GPR achieving the highest accuracy, indicated by an RMSE of 4.14 in validation and 3.89 in testing.

Keywords: air pollution, anthropogenic and natural sources, machine learning, Gaussian process regression, tree ensemble, forecasting models, particulate matter

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Authors: Kiurski S. Jelena, Kecić S. Vesna, Aksentijević M. Snežana

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Samples of tap and wastewater were collected in three offset printing facilities in Novi Sad, Serbia. Ten physicochemical parameters were analyzed within all collected samples: pH, conductivity, m - alkalinity, p - alkalinity, acidity, carbonate concentration, hydrogen carbonate concentration, active oxygen content, chloride concentration and total alkali content. All measurements were conducted using the standard analytical and instrumental methods. Comparing the obtained results for tap water and wastewater, a clear quality difference was noticeable, since all physicochemical parameters were significantly higher within wastewater samples. The study also involves the application of simple linear regression analysis on the obtained dataset. By using software package ORIGIN 5 the pH value was mutually correlated with other physicochemical parameters. Based on the obtained values of Pearson coefficient of determination a strong positive correlation between chloride concentration and pH (r = -0.943), as well as between acidity and pH (r = -0.855) was determined. In addition, statistically significant difference was obtained only between acidity and chloride concentration with pH values, since the values of parameter F (247.634 and 182.536) were higher than F_critical (5.59). In this way, results of statistical analysis highlighted the most influential parameter of water contamination in offset printing, in the form of acidity and chloride concentration. The results showed that variable dependence could be represented by the general regression model: y = a₀ + a₁x+ k, which further resulted with matching graphic regressions.

Keywords: pollution, printing industry, simple linear regression analysis, wastewater

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Authors: Amit Das

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Background and significance of the study: Generally investors and market forecasters use financial statement for investigation while it awakens contribute to investing. The main vicinity of financial accounting and reporting practices recommends a few basic financial performance indicators, namely, return on capital employed, return on assets and earnings per share, which is associated considerably with share prices. It is principally true in case of Indian pharmaceutical companies also. Share investing is intriguing a financial risk in addition to investors look for those financial evaluations which have noteworthy shock on share price. A crucial intention of financial statement analysis and reporting is to offer information which is helpful predominantly to exterior clients in creating credit as well as investment choices. Sound financial performance attracts the investors automatically and it will increase the share price of the respective companies. Keeping in view of this, this research work investigates the impact of financial performance indicators on share price of pharmaceutical companies in India which is listed in the Bombay Stock Exchange. Methodology: This research work is based on secondary data collected from moneycontrol database on September 28, 2015 of top 101 pharmaceutical companies in India. Since this study selects four financial performance indicators purposively and availability in the database, that is, earnings per share, return on capital employed, return on assets and net profits as independent variables and one dependent variable, share price of 101 pharmaceutical companies. While analysing the data, correlation statistics, multiple regression technique and appropriate test of significance have been used. Major findings: Correlation statistics show that four financial performance indicators of 101 pharmaceutical companies are associated positively and negatively with its share price and it is very much significant that more than 80 companies’ financial performances are related positively. Multiple correlation test results indicate that financial performance indicators are highly related with share prices of the selected pharmaceutical companies. Furthermore, multiple regression test results illustrate that when financial performances are good, share prices have been increased steadily in the Bombay stock exchange and all results are statistically significant. It is more important to note that sensitivity indices were changed slightly through financial performance indicators of selected pharmaceutical companies in India. Concluding statements: The share prices of pharmaceutical companies depend on the sound financial performances. It is very clear that share prices are changed with the movement of two important financial performance indicators, that is, earnings per share and return on assets. Since 101 pharmaceutical companies are listed in the Bombay stock exchange and Sensex are changed with this, it is obvious that Government of India has to take important decisions regarding production and exports of pharmaceutical products so that financial performance of all the pharmaceutical companies are improved and its share price are increased positively.

Keywords: financial performance indicators, share prices, pharmaceutical companies, India

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Authors: Yazan Khalid Abed-Allah Migdadi

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The aim of this study is identifying the effective operations competitive advantages of mobile phone service providers across countries. All Arab countries in the Middle East region were surveyed except Syria, and 27 out of 31 service providers were surveyed. Data collected from corporations’ annual reports, websites and other professional institutions published sources. Multiple linear regression analysis test was used to identify the relationship between operations competitive advantages and market share. The effective operations competitive advantages were; diversity of offers and service accessibility

Keywords: competitive advantage, mobile telecommunication operations, Middle East, service provider

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Authors: Jiexuan Lin, Huiyi Chen

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The development of L2 pronunciation competence remains understudied in the literature and it is not clear what may influence learners’ development of L2 pronunciation. The present study was an attempt to find out which of the two common factors in L2 acquisition, i.e., foreign language anxiety or self-perceived L2 proficiency, can better predict Chinese EFL learners’ pronunciation performance. 78 first-year English majors, who had received a three-month pronunciation training course, were asked to 1) fill out a questionnaire on foreign language classroom anxiety, 2) self-report their L2 proficiency in general, in speaking and in pronunciation, and 3) complete an oral and a written test on their L2 pronunciation (the score of the oral part indicates participants’ pronunciation proficiency in oral production, and the score of the written part indexes participants’ ability in applying pronunciation knowledge in comprehension.) Results showed that the pronunciation scores were negatively correlated with the anxiety scores, and were positively correlated with the self-perceived pronunciation proficiency. But only the written scores in the L2 pronunciation test, not the oral scores, were positively correlated with the L2 self-perceived general proficiency. Neither the oral nor the written scores in the L2 pronunciation test had a significant correlation with the self-perceived speaking proficiency. Given the fairly strong correlations, the anxiety scores and the self-perceived pronunciation proficiency were put in regression models to predict L2 pronunciation performance. The anxiety factor alone accounted for 13.9% of the variance and the self-perceived pronunciation proficiency alone explained 12.1% of the variance. But when both anxiety scores and self-perceived pronunciation proficiency were put in a stepwise regression model, only the anxiety scores had a significant and unique contribution to the L2 pronunciation performance (4.8%). Taken together, the results suggested that the learners’ anxiety level could better predict their L2 pronunciation performance, compared with the self-perceived proficiency levels. The obtained data have the following pedagogical implications. 1) Given the fairly strong correlation between anxiety and L2 pronunciation performance, the instructors who are interested in predicting learners’ L2 pronunciation proficiency may measure their anxiety level, instead of their proficiency, as the predicting variable. 2) The correlation of oral scores (in the pronunciation test) with pronunciation proficiency, rather than with speaking proficiency, indicates that a) learners after receiving some amounts of training are to some extent able to evaluate their own pronunciation ability, implying the feasibility of incorporating self-evaluation and peer comments in course instruction; b) the ‘proficiency’ measure used to predict pronunciation performance should be used with caution. The proficiency of specific skills seemingly highly related to pronunciation (i.e., speaking in this case) may not be taken for granted as an effective predictor for pronunciation performance. 3) The correlation between the written scores with general L2 proficiency is interesting.

Keywords: anxiety, Chinese EFL learners, L2 pronunciation, self-perceived L2 proficiency

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Authors: İsmail İnce

Abstract:

The aim of this study is to determine index and mechanical properties of pyroclastic rock in a practical way by means of electrical resistivity method. For this purpose, electrical resistivity, uniaxial compressive strength, point load strength, P-wave velocity, density and porosity values of 10 different pyroclastic rocks were measured in the laboratory. A simple regression analysis was made among the index-mechanical properties of the samples compatible with electrical resistivity values. A strong exponentially relation was found between index-mechanical properties and electrical resistivity values. The electrical resistivity method can be used to assess the engineering properties of the rock from which it is difficult to obtain regular shaped samples as a non-destructive method.

Keywords: electrical resistivity, index-mechanical properties, pyroclastic rocks, regression analysis

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Authors: Y. de Smet, J. Hubinont

Abstract:

PROMETHEE and GAIA are well-known Multiple Criteria Decision Aid methods. Given an evaluation table and preference parameters they allow to rank the alternatives, to visualize the problem, to perform sensitivity and robustness analysis, etc. Unfortunately, it is often hard for the Decision Maker (DM) to estimate the precise values of these parameters. Therefore an alternative option is to give ranges of potential values in order to apply Stochastic Multicriteria Acceptability Analysis. This has been recently studied in the context of the SMAA-PROMETHEE method. The aim of this contribution is to propose an SMAA extension of GAIA. We show how this tool can be useful and provide complementary information to SMAA-PROMETHEE. This is illustrated on a pedagogical example.

Keywords: multiple criteria decision making, PROMETHEE, GAIA, SMAA

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Authors: Y. Rathiranee, D. M. Semasinghe

Abstract:

This study attempts to identify the factors influencing on women empowerment of rural area in Sri Lanka through micro finance services. Data were collected from one hundred (100) rural women involving self employment activities through a questionnaire using direct personal interviews. Judgment and Convenience Random sampling technique was used to select the sample size from three Divisional Secretariat divisions of Kandawalai, Poonakari and Karachchi in Kilinochchi District. The factor analysis was performed on fourteen (14) variables for screening and reducing the variables to identify the influencing factors on empowerment. Multiple regression analysis was used to identify the relationship between the three empowerment factors and the impact of micro-finance on overall empowerment of rural women. The result of this study summarized the variables into three factors namely decision making, freedom to mobility and family support and which are positively associated with empowerment. In addition to this the value of adjusted R2 is 0.248 indicates that all the variables extracted can be explained 24.8% of the variation in the women empowerment through microfinance. Independent variables of these three factors have a positive correlation with women empowerment as well as significant values at 5 percent level.

Keywords: influencing factors, micro finance, rural women, women empowerment

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Authors: Leng Jian-Wei, Wang Lai-Jun, Li Ye

Abstract:

In order to measure and analyze the transportation situation within the counties of Shaanxi province over a certain period of time and to promote the province's future transportation planning and development, this paper proposes a reasonable layout plan and compares model rationality. The study uses entropy weight method to measure the transportation advantages of 107 counties in Shaanxi province from three dimensions: road network density, trunk line influence and location advantage in 2013 and 2021, and applies spatial autocorrelation analysis method to analyze the spatial layout and development trend of county-level transportation, and conducts ordinary least square (OLS)regression on transportation impact factors and other influencing factors. The paper also compares the regression fitting degree of the Geographically weighted regression(GWR) model and the OLS model. The results show that spatially, the transportation advantages of Shaanxi province generally show a decreasing trend from the Weihe Plain to the surrounding areas and mainly exhibit high-high clustering phenomenon. Temporally, transportation advantages show an overall upward trend, and the phenomenon of spatial imbalance gradually decreases. People's travel demands have changed to some extent, and the demand for rapid transportation has increased overall. The GWR model regression fitting degree of transportation advantages is 0.74, which is higher than the OLS regression model's fitting degree of 0.64. Based on the evolution of transportation advantages, it is predicted that this trend will continue for a period of time in the future. To improve the transportation advantages of Shaanxi province increasing the layout of rapid transportation can effectively enhance the transportation advantages of Shaanxi province. When analyzing spatial heterogeneity, geographic factors should be considered to establish a more reliable model

Keywords: traffic dominance, GWR model, spatial autocorrelation analysis, temporal and spatial evolution

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Authors: Wanida Suwunniponth

Abstract:

The purpose of this research was to investigate the relationship between the factors of using online social network for tourism destination in case of Bangkok area in Thailand, by extending the use of technology acceptance model (TAM). This study employed by quantitative research and the target population were entrepreneurs and local people in Bangkok who use social network-Facebook concerning tourist destinations in Bangkok. Questionnaire was used to collect data from 300 purposive samples. The multiple regression analysis and path analysis were used to analyze data. The results revealed that most people who used Facebook for promoting tourism destinations in Bangkok perceived ease of use, perceived usefulness, perceived trust in using Facebook and influenced by social normative as well as having positive attitude towards using this application. Addition, the hypothesis results indicate that acceptance of online social network-Facebook was related to the positive attitude towards using of Facebook and related to their intention to use this application for tourism.

Keywords: Facebook, online social network, technology acceptance model, tourism destination

Procedia PDF Downloads 343

Authors: Strahinja Z. Kovačević, Lidija R. Jevrić, Sanja O. Podunavac Kuzmanović

Abstract:

The relationship between antibacterial activity of eighteen different substituted benzimidazole derivatives and their molecular characteristics was studied using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on inhibitory activity towards Staphylococcus aureus, by using molecular descriptors, as well as minimal inhibitory activity (MIC). Molecular descriptors were calculated from the optimized structures. Principal component analysis (PCA) followed by hierarchical cluster analysis (HCA) and multiple linear regression (MLR) was performed in order to select molecular descriptors that best describe the antibacterial behavior of the compounds investigated, and to determine the similarities between molecules. The HCA grouped the molecules in separated clusters which have the similar inhibitory activity. PCA showed very similar classification of molecules as the HCA, and displayed which descriptors contribute to that classification. MLR equations, that represent MIC as a function of the in silico molecular descriptors were established. The statistical significance of the estimated models was confirmed by standard statistical measures and cross-validation parameters (SD = 0.0816, F = 46.27, R = 0.9791, R2CV = 0.8266, R2adj = 0.9379, PRESS = 0.1116). These parameters indicate the possibility of application of the established chemometric models in prediction of the antibacterial behaviour of studied derivatives and structurally very similar compounds.

Keywords: antibacterial, benzimidazole, molecular descriptors, QSAR

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Authors: M. Miljkovic, A. Urakpo, M. Simic-Koumoutsaris

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Benefit-risk assessment (BRA) is a valuable tool that takes place in multiple stages during a medicine's lifecycle, and this assessment can be conducted in a variety of ways. The aim was to summarize current BRA methods used during approval decisions and in post-approval settings and to see possible future directions. Relevant reviews, recommendations, and guidelines published in medical literature and through regulatory agencies over the past five years have been examined. BRA implies the review of two dimensions: the dimension of benefits (determined mainly by the therapeutic efficacy) and the dimension of risks (comprises the safety profile of a drug). Regulators, industry, and academia have developed various approaches, ranging from descriptive textual (qualitative) to decision-analytic (quantitative) models, to facilitate the BRA of medicines during the product lifecycle (from Phase I trials, to authorization procedure, post-marketing surveillance and health technology assessment for inclusion in public formularies). These approaches can be classified into the following categories: stepwise structured approaches (frameworks); measures for benefits and risks that are usually endpoint specific (metrics), simulation techniques and meta-analysis (estimation techniques), and utility survey techniques to elicit stakeholders’ preferences (utilities). All these approaches share the following two common goals: to assist this analysis and to improve the communication of decisions, but each is subject to its own specific strengths and limitations. Before using any method, its utility, complexity, the extent to which it is established, and the ease of results interpretation should be considered. Despite widespread and long-time use, BRA is subject to debate, suffers from a number of limitations, and currently is still under development. The use of formal, systematic structured approaches to BRA for regulatory decision-making and quantitative methods to support BRA during the product lifecycle is a standard practice in medicine that is subject to continuous improvement and modernization, not only in methodology but also in cooperation between organizations.

Keywords: benefit-risk assessment, benefit-risk profile, product lifecycle, quantitative methods, structured approaches

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Authors: Hua Cao, Laurent Peyrodie, Olivier Agnani, Cecile Donze

Abstract:

Multiple sclerosis (MS) is a disease, which affects the central nervous system, and causes balance problem. In clinical, this disorder is usually evaluated using static posturography. Some linear or nonlinear measures, extracted from the posturographic data (i.e. center of pressure, COP) recorded during a balance test, has been used to analyze postural control of MS patients. In this study, the trend (TREND) and the sample entropy (SampEn), two nonlinear parameters were chosen to investigate their relationships with the expanded disability status scale (EDSS) score. Forty volunteers with different EDSS scores participated in our experiments with eyes open (EO) and closed (EC). TREND and two types of SampEn (SampEn1 and SampEn2) were calculated for each combined COP’s position signal. The results have shown that TREND had a weak negative correlation to EDSS while SampEn2 had a strong positive correlation to EDSS. Compared to TREND and SampEn1, SampEn2 showed a better significant correlation to EDSS and an ability to discriminate the MS patients in the EC case. In addition, the outcome of the study suggests that the multi-dimensional nonlinear analysis could provide some information about the impact of disability progression in MS on dynamics of the COP data.

Keywords: balance, multiple sclerosis, nonlinear analysis, postural sway

Procedia PDF Downloads 338