Search results for: multiple stepwise regression analysis

Authors: Fredrick Olatunji Ajegbomogun, Bello Modinat Morenikeji, Okorie Nancy Chituru

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Electronic information resources are highly relevant to students' academic and research needs but are grossly underutilized, despite the institutional commitment to making them available. The under-utilisation of these resources could be attributed to a low level of study behaviour coupled with a low level of computer self-efficacy. This study assessed computer self-efficacy, study behaviour, and the use of electronic information resources by students in selected polytechnics in Ogun State. A simple random sampling technique using Krejcie and Morgan's (1970) Table was used to select 370 respondents for the study. A structured questionnaire was used to collect data on respondents. Data were analysed using frequency counts, percentages, mean, standard deviation, Pearson Product Moment Correlation (PPMC) and multiple regression analysis. Results reveal that the internet (= 1.94), YouTube (= 1.74), and search engines (= 1.72) were the common information resources available to the students, while the Internet (= 4.22) is the most utilized resource. Major reasons for using electronic information resources were to source materials and information (= 3.30), for research (= 3.25), and to augment class notes (= 2.90). The majority (91.0%) of the respondents have a high level of computer self-efficacy in the use of electronic information resources through selecting from screen menus (= 3.12), using data files ( = 3.10), and efficient use of computers (= 3.06). Good preparation for tests (= 3.27), examinations (= 3.26), and organization of tutorials (= 3.11) are the common study behaviours of the respondents. Overall, 93.8% have good study behaviour. Inadequate computer facilities to access information (= 3.23), and poor internet access (= 2.87) were the major challenges confronting students’ use of electronic information resources. According to the PPMC results, study behavior (r = 0.280) and computer self-efficacy (r = 0.304) have significant (p 0.05) relationships with the use of electronic information resources. Regression results reveal that self-efficacy (=0.214) and study behavior (=0.122) positively (p 0.05) influenced students' use of electronic information resources. The study concluded that students' use of electronic information resources depends on the purpose, their computer self-efficacy, and their study behaviour. Therefore, the study recommended that the management should encourage the students to improve their study habits and computer skills, as this will enhance their continuous and more effective utilization of electronic information resources.

Keywords: computer self-efficacy, study behaviour, electronic information resources, polytechnics, Nigeria

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Authors: Komal Babbar

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Multiuser Detection is the intelligent estimation/demodulation of transmitted bits in the presence of Multiple Access Interference. The authors have presented the Bit-error rate (BER) achieved by linear multi-user detectors: Matched filter (which treats the MAI as AWGN), Decorrelating and MMSE. In this work, authors investigate the bit error probability analysis for Matched filter, decorrelating, and MMSE. This problem arises in several practical CDMA applications where the receiver may not have full knowledge of the number of active users and their signature sequences. In particular, the behavior of MAI at the output of the Multi-user detectors (MUD) is examined under various asymptotic conditions including large signal to noise ratio; large near-far ratios; and a large number of users. In the last section Authors also shows Matlab Simulation results for Multiuser detection techniques i.e., Matched filter, Decorrelating, MMSE for 2 users and 10 users.

Keywords: code division multiple access, decorrelating, matched filter, minimum mean square detection (MMSE) detection, multiple access interference (MAI), multiuser detection (MUD)

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Authors: Laidi Maamar, Achwak Madani, Abdellah El Ahdj Abdellah

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The aim of this work is to use Support Vector regression (SVR) combined with dragonfly, firefly, Bee Colony and particle swarm Optimization algorithm to predict global solar radiation on horizontal surfaces in some cities in Algeria. Combining these optimization algorithms with SVR aims principally to enhance accuracy by fine-tuning the parameters, speeding up the convergence of the SVR model, and exploring a larger search space efficiently; these parameters are the regularization parameter (C), kernel parameters, and epsilon parameter. By doing so, the aim is to improve the generalization and predictive accuracy of the SVR model. Overall, the aim is to leverage the strengths of both SVR and optimization algorithms to create a more powerful and effective regression model for various cities and under different climate conditions. Results demonstrate close agreement between predicted and measured data in terms of different metrics. In summary, SVM has proven to be a valuable tool in modeling global solar radiation, offering accurate predictions and demonstrating versatility when combined with other algorithms or used in hybrid forecasting models.

Keywords: support vector regression (SVR), optimization algorithms, global solar radiation prediction, hybrid forecasting models

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Authors: Sixing Chen, Shuai Yang

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Online celebrity business, also known as Internet celebrity business (or Wanghong business in Chinese), is an emerging relational C2C business model, and an alternative to traditional C2C transactional business models. There are already millions of these consumers, and this number is growing. In this model, consumer purchase decisions are driven by recommendations and endorsements in videos posted online by celebrities. The purpose of this paper is to determine the relational constructs within consumer relationships in the Internet celebrity business model and to investigate relationships between the constructs and consumer purchase intention. A questionnaire-based study was conducted with consumers who had an awareness of, or prior purchase experience with online celebrities. The results of exploratory factor analysis (EFA) and multiple regression analysis revealed three valid relational constructs: product experience sharing, lifestyle association, and real-time interaction. This study indicated that these constructs had the direct effect on consumer preference and purchase intention. The findings of this study provide insight into a business model in which online shopping is driven by celebrities. They suggest that online celebrities should pay more attention to product experience sharing, life style association and real-time interaction for managing their product promotions. These are the most salient factors with respect to the relational constructs identified in this study.

Keywords: customer relationship, customer to customer, Internet celebrity, online celebrity, online marketing, purchase intention

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Authors: Mohammad Abu Nassar, Mahmoud Al Khalilah, Hussein Abu Nassar

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The purpose of this study is to examine whether corporate tax avoidance practices can impact firm value in the Jordanian context. The study employs a quantitative approach using s sample of (124) industrial and services companies listed on the Amman Stock Exchange for the period from 2010 to 2019. Multiple linear regression analysis has been applied to test the study's hypothesis. The study employs effective tax rate and book-tax difference to measure tax avoidance and Tobin's Q factor to measure firm value. The results of the study revealed that tax avoidance practices, when measured using effective tax rates, do not significantly impact firm value. When the book-tax difference is used to measure tax avoidance, the study results showed a negative impact on firm value. The result of the study has not supported the traditional view of tax avoidance as a transfer of wealth from the government to shareholders for industrial and services companies listed on the Amman Stock Exchange, indicating that Jordanian firms should not use tax avoidance strategies to enhance their value.

Keywords: tax avoidance, effective tax rate, book-tax difference, firm value, Amman stock exchange

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Authors: Velly Anatasia

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The worldwide annual expenditure for cosmetics is estimated at U.S. $18 billion and many players in the field are competing aggressively to capture more and more markets. Players in the cosmetics industry strive to be the foremost by establish customer loyalty. Furthermore, customer loyalty is portrayed by brand loyalty. Therefore, brand loyalty is the key determine of winning the competition in tight market. This study examines the influence of brand loyalty on cosmetics buying behavior of female consumers in Jakarta as capital of Indonesia. The seven factors of brand loyalty are brand name, Product quality, price, design, promotion, servicesquality and store environment. The paper adopted descriptive analysis, factor loading and multiple regression approach to test the hypotheses. The data has been collected by using questionnaires which were distributed and self-administered to 125female respondents accustomed using cosmetics. The findings of this study indicated that promotion has shown strong correlation with brand loyalty. The research results showed that there is positive and significant relationship between factors of brand loyalty (brand name, product quality, price, design, promotion, services quality and store environment) with cosmetics brand loyalty.

Keywords: brand loyalty, brand name, product quality, service quality, promotion

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Authors: Apollinaire Barme, Simon Tamayo, Arthur Gaudron

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This paper presents a statistical approach to identify explanatory variables linearly related to e-commerce sales. The proposed methodology allows specifying a regression model in order to quantify the relevance between openly available data (economic and demographic) and national e-commerce sales. The proposed methodology consists in collecting data, preselecting input variables, performing regressions for choosing variables and models, testing and validating. The usefulness of the proposed approach is twofold: on the one hand, it allows identifying the variables that influence e- commerce sales with an accessible approach. And on the other hand, it can be used to model future sales from the input variables. Results show that e-commerce is linearly dependent on 11 economic and demographic indicators.

Keywords: e-commerce, statistical modeling, regression, empirical research

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Authors: Mehmet Oren, Susan Pedersen, Sevket C. Cetin

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Despite the frequently criticized disadvantages of the traditional used paper and pencil assessment, it is the most frequently used method in our schools. Although assessments do an acceptable measurement, they are not capable of measuring all the aspects and the richness of learning and knowledge. Also, many assessments used in schools decontextualize the assessment from the learning, and they focus on learners’ standing on a particular topic but do not concentrate on how student learning changes over time. For these reasons, many scholars advocate that using simulations and games (S&G) as a tool for assessment has significant potentials to overcome the problems in traditionally used methods. S&G can benefit from the change in technology and provide a contextualized medium for assessment and teaching. Furthermore, S&G can serve as an instructional tool rather than a method to test students’ learning at a particular time point. To investigate the potentials of using educational games as an assessment and teaching tool, this study presents the implementation and the validation of an automated embedded assessment (AEA), which can constantly monitor student learning in the game and assess their performance without intervening their learning. The experiment was conducted on an undergraduate level engineering course (Digital Circuit Design) with 99 participant students over a period of five weeks in Spring 2016 school semester. The purpose of this research study is to examine if the proposed method of AEA is valid to assess student learning in a 3D Educational game and present the implementation steps. To address this question, this study inspects three aspects of the AEA for the validation. First, the evidence-centered design model was used to lay out the design and measurement steps of the assessment. Then, a confirmatory factor analysis was conducted to test if the assessment can measure the targeted latent constructs. Finally, the scores of the assessment were compared with an external measure (a validated test measuring student learning on digital circuit design) to evaluate the convergent validity of the assessment. The results of the confirmatory factor analysis showed that the fit of the model with three latent factors with one higher order factor was acceptable (RMSEA < 0.00, CFI =1, TLI=1.013, WRMR=0.390). All of the observed variables significantly loaded to the latent factors in the latent factor model. In the second analysis, a multiple regression analysis was used to test if the external measure significantly predicts students’ performance in the game. The results of the regression indicated the two predictors explained 36.3% of the variance (R2=.36, F(2,96)=27.42.56, p<.00). It was found that students’ posttest scores significantly predicted game performance (β = .60, p < .000). The statistical results of the analyses show that the AEA can distinctly measure three major components of the digital circuit design course. It was aimed that this study can help researchers understand how to design an AEA, and showcase an implementation by providing an example methodology to validate this type of assessment.

Keywords: educational video games, automated embedded assessment, assessment validation, game-based assessment, assessment design

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Authors: M. Tahir Demirsel, Mustafa Atsan

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Many elements of the environment in which businesses operate today leave them faced with unexpected threats and opportunities. One of the major threats is business crisis. The crisis is a state of affairs in a business wherein the executives must take urgent and unprecedented action to try to save the business from failure. In order to survive in the business environment, organizations should be prepared for the potential crises. Technological developments, uncertainty in the market and the intense competition increase the probability of encountering a crisis for organizations. Therefore, by acting proactively to predict crisis, to detect signals of crisis and be prepared for a crisis by taking necessary precautions accordingly, is of great importance for businesses. In this context, the objective of this study is to reveal that how much organizations are proactive and can predict the future crises and investigate whether they are prepared for possible crises or not. The research was conducted on 222 business executives in one of the major industrial zones of Turkey, Konya Organized Industrial Zone (KOS). The findings are analyzed through descriptive statistics and multiple regression analysis. According to the results, it has been observed that organizations cannot predict the crisis signals and are not prepared for potential crises.

Keywords: crisis preparedness, crisis signals, industrial organizations, proactivity

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Authors: Minttu Laukkanen, Janne Huiskonen

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This study investigates the sharing economy business models as examples of the sustainable business models. The aim is to contribute to the limited literature on sharing economy in connection with sustainable business models by explaining sharing economy business models value capturing. Specifically, this research answers the following question: How business model choices affect captured sustainable value? A multiple case study approach is applied in this study. Twenty different successful sharing economy business models focusing on consumer business and covering four main areas, accommodation, mobility, food, and consumer goods, are selected for analysis. The secondary data available on companies’ websites, previous research, reports, and other public documents are used. All twenty cases are analyzed through the sharing economy business model framework and sustainable value analysis framework using qualitative data analysis. This study represents general sharing economy business model value attributes and their specifications, i.e. sustainable value propositions for different stakeholders, and further explains the sustainability impacts of different sharing economy business models through captured and uncaptured value. In conclusion, this study represents how business model choices affect sustainable value capturing through eight business model attributes identified in this study. This paper contributes to the research on sustainable business models and sharing economy by examining how business model choices affect captured sustainable value. This study highlights the importance of careful business model and sustainability impacts analyses including the triple bottom line, multiple stakeholders and value captured and uncaptured perspectives as well as sustainability trade-offs. It is not self-evident that sharing economy business models advance sustainability, and business model choices does matter.

Keywords: sharing economy, sustainable business model innovation, sustainable value, value capturing

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Authors: Leonard Simoni, Ilir Alimehmeti, Ervina Shirka, Endri Hasimi, Ndricim Kallashi, Verona Beka, Suerta Kabili, Artan Goda

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Background: Diabetes Mellitus type 2, small vessel calibre, stented length of vessel, complex lesion morphology, and prior bypass surgery have resulted risk factors for In-Stent Restenosis (ISR). However, there are some contradictory results about body mass index (BMI) as a risk factor for ISR. Purpose: We want to identify clinical, lesional and procedural factors that can predict clinical ISR in our patients. Methods: Were enrolled 759 patients who underwent first-time elective PCI with Bare Metal Stents (BMS) from September 2011 to December 2013 in our Department of Cardiology and followed them for at least 1.5 years with a median of 862 days (2 years and 4 months). Only the patients re-admitted with ischemic heart disease underwent control coronary angiography but no routine angiographic control was performed. Patients were categorized in ISR and non-ISR groups and compared between them. Multivariate analysis - Binary Logistic Regression: Forward Conditional Method was used to identify independent predictive risk factors. P was considered statistically significant when <0.05. Results: ISR compared to non-ISR individuals had a significantly lower BMI (25.7±3.3 vs. 26.9±3.7, p=0.004), higher risk anatomy (LM + 3-vessel CAD) (23% vs. 14%, p=0.03), higher number of stents/person used (2.1±1.1 vs. 1.75±0.96, p=0.004), greater length of stents/person used (39.3±21.6 vs. 33.3±18.5, p=0.01), and a lower use of clopidogrel and ASA (together) (95% vs. 99%, p=0.012). They also had a higher, although not statistically significant, prevalence of Diabetes Mellitus (42% vs. 32%, p=0.072) and a greater number of treated vessels (1.36±0.5 vs. 1.26±0.5, p=0.08). In the multivariate analysis, Diabetes Mellitus type 2 and multiple stents used were independent predictors risk factors for In-Stent Restenosis, OR 1.66 [1.03-2.68], p=0.039, and OR 1.44 [1.16-1.78,] p=0.001, respectively. On the other side higher BMI and use of clopidogrel and ASA together resulted protective factors OR 0.88 [0.81-0.95], p=0.001 and OR 0.2 [0.06-0.72] p=0.013, respectively. Conclusion: Diabetes Mellitus and multiple stents are strong predictive risk factors, whereas the use of clopidogrel and ASA together are protective factors for clinical In-Stent Restenosis. Paradoxically High BMI is a protective factor for In-stent Restenosis, probably related to a larger diameter of vessels and consequently a larger diameter of stents implanted in these patients. Further studies are needed to clarify this finding.

Keywords: body mass index, diabetes mellitus, in-stent restenosis, percutaneous coronary intervention

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Authors: Elvira Mustikawati P.H., Iis Dewi Ratih, Dita Amelia

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Bojonegoro has proclaimed a policy of zero malnutrition. Therefore, as an effort to solve the cases of malnutrition children in Bojonegoro, this study used the approach geographically Mixed Weighted Regression (MGWR) to determine the factors that influence the percentage of malnourished children under five in which factors can be divided into locally influential factor in each district and global factors that influence throughout the district. Based on the test of goodness of fit models, R2 and AIC values in GWR models are better than MGWR models. R2 and AIC values in MGWR models are 84.37% and 14.28, while the GWR models respectively are 91.04% and -62.04. Based on the analysis with GWR models, District Sekar, Bubulan, Gondang, and Dander is a district with three predictor variables (percentage of vitamin A, the percentage of births assisted health personnel, and the percentage of clean water) that significantly influence the percentage of malnourished children under five.

Keywords: GWR, MGWR, R2, AIC

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Authors: Dieudonne Uwizeye

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Introduction: Diarrhoea is one of the major causes of morbidity and mortality among communities living in urban informal settlements of developing countries. It is assumed that mountainous environment introduces variations of the burden among residents of the same settlements. Design and Objective: A cross-sectional study was done in Kigali to explore the effect of mountainous informal settlements on diarrhoea risk variations. Data were collected among 1,152 households through household survey and transect walk to observe the status of sanitation. The outcome variable was the incidence of diarrhoea among household members of any age. The study used the most knowledgeable person in the household as the main respondent. Mostly this was the woman of the house as she was more likely to know the health status of every household member as she plays various roles: mother, wife, and head of the household among others. The analysis used cross tabulation and logistic regression analysis. Results: Results suggest that risks for diarrhoea vary depending on home location in the settlements. Diarrhoea risk increased as the distance from the road increased. The results of the logistic regression analysis indicate the adjusted odds ratio of 2.97 with 95% confidence interval being 1.35-6.55 and 3.50 adjusted odds ratio with 95% confidence interval being 1.61-7.60 in level two and three respectively compared with level one. The status of sanitation within and around homes was also significantly associated with the increase of diarrhoea. Equally, it is indicated that stable households were less likely to have diarrhoea. The logistic regression analysis indicated the adjusted odds ratio of 0.45 with 95% confidence interval being 0.25-0.81. However, the study did not find evidence for a significant association between diarrhoea risks and household socioeconomic status in the multivariable model. It is assumed that environmental factors in mountainous settings prevailed. Households using the available public water sources were more likely to have diarrhoea in their households. Recommendation: The study recommends the provision and extension of infrastructure for improved water, drainage, sanitation and wastes management facilities. Equally, studies should be done to identify the level of contamination and potential origin of contaminants for water sources in the valleys to adequately control the risks for diarrhoea in mountainous urban settings.

Keywords: urbanisation, diarrhoea risk, mountainous environment, urban informal settlements in Rwanda

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Authors: Jui Chen Wu, Ming Yi Hsu

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Background and Purpose: Shift work of nursing staff is inevitable in hospital to provide continuing medical care. However, shift work is considered as a health hazard that may cause physical and psychological problems. Serious workplace fatigue of nursing shift work might impact on family, social and work life, moreover, causes serious reduction of quality of medical care, or even malpractice. This study aims to explore relationships among nursing staff’s shift, workplace fatigue and quality of working life. Method: Structured questionnaires were used in this study to explore relationships among shift work, workplace fatigue and quality of working life in nursing staffs. We recruited 590 nursing staffs in different Community Teaching hospitals in Taiwan. Data analysed by descriptive statistics, single sample t-test, single factor analysis, Pearson correlation coefficient and hierarchical regression, etc. Results: The overall workplace fatigue score is 50.59 points. In further analysis, the score of personal burnout, work-related burnout, over-commitment and client-related burnout are 57.86, 53.83, 45.95 and 44.71. The basic attributes of nursing staff are significantly different from those of workplace fatigue with different ages, licenses, sleeping quality, self-conscious health status, number of care patients of chronic diseases and number of care people in the obstetric ward. The shift variables revealed no significant influence on workplace fatigue during the hierarchical regression analysis. About the analysis on nursing staff’s basic attributes and shift on the quality of working life, descriptive results show that the overall quality of working life of nursing staff is 3.23 points. Comparing the average score of the six aspects, the ranked average score are 3.47 (SD= .43) in interrelationship, 3.40 (SD= .46) in self-actualisation, 3.30 (SD= .40) in self-efficacy, 3.15 (SD= .38) in vocational concept, 3.07 (SD= .37) in work aspects, and 3.02 (SD= .56) in organization aspects. The basic attributes of nursing staff are significantly different from quality of working life in different marriage situations, education level, years of nursing work, occupation area, sleep quality, self-conscious health status and number of care in medical ward. There are significant differences between shift mode and shift rate with the quality of working life. The results of the hierarchical regression analysis reveal that one of the shifts variables 'shift mode' which does affect staff’s quality of working life. The workplace fatigue is negatively correlated with the quality of working life, and the over-commitment in the workplace fatigue is positively related to the vocational concept of the quality of working life. According to the regression analysis of nursing staff’s basic attributes, shift mode, workplace fatigue and quality of working life related shift, the results show that the workplace fatigue has a significant impact on nursing staff’s quality of working life. Conclusion: According to our study, shift work is correlated with workplace fatigue in nursing staffs. This results work as important reference for human resources management in hospitals to establishing a more positive and healthy work arrangement policy.

Keywords: nursing staff, shift, workplace fatigue, quality of working life

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Authors: T. Damak, S. Houidi, M. A. Ben Ayed, N. Masmoudi

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The Versatile Video Coding standard (VVC) is actually under development by the Joint Video Exploration Team (or JVET). An Adaptive Multiple Transforms (AMT) approach was announced. It is based on different transform modules that provided an efficient coding. However, the AMT solution raises several issues especially regarding the complexity of the selected set of transforms. This can be an important issue, particularly for a future industrial adoption. This paper proposed an efficient hardware implementation of the most used transform in AMT approach: the DCT II. The developed circuit is adapted to different block sizes and can reach a minimum frequency of 192 MHz allowing an optimized execution time.

Keywords: adaptive multiple transforms, AMT, DCT II, hardware, transform, versatile video coding, VVC

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Authors: Hechmi Saidi, Noureddine Hamdi

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The performance of decode and forward (DF) multihop free space optical (FSO) scheme deploying multiple input multiple output (MIMO) configuration under gamma-gamma (GG) statistical distribution, that adopts M-ary pulse position modulation (MPPM) coding, is investigated. We have extracted exact and estimated values of symbol-error rates (SERs) respectively. The probability density function (PDF)’s closed-form formula is expressed for our designed system. Thanks to the use of DF multihop MIMO FSO configuration and MPPM signaling, atmospheric turbulence is combatted; hence the transmitted signal quality is improved.

Keywords: free space optical, gamma gamma channel, radio frequency, decode and forward, multiple-input multiple-output, M-ary pulse position modulation, symbol error rate

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Authors: Hatice Boyacioglu, Nursel Akkaya, Humeyra Ozge Yilanci, Hilmi Kansu, Nihal Avcu

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The strong relationship between the reduction in the size of the pulp cavity and increasing age has been reported in the literature. This relationship can be utilized to estimate the age of an individual by measuring the pulp cavity size using dental radiographs as a non-destructive method. The purpose of this study is to develop a population specific regression model for age estimation in a sample of Turkish adults by applying Cameriere’s method on panoramic radiographs. The sample consisted of 100 panoramic radiographs of Turkish patients (40 men, 60 women) aged between 20 and 70 years. Pulp and tooth area ratios (AR) of the maxilla¬¬ry canines were measured by two maxillofacial radiologists and then the results were subjected to regression analysis. There were no statistically significant intra-observer and inter-observer differences. The correlation coefficient between age and the AR of the maxillary canines was -0.71 and the following regression equation was derived: Estimated Age = 77,365 – ( 351,193 × AR ). The mean prediction error was 4 years which is within acceptable errors limits for age estimation. This shows that the pulp/tooth area ratio is a useful variable for assessing age with reasonable accuracy. Based on the results of this research, it was concluded that Cameriere’s method is suitable for dental age estimation and it can be used for forensic procedures in Turkish adults. These instructions give you guidelines for preparing papers for conferences or journals.

Keywords: age estimation by teeth, forensic dentistry, panoramic radiograph, Cameriere's method

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Authors: Tauha Hussain Ali, Shabir Hussain Khahro, Nafees Ahmed Memon

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Accurate prediction of project time for planning and bid preparation stage should contain realistic dates. Constructors use their experience to estimate the project duration for the new projects, which is based on intuitions. It has been a constant concern to both researchers and constructors to analyze the accurate prediction of project duration for bid preparation stage. In Pakistan, such study for time cost relationship has been lacked to predict duration performance for the construction projects. This study is an attempt to explore the time cost relationship that would conclude with a mathematical model to predict the time for the drainage rehabilitation projects in the province of Sindh, Pakistan. The data has been collected from National Engineering Services (NESPAK), Pakistan and regression analysis has been carried out for the analysis of results. Significant relationship has been found between time and cost of the construction projects in Sindh and the generated mathematical model can be used by the constructors to predict the project duration for the upcoming projects of same nature. This study also provides the professionals with a requisite knowledge to make decisions regarding project duration, which is significantly important to win the projects at the bid stage.

Keywords: BTC Model, project time, relationship of time cost, regression

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Authors: Jamal Fayazi, Farhad Anoosheh, Mohammad R. Ghorbani, Ali R. Paydar

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In this study, to determine the best non-linear regression model describing the growth curve of native poultry, 9657 chicks of generations 18, 19, and 20 raised in Mazandaran breeding center were used. Fowls and roosters of this center distributed in south of Caspian Sea region. To estimate the genetic variability of none linear regression parameter of growth traits, a Gibbs sampling of Bayesian analysis was used. The average body weight traits in the first day (BW1), eighth week (BW8) and twelfth week (BW12) were respectively estimated as 36.05, 763.03, and 1194.98 grams. Based on the coefficient of determination, mean squares of error and Akaike information criteria, Gompertz model was selected as the best growth descriptive function. In Gompertz model, the estimated values for the parameters of maturity weight (A), integration constant (B) and maturity rate (K) were estimated to be 1734.4, 3.986, and 0.282, respectively. The direct heritability of BW1, BW8 and BW12 were respectively reported to be as 0.378, 0.3709, 0.316, 0.389, 0.43, 0.09 and 0.07. With regard to estimated parameters, the results of this study indicated that there is a possibility to improve some property of growth curve using appropriate selection programs.

Keywords: direct heritability, Gompertz, growth traits, maturity weight, native poultry

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Authors: Jonardan Koner, Avinash Purandare

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In today’s globalized world international business is a very key area for the country's growth. Some of the strategic areas for holding up a country’s international business to grow are in the areas of connecting Ports, Road Network, and Rail Network. India’s International Business is booming both in Exports as well as Imports. Ports play a very central part in the growth of international trade and ensuring competitive ports is of critical importance. India has a long coastline which is a big asset for the country as it has given the opportunity for development of a large number of major and minor ports which will contribute to the maritime trades’ development. The National Economic Development of India requires a well-functioning seaport system. To know the comparative strength of Indian ports over South-east Asian similar ports, the study is considering the objectives of (I) to identify the key parameters of an international mega container port, (II) to compare the five selected container ports (JNPT, Chennai, Singapore, Dubai, and Colombo Ports) according to user of the ports and iii) to measure the growth of selected five container ports’ throughput over time and their comparison. The study is based on both primary and secondary databases. The linear time trend analysis is done to show the trend in quantum of exports, imports and total goods/services handled by individual ports over the years. The comparative trend analysis is done for the selected five ports of cargo traffic handled in terms of Tonnage (weight) and number of containers (TEU’s). The comparative trend analysis is done between containerized and non-containerized cargo traffic in the five selected five ports. The primary data analysis is done comprising of comparative analysis of factor ratings through bar diagrams, statistical inference of factor ratings for the selected five ports, consolidated comparative line charts of factor rating for the selected five ports, consolidated comparative bar charts of factor ratings of the selected five ports and the distribution of ratings (frequency terms). The linear regression model is used to forecast the container capacities required for JNPT Port and Chennai Port by the year 2030. Multiple regression analysis is carried out to measure the impact of selected 34 explanatory variables on the ‘Overall Performance of the Port’ for each of the selected five ports. The research outcome is of high significance to the stakeholders of Indian container handling ports. Indian container port of JNPT and Chennai are benchmarked against international ports such as Singapore, Dubai, and Colombo Ports which are the competing ports in the neighbouring region. The study has analysed the feedback ratings for the selected 35 factors regarding physical infrastructure and services rendered to the port users. This feedback would provide valuable data for carrying out improvements in the facilities provided to the port users. These installations would help the ports’ users to carry out their work in more efficient manner.

Keywords: throughput, twenty equivalent units, TEUs, cargo traffic, shipping lines, freight forwarders

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Authors: Pongsatorn Tantrabundit, Lersak Phothong, Ong-art Chanprasitchai

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Due to the emergence of the Internet, it has extended the traditional Word-of-Mouth (WOM) to a new form called “Electronic Word-of-Mouth (eWOM).” Unlike traditional WOM, eWOM is able to present information in various ways by applying different components. Each eWOM component generates different effects on online consumer behavior. This research investigates the effects of Webcare (responding message) from product/ service providers on negative eWOM by applying two types of products (search and experience). The proposed conceptual model was developed based on the combination of the stages in consumer decision-making process, theory of reasoned action (TRA), theory of planned behavior (TPB), the technology acceptance model (TAM), the information integration theory and the elaboration likelihood model. The methodology techniques used in this study included multivariate analysis of variance (MANOVA) and multiple regression analysis. The results suggest that Webcare does slightly increase Thai online consumer’s perceptions on perceived eWOM trustworthiness, information diagnosticity and quality. For negative eWOM, we also found that perceived eWOM Trustworthiness, perceived eWOM diagnosticity and quality have a positive relationship with eWOM influence whereas perceived valence has a negative relationship with eWOM influence in Thai online consumers.

Keywords: consumer behavior, electronic word-of-mouth, online review, online word-of-mouth, Thai online consumer, webcare

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Authors: Jonghae Park, Daesung Kim

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The impact of aggressive and conservative working capital‘s strategies on the value and profitability of the firms has been evaluated by applying the panel data regression analysis. The control variables used in the regression models are natural log of firm size, sales growth, and debt. We collected a panel of 13,988 companies listed on the Korea stock market covering the period 2000-2016. The major findings of this study are as follow: 1) We find a significant negative correlation between firm profitability and the number of days inventory (INV) and days accounts payable (AP). The firm’s profitability can also be improved by reducing the number of days of inventory and days accounts payable. 2) We also find a significant positive correlation between firm profitability and the number of days accounts receivable (AR) and cash ratios (CR). In other words, the cash is associated with high corporate profitability. 3) Tobin's analysis showed that only the number of days accounts receivable (AR) and cash ratios (CR) had a significant relationship. In conclusion, companies can increase profitability by reducing INV and increasing AP, but INV and AP did not affect corporate value. In particular, it is necessary to increase CA and decrease AR in order to increase Firm’s profitability and value.

Keywords: working capital, working capital management, firm value, profitability

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Authors: Emmanuel Ukpe, S. M. F. D. Syed Mustapha

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Trust in an organization has been perceived as one of the key factors behind knowledge sharing, mainly in an unstructured work environment. In an informal working environment, to instill trust among individuals is a challenge and even more in the virtual environment. The study has contributed in developing the framework for building trust in an unstructured organization in performing knowledge sharing in a virtual environment. The artifact called KAPE (Knowledge Acquisition, Processing, and Exchange) was developed for knowledge sharing for the informal organization where the framework was incorporated. It applies to Cassava farmers to facilitate knowledge sharing using web-based platform. A survey was conducted; data were collected from 382 farmers from 21 farm communities. Multiple regression technique, Cronbach’s Alpha reliability test; Tukey’s Honestly significant difference (HSD) analysis; one way Analysis of Variance (ANOVA), and all trust acceptable measures (TAM) were used to test the hypothesis and to determine noteworthy relationships. The results show a significant difference when there is a trust in knowledge sharing between farmers, the ones who have high in trust acceptable factors found in the model (M = 3.66 SD = .93) and the ones who have low on trust acceptable factors (M = 2.08 SD = .28), (t (48) = 5.69, p = .00). Furthermore, when applying Cognitive Expectancy Theory, the farmers with cognitive-consonance show higher level of trust and satisfaction with knowledge and information from KAPE, as compared with a low level of cognitive-dissonance. These results imply that the adopted trust model KAPE positively improved knowledge sharing activities in an informal environment amongst rural farmers.

Keywords: trust, knowledge, sharing, knowledge acquisition, processing and exchange, KAPE

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Authors: Yijun Shao, Yan Cheng, Rashmee U. Shah, Charlene R. Weir, Bruce E. Bray, Qing Zeng-Treitler

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Deep neural network (DNN) models are being explored in the clinical domain, following the recent success in other domains such as image recognition. For clinical adoption, outcome prediction models require explanation, but due to the multiple non-linear inner transformations, DNN models are viewed by many as a black box. In this study, we developed a deep neural network model for predicting 1-year mortality of patients who underwent major cardio vascular procedures (MCVPs), using temporal image representation of past medical history as input. The dataset was obtained from the electronic medical data warehouse administered by Veteran Affairs Information and Computing Infrastructure (VINCI). We identified 21,355 veterans who had their first MCVP in 2014. Features for prediction included demographics, diagnoses, procedures, medication orders, hospitalizations, and frailty measures extracted from clinical notes. Temporal variables were created based on the patient history data in the 2-year window prior to the index MCVP. A temporal image was created based on these variables for each individual patient. To generate the explanation for the DNN model, we defined a new concept called impact score, based on the presence/value of clinical conditions’ impact on the predicted outcome. Like (log) odds ratio reported by the logistic regression (LR) model, impact scores are continuous variables intended to shed light on the black box model. For comparison, a logistic regression model was fitted on the same dataset. In our cohort, about 6.8% of patients died within one year. The prediction of the DNN model achieved an area under the curve (AUC) of 78.5% while the LR model achieved an AUC of 74.6%. A strong but not perfect correlation was found between the aggregated impact scores and the log odds ratios (Spearman’s rho = 0.74), which helped validate our explanation.

Keywords: deep neural network, temporal data, prediction, frailty, logistic regression model

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Authors: Theresia Dwi Hastuti, Kristiana Haryanti, Agustine Eva Maria Soekesi

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Today's family business continues to grow in big cities and in rural areas throughout Indonesia in line with the development of the business world and global competition. This study aims to analyze the effect of company value, leadership, and ownership succession on the financial performance of the family business. The research method was carried out quantitatively with multiple regression. The respondent amounted to 63 entrepreneurs. This study found that company value, leadership succession, relationships, and communication affect the financial performance of the family business.

Keywords: company value, family business, financial performance, leadership succession, ownership succession

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Authors: Nattapong Techarattanased

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The objectives of this research were to study the influence of market orientation and supply chain management on competitive capability in case of the automotive parts industry in Thailand. This study employed by survey research and questionnaire was used to collect the data from 400 entrepreneurs in the automotive parts industry in Thailand. The descriptive statistics and multiple regression analysis were used to analyze data. The results revealed that the overall dimensions of marketing orientation, namely, responsiveness, intelligence generation, and intelligence dissemination were rated at the high level. As well, the overall dimensions of supply chain management, namely, collaboration, communication, trust, and commitment were also rated at the high level. Furthermore, the hypothesis testing results showed that supply chain management and market orientation affected competitive capability of the automotive parts industry in Thailand which these two variables could be combined to predict competitive capability of the automotive parts industry in Thailand by 31.5 percent.

Keywords: automotive parts industry, competitive capability, market orientation, supply chain management

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Authors: Rajarshi Sharma, Rashidul Alam, Visavino Seleyi, Yuvila Sangtam

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The Intensity-Duration-Frequency (IDF) relationship of rainfall amounts is one of the most commonly used tools in water resources engineering for planning, design and operation of water resources project, or for various engineering projects against design floods. The establishment of such relationships was reported as early as in 1932 (Bernard). Since then many sets of relationships have been constructed for several parts of the globe. The objective of this research is to derive IDF relationship of rainfall for western watershed of Guwahati, Assam. These relationships are useful in the design of urban drainage works, e.g. storm sewers, culverts and other hydraulic structures. In the study, rainfall depth for 10 years viz. 2001 to 2010 has been collected from the Regional Meteorological Centre Borjhar, Guwahati. Firstly, the data has been used to construct the mass curve for duration of more than 7 hours rainfall to calculate the maximum intensity and to form the intensity duration curves. Gumbel’s frequency analysis technique has been used to calculate the probable maximum rainfall intensities for a period of 2 yr, 5 yr, 10 yr, 50 yr, 100 yr from the maximum intensity. Finally, regression analysis has been used to develop the intensity-duration-frequency (IDF) curve. Thus, from the analysis the values for the constants ‘a’,‘b’ &‘c’ have been found out. The values of ‘a’ for which the sum of the squared deviation is minimum has been found out to be 40 and when the corresponding value of ‘c’ and ‘b’ for the minimum squared deviation of ‘a’ are 0.744 and 1981.527 respectively. The results obtained showed that in all the cases the correlation coefficient is very high indicating the goodness of fit of the formulae to estimate IDF curves in the region of interest.

Keywords: intensity-duration-frequency relationship, mass curve, regression analysis, correlation coefficient

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Authors: Lamiche Chaabane

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In this study, a new method for solving sequence alignment problem is proposed, which is named ITS (Improved Tabu Search). This algorithm is based on the classical Tabu Search (TS). ITS is implemented in order to obtain results of multiple sequence alignment. Several ideas concerning neighbourhood generation, move selection mechanisms and intensification/diversification strategies for our proposed ITS is investigated. ITS have generated high-quality results in terms of measure of scores in comparison with the classical TS and simple iterative search algorithm.

Keywords: multiple sequence alignment, tabu search, improved tabu search, neighbourhood generation, selection mechanisms

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Authors: Uttam Aryal, Shekhar Thapaliya

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This research paper presents a comprehensive analysis of the factors contributing to student dropout at Makawanpur Multiple Campus, utilizing primary data collected directly from dropped out as well as regular students and academic staff. Employing a mixed-method approach, combining qualitative and quantitative methods, this study examines into the complicated issue of student dropout. Data collection methods included surveys, interviews, and a thorough examination of academic records covering multiple academic years. The study focused on students who left their programs prematurely, as well as current students and academic staff, providing a well-rounded perspective on the issue. The analysis reveals a shaded understanding of the factors influencing student dropout, encompassing both academic and non-academic dimensions. These factors include academic challenges, personal choices, socioeconomic barriers, peer influences, and institutional-related issues. Importantly, the study highlights the most influential factors for dropout, such as the pursuit of education abroad, financial restrictions, and employment opportunities, shedding light on the complex web of circumstances that lead students to discontinue their education. The insights derived from this study offer actionable recommendations for campus administrators, policymakers, and educators to develop targeted interventions aimed at reducing dropout rates and improving student retention. The study underscores the importance of addressing the diverse needs and challenges faced by students, with the ultimate goal of fostering a supportive academic environment that encourages student success and program completion.

Keywords: drop out, students, factors, opportunities, challenges

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Authors: Danielle M. Barna, Kolbjørn Engeland, Thordis Thorarinsdottir, Chong-Yu Xu

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Design flood values give estimates of flood magnitude within a given return period and are essential to making adaptive decisions around land use planning, infrastructure design, and disaster mitigation. Often design flood values are needed at locations with insufficient data. Additionally, in hydrologic applications where flood retention is important (e.g., floodplain management and reservoir design), design flood values are required at different flood durations. A statistical approach to this problem is a development of a regression model for extremes where some of the parameters are dependent on flood duration in addition to being covariate-dependent. In hydrology, this is called a regional flood-duration-frequency (regional-QDF) model. Typically, the underlying statistical distribution is chosen to be the Generalized Extreme Value (GEV) distribution. However, as the support of the GEV distribution depends on both its parameters and the range of the data, special care must be taken with the development of the regional model. In particular, we find that the GEV is problematic when developing a GAMLSS-type analysis due to the difficulty of proposing a link function that is independent of the unknown parameters and the observed data. We discuss these challenges in the context of developing a regional QDF model for Norway.

Keywords: design flood values, bayesian statistics, regression modeling of extremes, extreme value analysis, GEV

Procedia PDF Downloads 72