Search results for: moderating variables

Authors: Abdul-Monim Batiha

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Aim: The aim of this study were to correlate Jordanian cancer patients’ quality of life and fatigue with selected variables (age, sex, religion, marital status, level of education, type of cancer, number of people living in the same household, type of radiotherapy, dose of radiotherapy, and hemoglobin level). Background: Radiotherapy and chemotherapy remain devastating agents that altered patients’ normal lives. Methods: A correlational design was used in this study to 80 cancer patients and required radiotherapy treatment using a convenience sampling procedure. Results: No significant differences were found in the relationship between quality of life scores and selected variables. A significant negative relationship was found between quality of life scores and the side effects of radiotherapy treatment. Significant positive relationships were found between fatigue scores measured by Piper Fatigue Scale and cancer complications, and radiotherapy side effects. Conclusion: Cancer patients’ quality of life and fatigue are affected by radiotherapy’s side effects and cancer complications. Implications for Nursing: Nurses should try to prevent and manage the negative side effects of radiotherapy and complications of cancer. Such an initiative would serve to design specific nursing interventions that have the potential to help patients enjoy their lives and perform their activities.

Keywords: cancer patients, piper fatigue scale, fatigue, quality of life, radiotherapy

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Authors: Gyoomi Kim, Jiyoung Bae

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The purpose of this study was to propose a framework that verifies the structural relationships among students’ use of digital English learning strategy (DELS), affective domains, and their individual variables. The study developed a hypothetical model based on previous studies on language learning strategy use as well as digital language learning. The participants were 720 Korean high school students and 430 university students. The instrument was a self-response questionnaire that contained 70 question items based on Oxford’s SILL (Strategy Inventory for Language Learning) as well as the previous studies on language learning strategies in digital learning environment in order to measure DELS and affective domains. The collected data were analyzed through structural equation modeling (SEM). This study used quantitative data analysis procedures: Explanatory factor analysis (EFA) and confirmatory factor analysis (CFA). Firstly, the EFA was conducted in order to verify the hypothetical model; the factor analysis was conducted preferentially to identify the underlying relationships between measured variables of DELS and the affective domain in the EFA process. The hypothetical model was established with six indicators of learning strategies (memory, cognitive, compensation, metacognitive, affective, and social strategies) under the latent variable of the use of DELS. In addition, the model included four indicators (self-confidence, interests, self-regulation, and attitude toward digital learning) under the latent variable of learners’ affective domain. Secondly, the CFA was used to determine the suitability of data and research models, so all data from the present study was used to assess model fits. Lastly, the model also included individual learner factors as covariates and five constructs selected were learners’ gender, the level of English proficiency, the duration of English learning, the period of using digital devices, and previous experience of digital English learning. The results verified from SEM analysis proposed a theoretical model that showed the structural relationships between Korean students’ use of DELS and their affective domains. Therefore, the results of this study help ESL/EFL teachers understand how learners use and develop appropriate learning strategies in digital learning contexts. The pedagogical implication and suggestions for the further study will be also presented.

Keywords: Digital English Learning Strategy, DELS, individual variables, learners' affective domains, Structural Equation Modeling, SEM

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Authors: Kayijuka Idrissa

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This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.

Keywords: statistical methods, traffic flow, Poisson distribution, car moving technics

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Authors: Ming Ma, Zhenyu Cai, Rui Li

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People are more vulnerable to health problems than ever before, such as overweight and obesity due to the change of built environment. In the high-rise buildings, the core-tube layout is closely associated with user’s physical activities which will affect human’s health in a long-term. As for the white-collars who spends the amount of time working in the office tower, using staircase seems to provide an opportunity for them to increase the physical activities in the workplaces. This paper is aiming to find out the specific relationship between health and core-tube in the office tower through analyzing the correlation between staircase’s layout and user’s health. The variables of staircase’s layout are consisted of two indicators: plan layout and space design, including nine factors while health variable is applying BIM as the only main factor. 14 office towers in downtown Shanghai are selected as the research samples because of its typical users’ pattern and similar core-tube layout. In the result, it is obvious that the users from these 14 cases have higher BMI than average partly because that the staircases are mainly designed for emergency and fire instead of daily use. After the regression and correlation analysis of the variables of health and staircases, it’s found that users’ BMI is significantly associated with the factors of floor guide-signs and distance from lobby to the staircase. In addition, the factors of comfort level of staircase such as width and daylighting have a certain correlation with users’ BMI.

Keywords: office tower, staircase, design, obesity, physical activity

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Authors: Hung-Chu Chen, Han Qi, Bauke de Vries

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Energy consumption in the urban environment has attracted numerous researches in recent decades. However, it is comparatively rare to find literary works which investigated 3D spatial analysis of urban energy demand modelling. In order to analyze the spatial correlation between urban morphology and energy demand comprehensively, this paper investigates their relation by using the spatial regression tool. In addition, the spatial regression tool which is applied in this paper is ordinary least squares regression (OLS) and geographically weighted regression (GWR) model. Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and building volume are explainers of urban morphology, which act as independent variables of Energy-land use (E-L) model. NDBI and NDVI are used as the index to describe five types of land use: urban area (U), open space (O), artificial green area (G), natural green area (V), and water body (W). Accordingly, annual electricity, gas demand and energy demand are dependent variables of the E-L model. Based on the analytical result of E-L model relation, it revealed that energy demand and urban morphology are closely connected and the possible causes and practical use are discussed. Besides, the spatial analysis methods of OLS and GWR are compared.

Keywords: energy demand model, geographically weighted regression, normalized difference built-up index, normalized difference vegetation index, spatial statistics

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Authors: Alemayehu Belay Emagnaw

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This study was conducted to investigate the relationship of mother and father involvement with students’ school performance and the effect of selected family demographic variables (mother and father education, family structure and sex of students) to the involvement of mothers and fathers in their children’s school performance. In addition, this study attempted to differentiate the level of involvement of mothers’ and fathers’ in their children’s school performance. The research was conducted in Bahirdar City, Ethiopia. A total of 175 students (boys were 85 and girls were 90) of grade 7th and 8th private primary schools were selected as respondents using stratified random sampling technique. The data were collected using a questionnaire. Analysis of the data showed that fathers and mothers have significant involvement in their children’s school performance. A significant difference was also found between mothers and fathers involvement in their children’s school performance. Mothers were better involved in their children school performance than fathers. The analysis of inter-correlation between variables showed that there is a statistically significant relationship between mother and father education, mother and father involvement, and school performance whereas, family structure and sex of the child had no significant relationship with school performance.

Keywords: family structure, parental education, parental involvement, school performance

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Authors: Oscar Norman Nekesa, Yoshitaka Kajita

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Tom Mboya Street is a vital urban corridor within the spectrum of Nairobi city, it experiences high volumes of pedestrian and vehicular traffic. Despite past intervention measures to lessen this catastrophe, rates have remained high. This highlights significant safety concerns that need urgent attention. This study investigates the correlation and pedestrian accident predictability with significant independent variables using multiple linear regression to model to develop effective mobility management strategies for accident mitigation. The methodology involves collecting and analyzing data on pedestrian accidents and various related independent variables. Data sources include the National Transport and Safety Authority (NTSA), Kenya National Bureau of Statistics, and Nairobi City County records, covering five years. This study aims to investigate that traffic volumes (pedestrian and vehicle), Vehicular speed, human factors, illegal parking, policy issues, urban-land use, built environment, traffic signals conditions, inadequate lighting, and insufficient traffic control measures significantly have predictability with the rate of pedestrian accidents. Explanatory variables related to road design and geometry are significant in predictor models for the Tom Mboya Road link but less influential in junction along the 5 km stretch road models. The most impactful variable across all models was vehicular traffic flow. The study recommends infrastructural improvements, enhanced enforcement, and public awareness campaigns to reduce accidents and improve urban mobility. These insights can inform policy-making and urban planning to enhance pedestrian safety along the dense packed Tom Mboya Street and similar urban settings. The findings will inform evidence-based interventions to enhance pedestrian safety and improve urban mobility.

Keywords: multiple linear regression, urban mobility, traffic management, Nairobi, Tom Mboya street, infrastructure conditions., pedestrian safety, correlation and prediction

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Authors: Murat Oral, Seda Bostancı, Sadık Ata, Kevser Dincer

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When evaluating the aesthetics of cities, an analysis of the urban form development depending on design properties with a variety of factors is performed together with a study of the effects of this appearance on human beings. Different methods are used while making an aesthetical evaluation related to a city. Entropy, in its preliminary meaning, is the mathematical representation of thermodynamic results. Measuring the entropy is related to the distribution of positional figures of a message or information from the probabilities standpoint. In this study, analysis of evaluation the urban skylines by the entropy approach was modelled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modelling technique. Input-output parameters were described by RBMTF if-then rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), Positive Medium (L6), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between application data and RBMTF is done by using absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF can be successfully used for the analysis of evaluation the urban skylines by the entropy approach. As a result, RBMTF model has shown satisfying relation with experimental results, which suggests an alternative method to evaluation of the urban skylines by the entropy approach.

Keywords: urban skylines, entropy, rule-based Mamdani type, fuzzy logic

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Authors: Lina Najafian, Hamidreza Vakilifard

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The present study focused on the relationship between the quality of accruals and non-systematic risk. The independent study variables included the ability of accruals, the information content of accruals, and amount of discretionary accruals considered as accruals quality measures. The dependent variable was non-systematic risk based on the Fama and French Three Factor model (FFTFM) and the capital asset pricing model (CAPM). The control variables were firm size, financial leverage, stock return, cash flow fluctuations, and book-to-market ratio. The data collection method was based on library research and document mining including financial statements. Multiple regression analysis was used to analyze the data. The study results showed that there is a significant direct relationship between financial leverage and discretionary accruals and non-systematic risk based on FFTFM and CAPM. There is also a significant direct relationship between the ability of accruals, information content of accruals, firm size, and stock return and non-systematic based on both models. It was also found that there is no relationship between book-to-market ratio and cash flow fluctuations and non-systematic risk.

Keywords: accruals quality, non-systematic risk, CAPM, FFTFM

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Authors: Irene H. Maralit

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Warning labels have been found to inform smokers about the health hazards of smoking, encourage smokers to quit, and prevent nonsmokers from starting to smoke. Warning labels on tobacco products are an ideal way of communicating with smokers. Since the intervention is delivered at the time of smoking, nearly all smokers are exposed to warning labels and pack-a-day smokers could be exposed to the warnings more than 7,000 times per year. Given the reach and frequency of exposure, the proponents want to know the effect of warning labels on smoking behavior. Its aims to identify the profile of the smokers associated with its behavioral variables that best describe the users’ perception. The behavioral variables are AVOID, THINK RISK and FORGO. This research study aims to determine if there is significant relationship between the effect of warning labels on cigarette package on Consumer behavior when grouped according to profile variable. The researcher used quota sampling to gather representative data through purposive means to determine the accurate representation of data needed in the study. Furthermore, the data was gathered through the use of a self-constructed questionnaire. The statistical method used were Frequency count, Chi square, multi regression, weighted mean and ANOVA to determine the scale and percentage of the three variables. After the analysis of data, results shows that most of the respondents belongs to age range 22–28 years old with percentage of 25.3%, majority are male with a total number of 134 with percentage of 89.3% and single with total number of 79 and percentage of 52.7%, mostly are high school graduates with total number of 59 and percentage of 39.3, with regards to occupation, skilled workers have the highest frequency of 37 with 24.7%, Majority of the income of the respondents falls under the range of Php 5,001-Php10,000 with 50.7%. And also with regards to the number of sticks consumed per day falls under 6–10 got the highest frequency with 33.3%. The respondents THINK RISK factor got the highest composite mean which is 2.79 with verbal interpretation of agree. It is followed by FORGO with 2.78 composite mean and a verbal interpretation of agree and AVOID variable with composite mean of 2.77 with agree as its verbal interpretation. In terms of significant relationship on the effects of cigarette label to consumer behavior when grouped according to profile variable, sex and occupation found to be significant.

Keywords: consumer behavior, smokers, warning labels, think risk avoid forgo

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Authors: Abdul Waris Jalili, Yanqing Wang, Som Suor

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This research paper explores the relationship between entrepreneurship education and students' entrepreneurial intentions. It aims to determine if entrepreneurship education reliably predicts students' intention to become entrepreneurs and how and when this relationship occurs. This study aims to investigate the predictive relationship between entrepreneurship education and student entrepreneurial intentions. The goal is to understand the factors that influence this relationship and to identify any mediating or moderating factors. A thorough and systematic search and review of empirical articles published between 2013 and 2023 were conducted. Three databases, Google Scholar, Science Direct, and PubMed, were explored to gather relevant studies. Criteria such as reporting empirical results, publication in English, and addressing the research questions were used to select 35 papers for analysis. The collective findings of the reviewed studies suggest a generally positive relationship between entrepreneurship education and student entrepreneurial intentions. However, recent findings indicate that this relationship may be more complex than previously thought. Mediators and moderators have been identified, highlighting instances where entrepreneurship education indirectly influences student entrepreneurial intentions. The review also emphasizes the need for more robust research designs to establish causality in this field. This research adds to the existing literature by providing a comprehensive review of the relationship between entrepreneurship education and student entrepreneurial intentions. It highlights the complexity of this relationship and the importance of considering mediators and moderators. The study also calls for future research to explore different facets of entrepreneurship education independently and examine complex relationships more comprehensively.

Keywords: entrepreneurship, entrepreneurship education, entrepreneurial intention, entrepreneurial self-efficacy

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Authors: Ayodele James Akinola

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This study examines how social and linguistic variables influenced communication between neurologists and patients in selected university teaching hospitals (UTHs) in southwestern Nigeria. Jacob Mey’s Pragmatic Acts, complemented by Emanuel and Emanuel’s model of doctor-patient relationship, served as the theoretical framework. Data comprising 22 audio-recorded neurologist-patient interactions were collected from two UTHs in the southwestern region of Nigeria. Data revealed that educational attainment of patients has insignificant influence on the interaction where the linguistic prowess of the patient has been impaired for consultative communication. However, the status influenced the degree of attention paid to patients by neurologists and determines the amount of time 'trying to help patients to communicate'. Patients with lower educational status and who could not communicate in English spent more time narrating their ailment to neurologists. Patients with higher educational status and could communicate in English saves consultation time as they express themselves briefly unlike those who were of little or no education in the clinics. Through this, diagnoses and therapeutic processes took eight to 12 minutes. 20 minutes was the longest duration recorded. Neurologist-patient interaction in the observed hospitals is shaped by neurologists’ experience, patients’ social variables and language.

Keywords: medical pragmatics, neurologist-patient interaction, nigeria, socio-linguistic influence

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Authors: Roberto Rosenhaim, Marcos Antonio Crus Moreira, Robson da Cunha, Gerson Gomes Cunha

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This work provides details on the wind speed behavior within cities of Arraial do Cabo and São Pedro da Aldeia located in the Lakes Region of the State of Rio de Janeiro, Brazil. This region has one of the best potentials for wind power generation. In interurban layer, wind conditions are very complex and depend on physical geography, size and orientation of buildings and constructions around, population density, and land use. In the same context, the fundamental surface parameter that governs the production of flow turbulence in urban canyons is the surface roughness. Such factors can influence the potential for power generation from the wind within the cities. Moreover, the use of wind on a small scale is not fully utilized due to complexity of wind flow measurement inside the cities. It is difficult to accurately predict this type of resource. This study demonstrates how fuzzy logic can facilitate the assessment of the complexity of the wind potential inside the cities. It presents a decision support tool and its ability to deal with inaccurate information using linguistic variables created by the heuristic method. It relies on the already published studies about the variables that influence the wind speed in the urban environment. These variables were turned into the verbal expressions that are used in computer system, which facilitated the establishment of rules for fuzzy inference and integration with an application for smartphones used in the research. In the first part of the study, challenges of the sustainable development which are described are followed by incentive policies to the use of renewable energy in Brazil. The next chapter follows the study area characteristics and the concepts of fuzzy logic. Data were collected in field experiment by using qualitative and quantitative methods for assessment. As a result, a map of the various points is presented within the cities studied with its wind viability evaluated by a system of decision support using the method multivariate classification based on fuzzy logic.

Keywords: behavior of winds, wind power, fuzzy logic, sustainable development

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Authors: Sujeeva Sebastian Pereira

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Language Anxiety (LA) – a distinct psychological construct of self-perceptions and behaviors related to classroom language learning – is perceived as a significant variable highly correlated with Second Language Acquisition (SLA). However, the existing scholarship has inadequately explored the nuances of LA in relation to South Asia, especially in terms of Sri Lankan higher education contexts. Thus, the current study, situated within the broad areas of Psychology of SLA and Applied Linguistics, investigates the impact of competency-based LA and identity-based LA on learner achievement among undergraduates of Sri Lanka. Employing a case study approach to explore the impact of LA, 750 undergraduates of the University of Sri Jayewardenepura, Sri Lanka, thus covering 25% of the student population from all seven faculties of the university, were selected as participants using stratified proportionate sampling in terms of ethnicity, gender, and disciplines. The qualitative and quantitative research inquiry utilized for data collection include a questionnaire consisting a set of structured and unstructured questions, and semi-structured interviews as research instruments. Data analysis includes both descriptive and statistical measures. As per the quantitative measures of data analysis, the study employed Pearson Correlation Coefficient test, Chi-Square test, and Multiple Correspondence Analysis; it used LA as the dependent variable, and two types of independent variables were used: direct and indirect variables. Direct variables encompass the four main language skills- reading, writing, speaking and listening- and test anxiety. These variables were further explored through classroom activities on grammar, vocabulary and individual and group presentations. Indirect variables are identity, gender and cultural stereotypes, discipline, social background, income level, ethnicity, religion and parents’ education level. Learner achievement was measured through final scores the participants have obtained for Compulsory English- a common first-year course unit mandatory for all undergraduates. LA was measured using the FLCAS. In order to increase the validity and reliability of the study, data collected were triangulated through descriptive content analysis. Clearly evident through both the statistical analysis and the qualitative analysis of the results is the significant linear negative correlation between LA and learner achievement, and the significant negative correlation between LA and culturally-operated gender stereotypes which create identity disparities in learners. The study also found that both competency-based LA and identity-based LA are experienced primarily and inescapably due to the apprehensions regarding speaking in English. Most participants who reported high levels of LA were from an urban socio-economic background of lower income families. Findings exemplify the linguistic inequality prevalent in the socio-cultural milieu in Sri Lankan society. This inequality makes learning English a dire need, yet, very much an anxiety provoking process because of many sociolinguistic, cultural and ideological factors related to English as a Second Language (ESL) in Sri Lanka. The findings bring out the intricate interrelatedness of both the dependent variable (LA) and the independent variables stated above, emphasizing that the significant linear negative correlation between LA and learner achievement is connected to the affective, cognitive and sociolinguistic domains of SLA. Thus, the study highlights the promise in linguistic practices such as code-switching, crossing and accommodating hybrid identities as strategies in minimizing LA and maximizing the experience of ESL.

Keywords: language anxiety, identity-based anxiety, competence-based anxiety, TESL, Sri Lanka

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Authors: Rajae Tahri, Omar Chokairi, Asmae Saadi, Souad Chaouir

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Background: The factors motivating students to choose a medical career is a long-standing topic of publication and discussion. To our knowledge, no national study on the motivation for choosing medical studies has been published to date. Population and methods: This is an observational, descriptive, and cross-sectional study of first-year medical students at the Faculty of Medicine and Pharmacy of Rabat. An anonymous questionnaire comprising 16 questions was developed and distributed to students during Embryology tutorials. The students were free to fill it in or not. The number of students who consented to participate in the survey was 266. The variables studied are the socio-demographic variables of the students and the reasons for choosing medical studies. Results: The most strongly and frequently chosen reasons for choice by our students were saving lives (64.9%), helping others (62.1%), love of medicine (57%), and reducing suffering (56.5%). The comparison of the results according to gender showed a significant difference between the degree of self-motivation of girls compared to that of boys (p <0.001). The reason that stood out the most for them was teamwork. The presence of a health professional in the family was associated with strong extrinsic motivation (p = 0.005). Conclusion: Understanding medical student career choices would improve our knowledge of the factors that influence medical student learning and performance. This knowledge will make it possible to adapt the educational strategies to maintain the motivation of the students throughout their course as well as during their exercise.

Keywords: motivation, motivational profiles, medical studies, Morocco

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Authors: Rita U. Onolemhemhen, Saheed L. Bello, Akin P. Iwayemi

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The effectiveness of energy demand policy depends on identifying the key drivers of energy demand both in the short-run and the long-run. This paper examines the influence of regional differences on the link between energy demand and other explanatory variables for Nigeria, China and USA using the Vector Error Correction Model (VECM) approach. This study employed annual time series data on energy consumption (ED), real gross domestic product (GDP) per capita (RGDP), real energy prices (P) and urbanization (N) for a thirty-six-year sample period. The utilized time-series data are sourced from World Bank’s World Development Indicators (WDI, 2016) and US Energy Information Administration (EIA). Results from the study, shows that all the independent variables (income, urbanization, and price) substantially affect the long-run energy consumption in Nigeria, USA and China, whereas, income has no significant effect on short-run energy demand in USA and Nigeria. In addition, the long-run effect of urbanization is relatively stronger in China. Urbanization is a key factor in energy demand, it therefore recommended that more attention should be given to the development of rural communities to reduce the inflow of migrants into urban communities which causes the increase in energy demand and energy excesses should be penalized while energy management should be incentivized.

Keywords: economic growth, energy demand, income, real GDP, urbanization, VECM

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Authors: Amirmohsen Behjat, Aleck Ostry, Christina Miewald, Bernie Pauly

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Substantial research has indicated that socioeconomic and demographic characteristics’ of neighborhoods are strong determinants of food security. The aim of this study was to develop a Food Insecurity Neighborhood Index (FINI) based on the associated socioeconomic and demographic variables to identify the areas at potential risk of food insecurity in rural British Columbia (BC). Principle Component Analysis (PCA) technique was used to calculate the FINI for each rural Dissemination Area (DA) using the food security determinant variables from Canadian Census data. Using ArcGIS, the neighborhoods with the top quartile FINI values were classified as food insecure. The results of this study indicated that the most food insecure neighborhood with the highest FINI value of 99.1 was in the Bulkley-Nechako (central BC) area whereas the lowest FINI with the value of 2.97 was for a rural neighborhood in the Cowichan Valley area. In total, 98.049 (19%) of the rural population of British Columbians reside in high food insecure areas. Moreover, the distribution of food insecure neighborhoods was found to be strongly dependent on the degree of rurality in BC. In conclusion, the cluster of food insecure neighbourhoods was more pronounced in Central Coast, Mount Wadington, Peace River, Kootenay Boundary, and the Alberni-Clayoqout Regional Districts.

Keywords: neighborhood food insecurity index, socioeconomic and demographic determinants, principal component analysis, Canada census, ArcGIS

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Authors: Ndidi Ofole

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Ongoing Boko Haram crisis and instability in North-Eastern Nigeria has placed additional stress on academic resilience of female undergraduates who are already challenged by gender discrimination in educational opportunities. Students without resilience lack stress hardiness to cope with academic challenges. There is a limited study on academic resilience targeting this disadvantaged population in Nigeria. Consequently, survey research design was employed to investigate the contextual and personal factors that could predict academic resilience among female undergraduates in Boko Haram Neighbourhood in North-Eastern, Nigeria. Five hundred and thirty female students with age range of 18 to 24 years ( = 19.2; SD=6.9) were randomly drawn from 3 Universities in North-Eastern Nigeria. They responded to five instruments, namely; Academic Resilience scale (r=0.72); Social Support questionnaire (r=0. 64); Social Connectedness questionnaire (r=0.75); Self-Efficacy scale (r=0. 68) and Emotional Regulation questionnaire (r=78). Results showed that there was significant positive relationship between the four independent variables and academic resilience. The variables jointly contributed 5.9% variance in the prediction of academic resilience. In terms of magnitude, social support was most potent while self-efficacy was the least. It concluded that the factors considered in this study are academic resilience facilitators. The outcomes of the study have both theoretical and practical implications.

Keywords: academic resilience, emotional regulation, school connectedness, self-efficacy , social support

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Authors: Nadeem Akhtar, An Ran, Cornelius B. Pratt

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China’s President Xi' vision of Belt and Road Initiative, an infrastructural project of development and connectivity, is attracting international students to Chinese universities, with Pakistan and India among the top-10 countries of origin of those students (Ministry of Education China, 2018). An additional factor in international students’ interest in Chinese universities is their improving global rankings of Chinese universities. Against that backdrop, this study addresses two overarching questions: (a) What factors explain South Asian students’ study-away experiences, particularly in their multicultural environments? and (b) What role do new media play in their adaptation to that environment? This study is guided by Stephen’s (2011) theoretical model, which suggests that social networks influence immigrants’ interactions with host and home culture. The present study used a structured questionnaire distributed through both WeChat and other online platforms to international students studying in Chinese universities. Preliminary results are threefold: (a) that the frequency of use of social media is a predictor of the level of adjustment of the students to their multicultural environment; (b) that social engagement with their international-student peers is a moderating factor in their experiential outcomes; and (c) length of stay in Chinese universities, surprisingly, was not a predictor of adaptation. A major implication of these findings is that, even though social media tend to be criticized for contributing to anomie and to diminishing social capital among youths and millennials, they can be poignant tools for cultural adaptation, particularly among international students in China. It remains to be seen if such outcomes occur among international students in other countries or world regions.

Keywords: adaptation, China's Belt and Road Initiative, international students, social media

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Authors: Yogish Huchaiah, Chandrashekara Krishnappa

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This study considers the optimization and validation of experimental results using Multi-Functional Criteria Technique (MFCT). MFCT is concerned with structuring and solving decision and planning problems involving multiple variables. Production of biodiesel from Composite Oil Methyl Esters (COME) of Jatropha and Pongamia oils, mixed in various proportions and Biodiesel thus obtained from two step transesterification process were tested for various Physico-Chemical properties and it has been ascertained that they were within limits proposed by ASTME. They were blended with Petrodiesel in various proportions. These Methyl Esters were blended with Petrodiesel in various proportions and coded. These blends were used as fuels in a computerized CI DI engine to investigate Performance and Emission characteristics. From the analysis of results, it was found that 180MEM4B20 blend had the maximum Performance and minimum Emissions. To validate the experimental results, MFCT was used. Characteristics such as Fuel Consumption (FC), Brake Power (BP), Brake Specific Fuel Consumption (BSFC), Brake Thermal Efficiency (BTE), Carbon dioxide (CO2), Carbon Monoxide (CO), Hydro Carbon (HC) and Nitrogen oxide (NOx) were considered as dependent variables. It was found from the application of this method that the optimized combination of Injection Pressure (IP), Mix and Blend is 178MEM4.2B24. Overall corresponding variation between optimization and experimental results was found to be 7.45%.

Keywords: COME, IP, MFCT, optimization, PI, PN, PV

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Authors: Carmen Cantuarias-Villessuzanne, Jeffrey Blain, Radmila Pineau

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Our research project aims at analyzing the sensitiveness of French households to urban biodiversity and urban ecosystem services (UES). Opinion surveys show that the French population is sensitive to biodiversity and ecosystem services loss, but the value given to these issues within urban fabric and real estate market lacks evidence. Using GIS data and economic evaluation, by hedonic price methods, weassess the isolated contribution of the explanatory variables of biodiversityand UES on the price of residential real estate. We analyze the variation of the valuefor three urban ecosystem services - flood control, proximity to green spaces, and refreshment - on the price of real estate whena property changes ownership. Our modeling and mapping focus on the price at theIRIS scale (statistical information unit) from 2014 to 2019. The main variables are internal characteristics of housing (area, kind of housing, heating), external characteristics(accessibility and infrastructure, economic, social, and physical environmentsuch as air pollution, noise), and biodiversity indicators and urban ecosystemservices for the Ile-de-France region. Moreover, we compare environmental values on the enhancement of greenspaces and their impact on residential choices. These studies are very useful for real estate developers because they enable them to promote green spaces, and municipalities to become more attractive.

Keywords: urban ecosystem services, sustainable real estate, urban biodiversity perception, hedonic price, environmental values

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Authors: Dai-Ling Li, Jung-Fa Cheng, Min-Lang Huang, Yun-Yao Chi

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The hedonic pricing model has been popularly applied to describe the economic value of environmental amenities in urban housing, but the results for cultural heritage variables remain relatively ambiguous. In this paper, integrated variables extending by GIS-based data and an existing typology of communities used to examine how cultural heritage and environmental amenities and disamenities affect housing prices across urban communities in Tainan, Taiwan. The developed models suggest that, although a sophisticated variable for central services is selected, the centrality of location is not fully controlled in the price models and thus picked up by correlated peripheral and central amenities such as cultural heritage, open space or parks. Analysis of these correlations permits us to qualify results and present a revised set of relatively reliable estimates. Positive effects on housing prices are identified for views, various types of recreational infrastructure and vicinity of nationally cultural sites and significant landscapes. Negative effects are found for several disamenities including wasteyards, refuse incinerators, petrol stations and industries. The results suggest that systematic hypothesis testing and reporting of correlations may contribute to consistent explanatory patterns in hedonic pricing estimates for cultural heritage and landscape amenities in urban.

Keywords: hedonic pricing model, cultural heritage, landscape amenities, housing

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Authors: Fernanda A. P. Peres, Thiago N. Peres, Flavio S. Fogliatto, Michel J. Anzanello

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Batch processes are widely used in food industry and have an important role in the production of high added value products, such as chocolate. Process performance is usually described by variables that are monitored as the batch progresses. Data arising from these processes are likely to display a strong correlation-autocorrelation structure, and are usually monitored using control charts based on multiway principal components analysis (MPCA). Process control of a new batch is carried out comparing the trajectories of its relevant process variables with those in a reference set of batches that yielded products within specifications; it is clear that proper determination of the reference set is key for the success of a correct signalization of non-conforming batches in such quality control schemes. In chocolate manufacturing, misclassifications of non-conforming batches in the conching phase may lead to significant financial losses. In such context, the accuracy of process control grows in relevance. In addition to that, the main assumption in MPCA-based monitoring strategies is that all batches are synchronized in duration, both the new batch being monitored and those in the reference set. Such assumption is often not satisfied in chocolate manufacturing process. As a consequence, traditional techniques as MPCA-based charts are not suitable for process control and monitoring. To address that issue, the objective of this work is to compare the performance of three dynamic time warping (DTW) methods in the alignment and synchronization of chocolate conching process variables’ trajectories, aimed at properly determining the reference distribution for multivariate statistical process control. The power of classification of batches in two categories (conforming and non-conforming) was evaluated using the k-nearest neighbor (KNN) algorithm. Real data from a milk chocolate conching process was collected and the following variables were monitored over time: frequency of soybean lecithin dosage, rotation speed of the shovels, current of the main motor of the conche, and chocolate temperature. A set of 62 batches with durations between 495 and 1,170 minutes was considered; 53% of the batches were known to be conforming based on lab test results and experts’ evaluations. Results showed that all three DTW methods tested were able to align and synchronize the conching dataset. However, synchronized datasets obtained from these methods performed differently when inputted in the KNN classification algorithm. Kassidas, MacGregor and Taylor’s (named KMT) method was deemed the best DTW method for aligning and synchronizing a milk chocolate conching dataset, presenting 93.7% accuracy, 97.2% sensitivity and 90.3% specificity in batch classification, being considered the best option to determine the reference set for the milk chocolate dataset. Such method was recommended due to the lowest number of iterations required to achieve convergence and highest average accuracy in the testing portion using the KNN classification technique.

Keywords: batch process monitoring, chocolate conching, dynamic time warping, reference set distribution, variable duration

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Authors: Wilhelmus Hary Susilo

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The marketplace would have at least some resources that are unique (e.g., well communication, knowledgeable employees, consumer value, effective transaction, efficient production processes and institutional branding). The institutions should have an advantage in resources and then could lead to positions of competitive advantage. These major challenges focus on increasing unique consumer value on reliable purchases that influence of loyalty and pursuit of a sustainable competitive advantage from the Institutions in Jakarta. Furthermore, a research was conducted with a quantitative method and a confirmatory strategic research design. The research resulted in entire confirmatory factors analysis (1st CFA and 2nd CFA) among variables pertains to; χ2//Df (9.30, 4.38, 6.95, 2.76, 2.97, 2.91, 2.32 and 6.90), GFI (0.72, 0.82, 0.82, 0.81, 0.78, 0.84, 0.89 and 0.70) and CFI (0.90, 0.95, 0.93, 0.92, 0.95, 0.91, 0.96 and 0.89), which indicates a good model. Furthermore, the hybrid model is well fit with, χ2//Df=1.84, P value = 0.00, RMSEA = 0.076, GFI = 0.76, NNFI= 0.95, PNFI= 0.82, IFI= 0.96, RFI= 0.91, AGFI= 0.71 and CFI= 0.96. The result was significant hypothesis, i.e. variables of communitization marketing 3.0 and price perception influenced to unique value of consumer with tvalue =4.46 and 5.89. Furthermore, the consumers value influenced the purchasing with t value = 5.94. Additionally, the loyalty, the ‘communitization’, and the character building marketing 3.0 are affecting the pursuit of a sustainable competitive advantage from institutions with t value = 7.57, -2.12, and 2.04. Finally, the test between the most superior variable dimensions is significantly correlated between INOV and WDES, RESPON and ATT covariance matrix value= 0.72 and 0.71. Thus, ‘communitization’ and character building marketing 3.0 with dimensions of responsibility and technologies would increase a competitive advantage with the dimensions of the innovation and the job design from the institutions.

Keywords: consumer loyalty, marketing 3.0, unique consumer value, purchase, sustainable competitive advantage

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Authors: Chokri Slim

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The relative failure of simultaneous equation models in the seventies has led researchers to turn to other approaches that take into account the dynamics of economic and financial systems. In this paper, we use an approach based on vector autoregressive model that is widely used in recent years. Their popularity is due to their flexible nature and ease of use to produce models with useful descriptive characteristics. It is also easy to use them to test economic hypotheses. The standard econometric techniques assume that the series studied are stable over time (stationary hypothesis). Most economic series do not verify this hypothesis, which assumes, when one wishes to study the relationships that bind them to implement specific techniques. This is cointegration which characterizes non-stationary series (integrated) with a linear combination is stationary, will also be presented in this paper. Since the work of Johansen, this approach is generally presented as part of a multivariate analysis and to specify long-term stable relationships while at the same time analyzing the short-term dynamics of the variables considered. In the empirical part, we have applied these concepts to study the dynamics of of the exchange rate in Tunisia, which is one of the most important economic policy of a country open to the outside. According to the results of the empirical study by the cointegration method, there is a cointegration relationship between the exchange rate and its determinants. This relationship shows that the variables have a significant influence in determining the exchange rate in Tunisia.

Keywords: stationarity, cointegration, dynamic models, causality, VECM models

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Authors: N. J. Shanono, J. G. Ndiritu

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The poor performance of water resource systems (WRS) has been reportedly linked to not only climate variability and the water demand dynamics but also human behaviour-driven unlawful activities. Some of these unlawful activities that have been adversely affecting water sector include unauthorized water abstractions, water wastage behaviour, refusal of water re‐use measures, excessive operational losses, discharging untreated or improperly treated wastewater, over‐application of chemicals by agricultural users and fraudulent WRS operation. Despite advances in WRS planning, operation, and analysis incorporating such undesirable human activities to quantitatively assess their impact on WRS performance remain elusive. This study was then inspired by the need to develop a methodological framework for WRS performance assessment that integrates the impact of human behaviour with WRS performance assessment analysis. We, therefore, proposed a conceptual framework for assessing the impact of human behaviour on WRS performance using the concept of socio-hydrology. The framework identifies and couples four major sources of WRS-related values (water values, water systems, water managers, and water users) using three missing links between human and water in the management of WRS (interactions, outcomes, and feedbacks). The framework is to serve as a database for choosing relevant social and hydrological variables and to understand the intrinsic relations between the selected variables to study a specific human-water problem in the context of WRS management.

Keywords: conceptual framework, human behaviour; socio-hydrology; water resource systems

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Authors: Theodorou Kyriaki, Ypsilantis George

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Vocabulary learning has attracted a lot of attention in recent years, contrary to the neglected part of the past. Along with the interest in finding successful vocabulary teaching strategies, many scholars focused on locating learning strategies used by language learners. As a result, more and more studies in the area of language pedagogy have been investigating the use of strategies in vocabulary learning by different types of learners. A common instrument in this field is the questionnaire, a tool of work that was enriched by questions involving current technology, and it was further implemented to a sample of 300 Greek students whose age varied from 9 and 17 years. Strategies located were grouped into the three categories of memory, cognitive, and compensatory type and associations between these dependent variables were investigated. In addition, relations between dependent and independent variables (such as age, sex, type of school, cultural background, and grade in English) were pursued to investigate the impact on strategy selection. Finally, results were compared to findings of other studies in the same field to contribute to a hypothesis of ethnic differences in strategy selection. Results initially discuss preferred strategies of all participants and further indicate that: a) technology affects strategy selection while b) differences between ethnic groups are not statistically significant. A number of successful strategies are presented, resulting from correlations of strategy selection and final school grade in English.

Keywords: acquisition of English, internet technology, research among Greek students, vocabulary learning strategies

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Authors: Mitku Malede Ymer

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The study was mainly intended to explore the impact of asset diversification on the financial performance of thirteen purposely selected Ethiopian commercial banks with seven consecutive years of data for the period 2011-2017, considering the availability of data. An explanatory research design has been employed to determine the impact of asset diversification on financial performance. In the meantime, a quantitative approach was used to construct the empirical model. Banks’ financial performance was measured using return on asset, and the four variables used to measure asset diversification were cash holding, fixed assets, foreign deposits, and NBE Bills, which were predictor variables. Again, the size of the bank was considered as a control variable. Then, a pooled panel regression model was employed to analyze the collected data. The result pretends that cash holding has a positive but marginally insignificant effect on financial performance, fixed assets, and foreign bank deposits have a positive and significant effect on financial performance, and NBE Bills have a negative and significant effect on banks' financial performance. Ultimately, it has been concluded that asset diversification has a significant effect on financial performance in the Ethiopian commercial banking sector. Hence, a researcher suggests that banks need to optimize their asset diversification so as to realize maximum profit and minimize the cost of funds based on the result of the study.

Keywords: asset diversification, financial performance, role, commercial banks

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Authors: Yongxin Chen, Min Zhang

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As industrial enterprises are the primary source of national pollution, environmental information disclosure is a crucial way to demonstrate to stakeholders the work they have done in fulfilling their environmental responsibilities and accepting social supervision. In the era of the digital economy, many companies, actively embracing the opportunities that come with digital transformation, have begun to apply digital technology to information collection and disclosure within the enterprise. However, less is known about the relationship between digital transformation and environmental disclosure. This study investigates how enterprise digital transformation affects environmental disclosure in 643 Chinese industrial companies, according to information processing theory. What is intriguing is that the depth (size) and breadth (diversity) of environmental disclosure linearly increase with the rise in the collection, processing, and analytical capabilities in the digital transformation process. However, the volume of data will grow exponentially, leading to a marginal increase in the economic and environmental costs of utilizing, storing, and managing data. In our empirical findings, linearly increasing benefits and marginal costs create a unique inverted U-shaped relationship between the degree of digital transformation and environmental disclosure in the Chinese industrial sector. Besides, based on the upper echelons theory, we also propose that the top management team with high stability and managerial capabilities will invest more effort and expense into improving environmental disclosure quality, lowering the carbon footprint caused by digital technology, maintaining data security etc. In both these contexts, the increasing marginal cost curves would become steeper, weakening the inverted U-shaped slope between DT and ED.

Keywords: digital transformation, environmental disclosure, the top management team, information processing theory, upper echelon theory

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence

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