Search results for: explanatory variables

Authors: N. Ismail, O. Thammajinda, U. Thongpanya

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Games-based learning (GBL) has become increasingly important in teaching and learning. This paper explains the first two phases (analysis and design) of a GBL development project, ending up with a prototype design based on students’ and teachers’ perceptions. The two phases are part of a full cycle GBL project aiming to help secondary school students in Thailand in their study of Comprehensive Sex Education (CSE). In the course of the study, we invited 1,152 students to complete questionnaires and interviewed 12 secondary school teachers in focus groups. This paper found that GBL can serve students in their learning about CSE, enabling them to gain understanding of their sexuality, develop skills, including critical thinking skills and interact with others (peers, teachers, etc.) in a safe environment. The objectives of this paper are to outline the development of GBL variables from the research question(s) into the developers’ flow chart, to be responsive to the GBL beneficiaries’ preferences and expectations, and to help in answering the research questions. This paper details the steps applied to generate GBL variables that can feed into a game flow chart to develop a GBL prototype. In our approach, we detailed two models: (1) Game Elements Model (GEM) and (2) Game Object Model (GOM). There are three outcomes of this research – first, to achieve the objectives and benefits of GBL in learning, game design has to start with the research question(s) and the challenges to be resolved as research outcomes. Second, aligning the educational aims with engaging GBL end users (students) within the data collection phase to inform the game prototype with the game variables is essential to address the answer/solution to the research question(s). Third, for efficient GBL to bridge the gap between pedagogy and technology and in order to answer the research questions via technology (i.e. GBL) and to minimise the isolation between the pedagogists “P” and technologist “T”, several meetings and discussions need to take place within the team.

Keywords: games-based learning, engagement, pedagogy, preferences, prototype

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Authors: J. García-Pérez

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An approach to compute optimum seismic design parameters is presented. It is based on the optimization of the expected present value of the total cost, which includes the initial cost of structures as well as the cost due to earthquakes. Different types of seismicity models are considered, including one for characteristic earthquakes. Uncertainties are included in some variables to observe the influence on optimum values. Optimum seismic design coefficients are computed for three different structural types representing high, medium and low rise buildings, located near and far from the seismic sources. Ordinary and important structures are considered in the analysis. The results of optimum values show an important influence of seismicity models as well as of uncertainties on the variables.

Keywords: importance factors, optimum parameters, seismic losses, seismic risk, total cost

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Authors: Tessy Treesa Jose, Sripathy M. Bhat

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Nursing is recognized as a stressful occupation and has indicated a probable high prevalence of distress. It is a helping profession requiring a high degree of commitment and involvement. If stress is intense, continuous and repeated, it becomes a negative phenomenon or "distress," which can lead to physical illness and psychological disorders. The frequency of common psychosomatic symptoms including sleeping problems, tension headache, chronic fatigue, palpitation etc. may be an indicator of nurses’ work-related stress level. Objectives of the study were to determine psychiatric morbidity among nurses and to find its association with selected variables. The study population consisted of 1040 registered nurses working in selected medical college hospitals and government hospitals of Udupi and Mangalore districts. Descriptive survey design was used to conduct the study. Subjects were selected by using purposive sampling. Data were gathered by administering background proforma and General Health questionnaire. Severe distress was experienced by 0.9% of nurses and 5.6% had some evidence of distress. Subjects who did not have any distress were 93.5%. No significant association between psychiatric morbidity in nurses and demographic variables was observed. With regard to work variables significant association is observed between psychiatric morbidity and total years of experience (z=10.67, p=0.03) and experience in current area of work (z=9.43, p=0.02).

Keywords: psychiatric morbidity, nurse, selected hospitals, working

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Authors: Francis Mark A. Fernandez, Chelca Ubay, Armithan Suguitan

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Regions or provinces in a definite state certainly contribute to the economy of their mainland. These regions or provinces are the ones supplying the mainland with different resources and assets. Thus, with a certain region separating from the mainland would indeed impinge the heart of an entire state to develop and expand. With these, the researchers decided to study on the effects of the separation of one’s region to its mainland and the consequences that will take place if the mainland would rule out the region to separate from them. The researchers wrote this paper to present the causes of the separation of Catalonia from Spain and the prediction regarding the pursuance of this region to revolt from its mainland, Spain. In conducting this research, the researchers utilized two analyses, namely: qualitative and quantitative. In qualitative, numerous of information regarding the existing experiences of the citizens of Catalonia were gathered by the authors to give certainty to the prediction of the researchers. Besides this undertaking, the researchers will also gather needed information and figures through books, journals and the published news and reports. In addition, to further support this prediction under qualitative analysis, the researchers intended to operate the Phenomenological research in which the examiners will exemplify the lived experiences of each citizen in Catalonia. Moreover, the researchers will utilize one of the types of Phenomenological research which is hermeneutical phenomenology by Van Manen. In quantitative analysis, the researchers utilized the regression analysis in which it will ascertain the causality in an underlying theory in understanding the relationship of the variables. The researchers assigned and identified different variables, wherein the dependent variable or the y which represents the prediction of the researchers, the independent variable however or the x represents the arising problems that grounds the partition of the region, the summation of the independent variable or the ∑x represents the sum of the problem and finally the summation of the dependent variable or the ∑y is the result of the prediction. With these variables, using the regression analysis, the researchers will be able to show the connections and how a single variable could affect the other variables. From these approaches, the prediction of the researchers will be specified. This research could help different states dealing with this kind of problem. It will further help certain states undergoing this problem by analyzing the causes of these insurgencies and the effects on it if it will obstruct its region to consign their full-pledge autonomy.

Keywords: autonomy, liberty, prediction, separation

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Authors: Adelina Castelo

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The increasing number of learners of Portuguese as Foreign Language in China justifies the need to define the phonetic profile of these learners and to design didactic materials that are adjusted to their specific problems in pronunciation. Different aspects of this topic have been studied, but the production of oral vowels still needs to be investigated. This study aims: (i) to identify the problems the Chinese learners of Portuguese experience in the pronunciation of oral vowels; (ii) to discuss the didactic implications drawn from those problems. The participants were eight native speakers of Mandarin Chinese that had been learning Portuguese in College for almost a year. They named pictured objects and their oral productions were recorded and phonetically transcribed. The selection of the objects to name took into account some linguistic variables (e.g. stress pattern, syllable structure, presence of the Portuguese oral vowels in different word positions according to stress location). The results are analysed in two ways: the impact of linguistic variables on the success rate in the vowels' production; the replacement strategies used in the non-target productions. Both analyses show that the Chinese learners of Portuguese (i) have significantly more difficulties with the mid vowels as well as the high central vowel and (ii) do not master the vowel height feature. These findings contribute to define the phonetic profile of these learners in terms of oral vowel production. Besides, they have important didactic implications for the pronunciation teaching to these specific learners. Those implications are discussed and exemplified.

Keywords: Chinese learners, learners’ phonetic profile, linguistic variables, Portuguese as foreign language, production data, pronunciation teaching, oral vowels

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Authors: Selin Kara-Bahçekapılı, Bengisu Nehir Aydın

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Objective: In this study, it is aimed to examine the relationship between childhood traumas (overprotection-control, emotional/physical/sexual abuse, emotional/physical neglect), age, emotional regulation difficulties, and the tendency of violence in adults. In the study, the direct and indirect effects of 6 sub-factors of childhood traumas, emotion regulation difficulties, and age on tendency to violence are evaluated on a model that theoretically reveals. Method: The population of this cross-sectional study consists of individuals between the ages of 18-65 living in Turkey. The data from 527 participants were obtained by online surveys and convenience sampling method within the scope of the study. As a result of exclusion criteria and then outlier data analysis, the data of 443 participants were included in the analysis. Data were collected by demographic information form, childhood trauma scale, emotion regulation difficulty scale, and violence tendency scale. Research data were analyzed by SPSS and AMOS using correlation, path analysis, direct and indirect effects. Results: According to the research findings, the variables in the model explained 28.2% of the variance of the mean scores of the individuals' tendency to violence. Emotion regulation difficulties have the most direct effect on the tendency to violence (d=.387; p<.01). The effects of excessive protection and control, emotional neglect, and physical neglect variables on the tendency to violence are not significant. When the significant and indirect effects of the variables on tendency to violence over emotion regulation difficulties are examined, age has a negative effect, emotional neglect has a positive effect, emotional abuse has a positive effect, and overprotection-control has a positive effect. The indirect effects of sexual abuse, physical neglect, and physical abuse on tendency to violence are not significant. Childhood traumas and age variables in the model explained 24.1% of the variance of the mean scores of the individuals’ emotion regulation difficulties. The variable that most affects emotion regulation difficulties is age (d=-.268; p<.001). The direct effects of sexual abuse, physical neglect, and physical abuse on emotion regulation difficulties are not significant. Conclusion: The results of the research emphasize the critical role of difficulty in emotion regulation on the tendency to violence. Difficulty in emotion regulation affects the tendency to violence both directly and by mediating different variables. In addition, it is seen that some sub-factors of childhood traumas have direct and/or indirect effects on the tendency to violence. Emotional abuse and age have both direct and indirect effects on the tendency to violence over emotion regulation difficulties.

Keywords: childhood trauma, emotion regulation difficulties, tendency to violence, path analysis

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Authors: Tarul Garg, P. N. Agrawal

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We propose to define the q-analogue of the α-Bernstein Kantorovich operators and then introduce the q-bivariate generalization of these operators to study the approximation of functions of two variables. We obtain the rate of convergence of these bivariate operators by means of the total modulus of continuity, partial modulus of continuity and the Peetre’s K-functional for continuous functions. Further, in order to study the approximation of functions of two variables in a space bigger than the space of continuous functions, i.e. Bögel space; the GBS (Generalized Boolean Sum) of the q-bivariate operators is considered and degree of approximation is discussed for the Bögel continuous and Bögel differentiable functions with the aid of the Lipschitz class and the mixed modulus of smoothness.

Keywords: Bögel continuous, Bögel differentiable, generalized Boolean sum, K-functional, mixed modulus of smoothness

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Authors: Ng Liang Shen, Ngahzaifa Abdul Ghani

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This research aimed at developing an early warning system for pre-diabetic and diabetics by analyzing simple and easily determinable signs and symptoms of diabetes among the people living in Malaysia using Particle Swarm Optimized Artificial. With the skyrocketing prevalence of Type 2 diabetes in Malaysia, the system can be used to encourage affected people to seek further medical attention to prevent the onset of diabetes or start managing it early enough to avoid the associated complications. The study sought to find out the best predictive variables of Type 2 Diabetes Mellitus, developed a system to diagnose diabetes from the variables using Artificial Neural Networks and tested the system on accuracy to find out the patent generated from diabetes diagnosis result in machine learning algorithms even at primary or advanced stages.

Keywords: diabetes diagnosis, Artificial Neural Networks, artificial intelligence, soft computing, medical diagnosis

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Authors: F. A. F. da Ponte, J. Q. Malveira, I. A. Maciel, M. C. G. Albuquerque

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In this work aviation, biofuel production was studied by fatty acids (C6 to C16) esterification. The process variables in heterogeneous catalysis were evaluated using an experimental design. Temperature and reaction time were the studied parameters, and the methyl esters content was the response of the experimental design. An ion exchange resin was used as a heterogeneous catalyst. The process optimization was carried out using response surface methodology (RSM) and polynomial model of second order. Results show that the most influential variables on the linear coefficient of each effect studied were temperature and reaction time. The best result of methyl esters conversion in the experimental design was under the conditions: 10% wt of catalyst; 100 °C and 4 hours of reaction. The best-achieved conversion was 96.5% wt of biofuel.

Keywords: esterification, ion-exchange resins, response surface methodology, biofuel

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Authors: Goran Sporiš, Dinko Vuleta, Stefan Lovro

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The purpose of the present study was to determine the associations between health-related quality of life (HRQOL) and physical activity (PA) in different domains. In this cross-sectional study, participants were 169 Croatian police officers (mean age 35.14±8.95 yrs, mean height 180.93±7.53 cm, mean weight 88.39±14.05 kg, mean body-mass index 26.90±3.39 kg/m2). The dependent variables were two general domains extracted from the HRQOL questionnaire: (1) physical component scale (PCS) and (2) mental component scale (MCS). The independent variables were job-related, transport, domestic and leisure-time PA, along with other factors: age, body-mass index, smoking status, psychological distress, socioeconomic status and time spent in sedentary behaviour. The associations between dependent and independent variables were analyzed by using multiple regression analysis. Significance was set up at p < 0.05. PCS was positively associated with leisure-time PA (β 0.28, p < 0.001) and socioeconomic status (SES) (β 0.16, p=0.005), but inversely associated with job-related PA (β -0.15, p=0.012), domestic-time PA (β -0.14, p=0.014), age (β -0.12, p=0.050), psychological distress (β -0.43, p<0.001) and sedentary behaviour (β -0.15, p=0.009). MCS was positively associated with leisure-time PA (β 0.19, p=0.013) and SES (β 0.20, p=0.002), while inversely associated with age (β -0.23, p=0.001), psychological distress (β -0.27, p<0.001) and sedentary behaviour (β -0.22, p=0.001). Our results added new information about the associations between domain-specific PA and both physical and mental component scale in police officers. Future studies should deal with the same associations in other stressful occupations.

Keywords: health, fitness, police force, relations

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Authors: S. Rustagi, N. S. Sodhi, B. Dhillon, T. Kaur

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The objective of this study was to check whether there is any relationship between electromyographic (EMG) and textural parameters during food texture evaluation. In this study, a total of eighteen mastication variables were measured for entire mastication, per chew mastication and three different stages of mastication (viz. early, middle and late) by EMG for five different foods using eight human subjects. Cluster analysis was used to reduce the number of mastication variables from 18 to 5, so that principal component analysis (PCA) could be applied on them. The PCA further resulted in two meaningful principal components. The principal component scores for each food were measured and correlated with five textural parameters (viz. hardness, cohesiveness, chewiness, gumminess and adhesiveness). Correlation coefficients were found to be statistically significant (p < 0.10) for cohesiveness and adhesiveness while if we reduce the significance level (p < 0.20) then chewiness also showed correlation with mastication parameters.

Keywords: electromyography, mastication, sensory, texture

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Authors: Godwin Chigozie Okpara, Eugene Iheanacho

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This paper examined the dynamic behavior of stock market development and the growth of Nigerian economy. The variables; market capitalization ratio, turnover ratio and liquidity proxies by the ratio of market capitalization to gross domestic product were sourced and computed from the Nigerian stock exchange fact books and the CBN statistical bulletin of the Central Bank of Nigeria. The variables were tested and found stationary and cointregrated using the augumented Dickey Fuller unit root test and the Johnson cointegration test respectively. The dynamic behavior of the stock market development model was verified using the error correction model. The result shows that about 0.4l percent of the short run deviation is corrected every year and also reveals that market capitalization ratio and market liquidity are positive and significant function of economic growth. In other words market capitalization ratio and liquidity positively and significantly impact economic growth. Market development variables such as turnover ratio and market restriction can exert positive but insignificant impact on the growth of the economy suggesting that securities transaction relative to the size of the securities market are not high enough to significantly engender economic growth in Nigeria. In the light of this, the researchers recommend that the regulatory body as well as the government, should provide a conducive environment capable of encouraging the growth and development of the stock market. This if well articulated will enhance the market turnover and the growth of the economy.

Keywords: market capitalization ratio, turnover ratio, liquidity, unit root test, cointegration

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Authors: Dasom Kim, William Xiu Shun Wong, Yoonjin Hyun, Donghoon Lee, Minji Paek, Sungho Byun, Namgyu Kim

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There have been many researches on document classification for classifying voluminous documents automatically. Through document classification, we can assign a specific category to each unlabeled document on the basis of various machine learning algorithms. However, providing labeled documents manually requires considerable time and effort. To overcome the limitations, the semi-supervised learning which uses unlabeled document as well as labeled documents has been invented. However, traditional document classifiers, regardless of supervised or semi-supervised ones, cannot sufficiently explain the reason or the process of the classification. Thus, in this paper, we proposed a methodology to visualize major topics and class components of each document. We believe that our methodology for visualizing topics and classes of each document can enhance the reliability and explanatory power of document classifiers.

Keywords: data mining, document classifier, text mining, topic modeling

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Authors: Reetinder Kaur, R. K. Pathak

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Mental health is recognised as an important global health concern. World Health Organisation in 2004 estimated that neuropsychiatric illnesses in India account for 10.8 percent of the global burden. The prevalence of serious mental illnesses is estimated as 6.5 percent by National Commission of Macroeconomics and Health in 2005. India spends only 0.06 percent of its health budget on mental health. One of the major problems that exist in Indian mental health care is the treatment gap due to scarcity of manpower, inadequate infrastructure and deficiencies in policy initiatives. As a result, traditional healing is a popular resource for mentally ill individuals and their families. The various traditional healing resources include faith healers, healers at temples and Dargahs. Chandigarh is a Union Territory located in North India. It has surplus manpower and infrastructure available for mental health care. Inspite of availability of mental health care services, mentally ill individuals and their families seek help from traditional healers at various Dargahs within or outside Chandigarh. For the present study, the data was collected from four dargahs. A total of thirty patients medically diagnosed with various mental illnesses, their family members who accompanied them and healers were part of this study. The aim of the study was to: Understand the interactions between healer, patient and family members during the course of treatment, understand explanations of mental illnesses and analyse the healing practices in context of culture. The interviews were conducted using an interview guide for the three sets of informants: Healers, patients and family members. The interview guide for healer focussed on the healing process, healer’s understanding of patient’s explanatory models, healer’s knowledge about mental illnesses and types of these illnesses cured by the healer. The interview guide for patients and family members focussed on their understanding of the symptoms, explanations for illness and help-seeking behaviour. The patients were observed over the weeks (every Thursday, the day of pir and healing) during their visits to the healer. Detailed discussions were made with the healer regarding the healing process and benefits of healing. The data was analysed thematically and the themes: The role of sacred, holistic healing, healer’s understanding of patient’s explanatory models of mental illness, the patient’s, and family’s understanding of mental illnesses, healer’s knowledge about mental illnesses, types of mental illnesses cured by the healer, bad dreams and their interpretation emerged. From the analysis of data, it was found that the healers concentrate their interventions in the social arena, ‘curing’ distressed patients by bringing significant changes in their social environment. It is suggested that in order to make the mental health care services effective in India, the collaboration between healers and psychiatrist is essential. However, certain specifications need to be made to make this kind of collaboration successful and beneficial for the stakeholders.

Keywords: Dargah, mental illness, traditional healing, policy

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Authors: Japnoor Garcha, Andrew P. Smith

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There has been a significant increase in the prevalence and estimates of neurodevelopmental disorders specially autism spectrum disorders in the last decade. The literature has seen increasing research on understanding well-being and mental health. The current studies have focused on seeing the impact of mental health and well-being in autism spectrum disorders and ADHD both with and without a diagnosis. To further understand the association and interaction of well-being and mental health with autism and ADHD a survey was given to 560 secondary school students. The survey used the well-being process questionnaire, the autism spectrum quotient, the ADHD self-report scale, and the strengths and difficulties questionnaire. The analysis conducted using SPSS showed that there was a significant correlation between anxiety, depression, AQ and ADHD. Anxiety and depression were also significantly correlated with all well-being and SDQ variables. The regression analysis showed that anxiety was significantly associated with positive well-being, negative well-being, emotional problems and prosocial behaviour whereas depression was significantly associated with positive well-being, negative well-being, physical health, flourishing, conduct problems, emotional problems and peer problems. This interaction led to the formation of a combined variable to see what impact the variables of anxiety, depression, AQ and ADHD would have coupled together. Further analysis showed that the combined variable was significantly correlated with all outcome variables. The regression analysis showed that the Combined variable was significantly correlated with emotional problems, and hyperactivity, stress, negative coping, psychological capital and sleepiness.

Keywords: AQ, adhd, sdq, well-being, combined variable

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Authors: Chantarat Manvichien, Kevin Wongleedee

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The purpose of this research was to study Thai passengers’ level of understanding and awareness of the cabin crew safety briefing in the airplane during the preparation to take off and landing. It is important to know if Thai passengers pay attention to cabin crew safety briefing and to suggest a better way to draw their attention. The independent variables included gender, age, income, levels of education, travelling purpose, and travelling frequency while the dependent variables was level of awareness. A simple random sampling method was utilized to get 400 respondents. The findings revealed the ranking the first three levels of importance by highest mean to lowest mean as follows: (1) It is important to listen to cabin crew safety briefing; (2) Cabin crew briefing is interesting; (3) Information from cabin crew safety briefing is easy to understand. In addition, the overall means was 3.27 with 0.800 SD.

Keywords: cabin crew, safety briefing, Thai passengers, awareness

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Authors: Naduni Ranasinghe

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E-learning environments are getting more popular than any other due to the impact of COVID19. Even though e-learning is one of the best solutions for the teaching-learning process in the academic process, it’s not without major challenges. Nowadays, machine learning approaches are utilized in the analysis of how behavioral factors lead to better adoption and how they related to better performance of the students in eLearning environments. During the pandemic, we realized the academic process in the eLearning approach had a major issue, especially for the performance of the students. Therefore, an approach that investigates student behaviors in eLearning environments using a data-intensive machine learning approach is appreciated. A hybrid approach was used to understand how each previously told variables are related to the other. A more quantitative approach was used referred to literature to understand the weights of each factor for adoption and in terms of performance. The data set was collected from previously done research to help the training and testing process in ML. Special attention was made to incorporating different dimensionality of the data to understand the dependency levels of each. Five independent variables out of twelve variables were chosen based on their impact on the dependent variable, and by considering the descriptive statistics, out of three models developed (Random Forest classifier, SVM, and Decision tree classifier), random forest Classifier (Accuracy – 0.8542) gave the highest value for accuracy. Overall, this work met its goals of improving student performance by identifying students who are at-risk and dropout, emphasizing the necessity of using both static and dynamic data.

Keywords: academic performance prediction, e learning, learning analytics, machine learning, predictive model

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Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: Kevin De Castro Cogle, Mirian Kubo, Maria Anastasiadi, Fady Mohareb, Claire Rossi

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Background: The bioaccessibility of bioactive compounds is a critical determinant of the nutritional quality of various food products. Despite its importance, there is a limited number of comprehensive studies aimed at assessing how the composition of a food matrix influences the bioaccessibility of a compound of interest. This knowledge gap has prompted a growing need to investigate the intricate relationship between food matrix formulations and the bioaccessibility of bioactive compounds. One such class of bioactive compounds that has attracted considerable attention is curcuminoids. These naturally occurring phytochemicals, extracted from the roots of Curcuma longa, have gained popularity owing to their purported health benefits and also well known for their poor bioaccessibility Project aim: The primary objective of this research project is to systematically assess the influence of matrix composition on the bioaccessibility of curcuminoids. Additionally, this study aimed to develop a series of predictive models for bioaccessibility, providing valuable insights for optimising the formula for functional foods and provide more descriptive nutritional information to potential consumers. Methods: Food formulations enriched with curcuminoids were subjected to in vitro digestion simulation, and their bioaccessibility was characterized with chromatographic and spectrophotometric techniques. The resulting data served as the foundation for the development of predictive models capable of estimating bioaccessibility based on specific physicochemical properties of the food matrices. Results: One striking finding of this study was the strong correlation observed between the concentration of macronutrients within the food formulations and the bioaccessibility of curcuminoids. In fact, macronutrient content emerged as a very informative explanatory variable of bioaccessibility and was used, alongside other variables, as predictors in a Bayesian hierarchical model that predicted curcuminoid bioaccessibility accurately (optimisation performance of 0.97 R2) for the majority of cross-validated test formulations (LOOCV of 0.92 R2). These preliminary results open the door to further exploration, enabling researchers to investigate a broader spectrum of food matrix types and additional properties that may influence bioaccessibility. Conclusions: This research sheds light on the intricate interplay between food matrix composition and the bioaccessibility of curcuminoids. This study lays a foundation for future investigations, offering a promising avenue for advancing our understanding of bioactive compound bioaccessibility and its implications for the food industry and informed consumer choices.

Keywords: bioactive bioaccessibility, food formulation, food matrix, machine learning, probabilistic modelling

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Authors: Thi Thanh Nga Pham, Damien Philippon, Alexis Drogoul, Thi Thu Thuy Nguyen, Tien Cong Nguyen

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Mekong River Delta region of Vietnam is recognized as one of the most vulnerable to climate change due to flooding and seawater rise and therefore an increased burden of climate change-related diseases. Changes in temperature and precipitation are likely to alter the incidence and distribution of vector-borne diseases such as dengue fever. In this region, the peak of the dengue epidemic period is around July to September during the rainy season. It is believed that climate is an important factor for dengue transmission. This study aims to enhance the capacity of dengue prediction by the relationship of dengue incidences with climate and environmental variables for Mekong River Delta of Vietnam during 2005-2015. Mathematical models for vector-host infectious disease, including larva, mosquito, and human being were used to calculate the impacts of climate to the dengue transmission with incorporating geospatial data for model input. Monthly dengue incidence data were collected at provincial level. Precipitation data were extracted from satellite observations of GSMaP (Global Satellite Mapping of Precipitation), land surface temperature and land cover data were from MODIS. The value of seasonal reproduction number was estimated to evaluate the potential, severity and persistence of dengue infection, while the final infected number was derived to check the outbreak of dengue. The result shows that the dengue infection depends on the seasonal variation of climate variables with the peak during the rainy season and predicted dengue incidence follows well with this dynamic for the whole studied region. However, the highest outbreak of 2007 dengue was not captured by the model reflecting nonlinear dependences of transmission on climate. Other possible effects will be discussed to address the limitation of the model. This suggested the need of considering of both climate variables and another variability across temporal and spatial scales.

Keywords: infectious disease, dengue, geospatial data, climate

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Authors: Bola Adeleke, Kayode Ogunsusi

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Heritage sites have evolved to preserve culture and heritage and also to educate and entertain tourists. Tourist travel decisions and behavior are influenced by destination image and value of the experience of tourists. Perceived value is one of the important tools for securing a competitive edge in tourism destinations. The model of Ritchie and Crouch distinguished 36 attributes of competitiveness which are classified into five factors which are quality of experience, touristic attractiveness, environment and infrastructure, entertainment/outdoor activities and cultural traditions. The study extended this model with a different grouping of the determinants of destination competitiveness. The theoretical framework used for this study assumes that apart from attractions already situated in the grove, satisfaction with destination common service, and entertainment and events, can all be used in creating a positive image for/and in attracting customers (destination selection) to visit Osun Sacred Osogbo Grove during and after annual celebrations. All these will impact positively on travel experience of customers as well as their spiritual fulfillment. Destination image has a direct impact on tourists’ satisfaction which consequently impacts on tourists’ likely future behavior on whether to revisit a cultural destination or not. The study investigated the variables responsible for destination image competitiveness of the Heritage Site; assessed the factors enhancing the destination image; and evaluated the perceived value realized by tourists from their cultural experience at the grove. A complete enumeration of tourists above 18 years of age who visited the Heritage Site within the month of March and April 2017 was taken. 240 respondents, therefore, were used for the study. The structured questionnaire with 5 Likert scales was administered. Five factors comprising 63 variables were used to determine the destination image competitiveness through principal component analysis, while multiple regressions were used to evaluate perceived value of tourists at the grove. Results revealed that 11 out of the 12 variables determining the destination image competitiveness were significant in attracting tourists to the grove. From the R-value, all factors predicted tourists’ value of experience strongly (R= 0.936). The percentage variance of customer value was explained by 87.70% of the variance of destination common service, entertainment and event satisfaction, travel environment satisfaction and spiritual satisfaction, with F-value being significant at 0.00. Factors with high alpha value contributed greatly to adding value to enhancing destination and tourists’ experience. 11 variables positively predicted tourist value with significance. Managers of Osun World Heritage Site should improve on variables critical to adding values to tourists’ experience.

Keywords: competitiveness, destination image, Osun Osogbo world heritage site, tourists

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Authors: Kawinphat Lertpongmanee

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The purposes of this study were (1) investigate the English language learning motivation and the attainment of their English proficiency, (2) to find out how motivation and motivational variables of the high and low proficiency subjects are related to their English proficiency. The respondents were 80 fourth-year from Faculty of Management Sciences students in Rajabhat Suansunadha University. The instruments used for data collection were questionnaires. The statistically analyzed by using the SPSS program for frequency, percentage, arithmetic mean, standard deviation (SD), t-test, one-way analysis of variance (ANOVA), and Pearson correlation coefficient. The findings of this study are summarized as there was a significant difference in overall motivation between high and low proficiency groups of subjects at .05 (p < .05), but not in overall motivational variables. Additionally, the high proficiency group had a significantly higher level of intrinsic motivation than did the low proficiency group at .05 (p < .05).

Keywords: English language proficiency, faculty of management sciences, motivation factors, proficiency subjects

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Authors: Amichai Ben ari, Daniella Margalit

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Medical procedures, such as surgery, may have traumatic significance for some children. This study examines the relationship between maltreatment in children and the development Pediatric Medical Traumatic Stress (PMTS). To this end, differences in the level of distress of children after surgery were examined between two groups: children who were maltreated ("children at risk") and children from the control group ("children who are not at risk"). The study involved 230 parents of children who came to the hospital to undergo surgery. Parents filled out demographic questionnaires to measure socioeconomic variables and psychological questionnaires to measure the distress of the child and parent before surgery. After 6 months from the time of surgery, the parents again filled in the questionnaire measuring the child's distress. The results of the study showed that the level of distress experienced by children at risk after surgery was significantly higher relative to children who are not at risk. It was also found that the level of distress experienced by parents of children at risk in relation to their child’s surgery is significantly higher compared to parents of children who are not at risk. Finally, it was found that the variables: (1) pre-morbid psychological functioning of the child. (2) Parental and family functioning in daily life. (3) Exposure of the child to traumatic events. (4) Support factors for the family. Are variables that predict the development of PMTS in children after surgery, but only for children at risk and not for children who are not at risk. The significance of the findings in relation to the need to identify at-risk populations in the hospitals and the policies derived from them were discussed, and several directions were raised for further research.

Keywords: children at risk, pediatric medical traumatic stress (PMTS), PTSD, medical procedures

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Authors: Oyesoji Aremu, Taiwo Williams

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This study examined some factors (academic self-efficacy, locus of control, motivation and gender) that could predict academic dishonesty among serially frustrated students in Ogun State, South West, Nigeria. Serial academically frustrated students are students who are unable to attain and meet academic expectations set by themselves or significant others. A sample of 250 undergraduate students selected from two faculties from a University in Ogun State,South West Nigeria took part in the study. Multiple regression analysis was employed to determine the joint and relative contributions of the independent variables to the prediction of the dependent variable. T-test was used to test the hypothesis determining the gender difference between the independent variables (academic self-efficacy, locus of control and motivation) and academic dishonesty of serial academically frustrated male and female students. The results of the study showed all the independent variables jointly contributed to predicting academic dishonesty, while only academic self-efficacy and motivation had relative contributions to the dependent measure. There was no significant difference in the academic self-efficacy and motivation among males and females on academic dishonesty of the serial academically frustrated students but locus of control showed a significant difference between male and female students on academic dishonesty. Implications for counseling of the findings are discussed in the study.

Keywords: academic dishonesty, serially frustrated students, academic self-efficacy, locus of control

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Authors: Praveen Vayalamkuzhi, Veeraragavan Amirthalingam

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Studies on safety on highways are becoming the need of the hour as over 400 lives are lost every day in India due to road crashes. In order to evaluate the factors that lead to different levels of crash severity, it is necessary to investigate the level of safety of highways and their relation to crashes. In the present study, an attempt is made to identify the factors that contribute to road crashes and to quantify their effect on the severity of road crashes. The study was carried out on a four-lane divided rural highway in India. The variables considered in the analysis includes components of horizontal alignment of highway, viz., straight or curve section; time of day, driveway density, presence of median; median opening; gradient; operating speed; and annual average daily traffic. These variables were considered after a preliminary analysis. The major complexities in the study are the heterogeneous traffic and the speed variation between different classes of vehicles along the highway. To quantify the impact of each of these factors, statistical analyses were carried out using Logit model and also negative binomial regression. The output from the statistical models proved that the variables viz., horizontal components of the highway alignment; driveway density; time of day; operating speed as well as annual average daily traffic show significant relation with the severity of crashes viz., fatal as well as injury crashes. Further, the annual average daily traffic has significant effect on the severity compared to other variables. The contribution of highway horizontal components on crash severity is also significant. Logit models can predict crashes better than the negative binomial regression models. The results of the study will help the transport planners to look into these aspects at the planning stage itself in the case of highways operated under heterogeneous traffic flow condition.

Keywords: geometric design, heterogeneous traffic, road crash, statistical analysis, level of safety

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Authors: Hassan Sadeghi Naeini, Mozhgan Sabzehparvar, Mahdiye Jafarnezhad, Neda Brumandi, Mohammad Parsa Sabzehparvar

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This study aims to discover the relationship between the factors of aesthetics, user experience, and social sustainability concerning the design of street furniture and the impact of these factors on the emotional arousal of citizens to encourage and make them prefer to use street furniture. The method used in this research included extracting indicators related to each of the factors of aesthetics, user experience, and social sustainability from the articles and then selecting indicators related to the purpose of the research in consultation with industrial design experts and architects. Finally, 9 variables for aesthetics, 7 variables for user experience, and 5 variables for evaluating social sustainability were selected. To identify the effect of each of these factors on street furniture and to recognize their relationship with each other. A 10-scale prioritization questionnaire, from 1, the least amount of importance, to 10, the most amount of importance, was answered by architects and industrial designers on the “Pors Line” online platform for three consecutive weeks, and a total of 82 people answered the questionnaire. The results showed that by using aesthetic factors in the design of street furniture and having a positive impact on users’ experience of using the product, we could expect the occurrence of behavioral factors, such as creating constructive interaction and product acceptance so that the satisfaction of the user in the use of street furniture and optimal interaction in the urban environment is formed, followed by that, the requirements of social sustainability will be met.

Keywords: visual aesthetic, user experience, social sustainability, street furniture

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Authors: Flavia Cordeiro, Fabio Silva, Alvaro Eiras, Jose Luiz Acebal

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Aedes aegypti is present in the tropical and subtropical regions of the world and is a vector of several diseases such as dengue fever, yellow fever, chikungunya, zika etc. The growth in the number of arboviruses cases in the last decades became a matter of great concern worldwide. Meteorological factors like mean temperature and precipitation are known to influence the infestation by the species through effects on physiology and ecology, altering the fecundity, mortality, lifespan, dispersion behaviour and abundance of the vector. Models able to describe the dynamics of the vector population size should then take into account the meteorological variables. The relationship between meteorological factors and the population dynamics of Ae. aegypti adult females are studied to provide a good set of predictors to model the dynamics of the mosquito population size. The time-series data of capture of adult females of a public health surveillance program from the city of Lavras, MG, Brazil had its association with precipitation, humidity and temperature analysed through a set of statistical methods for time series analysis commonly adopted in Signal Processing, Information Theory and Neuroscience. Cross-correlation, multicollinearity test and whitened cross-correlation were applied to determine in which time lags would occur the influence of meteorological variables on the dynamics of the mosquito abundance. Among the findings, the studied case indicated strong collinearity between humidity and precipitation, and precipitation was selected to form a pair of descriptors together with temperature. In the techniques used, there were observed significant associations between infestation indicators and both temperature and precipitation in short, mid and long terms, evincing that those variables should be considered in entomological models and as public health indicators. A descriptive model used to test the results exhibits a strong correlation to data.

Keywords: Aedes aegypti, cross-correlation, multicollinearity, meteorological variables

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Authors: Amir Ikram, Faisal Ijaz, Qin Su

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The empirical study was undertaken to explore the determinants of non-performing loans (NPLs) of small and medium enterprises (SMEs) sector held by the commercial banks. Primary data was collected through well-structured survey questionnaire from credit analysts/bankers of 42 branches of 9 commercial banks, operating in the district of Lahore (Pakistan), for 2014-2015. Selective descriptive analysis and Pearson chi-square technique were used to illustrate and evaluate the significance of different variables affecting NPLs. Branch age, duration of the loan, and credit policy were found to be significant determinants of NPLs. The study proposes that bank-specific and SME-specific microeconomic variables directly influence NPLs, while macroeconomic factors act as intermediary variables. Framework exhibiting causal nexus of NPLs was also drawn on the basis of empirical findings. The results elaborate various origins of NPLs and suggest that they are primarily instigated by the loan sanctioning procedure of the financial institution. The paper also underlines the risk management practices adopted by the bank at branch level to averse the risk of loan default. Empirical investigation of bank-specific microeconomic factors of NPLs with respect to Pakistan’s economy is the novelty of the study. Broader strategic policy implications are provided for credit analysts and entrepreneurs.

Keywords: commercial banks, microeconomic factors, non-performing loans, small and medium enterprises

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Authors: Omid Ataei Nia, Karim Salahshoor

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In this paper, a new precise and reliable sensor network methodology is introduced for unit processes and operations using the Constriction Coefficient Particle Swarm Optimization (CPSO) method. CPSO is introduced as a new search engine for optimal sensor network design purposes. Furthermore, a Square Root Unscented Kalman Filter (SRUKF) algorithm is employed as a new data reconciliation technique to enhance the stability and accuracy of the filter. The proposed design procedure incorporates precision, cost, observability, reliability together with importance-of-variables (IVs) as a novel measure in Instrumentation Criteria (IC). To the best of our knowledge, no comprehensive approach has yet been proposed in the literature to take into account the importance of variables in the sensor network design procedure. In this paper, specific weight is assigned to each sensor, measuring a process variable in the sensor network to indicate the importance of that variable over the others to cater to the ultimate sensor network application requirements. A set of distinct scenarios has been conducted to evaluate the performance of the proposed methodology in a simulated Continuous Stirred Tank Reactor (CSTR) as a highly nonlinear process plant benchmark. The obtained results reveal the efficacy of the proposed method, leading to significant improvement in accuracy with respect to other alternative sensor network design approaches and securing the definite allocation of sensors to the most important process variables in sensor network design as a novel achievement.

Keywords: constriction coefficient PSO, importance of variable, MRMSE, reliability, sensor network design, square root unscented Kalman filter

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Authors: Nitin Joseph

Abstract:

Objectives: This study was done to assess emotional intelligence levels and to find out its association with socio demographic variables and perceived stress among medical students. Material and Methods: This study was done among first and second year medical students. Data was collected using a self-administered questionnaire. Results: Emotional intelligence scores was found to significantly increase with age of the participants (F=2.377, P < 0.05). Perceived stress was found to be significantly more among first year (t=1.997, P=0.05). Perceived stress was found to significantly decrease with increasing emotional intelligence scores (r = – 0.226, P < 0.001). Conclusion: First year students were found to be more vulnerable to stress than their seniors probably due to lesser emotional intelligence. As both these parameters are related, ample measures to improve emotional intelligence needs to be supported in the training curriculum of beginners so as to make them more stress free during early student life.

Keywords: emotional intelligence, medical students, perceived stress, socio demographic variables

Procedia PDF Downloads 430