Search results for: robust penalized regression

Authors: Bruce G. Wilson

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The collection of municipal solid waste at the curbside is a complex operation that is repeated daily under varying circumstances around the world. There have been several attempts to develop Monte Carlo simulation models of the waste collection process dating back almost 50 years. Despite this long history, the use of simulation modeling as a planning or optimization tool for waste collection is still extremely limited in practice. Historically, simulation modeling of waste collection systems has been hampered by the limitations of computer hardware and software and by the availability of representative input data. This paper outlines the development of a Monte Carlo simulation model that overcomes many of the limitations contained in previous models. The model uses a general purpose simulation software program that is easily capable of modeling an entire waste collection network. The model treats the stops on a waste collection route as a queue of work to be processed by a collection vehicle (or server). Input data can be collected from a variety of sources including municipal geographic information systems, global positioning system recorders on collection vehicles, and weigh scales at transfer stations or treatment facilities. The result is a flexible model that is sufficiently robust that it can model the collection activities in a large municipality, while providing the flexibility to adapt to changing conditions on the collection route.

Keywords: modeling, queues, residential waste collection, Monte Carlo simulation

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Authors: Yuthapoom Thanakijborisut

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This paper studies consumption insurance against the chronic illness in Thailand. The study estimates the impact of household consumption in the chronic illness on consumption growth. Chronic illness is the health care costs of a person or a household’s decision in treatment for the long term; the causes and effects of the household’s ability for smooth consumption. The chronic illnesses are measured in health status when at least one member within the household faces the chronic illness. The data used is from the Household Social Economic Panel Survey conducted during 2007 and 2012. The survey collected data from approximately 6,000 households from every province, both inside and outside municipal areas in Thailand. The study estimates the change in household consumption by using an ordinary least squares (OLS) regression model. The result shows that the members within the household facing the chronic illness would reduce the consumption by around 4%. This case indicates that consumption insurance in Thailand is quite sufficient against chronic illness.

Keywords: consumption insurance, chronic illness, health care, Thailand

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Authors: Samantha Vennice G. Sarcia

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A person dies every 40 seconds throughout the world due to suicide-related behaviors. Suicidal ideation is a strong precursor to suicide completion. It is one of the major health challenges faced by the world today thus, it is highly substantial. The present study investigated the influence of personality traits and socio-demographic characteristics in predicting suicidal ideation. Using the Suicide Behaviors Questionnaire-Revised and the Big Five Inventory, the degree of suicidal ideation and the associated personality traits were identified. Out of 194 students from the allied health courses, the findings suggest that the college students are at-risk and have passive thoughts about suicide. Using multiple regression analysis, there was an identified significant relationship among the factors associated with suicidal ideation, particularly the number of persons in the household, living arrangement, attendance in church activities, agreeableness, conscientiousness, and neuroticism. Findings can help in the development of campus-based suicide prevention programs.

Keywords: depression, personality traits, suicidal ideation, suicide

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Authors: Aminu Hamza

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This study examines the factors that play vital role in the adoption of mobile payment system among consumers in Nigeria. Technology Acceptance Model (TAM) was used with two additional variables to form the conceptual model. The study was conducted in three Universities in Kano state, Nigeria. Convenience sampling method was used with a total valid 202 respondents which involved the students of Bayero University Kano (BUK), Northwest University, and Kano University of Science and Technology (KUST) Wudil, Kano, Nigeria. Results of the regression analysis revealed that Perceived ease of use (PEOU) and Perceived usefulness (PU) have significant and positive correlation with the behavioral intention to adopt mobile payment system. The findings of this study would be useful to the policy makers Central Bank of Nigeria (CBN), mobile network operators and providers of the services.

Keywords: mobile payment system, Nigeria, technology adoption, technology acceptance model

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Authors: Regina Chua

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To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.

Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling

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Authors: Martin A. Curry

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Madeline Island is a small island community in Wisconsin, USA. Located in Lake Superior, it has been home to the Anishinaabe/Ojibway people for 1000s of years and is known as Moningwankuaning Minis-"The Island of the Golden Breasted Woodpecker". The community relies on summer tourism as its source of income, with a small population of 400 year-round residents. Supervisor Martin A. Curry (Ojibway/German descent) has been working on a fiscally responsible, environmentally principled and culturally centered approach to waste diversion and recycling. The tenets of this program encompass plastics, paper, food waste, local farming, energy production and art education. Through creative writing for the local newspaper and creative interactions, Martin has worked to engage the community in a more robust interest in waste diversion, including setting up a free-will donation store that incorporates elder volunteering opportunities, a compost program that works with the local community garden, biodiesel production and an art program that works with children from the local island school to make paper, grow local food and paint murals. The entirety of this program is based on the Ojibway concept of Mino-Bimadiiziwiin- "The Good Life" and benefits the community and its guests and represents a microcosm of the global dilemmas of waste and recycling.

Keywords: recycling, waste diversion, island, Native American, art

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Authors: Nutcha Taneepanichskul, Helen C. Hailes, Mark Miodownik

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Plastic waste has emerged as a critical global environmental challenge, primarily driven by the prevalent use of conventional plastics derived from petrochemical refining and manufacturing processes in modern packaging. While these plastics serve vital functions, their persistence in the environment post-disposal poses significant threats to ecosystems. Addressing this issue necessitates approaches, one of which involves the development of biodegradable plastics designed to degrade under controlled conditions, such as industrial composting facilities. It is imperative to note that compostable plastics are engineered for degradation within specific environments and are not suited for uncontrolled settings, including natural landscapes and aquatic ecosystems. The full benefits of compostable packaging are realized when subjected to industrial composting, preventing environmental contamination and waste stream pollution. Therefore, effective sorting technologies are essential to enhance composting rates for these materials and diminish the risk of contaminating recycling streams. In this study, it leverage hyperspectral imaging technology (HSI) coupled with advanced machine learning algorithms to accurately identify various types of plastics, encompassing conventional variants like Polyethylene terephthalate (PET), Polypropylene (PP), Low density polyethylene (LDPE), High density polyethylene (HDPE) and biodegradable alternatives such as Polybutylene adipate terephthalate (PBAT), Polylactic acid (PLA), and Polyhydroxyalkanoates (PHA). The dataset is partitioned into three subsets: a training dataset comprising uncontaminated conventional and biodegradable plastics, a validation dataset encompassing contaminated plastics of both types, and a testing dataset featuring real-world packaging items in both pristine and contaminated states. Five distinct machine learning algorithms, namely Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Logistic Regression, and Decision Tree Algorithm, were developed and evaluated for their classification performance. Remarkably, the Logistic Regression and CNN model exhibited the most promising outcomes, achieving a perfect accuracy rate of 100% for the training and validation datasets. Notably, the testing dataset yielded an accuracy exceeding 80%. The successful implementation of this sorting technology within recycling and composting facilities holds the potential to significantly elevate recycling and composting rates. As a result, the envisioned circular economy for plastics can be established, thereby offering a viable solution to mitigate plastic pollution.

Keywords: biodegradable plastics, sorting technology, hyperspectral imaging technology, machine learning algorithms

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Authors: Shubhangi Salokhe

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Agriculture encompasses crop and livestock production, forestry, and fisheries for food and non-food products. Farmers combine land, water, commercial inputs, labor, and their management skills into practices and systems that produce food and fibre. Harvesting of agricultural produce is either followed by the processing of fresh produce or storage for later consumption. All these activities result in a vast generation of waste in terms of crop residue or food waste. So, a large amount of agricultural waste is produced every year. Waste arising from food and agricultural sectors has the potential for vast applications. So, agricultural waste management is an essential component of sustainable agriculture. The major portion of the waste comes from the residues of crops on farms, food processing, livestock, aquaculture, and agro-industry waste. Therefore, management of these agricultural wastes is an important task, and it requires robust strategic planning. It can contribute to three pillars of sustainable agriculture development. It protects the environment (environmental pillar), enhances the livelihoods of farmers (economic pillar), and can contribute to increasing the sustainability of the agricultural sector (social pillar). This paper addresses the essential technological aspects, possible solutions, and sound policy concerns to accomplish long-term way out of agriculture waste management and to minimize the negative impact of waste on the environment. The author has developed a sustainable agriculture waste management model for improving the sustainability of agriculture.

Keywords: agriculture, development, management, waste

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Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

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Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

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Authors: Thachamon Sinsoongsud, Noppawan Piaseu

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This predictive study was aimed to 1) describe self efficacy for risk reduction and preventive behavior for osteoporosis, and 2) examine factors predicting preventive behavior for osteoporosis in nursing students. Through purposive sampling, the sample included 746 nursing students in a public university in Bangkok, Thailand. Data were collected by a self-reported questionnaire on self efficacy and preventive behavior for osteoporosis. Data were analyzed using descriptive statistics and multiple regression analysis with stepwise method. Results revealed that majority of the students were female (98.3%) with mean age of 19.86 + 1.26 years. The students had self efficacy and preventive behavior for osteoporosis at moderate level. Self efficacy and level of education could together predicted 35.2% variance of preventive behavior for osteoporosis (p< .001). Results suggest approaches for promoting preventive behavior for osteoporosis through enhancing self efficacy among nursing students in a public university in Bangkok, Thailand.

Keywords: osteoporosis, self-efficacy, preventive behavior, nursing students

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Authors: Romana P. Khokhar

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The purpose of this study was to explore the impact of work-family conflict on self-esteem. On the basis of the literature reviewed, it was hypothesized that 1) work-family conflict has an impact on self- esteem, 2). There would be a gender difference on the variable of work family conflict. Data for this study was taken from a sample of 70 employees within the banking industry since this industry is generally associated with higher levels of work-family conflict. Statistical tests performed were regression and t-test. Self-esteem was assessed with the 10-item Rosenberg Self-Esteem Scale (RSE; Rosenberg, 1965) and Work-Family Conflict Scale (WFCS; Netemeyer, R. G., Boles, J. S., & McMurrian, R. 1996) was used to assess the level of work –family conflict. The results indicated that an increase in work-family conflict resulted in lower self-esteem due to the various pressures evidenced in a complicated network of direct and indirect influences. It was also determined that there is less effect of work-family conflict on the female workers, as opposed to the male population, leading to the conclusion that in the case of the female workers the impact on self-esteem was not significant.

Keywords: work and family conflict, self-esteem, employee

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Authors: Ayantika Biswas

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Hypertension still remains one of the most important preventable contributors to adult mortality and morbidity and a major public health challenge worldwide. Studying regional and rural-urban differences in prevalence and assessment of the contributions of different indicators is essential in determining the drivers of this condition. The 2015-16 National Family Health Survey data has been used for the study. Bivariate analysis, multinomial regression analysis, concentration indices and decomposition of concentration indices assessing contribution of factors has been undertaken in the present study. An overall concentration index of 0.003 has been found for hypertensive population, which shows its concentration among the richer wealth quintiles. The contribution of factors like age 45 to 49 years, years of schooling between 5 to 9 years are factors that are important contributors to inequality in hypertension occurrence. Studies should be conducted to find approaches to prevent or delay the onset of the condition.

Keywords: hypertension, decomposition, inequalities, India

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Authors: Dennis L. Owuor, Okuthe P. Kogeda, Johnson I. Agbinya

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Mobile localization has attracted a great deal of attention recently due to the introduction of wireless networks. Although several localization algorithms and systems have been implemented and discussed in the literature, very few researchers have exploited the gap that exists between indoor localization, tracking, external storage of location information and outdoor localization for the purpose of digital forensics during and after a disaster. The contribution of this paper lies in the implementation of a robust system that is capable of locating, tracking mobile device users and store location information for both indoor and partially outdoor the cloud. The system can be used during disaster to track and locate mobile phone users. The developed system is a mobile application built based on Android, Hypertext Preprocessor (PHP), Cascading Style Sheets (CSS), JavaScript and MATLAB for the Android mobile users. Using Waterfall model of software development, we have implemented a three level system that is able to track, locate and store mobile device information in secure database (cloud) on almost a real time basis. The outcome of the study showed that the developed system is efficient with regard to the tracking and locating mobile devices. The system is also flexible, i.e. can be used in any building with fewer adjustments. Finally, the system is accurate for both indoor and outdoor in terms of locating and tracking mobile devices.

Keywords: indoor localization, digital forensics, fingerprinting, tracking and cloud

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Authors: Harris Maduku, Irrshad Kaseeram

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The objective of this paper is to understand the factors behind the formalisation willingness of South African black owned SMMEs. Cross-sectional data were collected using a questionnaire from 390 informal businesses in Johannesburg and Pretoria using stratified random sampling and clustered sampling. This study employed a multinomial logistic regression to quantitatively understand what encourages informal SMMEs to be willing to mainstreaming their operations. We find government support, corruption, employment compensation, family labour, success perception, education status, age and financing as key drivers on willingness of SMMEs to formalize their operations. The findings of our study points to government departments to invest more on both financial and non-financial strategies like capacity building and business education on informal SMMEs to cultivate their willingness to mainstream.

Keywords: mainstreaming, transition, informal, willingness, multinomial logit

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Authors: Mabrouka Immhemd Al-Werfalli

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How are political alienation and corruption related? What is the nature of relationship linking corruption and political alienation? When citizens withdraw their loyalty from their political regime and leaders, they highlight their alienation from them. The link between corruption and political alienation is that the individual would intentionally involve in corruption particularly when a state of lawlessness prevails. This paper represents a challenge- how to gauge a link between political alienation culture of corruption and corruption. It aims to highlight the political alienation related factors that determine the levels of corruption in Libya. One of the most prominent reasons for the Libyan uprising in February 2011 was the pervasiveness of corruption. Corruption in Libya remained a significant problem despite a robust anti-corruption discourse and harsh legislation undertaken by the previous regime. The long-standing political corruption in Libya has offered ample opportunity for the evolution of a structure of negative values and morals. This has formed what is termed as a ‘culture of corruption’, which has induced people to accept and justify corrupt behavior. The paper is a part of a study concerns the phenomenon of political alienation in Libya which was based on a survey conducted in 2001 in the city of Benghazi. The finding shows that abuse of power, embezzlement and misuse of public funds for personal enrichment was thought to be rife within public bodies, institutions, companies, factories, banks and enterprises owned entirely or partially by the state.

Keywords: Libya, abuse of power, anti-corruption, corruption, culture of corruption, embezzlement, participation in corruption, political alienation

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Authors: Hyeondal Jeong, Yoonjung Baek

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This study examines the relationship between ethical leadership and individual creativity and focused on mediating effects of psychological safety. In order to clarify the mechanism of ethical leadership, psychological safety of the members was set as a mediator. Using data gathered from a sample of 150 employees. For data analysis, exploratory factor analysis, correlation analysis, hierarchical regression analysis and Sobel-Test were performed. The results showed that ethical leadership had a positive effect on psychological safety and individual creativity, and psychological safety had a positive mediating effect. Since the mediating effect of psychological safety has been confirmed, we need to find ways to improve the psychological safety of the members in terms of organizational management. Psychological safety has a positive effect on individual creativity, which can have a positive impact on innovation throughout the organization.

Keywords: ethical leadership, creativity, psychological safety, ethics management, innovative behaviors

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Authors: Mahmoud Timar, Javad Joukar Borazjani

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A dynamic organization helps the management to overcome both internal and external uncertainties and complexities of the organization with more confidence and efficiency. Regarding this issue, in this paper, the influence of organizational culture factors over organizational learning components, which both of them are considered as important characteristics of a dynamic organization, has been studied in three subsidiary companies (production, consultation and service) of National Iranian Oil Company, and moreover we also tried to identify the most dominant culture in these three subsidiaries. Analysis of 840 received questionnaires by SPSS shows that there is a significant relationship between the components of organizational culture and organizational learning; however the rate of relationship between these two factors was different among the examined companies. By the use of Regression, it has been clarified that in the servicing company the highest relationship is between mission and learning environment, while in production division, there is a significant relationship between adaptability and learning needs satisfaction and however in consulting company the highest relationship is between involvement and applying learning in workplace.

Keywords: denison model, culture, leaning, organizational culture, organizational learning

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Authors: S. Muogbo Uju, U. Akpunonu Evan

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The prevailing harsh environment factors coupled with high poverty rate and unemployment propels a high rate of entrepreneurial activities in developing economies. Women entrepreneurs operate with gender bias among other constraints that can constitute a threats or create opportunity for women entrepreneurs. This empirical paper investigates and critically examines women entrepreneurship as an inventive approach to ensure a sustainable development in Anambra state. The study used descriptive statistics (frequencies, mean, and percentages) to answer the three research questions posed. Hypotheses testing were done with Pearson product moment correlation and multiple regression were employed in data analysis. Consequently, the finding of this study portrayed a significant impact between women entrepreneurship activity, job creation and wealth creation.

Keywords: women entrepreneurs, skill acquisition, sustainability, wealth creation, job creation, economic development

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Authors: Emine Teke, Soner Kuşlu, Sabri Çolak, Turan Çalban

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The aim of the present study was to investigate the dissolution kinetics of ulexite in sodium dihydrogen phosphate in a mechanical agitation system and also to declare an alternative reactant to produce the boric acid. Reaction temperature, concentration of sodium dihydrogen phosphate, stirring speed, solid-liquid ratio, and ulexite particle size were selected as parameters. The experimental results were successfully correlated by using linear regression and a statistical program. Dissolution curves were evaluated in order to test the shrinking core models for solid-fluid systems. It was observed that increase in the reaction temperature and decrease in the solid/liquid ratio causes an increase in the dissolution rate of ulexite. The activation energy was found to be 36.4 kJ/mol. The leaching of ulexite was controlled by diffusion through the ash (or product) layer.

Keywords: ulexite, sodium dihydrogen phosphate, leaching kinetics, boron

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Authors: Ying Ying Liu, Austin Cooke, Parimala Thulasiraman

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Internet of Things (IoT) has attracted a recent spark in research on Internet of Vehicles (IoV). In this paper, we focus on one research area in IoV: preserving location privacy of vehicle data. We discuss existing location privacy preserving techniques and provide a scheme for evaluating these techniques under IoV traffic condition. We propose a different strategy in applying Differential Privacy using k-d tree data structure to preserve location privacy and experiment on real world Gowalla data set. We show that our strategy produces differentially private data, good preservation of utility by achieving similar regression accuracy to the original dataset on an LSTM (Long Term Short Term Memory) neural network traffic predictor.

Keywords: differential privacy, internet of things, internet of vehicles, location privacy, privacy preservation scheme

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Authors: Kyung-Ja Cho, Sun Jin Park

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This study examined what effective dimension affects facial attractiveness. Two orthogonal dimensions, sharp-soft and babyish-mature, were used to rate the levels of facial attractiveness in 20’s women. This research also investigated the sex difference on the effect of effective dimension of face on attractiveness. The test subjects composed of 15 males and 18 females. They looked 330 photos of women in 20s. Then they rated the levels of the effective dimensions of faces with sharp-soft and babyish-mature, and the attraction with charmless-charming. The respond forms were Likert scales, the answer was scored from 1 to 9. As a result of multiple regression analysis, the subject reported the milder and younger appearance as more attractive. Both male and female subjects showed the same evaluation. This result means that two effective dimensions have the effect on estimating attractiveness.

Keywords: affective dimension of faces, facial attractiveness, sharp-soft, babyish-mature

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Authors: Farzaneh Golshekoh

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The aim of this study was to examine the relationship between religious beliefs, family responsibility and emotional atmosphere with a tendency to addiction in high school female students in Ahwaz. The sample consisted of 250 students who were selected by cluster random sampling from among all high school female students in Ahvaz. Measuring tools were Iranian tendency towards addiction (IAPS), responsibility California Psychological Inventory (CPI), emotional family atmosphere (AFC) and religious beliefs. The simple correlation coefficient at α=0/05 showed that there is a significant negative relationship between religious beliefs, family responsibility and emotional atmosphere with a tendency to abuse female students. The regression analysis showed that the variables of the emotional atmosphere of the family and religious beliefs as predictors of female students have a tendency to addiction.

Keywords: emotional atmosphere, family responsibility, religious beliefs, tendency to addiction

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Authors: T. Garba, Y. Y. Babanyara, T. O. Quddus, A. K. Mukatari

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Human activities make environmental parameters in order to keep on changing globally. While some changes are necessary and beneficial to flora and fauna, others have serious consequences threatening the survival of their natural habitat if these changes are not properly monitored and mitigated. In-situ assessments are characterized by many challenges due to the absence of time series data and sometimes areas to be observed or monitored are inaccessible. Satellites Remote Sensing provide us with the digital images of same geographic areas within a pre-defined interval. This makes it possible to monitor and detect changes of environmental phenomena. This paper, therefore, reviewed the commonly use changes detection techniques globally such as image differencing, image rationing, image regression, vegetation index difference, change vector analysis, principal components analysis, multidate classification, post-classification comparison, and visual interpretation. The paper concludes by suggesting the use of more than one technique.

Keywords: environmental phenomena, change detection, monitor, techniques

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Authors: Won-Seok Kim, Hyung-Ik Shin

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Self-rated health (SRH) is a subjective assessment of individual health and has been identified as a strong predictor for mortality and morbidity. However few studies have been directed to the factors associated with SRH in persons with disabilities (PWD). We used data of 7th Korean national survey for 5307 PWD in 2008. Multiple logistic regression analysis was performed to find out independent risk factors for poor SRH in PWD. As a result, indicators of physical condition (poor instrumental ADL), socioeconomic disadvantages (poor education, economically inactive, low self-rated social class, medicaid in health insurance, presence of unmet need for hospital use) and social participation and networks (no use of internet service) were selected as independent risk factors for poor SRH in final model. Findings in the present study would be helpful in making a program to promote the health and narrow the gap of health status between the PWD.

Keywords: disabilities, risk factors, self-rated health, socioeconomic disadvantages, social networks

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Authors: Iqbal Abd. Muhbir Hadi Anam

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The purpose of the study is to discuss the relationship between organizational culture, teacher psychological empowerment, and organizational citizenship behavior at the University of Bangkalan District. The data was obtained using a survey of 100 respondents tested for validity and reliability. The analytical technique used is a hierarchical regression test. The results showed that the organizational culture of the university had a strong influence on the psychological empowerment of teachers and the psychological empowerment of teachers and that the organizational culture and psychological empowerment of teachers provided effective predictions of the psychological empowerment of the university. In addition, organizational culture directly or indirectly influences teachers' organizational citizenship behavior through psychological empowerment. Given these results, universities need to build an organizational culture that reflects the nature of the university.

Keywords: organizational behavior, teacher psychological empowerment, organizational citizenship behavior, universities

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Authors: Lidia Sanchis-Marco, Antonio Rubia

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In this paper we analyze the state-dependent risk-spillover in different economic areas. To this end, we apply the quantile regression-based methodology developed in Adams, Füss and Gropp approach to examine the spillover in conditional tails of daily returns of indices of the banking industry in the US, BRICs, Peripheral EMU, Core EMU, Scandinavia, the UK and Emerging Markets. This methodology allow us to characterize size, direction and strength of financial contagion in a network of bilateral exposures to address cross-border vulnerabilities under different states of the economy. The general evidence shows as the spillover effects are higher and more significant in volatile periods than in tranquil ones. There is evidence of tail spillovers of which much is attributable to a spillover from the US on the rest of the analyzed regions, specially on European countries. In sharp contrast, the US banking system show more financial resilience against foreign shocks.

Keywords: spillover effects, Bank Contagion, SDSVaR, expected shortfall, VaR, expectiles

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Authors: Karwan Khudhir

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A cross-sectional study was carried out to determine the prevalence of musculoskeletal disorders (MSDs) and psychosocial factors associated with it, among Kurdistan nursing professionals. Simple random sampling was used to select 220 nurses and data were collected by self-administrative questionnaire. Results of the study showed that the overall prevalence of MSDs among Kurdistan nurses was 74% in different body regions and, by body regions, neck pain was reported to be the highest complaint of twelve-month MSDs (48.4%) compared to other body parts. Logistic regression analysis indicated 6 variables that are significantly associated with musculoskeletal disorders: smoking (OR=19.472, 95% CI: 5.396, 70.273), BMI (OR= 5.106, 95% CI: 1.735, 15.025), physical activity (OR=8.639, 95% CI: 3.075, 24.271), psychological demand (OR=6.685, 95% CI: 3.318, 13.468), social support (OR=3.143, 95% CI: 1.202, 4.814) and job satisfaction (OR=2.44, 95% CI: 1.04, 5.63). Prevention strategies and health education which emphasizes on psychosocial risk factors and how to improve working conditions should be introduced.

Keywords: Kurdistan Region, Iraq, musculoskeletal disorders, nurses, psycho-social factors

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Authors: Silvia Grassi, Stefano Schiavon, Ernestina Casiraghi, Cristina Alamprese

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Dry-cured ham is an uncooked meat product particularly appreciated for its peculiar sensory traits among which lipid component plays a key role in defining quality and, consequently, consumers’ acceptability. Usually, fat content and distribution are chemically determined by expensive, time-consuming, and destructive analyses. Moreover, different sensory techniques are applied to assess product conformity to desired standards. In this context, visual systems are getting a foothold in the meat market envisioning more reliable and time-saving assessment of food quality traits. The present work aims at developing a simple but systematic and objective visual methodology to assess the fat amount of dry-cured ham slices, in terms of total, intermuscular and intramuscular fractions. To the aim, 160 slices from 80 PDO dry-cured hams were evaluated by digital image analysis and Soxhlet extraction. RGB images were captured by a flatbed scanner, converted in grey-scale images, and segmented based on intensity histograms as well as on a multi-stage algorithm aimed at edge enhancement. The latter was performed applying the Canny algorithm, which consists of image noise reduction, calculation of the intensity gradient for each image, spurious response removal, actual thresholding on corrected images, and confirmation of strong edge boundaries. The approach allowed for the automatic calculation of total, intermuscular and intramuscular fat fractions as percentages of the total slice area. Linear regression models were run to estimate the relationships between the image analysis results and the chemical data, thus allowing for the prediction of the total, intermuscular and intramuscular fat content by the dry-cured ham images. The goodness of fit of the obtained models was confirmed in terms of coefficient of determination (R²), hypothesis testing and pattern of residuals. Good regression models have been found being 0.73, 0.82, and 0.73 the R2 values for the total fat, the sum of intermuscular and intramuscular fat and the intermuscular fraction, respectively. In conclusion, the edge enhancement visual procedure brought to a good fat segmentation making the simple visual approach for the quantification of the different fat fractions in dry-cured ham slices sufficiently simple, accurate and precise. The presented image analysis approach steers towards the development of instruments that can overcome destructive, tedious and time-consuming chemical determinations. As future perspectives, the results of the proposed image analysis methodology will be compared with those of sensory tests in order to develop a fast grading method of dry-cured hams based on fat distribution. Therefore, the system will be able not only to predict the actual fat content but it will also reflect the visual appearance of samples as perceived by consumers.

Keywords: dry-cured ham, edge detection algorithm, fat content, image analysis

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Authors: Gaurav Kumar Sinha

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The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

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Authors: Naoya Ozaki, Takuya Watanabe, Ryosuke Matsumoto, Noriko Fukasawa

Abstract:

In the metropolitan areas in Japan, in many stations, shopping areas are set up, and escalators and elevators are installed to make the stations be barrier-free. Further, many areas around the stations are being redeveloped. Railway business operators want to know how much effect these circumstances have on attractiveness of the station or number of passengers using the station. So, we performed a questionnaire survey of the station users in the metropolitan areas for finding factors to affect the attractiveness of stations. Then, based on the analysis of the survey, we developed a method to quantitatively evaluate attractiveness of the stations. We also developed an estimation method for number of passengers based on combination of attractiveness of the station quantitatively evaluated and the residential and labor population around the station. Then, we derived precise linear regression models estimating the attractiveness of the station and number of passengers of the station.

Keywords: attractiveness of the station, estimation method, number of passengers of the station, redevelopment around the station, renovation of the station

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