Search results for: health data

Authors: Emine Öğüt, Mehtap Öztürk, Adem Öğüt

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Affective commitment is defined as a strong belief in and acceptance of the organization’s goals and values. Organizational justice is an antecedent of the organizational commitment and it has the potential to create powerful benefits for organizations and employees alike. When perceived unfairness among employees increases, affective commitment decreases and absenteeism increases accordingly. In this research, relationships between organizational justice perception, affective commitment and absenteeism is analysed. In this regard, a field study has been conducted over the physicians working in the hospitals of the Health Ministry and University Hospitals in the province of Konya. The partial least squares (PLS) method is used to analyse the survey data. The findings of the research shows that there is a positive statistically significant relationship between organizational justice perception and affective commitment while there is a negative statistically significant relationship between organizational justice and absenteeism.

Keywords: organizational justice, affective commitment, absenteeism, healthcare management

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Authors: Ritu Vashistha, Jitender Kumar

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Clustering using the K-means algorithm is a very common way to understand and analyze the obtained output data. When a similar object is grouped, this is called the basis of Clustering. There is K number of objects and C number of cluster in to single cluster in which k is always supposed to be less than C having each cluster to be its own centroid but the major problem is how is identify the cluster is correct based on the data. Formulation of the cluster is not a regular task for every tuple of row record or entity but it is done by an iterative process. Each and every record, tuple, entity is checked and examined and similarity dissimilarity is examined. So this iterative process seems to be very lengthy and unable to give optimal output for the cluster and time taken to find the cluster. To overcome the drawback challenge, we are proposing a formula to find the clusters at the run time, so this approach can give us optimal results. The proposed approach uses the Euclidian distance formula as well melanosis to find the minimum distance between slots as technically we called clusters and the same approach we have also applied to Ant Colony Optimization(ACO) algorithm, which results in the production of two and multi-dimensional matrix.

Keywords: ant colony optimization, data clustering, centroids, data mining, k-means

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Authors: Frederico Fialho Teixeira, Islam Mashaly, Maryam Shafiei, Jurij Karlovsek

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The ubiquity of data gathering and smart technologies, advancements in virtual technologies, and the development of the internet of things (IoT) have created urgent demands for the development of frameworks and efficient workflows for data collection, visualisation, and analysis. Digital twin, in different scales of the city into the building, allows for bringing together data from different sources to generate fundamental and illuminating insights for the management of current facilities and the lifecycle of amenities as well as improvement of the performance of current and future designs. Over the past two decades, there has been growing interest in the topic of digital twin and their applications in city and building scales. Most such studies look at the urban environment through a homogeneous or generalist lens and lack specificity in particular characteristics or identities, which define an urban university campus. Bridging this knowledge gap, this paper offers a framework for developing a digital twin for a university campus that, with some modifications, could provide insights for any large-scale digital twin settings like towns and cities. It showcases how currently unused data could be purposefully combined, interpolated and visualised for producing analysis-ready data (such as flood or energy simulations or functional and occupancy maps), highlighting the potential applications of such a framework for campus planning and policymaking. The research integrates campus-level data layers into one spatial information repository and casts light on critical data clusters for the digital twin at the campus level. The paper also seeks to raise insightful and directive questions on how digital twin for campus can be extrapolated to city-scale digital twin. The outcomes of the paper, thus, inform future projects for the development of large-scale digital twin as well as urban and architectural researchers on potential applications of digital twin in future design, management, and sustainable planning, to predict problems, calculate risks, decrease management costs, and improve performance.

Keywords: digital twin, smart campus, framework, data collection, point cloud

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Authors: Huma Khan, Faiza Akhtar

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The present study investigates the effects of burnout toward job performance and job satisfaction with the moderating role of hope and self-efficacy. Findings from 310 frontline employees of Pakistani commercial banks (Lahore, Karachi & Islamabad) disclosed burnout has negative significant effects on job performance and job satisfaction. Simple random sampling technique was used to collect data and inferential statistics were applied to analyzed the data. However, results disclosed no moderation effect of hope on burnout, job performance or with job satisfaction. Moreover, Data significantly supported the moderation effect of self-efficacy. Study further shed light on the development of psychological capital. Importance of the implication of the current finding is discussed.

Keywords: burnout, hope, job performance, job satisfaction, psychological capital, self-efficacy

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Authors: Daniel D'Souza, Ping Zou

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The period before, during, and after menopause is a sensitive time for women as they experience intense physical and psychological health changes and symptoms. These changes accompany the hormonal changes that mark the end of a woman’s reproductive age. To help mitigate and cope with these changes, prompt and correct treatment is needed. eHealth has emerged as a branch of telemedicine in the past few decades as an alternate avenue for patients to receive care quickly and conveniently, as it relies on the Internet and computers. Within the past few years, eHealth has also given rise to mHealth, which is the use of personal mobile devices to receive treatment and care. However, there is a lack of study on their use for menopause. This review aimed to review and summarize the literature for eHealth or mHealth and menopause. Several databases related to women’s health and digital health were searched for original studies about eHealth or mHealth and menopause. The search yielded 25 results. The results were generally positive, with these interventions being feasible and having positive effects on physical and psychosocial outcomes. However, several issues were raised regarding their design process that may inadvertently prevent these interventions from addressing the needs of all potential users. Therefore, while eHealth and mHealth certainly represent a future model of healthcare delivery for menopausal women, further research and design modifications are needed before this can happen.

Keywords: eHealth, menopause, mHealth, midlife women

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Authors: Moohyun Lee, Soojung Hur, Yongwan Park

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In this paper is proposed a method uses only LIDAR system to classification an obstacle and determine its type by establishing database for classifying obstacles based on LIDAR. The existing LIDAR system, in determining the recognition of obstruction in an autonomous vehicle, has an advantage in terms of accuracy and shorter recognition time. However, it was difficult to determine the type of obstacle and therefore accurate path planning based on the type of obstacle was not possible. In order to overcome this problem, a method of classifying obstacle type based on existing LIDAR and using the width of obstacle materials was proposed. However, width measurement was not sufficient to improve accuracy. In this research, the width data was used to do the first classification; database for LIDAR intensity data by four major obstacle materials on the road were created; comparison is made to the LIDAR intensity data of actual obstacle materials; and determine the obstacle type by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that data declined in quality in comparison to 3D LIDAR and it was possible to classify obstacle materials using 2D LIDAR.

Keywords: obstacle, classification, database, LIDAR, segmentation, intensity

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Authors: Yogesh Kumar, Adarsh Kumar

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A body farm is a research facility where research is done on forensic investigation and medico-legal disciplines like forensic entomology, forensic pathology, forensic anthropology, forensic archaeology, and related areas of forensic veterinary. All the research is done to collect data on the rate of decomposition (animal and human) and forensically important insects to assist in crime detection. The data collected is used by forensic pathologists, forensic experts, and other experts for the investigation of crime cases and further research. The research work includes different conditions of a dead body like fresh, bloating, decay, dry, and skeleton, and data on local insects which depends on the climatic conditions of the local areas of that country. Therefore, it is the need of time to collect appropriate data in managed conditions with a proper set-up in every country. Hence, it is the duty of the scientific community of every country to establish/propose such facilities for justice and social management. The body farms are also used for training of police, military, investigative dogs, and other agencies. At present, only four countries viz. U.S., Australia, Canada, and Netherlands have body farms and related facilities in organised manner. There is no body farm in Asia also. In India, we have been trying to establish a body farm in A&N Islands that is near Singapore, Malaysia, and some other Asian countries. In view of the above, it becomes imperative to discuss the matter with Asian countries to collect the data on decomposition in a proper manner by establishing a body farm. We can also share the data, knowledge, and expertise to collaborate with one another to make such facilities better and have good scientific relations to promote science and explore ways of investigation at the world level.

Keywords: body farm, rate of decomposition, forensically important flies, time since death

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Authors: Tareq Nikzad

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Since the first bank was established in 1933, Afghanistan's banking sector has seen a number of variations but hasn't been able to grow to its full potential because of the civil war. The implementation of dual banks in Afghanistan is investigated in this study in relation to the effects of inflation and interest rates. This research took data from World Bank Data (WBD) over a period of nineteen years. For the banking sector, inflation, which is the general rise in prices of goods and services over time, presents considerable difficulties. The objectives of this research are to analyze the effect of inflation and interest rates on conventional and Islamic banks in Afghanistan, identify potential differences between these two banking models, and provide insights for policymakers and practitioners. A mixed-methods approach is used in the research to analyze quantitative data and qualitatively examine the unique difficulties that banks in Afghanistan's economic atmosphere encounter. The findings contribute to the understanding of the relationship between interest rate, inflation rate, and the performance of both banking systems in Afghanistan. The paper concludes with recommendations for policymakers and banking institutions to enhance the stability and growth of the banking sector in Afghanistan. Interest is described as "a prefixed rate for use or borrowing of money" from an Islamic perspective. This "prefixed rate," known in Islamic economics as "riba," has been described as "something undesirable." Furthermore, by using the time series regression data technique on the annual data from 2003 to 2021, this research examines the effect of CPI inflation rate and interest rate of Banking in Afghanistan.

Keywords: inflation, Islamic banking, conventional banking, interest, Afghanistan, impact

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Authors: Diep The Tai, Huynh Phuong Thao, Tran Cong Luan, Nguyen Thi Hong Huong, Truong Thi Xuan Lien

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Backgrounds: Depression is a prevalent mental health concern among university students. This cross-sectional study explores the factors associated with depression among university students in Vietnam. Methods: In 2022, a web-based survey was conducted among 2,304 students from different universities across North, Central, and South Vietnam. The Pearson chi-squared test was used to analyze the statistical associations between socio-demographic factors, depression levels, and social media addiction. Results: The results showed that 33,9% of freshmen experienced severe depression, with higher rates among females (69,8%) than males (30,2%). Health field students had the highest proportion of severe depression (52%). Social media addiction was prevalent among freshmen (29%) and health students (54,4%). Factors such as family infections, study pressure, hometown, studying in public places, and social media addiction were strongly linked to higher depression levels. However, spending more time communicating with friends and studying at home had a protective effect against depression. Notably, social media addiction was significantly associated with increased depression levels. Conclusion: The study highlights the influence of family COVID-19 infections, academic pressures, studying in public places, hometown, social media addiction, and lack of social interactions on depression levels. It underscores the importance of comprehensive approaches to address depression, promote resilience, and provide support to students during future outbreaks.

Keywords: Depression, social media addiction, mental health, university students, Vietnam

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Authors: Pranab Kumar Goswami, Elena Gurung

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Small and medium enterprises (SME) are considered as the driving force for the economic growth of a developing country like India. Most of the SMEs are located in residential/non-industrial areas to avoid legal obligations of occupational safety and health (OSH) provisions. This study was conducted in Delhiwith a view to analyze the accidents that occurredduringthe year 2019 & 2020. The objective of the study was to find out the accident prone SMEs in Delhi and major causes of such accidents. Methods: Survey and comprehensive data analysis methods, followed by applying simple statistical techniques, were used for this study. The accident reports for the study period collected from the labour department and police stations were analyzed for the study. The injured workers were interviewed to ascertain safety compliances, training and awareness programs, etc. The study was completed in March2021. Results: It was found that most of the accidents took place in SMEs located in residential/non- industrial areas in Delhi. The accident-prone machines were found to be power presses (42%) and injection moulding machines (37%). Predominantly unsafe machinery or unsafe working conditions and lack of training of worker were observed to be the major causes of accidents in such industries. Conclusions: It was concluded from the study that unsafe machinery/equipment and lack of proper training to the workers were two main reasons for increase in accidents.It was also concluded that the industries located in industrial areas were better placed in terms of workplace compliances. The managements who were running their operations from residential/non-industrial areaswere found to be less aware on health and safety issues. Lack of enforcement by government agencies in such areas has escalated this problem. Adequate training to workers, managing safe & healthy workplace, and sustained enforcement can reduce accidents in such industries.

Keywords: SME, accident prevention, cause of accident, unorganised

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Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

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The cultural park of the Ahaggar, occupying a large area of Algeria, is characterized by a rich wetlands area to be preserved and managed both in time and space. The management of a large area, by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information...), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Remote sensing imaging data have been very useful in the last decade in very interesting applications. They can aid in several domains such as the detection and identification of diverse wetland surface targets, topographical details, and geological features... In this work, we try to extract automatically wetlands area using multispectral remotely sensed data on-board the Earth Observing 1 (EO-1) and Landsat satellite. Both are high-resolution multispectral imager with a 30 m resolution. The instrument images an interesting surface area. We have used images acquired over the several area of interesting in the National Park of Ahaggar in the south of Algeria. An Extraction Algorithm is applied on the several spectral index obtained from combination of different spectral bands to extract wetlands fraction occupation of land use. The obtained results show an accuracy to distinguish wetlands area from the other lad use themes using a fine exploitation on spectral index.

Keywords: multispectral data, EO1, landsat, wetlands, Ahaggar, Algeria

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Authors: Janne Engblom, Elias Oikarinen

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A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models are dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Arellano-Bover/Blundell-Bond Generalized method of moments (GMM) estimator which is an extension of the Arellano-Bond model where past values and different transformations of past values of the potentially problematic independent variable are used as instruments together with other instrumental variables. The Arellano–Bover/Blundell–Bond estimator augments Arellano–Bond by making an additional assumption that first differences of instrument variables are uncorrelated with the fixed effects. This allows the introduction of more instruments and can dramatically improve efficiency. It builds a system of two equations—the original equation and the transformed one—and is also known as system GMM. In this study, Finnish housing price dynamics were examined empirically by using the Arellano–Bover/Blundell–Bond estimation technique together with ordinary OLS. The aim of the analysis was to provide a comparison between conventional fixed-effects panel data models and dynamic panel data models. The Arellano–Bover/Blundell–Bond estimator is suitable for this analysis for a number of reasons: It is a general estimator designed for situations with 1) a linear functional relationship; 2) one left-hand-side variable that is dynamic, depending on its own past realizations; 3) independent variables that are not strictly exogenous, meaning they are correlated with past and possibly current realizations of the error; 4) fixed individual effects; and 5) heteroskedasticity and autocorrelation within individuals but not across them. Based on data of 14 Finnish cities over 1988-2012 differences of short-run housing price dynamics estimates were considerable when different models and instrumenting were used. Especially, the use of different instrumental variables caused variation of model estimates together with their statistical significance. This was particularly clear when comparing estimates of OLS with different dynamic panel data models. Estimates provided by dynamic panel data models were more in line with theory of housing price dynamics.

Keywords: dynamic model, fixed effects, panel data, price dynamics

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Authors: Okorowo Cyril Agochi

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The Niger Delta Region of Nigeria is home to about 20 million people and 40 different ethnic groups. The region has an area of seventy thousand square kilometers (70,000 KM2) of wetlands, formed primarily by sediments deposition and makes up 7.5 percent of Nigeria's total landmass. The notable ecological zones in this region includes: coastal barrier islands; mangrove swamp forests; fresh water swamps; and lowland rainforests. This incredibly naturally-endowed ecosystem region, which contains one of the highest concentrations of biodiversity on the planet, in addition to supporting abundant flora and fauna, is threatened by the inhuman act known as gas flaring. Gas flaring is the combustion of natural gas that is associated with crude oil when it is pumped up from the ground. In petroleum-producing areas such as the Niger Delta region of Nigeria where insufficient investment was made in infrastructure to utilize natural gas, flaring is employed to dispose of this associated gas. This practice has impoverished the communities where it is practiced, with attendant environmental, economic and health challenges. This paper discusses the adverse environmental and health implication associated with the practice, the role of Government, Policy makers, Oil companies and the Local communities aimed at bring this inhuman practice to a prompt end.

Keywords: natural combustion, emission, environment, flaring, gas, health, Niger Delta

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Authors: Haripriya Chakraborty

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The healthcare system in the United States is considered to be one of the most inefficient and expensive systems when compared to other developed countries. Consequently, there are persistent concerns regarding the overall functioning of this system. For instance, the large number of uninsured individuals and high premiums are pressing issues that are shown to have a negative effect on health outcomes with possible life-threatening consequences. The Affordable Care Act (ACA), which was signed into law in 2010, was aimed at improving some of these inefficiencies. This paper aims at providing a computational mechanism to examine some of these inefficiencies and the effects that policy proposals may have on reducing these inefficiencies. Agent-based modeling is an invaluable tool that provides a flexible framework to model complex systems. It can provide an important perspective into the nature of some interactions that occur and how the benefits of these interactions are allocated. In this paper, we propose a novel and versatile agent-based model with realistic assumptions to simulate the dynamics of a health insurance marketplace that contains a mixture of private and public insurers and individuals. We use this model to analyze the characteristics, motivations, payoffs, and strategies of these agents. In addition, we examine the effects of certain policies, including some of the provisions of the ACA, aimed at reducing the uninsured rate and the cost of premiums to move closer to a system that is more equitable and improves health outcomes for the general population. Our test results confirm the usefulness of our agent-based model in studying this complicated issue and suggest some implications for public policies aimed at healthcare reform.

Keywords: agent-based modeling, healthcare reform, insurance markets, public policy

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Authors: Amogh Katti, J. Sai Asritha, D. Nivedh, M. Kalyan Srinivas, B. Somnath Chakravarthi

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Today's modern education system uses Learning Management System (LMS) portals for the scoring and grading of student performances, to maintain student records, and teachers are instructed to accept assignments through online submissions of .pdf,.doc,.ppt, etc. There is a risk of data tampering in the traditional portals; we will apply the Blockchain model instead of this traditional model to avoid data tampering and also provide a decentralized mechanism for overall fairness. Blockchain technology is a better and also recommended model because of the following features: consensus mechanism, decentralized system, cryptographic encryption, smart contracts, Ethereum blockchain. The proposed system ensures data integrity and tamper-proof assignment submission and grading, which will be helpful for both students and also educators.

Keywords: education technology, learning management system, decentralized applications, blockchain

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Authors: Lito M. Amit, Venecio U. Ultra, Young-Woong Song

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The business process outsourcing (BPO) in the Philippines is expanding rapidly attracting more than 2% of total employment. Currently, the BPO industry is confronted with several issues pertaining to sustainable productivity such as meeting the staffing gap, high rate of employees’ turnover and workforce retention, and the occupational health and safety (OHS) of call center agents. We conducted a survey of OHS programs and health concerns among call center agents in the Philippines and determined the sociocultural factors that affect the vulnerability of call center agents to occupational health risks and hazards. The majority of the agents affirmed that OHS are implemented and OHS orientation and emergency procedures were conducted at employment initiations, perceived favorable and convenient working environment except for occasional noise disturbances and acoustic shock, visual, and voice fatigues. Male agents can easily adjust to the demands and changes in their work environment and flexible work schedules than female agents. Female agents have a higher tendency to be pressured and humiliated by low work performance, experience a higher incidence of emotional abuse, psychological abuse, and experience more physical stress than male agents. The majority of the call center agents had a night-shift schedule and regardless of other factors, night shift work brings higher stress to agents. While working in a call center, higher incidence of headaches and insomnia, burnout, suppressed anger, anxiety, and depressions were experienced by female, younger (21-25 years old) and those at night shift than their counterpart. Most common musculoskeletal disorders include body pain in the neck, shoulders and back; and hand and wrist disorders and these are commonly experienced by female and younger workers. About 30% experienced symptoms of cardiovascular and gastrointestinal disorders and weakened immune systems. Overall, these findings have shown the variable vulnerability by a different subpopulation of call center agents and are important in the occupational health risk prevention and management towards a sustainable human resource for BPO industry in the Philippines.

Keywords: business process outsourcing industry, health risk of call center agents, socio-cultural determinants, Philippines

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Authors: A. Yousuf, M. Iqbal, A. Mir, S. Aziz

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This study deals with the women’s right to land for gender equality. Economic Transformation Initiative, Gilgit-Baltistan (ETI-GB), an ambitious program supported by International Fund for Agricultural Development United Nation (IFAD, UN), aims to strengthen land reforms process in disputed area of Gilgit-Baltistan (GB) Pakistan, that is taking place first time in the history. This project is a brick to build the foundation of land reforms and land policies in GB. The ETI-GB provides substantive support to government of GB in developing policy measures and initiatives to promote women’s right to have and to own land is kind of unconventional step in a very traditional society. It would be interesting to have discussion and document the people’s response regarding this project. The study has used mixed method for data collection. For qualitative data, content analysis is used to have a thorough understanding of different types of land reforms across the globe particularly in South Asia. Theoretical understanding of the literature is essential which provides the basis why land reforms are important and how far it plays an important role when it comes to eliminating inequality. Focused group discussion was carried out for verification and triangulation of data. For quantitative, survey was conducted to take responses from the people of the region and analyzed. The program is implemented in Ghizer district of GB. 2340 households were identified as beneficiaries of newly developed land. Among them, 2285 were men households, and 55 were women households. There is a significant difference between men and women households. In spite of great difference, it is a great achievement of the donor that in history of GB, first time women are going to be entitled to land ownership. GB is a patriarchal society, many social factors like cultural, religious play role for gender inequality. In developing countries, such as Pakistan, the awareness of land property rights has not been given proper attention to gender equality development frameworks. It is argued that land property rights of women have not been taken into mainstream policymaking in the development of nation building process. Consequently, this has generated deprivation of women’s property rights, low income level, lack of education and poor health. This paper emphasises that there should have proper land property right of women in Gilgit-Baltistan Pakistan, provided that the gender empowerment could be increased in terms of women’s property rights.

Keywords: gender equality, women right to land ownership, property rights, women empowerment

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Authors: Sheng-Hung Chen, Grace Mmametena Mahlangu, Hui-Cheng Wang

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This study aims to explore the trends of the Entrepreneurial Framework Conditions (EFCs) in the five African regions. The Global Entrepreneur Monitor (GEM) is the primary source of data. The data drawn were organized into a panel (2000-2021) and obtained from the National Expert Survey (NES) databases as harmonized by the (GEM). The Methodology used is descriptive and uses mainly charts and tables; this is in line with the approach used by the GEM. The GEM draws its data from the National Expert Survey (NES). The survey by the NES is administered to experts in each country. The GEM collects entrepreneurship data specific to each country. It provides information about entrepreneurial ecosystems and their impact on entrepreneurship. The secondary source is from the literature review. This study focuses on the following GEM indicators: Financing for Entrepreneurs, Government support and Policies, Taxes and Bureaucracy, Government programs, Basic School Entrepreneurial Education and Training, Post school Entrepreneurial Education and Training, R&D Transfer, Commercial And Professional Infrastructure, Internal Market Dynamics, Internal Market Openness, Physical and Service Infrastructure, and Cultural And Social Norms, based on GEM Report 2020/21. The limitation of the study is the lack of updated data from some countries. Countries have to fund their own regional studies; African countries do not regularly participate due to a lack of resources.

Keywords: trend analysis, entrepreneurial framework conditions (EFCs), African region, government programs

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Authors: Marianne Dæhlen

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Periods of apprenticeships are characteristic of many vocational educational training (VET) systems. In many countries, becoming a skilled worker implies that the journey starts with an application for apprenticeships at a company or another relevant training establishment. In Norway, where this study is conducted, VET students start their journey with two years of school-based training before applying for two years of apprenticeship. Previous research has shown that access to apprenticeships differs by family background (socio-economic, immigrant, etc.), gender, school grades, and region. The question we raise in this study is whether the status, reputation, or position of the vocational school contributes to VET students’ access to apprenticeships. Data and methods: Register data containing information about schools’ and VET students’ characteristics will be analyzed in multilevel regression analyses. At the school level, the data will contain information on school size, shares of immigrants and/or share of male/female students, and grade requirements for admission. At the VET-student level, the register contains information on e.g., gender, school grades, educational program/trade, obtaining apprenticeship or not. The data set comprises about 3,000 students. Results: The register data is expected to be received in November 2024 and consequently, any results are not present at the point of this call. The planned article is part of a larger research project granted from the Norwegian Research Council and will, accordingly to the plan, start up in December 2024.

Keywords: apprenticeships, VET-students’ characteristics, vocational schools, quantitative methods

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Authors: Herminio Martínez-García, Juan Gámiz, Yolanda Bolea, Antoni Grau

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This article presents an interactive system for data acquisition in vehicle testing according to the test process defined in automotive directive 2004/104/EC. The project has been designed and developed by authors for the Spanish company Applus-LGAI. The developed project will result in a new process, which will involve the creation of braking cycle test defined in the aforementioned automotive directive. It will also allow the analysis of new vehicle features that was not feasible, allowing an increasing interaction with the vehicle. Potential users of this system in the short term will be vehicle manufacturers and in a medium term the system can be extended to testing other automotive components and EMC tests.

Keywords: automotive process, data acquisition system, electromagnetic compatibility (EMC) testing, European Directive 2004/104/EC

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Authors: Jaqueline Maria Ribeiro Vieira

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Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). Previously we developed and proposed a novel strategy capable of detecting patterns at borehole images that may point to regions that have tension and breakout characteristics, based on segmented images. In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge data set configurations.

Keywords: image segmentation, oil well visualization, classifiers, data-mining, visual computer

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Authors: Chidiebere C. Agoha, Armstong C. Awuzie, Chukwuebuka N. Onwubuariri, Joy O. Njoku

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Spatial analysis is a field of study that utilizes geographic or spatial information to understand and analyze patterns, relationships, and trends in data. It is characterized by the use of geographic or spatial information, which allows for the analysis of data in the context of its location and surroundings. It is different from non-spatial or aspatial techniques, which do not consider the geographic context and may not provide as complete of an understanding of the data. Spatial analysis is applied in a variety of fields, which includes urban planning, environmental science, geosciences, epidemiology, marketing, to gain insights and make decisions about complex spatial problems. This review paper explores definitions of spatial analysis from various sources, including examples of its application and different analysis techniques such as Buffer analysis, interpolation, and Kernel density analysis (multi-distance spatial cluster analysis). It also contrasts spatial analysis with non-spatial analysis.

Keywords: aspatial technique, buffer analysis, epidemiology, interpolation

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Authors: Armanul Hoque Shaon, Md Baizid Mahmud, Askander Nobi, Md. Raju Ahmed, Md. Jiabul Hoque

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In the Internet of Things (IoT), devices are linked to the internet through a wireless network, allowing them to collect and transmit data without the need for a human operator. Agriculture relies heavily on wireless sensors, which are a vital component of the Internet of Things (IoT). This kind of wireless sensor network monitors physical or environmental variables like temperatures, sound, vibration, pressure, or motion without relying on a central location or sink and collaboratively passes its data across the network to be analyzed. As the primary source of plant nutrients, the soil is critical to the agricultural industry's continued growth. We're excited about the prospect of developing an Internet of Things (IoT) solution. To arrange the network, the sink node collects groundwater levels and sends them to the Gateway, which centralizes the data and forwards it to the sensor nodes. The sink node gathers soil moisture data, transmits the mean to the Gateways, and then forwards it to the website for dissemination. The web server is in charge of storing and presenting the moisture in the soil data to the web application's users. Soil characteristics may be collected using a networked method that we developed to improve rice production. Paddy land is running out as the population of our nation grows. The success of this project will be dependent on the appropriate use of the existing land base.

Keywords: IoT based agriculture monitoring, intelligent irrigation, communicating network, rice production

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Authors: Thanh Noi Phan, Martin Kappas, Jan Degener

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The currently launched Sentinel 2 (S2) satellite (June, 2015) bring a great potential and opportunities for land use/cover map applications, due to its fine spatial resolution multispectral as well as high temporal resolutions. So far, there are handful studies using S2 real data for land cover classification. Especially in northern Vietnam, to our best knowledge, there exist no studies using S2 data for land cover map application. The aim of this study is to provide the preliminary result of land cover classification using Sentinel -2 data with a rising state – of – art classifier, Random Forest. A case study with heterogeneous land use/cover in the eastern of Hanoi Capital – Vietnam was chosen for this study. All 10 spectral bands of 10 and 20 m pixel size of S2 images were used, the 10 m bands were resampled to 20 m. Among several classified algorithms, supervised Random Forest classifier (RF) was applied because it was reported as one of the most accuracy methods of satellite image classification. The results showed that the red-edge and shortwave infrared (SWIR) bands play an important role in land cover classified results. A very high overall accuracy above 90% of classification results was achieved.

Keywords: classify algorithm, classification, land cover, random forest, sentinel 2, Vietnam

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Authors: Jeni Stolow, Lina Moses, Carl Kendall

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Zika virus (ZIKV) reemerged as a global threat in 2015 with Brazil at its epicenter. Brazilians have a long history of combatting Aedes aegypti mosquitos as it is a common vector for dengue, chikungunya, and yellow fever. As a response to the epidemic, public health authorities promoted ZIKV prevention behaviors such as mosquito bite prevention, reproductive counseling for women who are pregnant or contemplating pregnancy, pregnancy avoidance, and condom use. Most prevention efforts from Brazil focused on the mosquito vector- utilizing recycled dengue approaches without acknowledging the context in which women were able to adhere to these prevention messages. This study used qualitative methods to explore how women in Fortaleza, Brazil perceive ZIKV, the Brazilian authorities’ ZIKV prevention recommendations, and the feasibility of adhering to these recommendations. A core study aim was to look at how women perceive their physical, social, and natural environment as it impacts women’s ability to adhere to ZIKV prevention behaviors. A Rapid Anthropological Assessment (RAA) containing observations, informational interviews, and semi-structured in-depth interviews were utilized for data collection. The study utilized Grounded Theory as the systematic inductive method of analyzing the data collected. Interviews were conducted with 35 women of reproductive age (15-39 years old), who primarily utilize the public health system. It was found that women’s self-identified economic class was associated with how strongly women felt they could prevent ZIKV. All women interviewed technically belong to the C-class, the middle economic class. Although all members of the same economic class, there was a divide amongst participants as to who perceived themselves as higher C-class versus lower C-class. How women saw their economic status was dictated by how they perceived their physical, social, and natural environment. Women further associated their environment and their economic class to their likelihood of contracting ZIKV, their options for preventing ZIKV, their ability to prevent ZIKV, and their willingness to attempt to prevent ZIKV. Women’s perceived economic status was found to relate to their structural environment (housing quality, sewage, and locations to supplies), social environment (family and peer norms), and natural environment (wetland areas, natural mosquito breeding sites, and cyclical nature of vectors). Findings from this study suggest that women’s perceived environment and economic status impact their perceived feasibility and desire to attempt behaviors to prevent ZIKV. Although ZIKV has depleted from epidemic to endemic status, it is suggested that the virus will return as cyclical outbreaks like that seen with similar arboviruses such as dengue and chikungunya. As the next ZIKV epidemic approaches it is essential to understand how women perceive themselves, their abilities, and their environments to best aid the prevention of ZIKV.

Keywords: Aedes aegypti, environment, prevention, qualitative, zika

Procedia PDF Downloads 138

Authors: Arman S. Kussainov, Altynbek K. Beisekov

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This work focuses on building an efficient universal procedure to construct a single density of states from the multiple pieces of data provided by the parallel implementation of the Wang Landau Monte Carlo based algorithm. The Ising and Pott models were used as the examples of the two-dimensional spin lattices to construct their densities of states. Sampled energy space was distributed between the individual walkers with certain overlaps. This was made to include the latest development of the algorithm as the density of states replica exchange technique. Several factors of immediate importance for the seamless stitching process have being considered. These include but not limited to the speed and universality of the initial parallel algorithm implementation as well as the data post-processing to produce the expected smooth density of states.

Keywords: density of states, Monte Carlo, parallel algorithm, Wang Landau algorithm

Procedia PDF Downloads 417

Authors: Ruchi Sharma, Rajasekhar Balasubramanian

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Motor vehicles emit a number of air pollutants, among which fine particulate matter (PM₂.₅) is of major concern in cities with high population density due to its negative impacts on air quality and human health. Typically, people spend more than 80% of their time indoors. Consequently, human exposure to traffic-related PM₂.₅ in indoor environments has received considerable attention. Most of the public residential buildings in tropical countries are designed for natural ventilation where indoor air quality tends to be strongly affected by the migration of air pollutants of outdoor origin. However, most of the previously reported traffic-related PM₂.₅ exposure assessment studies relied on ambient PM₂.₅ concentrations and thus, the health impact of traffic-related PM₂.₅ on occupants in naturally ventilated buildings remains largely unknown. Therefore, a systematic field study was conducted to assess indoor human exposure to traffic-related PM₂.₅ with and without mitigation measures in a typical naturally ventilated residential apartment situated near a road carrying a large volume of traffic. Three PM₂.₅ exposure scenarios were simulated in this study, i.e., Case 1: keeping all windows open with a ceiling fan on as per the usual practice, Case 2: keeping all windows fully closed as a mitigation measure, and Case 3: keeping all windows fully closed with the operation of a portable indoor air cleaner as an additional mitigation measure. The indoor to outdoor (I/O) ratios for PM₂.₅ mass concentrations were assessed and the effectiveness of using the indoor air cleaner was quantified. Additionally, potential human health risk based on the bioavailable fraction of toxic trace elements was also estimated for the three cases in order to identify a suitable mitigation measure for reducing PM₂.₅ exposure indoors. Traffic-related PM₂.₅ levels indoors exceeded the air quality guidelines (12 µg/m³) in Case 1, i.e., under natural ventilation conditions due to advective flow of outdoor air into the indoor environment. However, while using the indoor air cleaner, a significant reduction (p < 0.05) in the PM₂.₅ exposure levels was noticed indoors. Specifically, the effectiveness of the air cleaner in terms of reducing indoor PM₂.₅ exposure was estimated to be about 74%. Moreover, potential human health risk assessment also indicated a substantial reduction in potential health risk while using the air cleaner. This is the first study of its kind that evaluated the indoor human exposure to traffic-related PM₂.₅ and identified a suitable exposure mitigation measure that can be implemented in densely populated cities to realize health benefits.

Keywords: fine particulate matter, indoor air cleaner, potential human health risk, vehicular emissions

Procedia PDF Downloads 130

Authors: Jinan Fiaidhi, Sabah Mohammed

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Diagnosing cataract severity is an important factor in deciding to undertake surgery. It is usually conducted by an ophthalmologist or through taking a variety of fundus photography that needs to be examined by the ophthalmologist. This paper carries out an investigation using a Siamese neural net that can be trained with small anchor samples to score cataract severity. The model used in this paper is based on a triplet loss function that takes the ophthalmologist best experience in rating positive and negative anchors to a specific cataract scaling system. This approach that takes the heuristics of the ophthalmologist is generally called the thick data approach, which is a kind of machine learning approach that learn from a few shots. Clinical Relevance: The lens of the eye is mostly made up of water and proteins. A cataract occurs when these proteins at the eye lens start to clump together and block lights causing impair vision. This research aims at employing thick data machine learning techniques to rate the severity of the cataract using Siamese neural network.

Keywords: thick data analytics, siamese neural network, triplet-loss model, few shot learning

Procedia PDF Downloads 115

Authors: Allison Futter

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Lifetime use of electronic cigarettes (EC) in college students has been estimated at around 50%; recent research shows Mobile Health (mHealth) technology is a promising tool to help address this public health issue, yet the majority of EC cessation mHealth tools found on smartphone app stores lack empirical support of their effectiveness. The Smiling Instead of Smoking (SiS) app is a positive psychology-based smartphone app for nondaily smokers. Due to previous success with brief, self-administered positive psychology exercises for cigarette cessation, this study examined the SiS App’s feasibility and effectiveness for EC cessation. Sixteen undergraduates used the SiS app for 3 weeks: one week before their quit date and 2 weeks after. As hypothesized, participants had significant declines in their craving and maintained pre-cessation levels of positive affect. There were no significant changes in dependency or self-efficacy. In the one-month follow-up survey, 38% of participants reported being abstinent. The app had an almost 4-star rating for its features (e.g., functionality, aesthetics, information, etc.) and participants reported moderate satisfaction with its use. Participants used the app, on average, 10 out of the 21 days of the prescribed app use. This study highlights the promise of mHealth support and positive psychology for EC cessation, adding to the understanding of possible ways to support EC quit attempts.

Keywords: e-cigarette cessation, mHealth, positive psychology, smartphone app

Procedia PDF Downloads 121

Authors: Niyiragira Sixte, Jules Verne Nakimana

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Introduction: Alcoholism is gradually becoming a public health issue due to its frequency, which continues to increase, especially in schools and at young ages. The general objective of the study was to contribute to the determination of the factors associated with alcohol consumption among young people. Methodology: This descriptive and analytical cross-sectional study entitled “Study of factors associated with alcohol consumption among young people aged 15 to 24. The study was conducted using a non-probability method, and the sampling technique was for convenience. The data collection technique used was the survey by questionnaire and the exploitation of the documentary. Microsoft Word 2013, Microsoft Excel 2.13 and EPI INFO7 software were used for this purpose. Results: The results of in study showed that 43.36% of the students surveyed took alcohol, and the factors associated with alcohol consumption are: religion, smoking and influence from friends. Conclusion: The prevalence of alcohol consumption among young people is very high, and awareness is more than necessary to prevent alcohol-related harm among young people.

Keywords: consumption, alcohol, young people, factors

Procedia PDF Downloads 87