Search results for: regularized regression

Authors: Marybec Griffin

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Purpose: The purpose of this cross-sectional study was to get a better understanding of healthcare usage and satisfaction among young adult gay men (YAGM), including the facility used as the usual source of healthcare, preference for coordinated healthcare, and if their primary care provider (PCP) adequately addressed the health needs of gay men. Methods: Interviews were conducted among n=800 YAGM in New York City (NYC). Participants were surveyed about their sociodemographic characteristics and healthcare usage and satisfaction access using multivariable logistic regression models. The surveys were conducted between November 2015 and June 2016. Results: The mean age of the sample was 24.22 years old (SD=4.26). The racial and ethnic background of the participants is as follows: 35.8% (n=286) Black Non-Hispanic, 31.9% (n=225) Hispanic/Latino, 20.5% (n=164) White Non-Hispanic, 4.4% (n=35) Asian/Pacific Islander, and 6.9% (n=55) reporting some other racial or ethnic background. 31.1% (n=249) of the sample had an income below $14,999. 86.7% (n=694) report having either public or private health insurance. For usual source of healthcare, 44.6% (n=357) of the sample reported a private doctor’s office, 16.3% (n=130) reported a community health center, and 7.4% (n=59) reported an urgent care facility, and 7.6% (n=61) reported not having a usual source of healthcare. 56.4% (n=451) of the sample indicated a preference for coordinated healthcare. 54% (n=334) of the sample were very satisfied with their healthcare. Findings from multivariable logistical regression models indicate that participants with higher incomes (AOR=0.54, 95% CI 0.36-0.81, p < 0.01) and participants with a PCP (AOR=0.12, 95% CI 0.07-0.20, p < 0.001) were less likely to use a walk-in facility as their usual source of healthcare. Results from the second multivariable logistic regression model indicated that participants who experienced discrimination in a healthcare setting were less likely to prefer coordinated healthcare (AOR=0.63, 95% CI 0.42-0.96, p < 0.05). In the final multivariable logistic model, results indicated that participants who had disclosed their sexual orientation to their PCP (AOR=2.57, 95% CI 1.25-5.21, p < 0.01) and were comfortable discussing their sexual activity with their PCP (AOR=8.04, 95% CI 4.76-13.58, p < 0.001) were more likely to agree that their PCP adequately addressed the healthcare needs of gay men. Conclusion: Understanding healthcare usage and satisfaction among YAGM is necessary as the healthcare landscape changes, especially given the relatively recent addition of urgent care facilities. The type of healthcare facility used as a usual source of care influences the ability to seek comprehensive and coordinated healthcare services. While coordinated primary and sexual healthcare may be ideal, individual preference for this coordination among YAGM is desired but may be limited due to experiences of discrimination in primary care settings.

Keywords: healthcare policy, gay men, healthcare access, Affordable Care Act

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Authors: Abdullahi Yahaya Musa, Harun Rann Bakari

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The study examined the determinants of food security among households in Maiduguri, Metropolis, Borno State, Nigeria. The objectives of the study are to: examine the determinants of food security among households; identify the coping strategies employed by food-insecure households in Maiduguri, Metropolis, Borno State, Nigeria. The population of the study is 843,964 respondents out of which 400 respondents were sampled. The study used a self-developed questionnaire to collect data from four hundred (400) respondents. Four hundred (400) copies of questionnaires were administered and all were retrieved, making 100% return rate. The study employed descriptive and inferential statistics for data analysis. Descriptive statistics (frequency counts and percentages) was used to analyze the socio-economic characteristics of the respondents and objective four, while inferential statistics (logit regression analysis) was used to analyze one. Four hundred (400) copies of questionnaires were administered and all the four hundred (400) were retrieved, making a 100% return rate. The results were presented in tables and discussed according to the research objectives. The study revealed that HHA, HHE, HHSZ, HHSX, HHAS, HHI, HHFS, HHFE, HHAC and HHCDR were the determinants of food security in Maiduguri Metropolis. Relying on less preferred foods, purchasing food on credit, limiting food intake to ensure children get enough, borrowing money to buy foodstuffs, relying on help from relatives or friends outside the household, adult family members skipping or reducing a meal because of insufficient finances and ration money to household members to buy street food were the coping strategies employed by food-insecure households in Maiduguri metropolis. The study recommended that Nigeria Government should intensify the fight against the Boko haram insurgency. This will put an end to Boko Haram Insurgency and enable farmers to return to farming in Borno state.

Keywords: internally displaced persons, food security, coping strategies, descriptive statistics, logistics regression model, odd ratio

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Authors: O. Abiodun Adeyinka, B. Adeyemo Adesesan

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The forensic use of handwriting depends on the analysis, comparison, and evaluation decisions made by forensic document examiners. When using biometric technology in forensic applications, it is necessary to compute Likelihood Ratio (LR) for quantifying strength of evidence under two competing hypotheses, namely the prosecution and the defense hypotheses wherein a set of assumptions and methods for a given data set will be made. It is therefore important to know how repeatable and reproducible our estimated LR is. This paper evaluated the accuracy and reproducibility of examiners' decisions. Confidence interval for the estimated LR were presented so as not get an incorrect estimate that will be used to deliver wrong judgment in the court of Law. The estimate of LR is fundamentally a Bayesian concept and we used two LR estimators, namely Logistic Regression (LoR) and Kernel Density Estimator (KDE) for this paper. The repeatability evaluation was carried out by retesting the initial experiment after an interval of six months to observe whether examiners would repeat their decisions for the estimated LR. The experimental results, which are based on handwriting dataset, show that LR has different confidence intervals which therefore implies that LR cannot be estimated with the same certainty everywhere. Though the LoR performed better than the KDE when tested using the same dataset, the two LR estimators investigated showed a consistent region in which LR value can be estimated confidently. These two findings advance our understanding of LR when used in computing the strength of evidence in handwriting using forensics.

Keywords: confidence interval, handwriting, kernel density estimator, KDE, logistic regression LoR, repeatability, reproducibility

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Authors: Faiz N. K. Yusufi, Aquil Ahmed, Jamal Ahmad

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Diabetes in India is growing at an alarming rate and the complications caused by it need to be controlled. Coronary heart disease (CHD) is one of the complications that will be discussed for prediction in this study. India has the second most number of diabetes patients in the world. To the best of our knowledge, there is no CHD risk score for Indian type 2 diabetes patients. Any form of CHD has been taken as the event of interest. A sample of 750 was determined and randomly collected from the Rajiv Gandhi Centre for Diabetes and Endocrinology, J.N.M.C., A.M.U., Aligarh, India. Collected variables include patients data such as sex, age, height, weight, body mass index (BMI), blood sugar fasting (BSF), post prandial sugar (PP), glycosylated haemoglobin (HbA1c), diastolic blood pressure (DBP), systolic blood pressure (SBP), smoking, alcohol habits, total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), very low density lipoprotein (VLDL), physical activity, duration of diabetes, diet control, history of antihypertensive drug treatment, family history of diabetes, waist circumference, hip circumference, medications, central obesity and history of CHD. Predictive risk scores of CHD events are designed by cox proportional hazard regression. Model calibration and discrimination is assessed from Hosmer Lemeshow and area under receiver operating characteristic (ROC) curve. Overfitting and underfitting of the model is checked by applying regularization techniques and best method is selected between ridge, lasso and elastic net regression. Youden’s index is used to choose the optimal cut off point from the scores. Five year probability of CHD is predicted by both survival function and Markov chain two state model and the better technique is concluded. The risk scores for CHD developed can be calculated by doctors and patients for self-control of diabetes. Furthermore, the five-year probabilities can be implemented as well to forecast and maintain the condition of patients.

Keywords: coronary heart disease, cox proportional hazard regression, ROC curve, type 2 diabetes Mellitus

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Authors: Dena Alhaloul

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The Middle East and North Africa (MENA) region is characterized by diverse cultures, economies, and social structures. Fertility rates in MENA have seen significant changes over time, with variations among countries and subregions. Understanding fertility patterns in this region is essential due to its impact on demographic dynamics, healthcare, labor markets, and social policies. Rising or declining fertility rates have far-reaching consequences for the region's socioeconomic development. The main thrust of this study is to comprehensively examine fertility rates in the Middle East and North Africa (MENA) region. It aims to understand the distribution, determinants, and temporal trends of fertility rates in MENA countries. The study seeks to provide insights into the factors influencing fertility decisions, assess how fertility rates have evolved over time, and potentially develop statistical models to characterize these trends. As for the methodology of the study, the study uses descriptive statistics to summarize and visualize fertility rate data. It also uses regression analyses to identify determinants of fertility rates as well as statistical modeling to characterize temporal trends in fertility rates. The conclusion of this study The research will contribute to a deeper understanding of fertility dynamics in the MENA region, shedding light on the distribution of fertility rates, their determinants, and historical trends.

Keywords: fertility, distribution, modeling, regression

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Authors: Zuoyong Zhang, Min Yu, Jinlong Zhao, Shudong He

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The Maillard reaction can produce the flavor enhancing substance through the chemical crosslinking between free amino group of the protein or polypeptide with the carbonyl of the reducing sugar. In this research, solutions of rapeseed meal peptide and D-xylose with or without L-cysteine (RXC or RX) were heated over a range of temperatures (80-140 °C) for 2 h. It was observed that RXs had a severe browning,while RXCs accompanied by more pH decrement with the temperature increasing. Then the correlation among data of quantitative sensory descriptive analysis, free amino acid (FAA) and GC–MS of RXCs and RXs were analyzed using the partial least square regression method. Results suggested that the Maillard reaction product (MRPs) with cysteine formed at 120 °C (RXC-120) had greater sensory properties especially meat-like flavor compared to other MRPs. Meanwhile, it revealed that glutamic and glycine not only had a positive contribution to meaty aroma but also showed a significant and positive influence on umami taste of RXs based on the FAA data. Moreover, the sulfur-containing compounds showed a significant positive correlation with the meat-like flavor of RXCs, while RXs depended on furans and nitrogenous-containing compounds with more caramel-like flavor. Therefore, a MRP with strong meaty flavor could be obtained at 120 °C by addition of cysteine.

Keywords: rapeseed meal, Maillard reaction, sensory characteristics, FAA, GC–MS, partial least square regression

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Authors: Debi Konukcu Onal, Tarkan Cavusoglu

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In modern societies, the costs of public goods and services are shared through taxes paid by citizens. However, taxation has always been a frictional issue, as tax obligations are perceived to be a financial burden for taxpayers rather than being merit that fulfills the redistribution, regulation and stabilization functions of the welfare state. The tax compliance literature evolves into discussing why people still pay taxes in systems with low costs of legal enforcement. Related empirical and theoretical works show that a wide range of socially oriented behavioral factors can stimulate voluntary compliance and subversive effects as well. These behavioral motivations are argued to be driven by self-enforcing rules of informal institutions, either independently or through interactions with legal orders set by formal institutions. The main focus of this study is to investigate empirically whether institutional particularities have a significant role in explaining the cross-country differences in the tax noncompliance levels. A part of the controversy about the driving forces behind tax noncompliance may be attributed to the lack of empirical evidence. Thus, this study aims to fill this gap through regression estimates, which help to trace the link between institutional quality and noncompliance on a cross-country basis. Tax evasion estimates of Buehn and Schneider is used as the proxy measure for the tax noncompliance levels. Institutional quality is quantified by three different indicators (percentile ranks of Worldwide Governance Indicators, ratings of the International Country Risk Guide, and the country ratings of the Freedom in the World). Robust Least Squares and Threshold Regression estimates based on the sample of the Organization for Economic Co-operation and Development (OECD) countries imply that tax compliance increases with institutional quality. Moreover, a threshold-based asymmetry is detected in the effect of institutional quality on tax noncompliance. That is, the negative effects of tax burdens on compliance are found to be more pronounced in countries with institutional quality below a certain threshold. These findings are robust to all alternative indicators of institutional quality, supporting the significant interaction of societal values with the individual taxpayer decisions.

Keywords: institutional quality, OECD economies, tax compliance, tax evasion

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Authors: Wei Yang, Xiaohui Cui, Weiping Zhu, Liqun Liu

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The rapid development of the Confucius Institute is attracting more and more attention from mainstream media around the world. Mainstream media plays a large role in public information dissemination and public opinion. This study presents efforts to analyze the correlation and functional relationship between domestic and foreign mainstream media by analyzing the amount of reports on the Confucius Institute. Three kinds of correlation calculation methods, the Pearson correlation coefficient (PCC), the Spearman correlation coefficient (SCC), and the Kendall rank correlation coefficient (KCC), were applied to analyze the correlations among mainstream media from three regions: mainland of China; Hong Kong and Macao (the two special administration regions of China denoted as SARs); and overseas countries excluding China, such as the United States, England, and Canada. Further, the paper measures the functional relationships among the regions using a regression model. The experimental analyses found high correlations among mainstream media from the different regions. Additionally, we found that there is a linear relationship between the mainstream media of overseas countries and those of the SARs by analyzing the amount of reports on the Confucius Institute based on a data set obtained by crawling the websites of 106 mainstream media during the years 2004 to 2014.

Keywords: mainstream media, Confucius institute, correlation analysis, regression model

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Authors: Lizhou Chen, Abdelhamid Belgaid, Assem Elsayed, Xiaoming Yang

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Compression index is essential in foundation settlement calculation. The traditional method for determining compression index is consolidation test which is expensive and time consuming. Many researchers have used regression methods to develop empirical equations for predicting compression index from soil properties. Based on a large number of compression index data collected from consolidation tests, the accuracy of some popularly empirical equations were assessed. It was found that primary compression index is significantly overestimated in some equations while it is underestimated in others. The sensitivity analyses of soil parameters including water content, liquid limit and void ratio were performed. The results indicate that the compression index obtained from void ratio is most accurate. The ANOVA (analysis of variance) demonstrates that the equations with multiple soil parameters cannot provide better predictions than the equations with single soil parameter. In other words, it is not necessary to develop the relationships between compression index and multiple soil parameters. Meanwhile, it was noted that secondary compression index is approximately 0.7-5.0% of primary compression index with an average of 2.0%. In the end, the proposed prediction equations using power regression technique were provided that can provide more accurate predictions than those from existing equations.

Keywords: compression index, clay, settlement, consolidation, secondary compression index, soil parameter

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Authors: Dieudonne Uwizeye

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

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

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Authors: P. Kazymbet, G. Abildinova, K.Makhambetov, M. Bakhtin, D. Rybalkina, K. Zhumadilov

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Conducted cytogenetic research in workers Stepnogorsk Mining-Chemical Combine (Akmola region) with the study of 26341 chromosomal metaphase. Using a regression analysis with program DataFit, version 5.0, dependence between exposure dose and the following cytogenetic exponents has been studied: frequency of aberrant cells, frequency of chromosomal aberrations, frequency of the amounts of dicentric chromosomes, and centric rings. Experimental data on calibration curves "dose-effect" enabled the development of a mathematical model, allowing on data of the frequency of aberrant cells, chromosome aberrations, the amounts of dicentric chromosomes and centric rings calculate the absorbed dose at the time of the study. In the dose range of 0.1 Gy to 5.0 Gy dependence cytogenetic parameters on the dose had the following equation: Y = 0,0067е^0,3307х (R2 = 0,8206) – for frequency of chromosomal aberrations; Y = 0,0057е^0,3161х (R2 = 0,8832) –for frequency of cells with chromosomal aberrations; Y =5 Е-0,5е^0,6383 (R2 = 0,6321) – or frequency of the amounts of dicentric chromosomes and centric rings on cells. On the basis of cytogenetic parameters and regression equations calculated absorbed dose in workers of uranium production at the time of the study did not exceed 0.3 Gy.

Keywords: Stepnogorsk, mathematical modeling, cytogenetic, dicentric chromosomes

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Authors: A. El-S. Makled, M. K. Al-Tamimi

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A mathematical model to predict the performance parameters (thrusts, chamber pressures, fuel mass flow rates, mixture ratios, and regression rates during firing time) of hybrid rocket motor (HRM) is evaluated. The internal ballistic (IB) hybrid combustion model assumes that the solid fuel surface regression rate is controlled only by heat transfer (convective and radiative) from flame zone to solid fuel burning surface. A laboratory HRM is designed, manufactured, and tested for low thrust profile space missions (10-15 N) and for validating the mathematical model (computer program). The polymer material and gaseous oxidizer which are selected for this experimental work are polymethyle-methacrylate (PMMA) and polyethylene (PE) as solid fuel grain and gaseous oxygen (GO₂) as oxidizer. The variation of various operational parameters with time is determined systematically and experimentally in firing of up to 20 seconds, and an average combustion efficiency of 95% of theory is achieved, which was the goal of these experiments. The comparison between recording fire data and predicting analytical parameters shows good agreement with the error that does not exceed 4.5% during all firing time. The current mathematical (computer) code can be used as a powerful tool for HRM analytical design parameters.

Keywords: hybrid combustion, internal ballistics, hybrid rocket motor, performance parameters

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Authors: Anita Sadat Sadati Rostami, Reza Almasi Ghaleh

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Surface electromyography (sEMG) offers important insights into muscle activation and has applications in fields including rehabilitation and human-computer interaction. The purpose of this work is to predict the degree of activation of two joints in the index finger using an LSTM-Transformer architecture trained on sEMG data from the Ninapro DB8 dataset. We apply advanced preprocessing techniques, such as multi-band filtering and customizable rectification methods, to enhance the encoding of sEMG data into features that are beneficial for regression tasks. The processed data is converted into spike patterns and simulated using Leaky Integrate-and-Fire (LIF) neuron models, allowing for neuromorphic-inspired processing. Our findings demonstrate that adjusting filtering parameters and neuron dynamics and employing the LSTM-Transformer model improves joint angle prediction performance. This study contributes to the ongoing development of deep learning frameworks for sEMG analysis, which could lead to improvements in motor control systems.

Keywords: surface electromyography, LSTM-transformer, spiking neural networks, hand kinematics, leaky integrate-and-fire neuron, band-pass filtering, muscle activity decoding

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Authors: Tsion Tekalegn

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In Ethiopia, improved potato varieties are essential for food security, but smallholders' adoption of improved technologies limits their productivity. For this study, data was collected based on a structured questionnaire randomly collected from the 329 sample farmers (158 adopters and 171 non-adopters). We estimate the adoption of improved variety and causal impact using Endogenous Switching Regression (ESR), and a propensity Score Matching (PSM) was used to test the treatment effect. This helps us estimate the effect of improved potato variety on smallholder farmer income by controlling for the role of the selection bias problem stemming from both observed and unobserved heterogeneity. According to the result, key determinants influencing adoption include livestock ownership, access to extension services, and farming experience, which positively affect the likelihood of adopting improved varieties. In contrast, access to irrigation negatively correlates with adoption, suggesting that farmers with reliable water sources perceive less need for improved varieties. The ESR model result confirmed that improved potato variety adoption increases the smallholder farmer income with an estimated gain of 8.77%. Thus, to improve the potato variety of the farming households, the government should give due emphasis to potato production, and the extension services need to be strengthened.

Keywords: adoption, improved potato varieties, endogenous switching regression, Ethiopia

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Authors: Basan Shrestha

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The relationship between the household size and the poverty is not well understood. Malthus followers advocate that the increasing population add pressure to the dwindling resource base due to increasing demand that would lead to poverty. Others claim that bigger households are richer due to availability of household labour for income generation activities. Facts from Nepal were analyzed to examine the relationship between the household size and poverty rate. The analysis of data from 3,968 Village Development Committee (VDC)/ municipality (MP) located in 75 districts of all five development regions revealed that the average household size had moderate positive correlation with the poverty rate (Karl Pearson's correlation coefficient=0.44). In a regression analysis, the household size determined 20% of the variation in the poverty rate. Higher positive correlation was observed in eastern Nepal (Karl Pearson's correlation coefficient=0.66). The regression analysis showed that the household size determined 43% of the variation in the poverty rate in east. The relation was poor in far-west. It could be because higher incidence of poverty was there irrespective of household size. Overall, the facts revealed that the bigger households were relatively poorer. With the increasing level of awareness and interventions for family planning, it is anticipated that the household size will decrease leading to the decreased poverty rate. In addition, the government needs to devise a mechanism to create employment opportunities for the household labour force to reduce poverty.

Keywords: household size, poverty rate, nepal, regional development

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Authors: Himayatullah Khan, Alena Fedorova

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The present paper analyses the income-consumption relationships in Pakistan using annual time series data from 1980-81 to 2010-1. The paper uses the Augmented Dickey-Fuller test to check the unit root and stationarity in these two time series. The paper finds that the two time series are nonstationary but stationary at their first difference levels. The Augmented Engle-Granger test and the Cointegrating Regression Durbin-Watson test imply that the two time series of consumption and income are cointegrated and that long-run marginal propensity to consume is 0.88 which is given by the estimated (static) equilibrium relation. The paper also used the error correction mechanism to find out to model dynamic relationship. The purpose of the ECM is to indicate the speed of adjustment from the short-run equilibrium to the long-run equilibrium state. The results show that MPC is equal to 0.93 and is highly significant. The coefficient of Engle-Granger residuals is negative but insignificant. Statistically, the equilibrium error term is zero, which suggests that consumption adjusts to changes in GDP in the same period. The short-run changes in GDP have a positive impact on short-run changes in consumption. The paper concludes that we may interpret 0.93 as the short-run MPC. The pair-wise Granger Causality test shows that both GDP and consumption Granger cause each other.

Keywords: cointegrating regression, Augmented Dickey Fuller test, Augmented Engle-Granger test, Granger causality, error correction mechanism

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Authors: Dwi Kartika Rukmi, Miftafu Darussalam

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Background: The disclosure of women’s HIV status toward their sexual partners is an important issue that should be regarded as one of the efforts to prevent and control the spread of HIV. Research on the disclosure of seropositive HIV status as well as women-related factors in Indonesia, especially Yogyakarta is only a few. Methods: This is a correlational descriptive research along with its cross-sectional approach on 329 women with HIV/AIDS at the Victory Plus NGO from June to July 2016. This research used a purposive sampling method and a questionnaire as the data collection technique. The bivariate analysis test was undertaken by using a chi-square and multivariate test along with a logistic regression. Result: The multivariate analysis and logistic regression show five independent variables related to the disclosure of seropositive HIV status of women with HIV/AIDS toward their sexual partners, namely ethnicity (aOR = 36,859; 95% CI; (6,544-207,616)) religion (aOR =0,255; 95%CI; (0,075-0,868)), discussion with partners prior to the HIV test (aOR =0,069; 95%CI; (0,065-0,438)) , types of sexual partners (aOR = 0.191; 95% CI; (0.082-0,445)) and knowledge on the partners’ HIV status (aOR = 0.036; 95% CI; (0.008-0.160)). The highest level of reason for seropositive HIV women not to be open about their partners’ status is the fear of being rejected by their partners and the environmental stigma of HIV AIDS disease. Conclusion: The disclosure of seropositive HIV status in women with HIV/AIDS in the Victory Plus NGO of Yogyakarta was 79.4% or classified as a high category with some related factors such as ethnicity, religion, discussion with partners prior to the HIV test, types of partners and knowledge on the partners’ HIV status.

Keywords: women, HIV, disclosure, sexual partner

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Authors: Kalandi Charan Pradhan

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In this study, we investigate does weather variation determine temporary labour migration using 210 sample households from six Semi-Arid Tropic (SAT) villages for the period of 2005-2014 in India. The study has made an attempt to examine how households use temporary labour migration as a coping mechanism to minimise the risk rather than maximize the utility of the households. The study employs panel Logit regression model to predict the probability of household having at least one temporary labour migrant. As per as econometrics result, it is found that along with demographic and socioeconomic factors; weather variation plays an important role to determine the decision of migration at household level. In order to capture the weather variation, the study uses mean crop yield deviation over the study periods. Based on the random effect logit regression result, the study found that there is a concave relationship between weather variation and decision of temporary labour migration. This argument supports the theory of New Economics of Labour Migration (NELM), which highlights the decision of labour migration not only maximise the households’ utility but it helps to minimise the risks.

Keywords: temporary migration, socioeconomic factors, weather variation, crop yield, logit estimation

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Authors: Mastawal Melese, Yismaw Assefa

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This study aims to identify household-level determinants of solid waste disposal (SWD) practices in Bure Town, north-western Ethiopia. Using a cross-sectional design and a mixed-methods approach, data were collected from 238 randomly selected households through structured interviews, focus group discussions, and field observations. Descriptive analysis revealed that 14.7% of households used composting as a primary SWD method, 37.4% practiced open dumping, 25.6% used burning, and 22.3% resorted to burial. Multinomial logistic regression showed that factors such as monthly income, age, family size, length of residence, sex, home ownership, solid waste sorting procedures, and education significantly influenced the choice of disposal method. Households with lower education, income, home ownership, and shorter residence times were more likely to use improper disposal methods. Females were found to be more likely to engage in better waste disposal practices than males. These findings underscore the need for context-specific interventions in newly developing towns to enhance household-level SWM systems by addressing key socio-economic factors.

Keywords: multinomial logistic regression, solid waste management, solid waste disposal, urban household

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Authors: Nixon Kuruvila, H. V. Ravindra

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Wire-cut Electro Discharge Machining (WEDM) is a special form of conventional EDM process in which electrode is a continuously moving conductive wire. The present study aims at determining parametric influence and optimum process parameters of Wire-EDM using Taguchi’s Technique and Genetic algorithm. The variation of the performance parameters with machining parameters was mathematically modeled by Regression analysis method. The objective functions are Dimensional Accuracy (DA) and Material Removal Rate (MRR). Experiments were designed as per Taguchi’s L16 Orthogonal Array (OA) where in Pulse-on duration, Pulse-off duration, Current, Bed-speed and Flushing rate have been considered as the important input parameters. The matrix experiments were conducted for the material Oil Hardened Non Shrinking Steel (OHNS) having the thickness of 40 mm. The results of the study reveals that among the machining parameters it is preferable to go in for lower pulse-off duration for achieving over all good performance. Regarding MRR, OHNS is to be eroded with medium pulse-off duration and higher flush rate. Finally, the validation exercise performed with the optimum levels of the process parameters. The results confirm the efficiency of the approach employed for optimization of process parameters in this study.

Keywords: dimensional accuracy (DA), regression analysis (RA), Taguchi method (TM), volumetric material removal rate (VMRR)

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: Likewin Thomas, M. V. Manoj Kumar, B. Annappa

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Traditional execution process follows the path of execution drawn by the process analyst without observing the behaviour of resource and other real-time constraints. Identifying process model, predicting the behaviour of resource and recommending the optimal path of execution for a real time process is challenging. The proposed AlfyMiner: αyM iner gives a new dimension in process execution with the novel techniques Process Model Analyser: PMAMiner and Resource behaviour Analyser: RBAMiner for recommending the probable path of execution. PMAMiner discovers next probable activity for currently executing activity in an online process using variant matching technique to identify the set of next probable activity, among which the next probable activity is discovered using decision tree model. RBAMiner identifies the resource suitable for performing the discovered next probable activity and observe the behaviour based on; load and performance using polynomial regression model, and waiting time using queueing theory. Based on the observed behaviour αyM iner recommend the probable path of execution with; next probable activity and the best suitable resource for performing it. Experiments were conducted on process logs of CoSeLoG Project1 and 72% of accuracy is obtained in identifying and recommending next probable activity and the efficiency of resource performance was optimised by 59% by decreasing their load.

Keywords: cross-organization process mining, process behaviour, path of execution, polynomial regression model

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Authors: Rabiaal Adawiyah Shazali, Corina Joseph

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The disclosure of Intellectual Capital (IC) information is getting more vital in today’s era of a knowledge-based economy. Companies are advised by accounting bodies to enhance IC disclosure which complements the conventional financial disclosures. There are no accounting standards for Intellectual Capital Disclosure (ICD), therefore the disclosure is entirely voluntary. Hence, this study aims to investigate the extent of ICD and to examine the relationship between corporate governance and ICD in Malaysia. This study employed content analysis of 100 annual reports by the top 100 public listed companies in Malaysia during 2012. The uniqueness of this study lies on its underpinning theory used where it applies the institutional isomorphism theory to support the effect of the attributes of corporate governance towards ICD. In order to achieve the stated objective, multiple regression analysis were employed to conduct this study. From the descriptive statistics, it was concluded that public listed companies in Malaysia have increased their awareness towards the importance of ICD. Furthermore, results from the multiple regression analysis confirmed that corporate governance affects the company’s ICD where the frequency of audit committee meetings and the board size has positively influenced the level of ICD in companies. Findings from this study would provide an incentive for companies in Malaysia to enhance the disclosure of IC. In addition, this study would assist Bursa Malaysia and other regulatory bodies to come up with a proper guideline for the disclosure of IC.

Keywords: annual report, content analysis, corporate governance, intellectual capital disclosure

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Authors: Hasan Serdar Öge, Esra Çiftçi, Kazım Karaboğa

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The main purpose of the research is to address the role of psychological harassment behaviors (mobbing) to which employees are exposed and personality characteristics over work alienation. Research population was composed of the employees of Provincial Special Administration. A survey with four sections was created to measure variables and reach out the basic goals of the research. Correlation and step-wise regression analyses were performed to investigate the separate and overall effects of sub-dimensions of psychological harassment behaviors and personality characteristic on work alienation of employees. Correlation analysis revealed significant but weak relationships between work alienation and psychological harassment and personality characteristics. Step-wise regression analysis revealed also significant relationships between work alienation variable and assault to personality, direct negative behaviors (sub dimensions of mobbing) and openness (sub-dimension of personality characteristics). Each variable was introduced into the model step by step to investigate the effects of significant variables in explaining the variations in work alienation. While the explanation ratio of the first model was 13%, the last model including three variables had an explanation ratio of 24%.

Keywords: alienation, five-factor personality characteristics, mobbing, psychological harassment, work alienation

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: Jui Chen Wu, Ming Yi Hsu

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

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

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Authors: Waleed Basuliman

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Anthropometric dimensions are considered one of the important factors when designing human-machine systems. In this study, the estimation of anthropometric dimensions has been improved by using Artificial Neural Network (ANN) model that is able to predict the anthropometric measurements of Saudi males in Riyadh City. A total of 1427 Saudi males aged 6 to 60 years participated in measuring 20 anthropometric dimensions. These anthropometric measurements are considered important for designing the work and life applications in Saudi Arabia. The data were collected during eight months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining 15 dimensions were set to be the measured variables (Model’s outcomes). The hidden layers varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was able to estimate the body dimensions of Saudi male population in Riyadh City. The network's mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found to be 0.0348 and 3.225, respectively. These results were found less, and then better, than the errors found in the literature. Finally, the accuracy of the developed neural network was evaluated by comparing the predicted outcomes with regression model. The ANN model showed higher coefficient of determination (R2) between the predicted and actual dimensions than the regression model.

Keywords: artificial neural network, anthropometric measurements, back-propagation

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Authors: Khalid Kaddoura, Ahmed Assad, Tarek Zayed

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Sewer pipelines are prone to deterioration over-time. In fact, their deterioration does not follow a fixed downward pattern. This is in fact due to the defects that propagate through their service life. Sewer pipeline defects are categorized into distinct groups. However, the main two groups are the structural and operational defects. By definition, the structural defects influence the structural integrity of the sewer pipelines such as deformation, cracks, fractures, holes, etc. However, the operational defects are the ones that affect the flow of the sewer medium in the pipelines such as: roots, debris, attached deposits, infiltration, etc. Yet, the process for each defect to emerge follows a cause and effect relationship. Deformation, which is the change of the sewer pipeline geometry, is one type of an influencing defect that could be found in many sewer pipelines due to many surrounding factors. This defect could lead to collapse if the percentage exceeds 15%. Therefore, it is essential to predict the deformation percentage before confronting such a situation. Accordingly, this study will predict the percentage of the deformation defect in sewer pipelines adopting the multiple regression analysis. Several factors will be considered in establishing the model, which are expected to influence the defamation defect severity. Besides, this study will construct a time-based curve to understand how the defect would evolve overtime. Thus, this study is expected to be an asset for decision-makers as it will provide informative conclusions about the deformation defect severity. As a result, inspections will be minimized and so the budgets.

Keywords: deformation, prediction, regression analysis, sewer pipelines

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Authors: Martial Amou

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This study was carried out to assess the situation of households’ livelihood under a changing climate pattern in the Zio district of Togo, West Africa. The study examined three important aspects: (i) assessment of households’ livelihood situation under a changing climate pattern, (ii) farmers’ perception and understanding of local climate change, (iii) determinants of adaptation strategies undertaken in cropping pattern to climate change. To this end, secondary sources of data, and survey data collected from 235 farmers in four villages in the study area were used. Adapted conceptual framework from Sustainable Livelihood Framework of DFID, two steps Binary Logistic Regression Model and descriptive statistics were used in this study as methodological approaches. Based on Sustainable Livelihood Approach (SLA), various factors revolving around the livelihoods of the rural community were grouped into social, natural, physical, human, and financial capital. Thus, the study came up that households’ livelihood situation represented by the overall livelihood index in the study area (34%) is below the standard average households’ livelihood security index (50%). The natural capital was found as the poorest asset (13%) and this will severely affect the sustainability of livelihood in the long run. The result from descriptive statistics and the first step regression (selection model) indicated that most of the farmers in the study area have clear understanding of climate change even though they do not have any idea about greenhouse gases as the main cause behind the issue. From the second step regression (output model) result, education, farming experience, access to credit, access to extension services, cropland size, membership of a social group, distance to the nearest input market, were found to be the significant determinants of adaptation measures undertaken in cropping pattern by farmers in the study area. Based on the result of this study, recommendations are made to farmers, policy makers, institutions, and development service providers in order to better target interventions which build, promote or facilitate the adoption of adaptation measures with potential to build resilience to climate change and then improve rural livelihood.

Keywords: climate change, rural livelihood, cropping pattern, adaptation, Zio District

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Authors: Daming Xu, Yuanyuan Wang

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Abstract: Under the trend of rapid expansion of urbanization, the motorized urban characteristics become more and more obvious, and the walkability of urban space is seriously affected. The construction of walkability of space, as the main mode of travel for the elderly in their daily lives, has become more and more important in the current social context of serious aging. Settlement is the most basic living unit of residents, and daily shopping, medical care, and other daily trips are closely related to the daily life of the elderly. Therefore, it is of great practical significance to explore the impact of built environment on elderly people's daily walking trips at the settlement level for the construction of pedestrian-friendly settlements for the elderly. The study takes three typical settlements in Harbin Daoli District in three different periods as examples and obtains data on elderly people's walking trips and built environment characteristics through field research, questionnaire distribution, and internet data acquisition. Finally, correlation analysis and multinomial logistic regression model were applied to analyze the influence mechanism of built environment on elderly people's walkability based on the control of personal attribute variables in order to provide reference and guidance for the construction of walkability for elderly people in built environment in the future.

Keywords: built environment, elderly, walkability, multinomial logistic regression model

Procedia PDF Downloads 76