Search results for: factors influencing SOC estimation

Authors: V. Mathad, S. Shivprasad, P. Shivsharannappa, M. K. Patil

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Introduction: Non-communicable diseases are emerging diseases in India. Government of India launched National Programme for Prevention and Control of Cardiovascular Diseases, Cancer and Stroke (NPCDCS) during the year 2008. The aim of the programme was to reduce the burden of non communicable diseases by health promotion and prompt treatment. Objective: The present study was intended to assess the impact of National Program for prevention and control of Cardiovascular Diseases, Diabetes, Cancer and Stroke Programme on biochemical and physiological factors influencing Type 2 diabetes in Kalaburagi District. Material and Method: NCD Clinic was established at District Hospital during April 2016. All the patients attending District Hospital Kalaburagi above the age of 30 years are screened for Non Communicable Diseases under NPCDCS Programme. A total sample of 7447 patients attending NCD Clinic situated at Kalaburagi district was assessed in this study. Pre structured and pretested schedule seeking information was obtained from all the patients by the counselor working under NPCDCS programme. All the Patients attending District Hospital were screened for Diabetes using Glucometer at NCD clinic. The suspected cases were further confirmed through Biochemical investigations like Fasting Blood glucose, HBA1c, Urine Glucose, Kidney Function test. SPSS 20 version was used for analysis of data. Chi square test, P values and odds ratio was used to study the association of factors. Results: A Total of 7447 patients attended NCD clinic during the year 2017-18 were analyzed, Diabetes was seen among 3028 individuals were as comorbidities along with Hypertension was seen among 757 individuals. The mean age of the population was 50 ± 2.84. 3440(46.2%) were males whereas Female constituted 4007(53.8%) of population. The incidence and prevalence of Diabetes being 8.6 and 12.8 respectively. Diabetes was more commonly seen during the age group of 40 to 69 years. Diabetes was significantly associated with Age group 40 to 69 years, obesity and female gender (p < 0.05). The risk of developing Hypertension and comorbidity conditions of hypertension and Diabetes was 1.224 and 1.305 times higher among males, whereas the risk of diabetes was 1.127 higher among females as compared to males. Conclusion: The screening for NCD has significantly increased after launching of NPCDCS programme. NCD was significantly associated with obesity, female gender, increased age as well as comorbid conditions like hypertension and tuberculosis.

Keywords: non-communicable diseases, NPCDCS programme, type 2 Diabetes, physiological factors

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Authors: Elena Castillo-López, Raúl Pereda, Julio Manuel de Luis, Rubén Pérez, Felipe Piña

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Sediments are an important source of accumulation of toxic contaminants within the aquatic environment. Bioassays are a powerful tool for the study of sediments in relation to their toxicity, but they can be expensive. This article presents a methodology to estimate the main physical property of intertidal sediments in coastal zones: heavy metals concentration. This study, which was developed in the Bay of Santander (Spain), applies classical and robust statistic to CASI-2 hyperspectral images to estimate heavy metals presence and ecotoxicity (TOC). Simultaneous fieldwork (radiometric and chemical sampling) allowed an appropriate atmospheric correction to CASI-2 images.

Keywords: remote sensing, intertidal sediment, airborne sensors, heavy metals, eTOCoxicity, robust statistic, estimation

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Authors: Yasmine Ahmed Shemeis

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Determining the impact of productivity increases on wage levels is often difficult due to the unavailability of individual-level productivity data. Accordingly, we proxy for productivity using a self-perceived measure of health based on the postulated positive relationship between better health and productivity improvements. Using Egypt’s labour market data for the years 2012 and 2018 and utilizing a Maximum Likelihood Estimation method, we address two issues: the endogeneity of health in the estimation of wages and a sample selection bias. Our findings indicate the great value that better health has in enhancing wage levels in Egypt’s private sector. Also, we find that overlooking the endogeneity of health underestimates its effect on wages. Thus, the improvement of health states is likely to be beneficial in improving labour market outcomes in terms of wages as well as labour productivity in Egypt.

Keywords: labour, Productivity, Wages, Endogeneity, Sample Selection

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Authors: Tomiwa, Akinyemi Clement

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Tropical regions experience diverse and complex precipitation patterns, posing significant challenges for accurate rainfall estimation and forecasting. This study addresses the problem of effectively classifying tropical rain types and refining the Z-R (Reflectivity-Rain Rate) relationship to enhance rainfall estimation accuracy. Through a combination of remote sensing, meteorological analysis, and machine learning, the research aims to develop an advanced classification framework capable of distinguishing between different types of tropical rain based on their unique characteristics. This involves utilizing high-resolution satellite imagery, radar data, and atmospheric parameters to categorize precipitation events into distinct classes, providing a comprehensive understanding of tropical rain systems. Additionally, the study seeks to improve the Z-R relationship, a crucial aspect of rainfall estimation. One year of rainfall data was analyzed using a Micro Rain Radar (MRR) located at The Federal University of Technology Akure, Nigeria, measuring rainfall parameters from ground level to a height of 4.8 km with a vertical resolution of 0.16 km. Rain rates were classified into low (stratiform) and high (convective) based on various microstructural attributes such as rain rates, liquid water content, Drop Size Distribution (DSD), average fall speed of the drops, and radar reflectivity. By integrating diverse datasets and employing advanced statistical techniques, the study aims to enhance the precision of Z-R models, offering a more reliable means of estimating rainfall rates from radar reflectivity data. This refined Z-R relationship holds significant potential for improving our understanding of tropical rain systems and enhancing forecasting accuracy in regions prone to heavy precipitation.

Keywords: remote sensing, precipitation, drop size distribution, micro rain radar

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Authors: Medagedara Kaushalya Sewwandi Supun Gunarathne

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This research explores the underlying motivations and consequences of individuals changing their sexual orientation as a response to sexual violence. The primary objective of the study is to unravel the psychological, emotional, and social factors that drive individuals, akin to Celie in Alice Walker’s ‘The Color Purple’, to contemplate and undergo changes in their sexual orientation following the trauma of sexual violence. Through an analytical and qualitative approach, the study employs in-depth textual and thematic analyses to scrutinize the complex interplay between sexual orientation and violence within the selected text. Through a close examination of Celie’s journey and experiences, the study reveals that her decision to switch sexual orientation arises from a desire for a more favorable and benevolent relationship driven by the absence of safety and refuge in her previous relationships. By establishing this bond between sexual orientation and violence, the research underscores how sexual violence can lead individuals to opt for a change in their sexual orientation. The findings highlight Celie’s transformation as a means to seek solace and security, thus concluding that sexual violence can prompt individuals to alter their sexual orientation. The ensuing discussion explores the implications of these findings, encompassing psychological, emotional, and social consequences, as well as the societal and cultural factors influencing the perception of sexual orientation. Additionally, it sheds light on the challenges and stigma faced by those who undergo such transformations. By comprehending the complex relationship between sexual violence and the decision to change sexual orientation, as exemplified by Celie in ‘The Color Purple’, a deeper understanding of the experiences of survivors who seek a safe haven through altering their sexual orientation can be attained.

Keywords: sexual violence, sexual orientation, refuge, transition

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Authors: Sarah Ledoux

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This paper analyses the quantitative effects of political content consumption in social media platforms on self-reported ideological preference across the Latin American region. Initially praising the democratic potential of the internet and its social networking websites, digital politics scholars have transitioned their discourse to warning against the undemocratic side-effects it cultivates, such as hate speech, filter bubbles, and ideological polarisation. Holding technology solely responsible for political trends worldwide is an oversimplification of the factors influencing social change. Nonetheless, widespread use of social media in new democracies raises questions on the reproduction of recent trends that have been observed in the US and Western Europe. Through the analysis of ordered logistic regressions on data from the 2018 AmericasBarometer survey, this study examines the extent to which the relationship between the consumption of political content on social media is related to ideological polarisation in Latin America. The findings indicate that there is a close link between consumption of political information on social media, specifically on Facebook and WhatsApp, and ideological positioning on the extremes of the political left- and right-wings. This relation holds when controlling for individual-level demographic and attitudinal factors, as well as country-level effects. These results demonstrate with empirical evidence that viewing political content on social media has a significant positive effect on the likelihood that citizens position themselves on the extreme ends of the left-right ideological spectrum and implies that political polarisation is a phenomenon that accompanies politically driven social media use.

Keywords: Latin America, polarisation, political consumption, political ideology, social media, survey

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Authors: Julia Terlet, Thomas H. Beach, Yacine Rezgui

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Urbanization, population growth, climate change and the current increase in water demand have made the adoption of innovative demand management strategies crucial to the water industry. Water conservation in urban areas has to be improved by encouraging consumers to adopt more sustainable habits and behaviours. This includes informing and educating them about their households’ water consumption and advising them about ways to achieve significant savings on a daily basis. This paper presents a study conducted in the context of the European FP7 WISDOM Project. By integrating innovative Information and Communication Technologies (ICT) frameworks, this project aims at achieving a change in water savings. More specifically, behavioural change will be attempted by implementing smart meters and in-home displays in a trial group of selected households within Cardiff (UK). Using this device, consumers will be able to receive feedback and information about their consumption but will also have the opportunity to compare their consumption to the consumption of other consumers and similar households. Following an initial survey, it appeared necessary to implement these in-home displays in a way that matches consumer's motivations to save water. The results demonstrated the importance of various factors influencing people’s daily water consumption. Both the relevant literature on the subject and the results of our survey therefore led us to include within the in-home device a variety of elements. It first appeared crucial to make consumers aware of the economic aspect of water conservation and especially of the significant financial savings that can be achieved by reducing their household’s water consumption on the long term. Likewise, reminding participants of the impact of their consumption on the environment by making them more aware of water scarcity issues around the world will help increasing their motivation to save water. Additionally, peer pressure and social comparisons with neighbours and other consumers, accentuated by the use of online social networks such as Facebook or Twitter, will likely encourage consumers to reduce their consumption. Participants will also be able to compare their current consumption to their past consumption and to observe the consequences of their efforts to save water through diverse graphs and charts. Finally, including a virtual water game within the display will help the whole household, children and adults, to achieve significant reductions by providing them with simple tips and advice to save water on a daily basis. Moreover, by setting daily and weekly goals for them to reach, the game will expectantly generate cooperation between family members. Members of each household will indeed be encouraged to work together to reduce their water consumption within different rooms of the house, such as the bathroom, the kitchen, or the toilets. Overall, this study will allow us to understand the elements that attract consumers the most and the features that are most commonly used by the participants. In this way, we intend to determine the main factors influencing water consumption in order to identify the measures that will most encourage water conservation in both the long and short term.

Keywords: behavioural change, ICT technologies, water consumption, water conservation

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Authors: Chan Kwon Park, Chae-Bogk Kim, Sung-Min Park

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This study is a research on the authenticity of transactions between corporations and quality of their relationships and transaction performances. As the factors of authenticity of transactions, honesty, transparency, customer orientation and consistency were selected; as the factors of quality of relationships, trust and commitment were selected, and as the factors of transactions performances, intention of repeat transactions and switching intention were selected, and on these relationships a hypothesis was established, and verification was conducted. First, the factors of the authenticity of transactions positively influenced the factors of quality of relationships. Thus, a higher level of authenticity of transactions can lead to higher level of trust and commitment. Second, the factors of quality of relationships made a positive influence on the intention of repeat transactions, while a negative influence in the switching intention. Third, it showed that trust and commitment as the factors of quality of relationships functioned partly as the parameter between the authenticity of transactions and transaction performances. Finally, it proved that the factors of the authenticity of transactions improved trust and commitment in transactions between corporations and further improved the intention of repeat transactions while they decreased the switching intention.

Keywords: authenticity of transactions, trust, commitment, intention of repeat transactions, switching intention

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Authors: Seyed-Yaser Nabavi-Chashmi, Davood Asadi, Karim Ahmadi, Eren Demir

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The landing phase of a UAV is very critical as there are many uncertainties in this phase, which can easily entail a hard landing or even a crash. In this paper, the estimation of relative distance and velocity to the ground, as one of the most important processes during the landing phase, is studied. Using accurate measurement sensors as an alternative approach can be very expensive for sensors like LIDAR, or with a limited operational range, for sensors like ultrasonic sensors. Additionally, absolute positioning systems like GPS or IMU cannot provide distance to the ground independently. The focus of this paper is to determine whether we can measure the relative distance and velocity of UAV and ground in the landing phase using just low-resolution images taken by a monocular camera. The Lucas-Konda feature detection technique is employed to extract the most suitable feature in a series of images taken during the UAV landing. Two different approaches based on Extended Kalman Filters (EKF) have been proposed, and their performance in estimation of the relative distance and velocity are compared. The first approach uses the kinematics of the UAV as the process and the calculated optical flow as the measurement; On the other hand, the second approach uses the feature’s projection on the camera plane (pixel position) as the measurement while employing both the kinematics of the UAV and the dynamics of variation of projected point as the process to estimate both relative distance and relative velocity. To verify the results, a sequence of low-quality images taken by a camera that is moving on a specifically developed testbed has been used to compare the performance of the proposed algorithm. The case studies show that the quality of images results in considerable noise, which reduces the performance of the first approach. On the other hand, using the projected feature position is much less sensitive to the noise and estimates the distance and velocity with relatively high accuracy. This approach also can be used to predict the future projected feature position, which can drastically decrease the computational workload, as an important criterion for real-time applications.

Keywords: altitude estimation, drone, image processing, trajectory planning

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Authors: Alba Barbara-i-Molinero, Rosalia Cascon-Pereira, Ana Beatriz Hernandez

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Students’ transitions from high school to the university have been challenged by the lack of continuity between both contexts. This mismatch directly affects students by generating feelings of anxiety and uncertainty, which increases the dropout rates and reduces students’ academic success. This discontinuity emanates because ‘transitions concern a restructuring of what the person does and who the person perceives him or herself to be’. Hence, identity becomes essential in these transitions. Generally, identity is the answer to questions such as who am I? or who are we? This is integrated by personal identity, and as many social identities as groups, the individual feels he/she is a part. A case in point to construct a social identity is the identification with a profession. For this reason, a way to lighten the generated tension during transitions is applying strategies orientated to enhance students’ professional identity in their point of entry to the higher education institution. That would create a sense of continuity between high school and higher education contexts, increasing their Professional Identity Strength. To develop the strategies oriented to enhance students Professional Identity, it is important to analyze what influences it. There exist several influencing factors that influence Professional Identity (e.g., professional status, the recommendation of family and peers, the academic environment, or the chosen bachelor degree). There is a gap in the literature analyzing the impact of these factors on more than one bachelor degree. In this regards, our study takes an additional step with the aim of evaluating the influence of several factors on Professional Identity using a cohort of university students from multiple degrees between the ages of 17-19 years. To do so, we used hierarchical regression analyses to assess the impact of the following factors: External Motivation Conditionals (EMC), Educational Experience Conditionals (EEC) and Personal Motivational Conditional (PMP). After conducting the analyses, we found that the assessed factors influenced students’ professional identity differently according to their bachelor degree and discipline. For example, PMC and EMC positively affected science students, while architecture, law and economics and engineering students were just influenced by PMC. Basing on that influences, we proposed three different strategies aimed to enhance students’ professional identity, in the short and long term. These strategies are: to enhance students’ professional identity before the incorporation to university through campuses and icebreaker activities; to apply recruitment strategies aimed to provide realistic information of the bachelor degree; and to incorporate different activities, such as in-vitro, in situ and self-directed activities aimed to enhance longitudinally students’ professional identity from the university. From these results, theoretical contributions and practical implications arise. First, we contribute to the literature by identifying which factors influence students from different bachelor degrees since there is still no evidence. And, second, using as a benchmark the obtained results, we contribute from a practical perspective, by proposing several alternative strategies to increase students’ professional identity strength aiming to lighten their transition from high school to higher education.

Keywords: professional identity, higher education, educational strategies , students

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Authors: Angkawinijwong Sasiwan, Setthasakko Watchaneeporn

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This paper aims to gain an understanding of supporting factors and barriers to implementing eco-efficiency of automotive industry in Thailand. It employs in-depth interviews with key involved informants, including environmental managers, plant managers and environmental officers of six leading companies. It is found that board of directors, legislation and customers’ need are three main supporting factors in implementing eco-efficiency. Data collection and lack of awareness and knowledge about eco-efficiency are identified as barriers.

Keywords: eco-efficiency, supporting factors, barriers, automotive industry, Thailand

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Authors: Lilian A. Okeke, I. Okeke, N. Waziri, S. Balogun, P. Nguku, O. Fawole

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Background: Access to ante-natal care services promotes safe motherhood and delivery with improved maternal and neonatal outcome. We conducted this study to identify factors influencing the utilization of antenatal care (ANC) and health delivery services. Methods: We conducted a cross sectional study. Households were numbered and a one in three sample was selected using a systematic sampling method. One hundred and ninety eight women who were either pregnant or had previous deliveries were interviewed using pretested structured questionnaires to obtain information on their socio-demographic characteristics, and reasons for non-utilization of ANC and health delivery services. We performed univariate and bivariate analysis using Epi info version 3.5.3. Results: The age of respondents ranged from (17-55 years) with a median age of 29 years. One hundred and ninety two (97%) utilized antenatal care services. Ninety three (47.9%) attended ANC at second trimester. More than half (58.6%) had ≥ 4 visits to ANC. One hundred and thirty one (66.2%) had their last delivery at home by a traditional birth attendant. Factors associated with ANC and health facility delivery services utilization were: age group 45-55 (OR 0.01; 95% CI: 0.00-0.16) and > 55 years (OR 0.03; 95% CI: 0.00-0.60), wife’s educational status (OR 3.17; 95% CI: 1.66-8.30), husband’s permission (OR 11.8; 95% CI 2.19-63.62), and distance ≥ 5km (OR 0.33; 95% CI: 0.16-0.60). Conclusion: ANC services were well utilized. Most women did not book early and had their last delivery at home. Predictors of ANC use and health facility delivery were age, wife’s educational status, husband's permission and long distance from health facility. A one-day health sensitization of the benefits of ANC utilization and the dangers of delivering at home was implemented.

Keywords: ante natal care, health facility, delivery services, rural area, Plateau state

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Authors: Mostafa Aminzadeh, Min Deng

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Modeling loss data is an important part of actuarial science. Actuaries use models to predict future losses and manage financial risk, which can be beneficial for marketing purposes. In the insurance industry, small claims happen frequently while large claims are rare. Traditional distributions such as Normal, Exponential, and inverse-Gaussian are not suitable for describing insurance data, which often show skewness and fat tails. Several authors have studied classical and Bayesian inference for parameters of composite distributions, such as Exponential-Pareto, Weibull-Pareto, and Inverse Gamma-Pareto. These models separate small to moderate losses from large losses using a threshold parameter. This research introduces a computational approach using a nonlinear regression model for loss data that relies on multiple predictors. Simulation studies were conducted to assess the accuracy of the proposed estimation method. The simulations confirmed that the proposed method provides precise estimates for regression parameters. It's important to note that this approach can be applied to datasets if goodness-of-fit tests confirm that the composite distribution under study fits the data well. To demonstrate the computations, a real data set from the insurance industry is analyzed. A Mathematica code uses the Fisher information algorithm as an iteration method to obtain the maximum likelihood estimation (MLE) of regression parameters.

Keywords: maximum likelihood estimation, fisher scoring method, non-linear regression models, composite distributions

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Authors: Tiee-Jian Wu, Chih-Yuan Hsu

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Mode estimation is an important task, because it has applications to data from a wide variety of sources. We propose a semi-parametric approach to estimate the mode of an unknown continuous multivariate density function. Our approach is based on a weighted average of a parametric density estimate using the Box-Cox transform and a non-parametric kernel density estimate. Our semi-parametric mode estimate improves both the parametric- and non-parametric- mode estimates. Specifically, our mode estimate solves the non-consistency problem of parametric mode estimates (at large sample sizes) and reduces the variability of non-parametric mode estimates (at small sample sizes). The performance of our method at practical sample sizes is demonstrated by simulation examples and two real examples from the fields of climatology and image recognition.

Keywords: Box-Cox transform, density estimation, mode seeking, semiparametric method

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Authors: Nooralhuda Aljlas

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In the ever-growing field of non-governmental organizations, the enhancement of performance management and measurement systems has been increasingly acknowledged by political, economic, social, legal, technological and environmental factors. Within Bahrain Athletics Association, such enhancement results from the key factors leading performance management including collaboration, feedback, human resource management, leadership and participative management. The exploratory, qualitative research conducted reviewed performance management theory. As reviewed, the key factors leading performance management were identified. Drawing on a non-governmental organization case study, the key factors leading Bahrain Athletics Association’s performance management were explored. By exploring the key factors leading Bahrain Athletics Association’s performance management, the research study proposed a theoretical framework of the key factors leading performance management in non-governmental organizations in general. The research study recommended further investigation of the role of the two key factors of command and control and leadership, combining military and civilian approaches to enhancing non-governmental organizations’ performance management.

Keywords: Bahrain athletics association, exploratory, key factor, performance management

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Authors: Bisola Olumegbon

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Globally, there were about 229 million cases of malaria in 2022. The sub-Saharan African region accounted for 92% of the reported cases and 94% of deaths. Nigeria had the highest number of malaria cases and deaths, representing 27% of global cases. This scholarly project was a case study guided by the political determinants of health. Triangulation of data using thematic analysis was used to identify the political determinants of malaria in Nigeria and to understand how the concept of interaction contributes to the persistence of the disease. The analysis involved a deductive and inductive approach based on the literature review and the evidence of political determinants gathered in the data. Participants’ in-depth interviews were used to collect data from frontline personnel. Data triangulation was done using thematic analysis, a method used to identify patterns and themes in qualitative data. The study findings revealed a correlation between political determinants of health and malaria management efforts in Nigeria. Some influencing factors included voting challenges, inadequate funding, lack of health priority from the government, noncompliance among patients, and hurdles to effective communication. The findings suggest a need to deliberately increase dedication to the political agenda, provide sufficient financial resources, enhance communication, and active community involvement to address the persistent malaria endemic effectively. Further study is recommended to identify interventions to address identified factors of political determinants of health to reduce malaria in Nigeria. Such intervention must involve collaboration with diverse stakeholders such as policymakers, healthcare professionals, community leaders, and researchers.

Keywords: malaria, malaria management, health worker, stakeholders, political determinant of health

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Authors: Rong Yuan, Zhao Tao

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Only a handful of literature have used to non-linear model to investigate the influencing factors of greenhouse gas (GHG) emissions in China’s manufacturing sectors. And there is a limit in investigating quantitatively and systematically the mechanism of correlation between economic development and GHG emissions considering inherent differences among manufacturing sub-sectors. Considering the sectorial characteristics, the manufacturing sub-sectors with various impacts of output on GHG emissions may be explained by different development modes in each manufacturing sub-sector, such as investment scale, technology level and the level of international competition. In order to assess the environmental impact associated with any specific level of economic development and explore the factors that affect GHG emissions in China’s manufacturing industry during the process of economic growth, using the threshold Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model, this paper investigated the influence impacts of GHG emissions for China’s manufacturing sectors of different stages of economic development. A data set from 28 manufacturing sectors covering an 18-year period was used. Results demonstrate that output per capita and investment scale contribute to increasing GHG emissions while energy efficiency, R&D intensity and FDI mitigate GHG emissions. Results also verify the nonlinear effect of output per capita on emissions as: (1) the Environmental Kuznets Curve (EKC) hypothesis is supported when threshold point RMB 31.19 million is surpassed; (2) the driving strength of output per capita on GHG emissions becomes stronger as increasing investment scale; (3) the threshold exists for energy efficiency with the positive coefficient first and negative coefficient later; (4) the coefficient of output per capita on GHG emissions decreases as R&D intensity increases. (5) FDI shows a reduction in elasticity when the threshold is compassed.

Keywords: China, GHG emissions, manufacturing industry, threshold STIRPAT model

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Authors: Andrey V. Timofeev

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This paper introduces an original method for guaranteed estimation of the accuracy of an ensemble of Lipschitz classifiers. The solution was obtained as a finite closed set of alternative hypotheses, which contains an object of classification with a probability of not less than the specified value. Thus, the classification is represented by a set of hypothetical classes. In this case, the smaller the cardinality of the discrete set of hypothetical classes is, the higher is the classification accuracy. Experiments have shown that if the cardinality of the classifiers ensemble is increased then the cardinality of this set of hypothetical classes is reduced. The problem of the guaranteed estimation of the accuracy of an ensemble of Lipschitz classifiers is relevant in the multichannel classification of target events in C-OTDR monitoring systems. Results of suggested approach practical usage to accuracy control in C-OTDR monitoring systems are present.

Keywords: Lipschitz classifiers, confidence set, C-OTDR monitoring, classifiers accuracy, classifiers ensemble

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Authors: Yamini Raju, Parminder S. Kang, Adam Moroz, Ross Clement, Alistair Duffy, Ashley Hopwell

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Accurate prediction of fresh produce demand is one the challenges faced by Small Medium Enterprise (SME) wholesalers. Current research in this area focused on limited number of factors specific to a single product or a business type. This paper gives an overview of the current literature on the variability factors used to predict demand and the existing forecasting techniques of short shelf life products. It then extends it by adding new factors and investigating if there is a time lag and possibility of noise in the orders. It also identifies the most important factors using correlation and Principal Component Analysis (PCA).

Keywords: demand forecasting, deteriorating products, food wholesalers, principal component analysis, variability factors

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Authors: Qingqing Feng, S. Thomas Ng, Frank Xu

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Energy consumption in domestic sector has been increasing rapidly in China all along these years. Confronted with environmental challenges, the international society has made a concerted effort by setting the Paris Agreement, the Sustainable Development Goals, and the New Urban Agenda. Thus it’s very important for China to put forward reasonable countermeasures to boost building energy conservation which necessitates looking into the actuality of residential energy end-use profile and its influence factors. In this study, questionnaire surveys have been conducted in Zhuhai city in China, a typical city in hot summer warm winter climate zone. The data solicited mainly include the occupancy schedule, building’s information, residents’ information, household energy uses, the type, quantity and use patterns of appliances and occupants’ satisfaction. Over 200 valid samples have been collected through face-to-face interviews. Descriptive analysis, clustering analysis, correlation analysis and sensitivity analysis were then conducted on the dataset to understand the energy end-use profile. The findings identify: 1) several typical clusters of occupancy patterns and appliances utilization patterns; 2) the top three sensitive factors influencing energy consumption; 3) the correlations between satisfaction and energy consumption. For China with many different climates zones, it’s difficult to find a silver bullet on energy conservation. The aim of this paper is to provide a theoretical basis for multi-stakeholders including policy makers, residents, and academic communities to formulate reasonable energy saving blueprints for hot and humid urban residential buildings in China.

Keywords: residential building, energy end-use profile, questionnaire survey, sustainability

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Authors: Ren Moses, Emmanuel Kidando, Eren Ozguven, Yassir Abdelrazig

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This study applied traffic speed and occupancy to develop clustering models that identify different traffic conditions. Particularly, these models are based on the Dirichlet Process Mixture of Generalized Linear regression (DML) and change-point regression (CR). The model frameworks were implemented using 2015 historical traffic data aggregated at a 15-minute interval from an Interstate 295 freeway in Jacksonville, Florida. Using the deviance information criterion (DIC) to identify the appropriate number of mixture components, three traffic states were identified as free-flow, transitional, and congested condition. Results of the DML revealed that traffic occupancy is statistically significant in influencing the reduction of traffic speed in each of the identified states. Influence on the free-flow and the congested state was estimated to be higher than the transitional flow condition in both evening and morning peak periods. Estimation of the critical speed threshold using CR revealed that 47 mph and 48 mph are speed thresholds for congested and transitional traffic condition during the morning peak hours and evening peak hours, respectively. Free-flow speed thresholds for morning and evening peak hours were estimated at 64 mph and 66 mph, respectively. The proposed approaches will facilitate accurate detection and prediction of traffic congestion for developing effective countermeasures.

Keywords: traffic congestion, multistate speed distribution, traffic occupancy, Dirichlet process mixtures of generalized linear model, Bayesian change-point detection

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Authors: Siti Noor Baiti Binti Mustafa

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Energy management studies regarding energy efficiency investments in Malaysia has yet to address the lack of empirical research that examines pro- sustainability behavior of managers in the industrial sector and how it influences energy efficiency investment decision-making. This study adopts the Theory of Planned Behavior (TPB) to examine the relationship between personal attitude, subjective norms, and perceived behavioral control (PBC), the intention of energy efficiency investments, and how perceptions of Non-Energy Benefits (NEB) influence these intentions among managers in the industrial sector in Malaysia. Managers from various sub-sectors in the industrial sector were selected from a sample of companies that are participants of the Government-led program named the Energy Audit Conditional Grant (EACG) that aimed to promote energy efficiency. Data collection was conducted through an online semi-structured, open-ended questionnaire and then later interviewed. The results of this explorative sequential qualitative study showed that perceived behavioral control was a significant predictor of energy efficiency investment intentions as compared to factors such as attitude and subjective norms. The level of awareness and perceptions towards NEB further played a significant factor in influencing energy efficiency investment decision-making as well. Various measures and policy recommendations are provided together with insights on factors that influence decision-makers intention to invest in energy efficiency, whilst new knowledge on NEB perceptions will be useful to enhance the attractiveness of energy-efficient investments.

Keywords: energy efficiency investments, non-energy benefits, theory of planned behavior, personal attitude, subjective norms, perceived behavioral control, Malaysia industrial sector

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Authors: M. Taleb, G. Tail, F. Z. Kara, B. Djedouani T. Moussa

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Necrophagous insects usually colonize cadavers within a short time after death. However, they are influenced by weather conditions, and their distribution and activity vary according to different time scales, which can affect the post-mortem interval (PMI) estimation. As no data have been published in Algeria on necrophagous insects visiting corpses, two field surveys were conducted in July 2012 and March 2013 at the National Institute for Criminalistics and Criminology (INCC) using rabbit carcasses (Oryctolagus cuniculus L.). The trials were designed to identify the necrophagous Diptera fauna of Algiers, Algeria and examine their variations according to environmental variables. Four hundred and eighteen Diptera adults belonging to five families were captured during this study. The species which were identified on human corpses in different regions of Algeria were also observed on the rabbit carcasses. Although seasonal variations of the species were observed, their abundance did not significantly vary between the two seasons. In addition to seasonal effects, the ambient temperature, the wind speed, and precipitation affect the number of trapped flies. These conclusions highlight the necessity of considering the environmental factors at a scene to estimate the post-mortem interval accurately. It is hoped that these findings provide basic information regarding the necrophagous Diptera fauna of Algeria.

Keywords: forensic entomology, necrophagous diptera, post-mortem interval, abiotic factors, Algeria

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Authors: Suzana Ramli, Wardah Tahir

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Estimation of surface runoff depth is a vital part in any rainfall-runoff modeling. It leads to stream flow calculation and later predicts flood occurrences. GIS (Geographic Information System) is an advanced and opposite tool used in simulating hydrological model due to its realistic application on topography. The paper discusses on calculation of surface runoff depth for two selected events by using GIS with Curve Number method for Upper Klang River basin. GIS enables maps intersection between soil type and land use that later produces curve number map. The results show good correlation between simulated and observed values with more than 0.7 of R2. Acceptable performance of statistical measurements namely mean error, absolute mean error, RMSE, and bias are also deduced in the paper.

Keywords: surface runoff, geographic information system, curve number method, environment

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Authors: Jennifer Duffy, Liz Fleming

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Teacher shortage in special education is an American educational problem. Due to the implementation of The No Child Left Behind Act (2001) and The Individuals with Disabilities Education Improvement Act (2004), there has been an increase in the number of students requiring special education services. Consequently, there has been an influx to hire more special education teachers. However, the historic challenge of hiring certified special education teachers has been intensified with this the profession’s increasing demand of positions to fill. Efforts to improve recruitment and entry into the field must be informed by an understanding of the factors that initially inspire special education teachers to choose this career pathway. Hence, an understanding of reasons why teachers select special education as a profession is needed. The purpose of this study was to explore personal, academic, and professional motivations that lead to the selection of special education as a career choice. Using the grounded theory approach, this research investigation examined the factors that were most instrumental in influencing applicants to select special education as a career choice. Over one hundred de-identified graduate school applications to Bay Path University’s Graduate Special Education Programs from 2014- 2017 were qualitatively analyzed. Grounded coding was used to discover themes that emerged in applicants’ admissions essays explaining why he/she was pursuing a career in special education. The central themes that were most influential in applicants’ selection of special education as a career trajectory were (a) personal/familial connections to disability, (b) meaningful paraprofessional experiences working with disabled children, (c) aptitudes for teaching, and (d) finding personal rewards and professional fulfillment by advocating for vulnerable children. Implications from these findings include educating family members of children with disabilities about possible career tracks in special education, designing programs for paraprofessionals to become certified teachers, exposing prospective teacher candidates to the field of special education, and recruiting professionals from the human services field who seek to improve the quality of life and educational opportunities for children with special needs.

Keywords: career choice, professional pathways to teaching children with disabilities, special education, teacher recruitment

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Authors: Mohammad Sadegh Narges, Zahra Ghadampour

Abstract:

Due to the specific condition, offshore pipelines are given careful consideration and care in both design and operation. Most of the offshore pipeline flows are multi-phase. Multi-phase flows construct different pattern or flow regimes (in simultaneous gas-liquid flow, flow regimes like slug flow, wave and …) under different circumstances. One of the influencing factors on the flow regime is the pipeline roughness value. So far, roughness value influences and the sensitivity of the present models to this parameter have not been taken into consideration. Therefore, roughness value influences on the flow regimes in offshore pipelines are discussed in this paper. Results showed that geometry, absolute pipeline roughness value (materials that the pipeline is made of) and flow phases prevailing the system are of the influential parameters on the flow regimes prevailing multi-phase pipelines in a way that a change in any of these parameters results in a change in flow regimes in all or part of the pipeline system.

Keywords: absolute roughness, flow regime, multi-phase flow, offshore pipelines

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Authors: Chad Brown

Abstract:

This paper establishes general conditions for the convergence rates of nonparametric sieve estimators with dependent data. We present two key results: one for nonstationary data and another for stationary mixing data. Previous theoretical results often lack practical applicability to deep neural networks (DNNs). Using these conditions, we derive convergence rates for DNN sieve estimators in nonparametric regression settings with both nonstationary and stationary mixing data. The DNN architectures considered adhere to current industry standards, featuring fully connected feedforward networks with rectified linear unit activation functions, unbounded weights, and a width and depth that grows with sample size.

Keywords: sieve extremum estimates, nonparametric estimation, deep learning, neural networks, rectified linear unit, nonstationary processes

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Authors: Divyanshi Singh

Abstract:

Women’s right to have choices, sense of self-worth and their right to have access to opportunities have been a subject of serious concern. The health of women and their children in Indian society is adversely affected by the woman’s inferior status within households. The level of human development in society is a reflection of the better status of a woman, which has a clear impact on the usage of contraceptive methods and maternal health. The study is an attempt to assess the performance of Indian states on the parameters of levels of development and to see how the developmental trajectory is influencing the choice for contraception and maternal health. The objective of the paper is to study the relationship between usage of contraception, maternal health and levels of human development in Indian states. Data from NFHS-4th round, AHS (2012-13) and census 2011 is used. Three indicators of human development (effective literacy, infant mortality and gross district domestic product) have been taken. Maternal health for the study has been measured in MMR, IMR and pregnancy resulted in abortions, stillbirths and miscarriage. The multiple regression analysis has been done to analyze the relationship between them. The Developmental factor is found to be greatly influencing the choice of family planning and thus they both show strong relation with maternal health.

Keywords: human development, contraceptive usage, maternal health, effective literacy

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Authors: Rosida A. Razak, Mohamad Shanudin Zakaria

Abstract:

The fundamental issues in ICT Governance (ICTG) implementation for Malaysian Public Sector (MPS) is how ICT be applied to support improvements in productivity, management effectiveness and the quality of services offered to its citizens. Our main concern is to develop and adopt a common definition and framework to illustrate how ICTG can be used to better align ICT with government’s operations and strategic focus. In particular, we want to identify and categorize factors that drive a successful ICTG process. This paper presents the results of an exploratory study to identify, validate and refine such Critical Success Factors (CSFs) and confirmed seven CSFs and nineteen sub-factors as influential factors that fit MPS after further validated and refined. The Delphi method applied in validation and refining process before being endorsed as appropriate for MPS. The identified CSFs reflect the focus areas that need to be considered strategically to strengthen ICT Governance implementation and ensure business success.

Keywords: IT governance, critical success factors, productivity, CSFs

Procedia PDF Downloads 271

Authors: Jiahao Tian, Michael D. Porter

Abstract:

Law enforcement agencies are tasked with crime prevention and crime reduction under limited resources. Having an accurate temporal estimate of the crime rate would be valuable to achieve such a goal. However, estimation is usually complicated by the interval-censored nature of crime data. We cast the problem of intensity estimation as a Poisson regression using an EM algorithm to estimate the parameters. Two special penalties are added that provide smoothness over the time of day and day of the week. This approach presented here provides accurate intensity estimates and can also uncover day-of-week clusters that share the same intensity patterns. Anticipating where and when crimes might occur is a key element to successful policing strategies. However, this task is complicated by the presence of interval-censored data. The censored data refers to the type of data that the event time is only known to lie within an interval instead of being observed exactly. This type of data is prevailing in the field of criminology because of the absence of victims for certain types of crime. Despite its importance, the research in temporal analysis of crime has lagged behind the spatial component. Inspired by the success of solving crime-related problems with a statistical approach, we propose a statistical model for the temporal intensity estimation of crime with censored data. The model is built on Poisson regression and has special penalty terms added to the likelihood. An EM algorithm was derived to obtain maximum likelihood estimates, and the resulting model shows superior performance to the competing model. Our research is in line with the smart policing initiative (SPI) proposed by the Bureau Justice of Assistance (BJA) as an effort to support law enforcement agencies in building evidence-based, data-driven law enforcement tactics. The goal is to identify strategic approaches that are effective in crime prevention and reduction. In our case, we allow agencies to deploy their resources for a relatively short period of time to achieve the maximum level of crime reduction. By analyzing a particular area within cities where data are available, our proposed approach could not only provide an accurate estimate of intensities for the time unit considered but a time-variation crime incidence pattern. Both will be helpful in the allocation of limited resources by either improving the existing patrol plan with the understanding of the discovery of the day of week cluster or supporting extra resources available.

Keywords: cluster detection, EM algorithm, interval censoring, intensity estimation

Procedia PDF Downloads 63