Search results for: factors influencing SOC estimation

Authors: Sun fang, Zhang Wenxin

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This paper establishes an evaluation index system for spatio-temporal patterns of urbanization, with the county as research unit. We use the Entropy Weight method, coefficient variance, the Theil index and ESDA-GIS to analyze spatial patterns and evolutionary characteristics of New-Type Urbanization in the Central Plains Economic Region (CPER) between 2000 and 2011. Results show that economic benefit, non-agricultural employment level and level of market development are the most important factors influencing the level of New-Type Urbanization in the CPER; overall regional differences in New-Type Urbanization have declined while spatial correlations have increased from 2000 to 2011. The overall spatial pattern has changed little, however; differences between the western and eastern areas of the CPER are clear, and the pattern of a strong west and weak east did not change significantly over the study period. Areas with high levels of New-Type Urbanization were mostly distributed along the Beijing-Guangzhou and LongHai Railways on both sides, a new influx of urbanization was tightly clustered around ZhengZhou in the Central Henan Urban Agglomeration, but this trend was found to be weakening slightly. The level of New-Type Urbanization in municipal districts was found to be much higher than it was in the county generally. Provincial borders experienced a lower rate of growth and a lower level of New-Type Urbanization than did any other areas, consistently forming clusters of cold spots and sub-cold spots. The analysis confirms that historical development, location, and diffusion effects of urban agglomeration are the main drivers of changes in New-Type Urbanization patterns in CPER.

Keywords: new-type urbanization, spatial pattern, central plains economic region, spatial evolution

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Authors: Jalila Jbilou, Salaheddine El Adlouni, Pierre Gosselin

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Background: West Nile virus is increasingly an important public health issue in North America. In Canada, WVN was officially reported in Toronto and Montréal for the first time in 2001. During the last decade, several WNV events have been reported in several Canadian provinces. The main objective of the present study is to update the frequency of the climate conditions favorable to WNV outbreaks in Canada. Method: Statistical frequency analysis has been used to estimate the return period for climate conditions associated with WNV outbreaks for the 1961–2050 period. The best fit is selected through the Akaike Information Criterion, and the parameters are estimated using the maximum likelihood approach. Results: Results show that the climate conditions related to the 2002 event, for Montreal and Toronto, are becoming more frequent. For Saskatoon, the highest DD20 events recorded for the last few decades were observed in 2003 and 2007. The estimated return periods are 30 years and 70 years, respectively. Conclusion: The emergence of WNV was related to extremely high DD values in the summer. However, some exceptions may be related to several factors such as virus persistence, vector migration, and also improved diagnosis and reporting levels. It is clear that such climate conditions have become much more common in the last decade and will likely continue to do so over future decades.

Keywords: West Nile virus, climate, North America, statistical frequency analysis, risk estimation, public health, modeling, scenario, temperature, precipitation

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Authors: Lizinis Cassendra Frederick Dony, Dewi Binti Tajuddin, Jirom Jeremy Frederick Dony, Andrew Nicholas

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Unemployed graduates have become among the world major concerns lately. 70% of Malaysian graduates are jobless. Due to this concerns, this paper aims to identify major factors influencing Sabah minority ethnic favorable in the entrepreneurialism business interest. Hence, extensive introductory entrepreneurship syllabus clusters development beginning from the early childhood, primary, secondary and university students. This may induce interest appeal and to develop focus group of self-employment. The study focus on 7 indicators consist of demographic profiles variable (DP), social norms (SN), attitude (A), self-efficacy (SE) and business management skills (BMS) with reference to university students’ entrepreneurial intention. This study also partially mediates the relationship between product attractiveness (PA) and the minority ethnic entrepreneurialism business interest (MEEBI), by testifying their direct and indirect relationships. Hence, this study provides new perception towards improving the graduates’ characteristic, capabilities to exploit the business opportunities in the market. Furthermore, this paper will assess the relationship with the product attractiveness(PA) as a mediator. The study encompasses on the type of Sabah minority ethnic (ME) and nature of family own business (FOB) background with the 280 samples students in UiTM Sabah and UMS. The descriptive and random sampling method of research which revealed that majority of the respondents agreed that FOB and entrepreneurship education had positively influenced the ethnic students’ involvement in the entrepreneurial process and career development either full-time or part-time basis.

Keywords: Demographic profile (DP), soci, unemployed graduates, Malaysian minority

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Authors: A. Asambe

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A study was conducted to determine the level of compliance with sanitary measures in piggeries, and awareness and risk factors of African swine fever in Benue State, Nigeria. Questionnaires were distributed to 74 respondents consisting of piggery owners and attendants in different piggeries across 12 LGAs to collect data for this study. Sanitary measures in piggeries were observed to be generally very poor, though respondents admitted being aware of ASF. Piggeries located within a 1 km radius of a slaughter slab (OR=9.2, 95% CI - 3.0-28.8), piggeries near refuse dump sites (OR=3.0, 95% CI - 1.0-9.5) and piggeries where farm workers wear their work clothes outside of the piggery premises (OR=0.2, 95% CI - 0.1-0.7) showed higher chances of ASFV infection and were significantly associated (p < 0.0001), (p < 0.05) and (p < 0.01), and were identified as potential risk factors. The study concluded that pigs in Benue State are still at risk of an ASF outbreak. Proper sanitary and hygienic practices is advocated and emphasized in piggeries, while routine surveillance for ASFV antibodies in pigs in Benue State is strongly recommended to provide a reliable reference data base to plan for the prevention of any devastating ASF outbreak.

Keywords: African swine fever, awareness, piggery, risk factors, sanitary measures

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Authors: Thananyada Buapian

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Overnutrition is emerging as a morbid disease in developing and Westernized countries. Because of its comorbidity diseases, it is cost-effective to prevent and manage this disease earlier. In Thailand, this alarming disease has long been studied, but the prevalence is still higher than that in the past. Physicians should recognize it well and have a definite direction to face and combat this dangerous disease. Rapid changes in the tremendous figure of overnutrition students indicate that genetic factors are not the primary determinants since human genes have remained unchanged for a century. This study aims to assess the prevalence of overnutrition students and to investigate the non-genetic factors affecting over nutrition students. A cross-sectional school-based survey was conducted. A two-stage sampling was adopted. Respondents included 1,850 students in grades 4 to 6 in Ayutthaya Province. An anthropometric measurement and questionnaire were developed. Childhood over nutrition was defined as a weight-for-height Z-score above +2SD of NCHS/WHO references. About thirty three percent of the children were over nutrition in Ayutthaya province. Stepwise multiple logistic regression analysis showed that 8 statistically significant non genetic factors explain the variation of childhood over nutrition by 18 percent. Sex is the prime factor to explain the variation of childhood over nutrition, followed by duration of light physical activities, duration of moderate physical activities, having been breastfed, the presence of a healthy role model of the caregiver, number of siblings, birth order, and occupation of the caregiver, respectively. Non genetic factors, especially the subjects’ demographic and physical activities, as well as the caregivers’ background and family environment, should be considered in viable approach to remedy this health imbalance in children.

Keywords: non genetic factors, non-genetic, over nutrition, over nutrition students

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

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The soil erosion by water has become one of the biggest problems of the environment in the world, threatening the majority of countries. There are several models to evaluate erosion. These models are still a simplified representation of reality. They permit the analysis of complex systems, measurements are complementary to allow an extrapolation in time and space and may combine different factors. The empirical model of soil loss proposed by Wischmeier and Smith (Universal Soil Loss Equation), is widely used in many countries. He considers that erosion is a multiplicative function of five factors: rainfall erosivity (the R factor) the soil erodibility factor (K), topography (LS), the erosion control practices (P) and vegetation cover and agricultural practices (C). In this work, we tried to develop a tool based on Web GIS functionality to evaluate soil losses caused by erosion taking into account five factors. This tool allows the user to integrate all the data needed for the evaluation (DEM, Land use, rainfall ...) in the form of digital layers to calculate the five factors taken into account in the USLE equation (R, K, C, P, LS). Accordingly, and after treatment of the integrated data set, a map of the soil losses will be achieved as a result. We tested the proposed tool on a watershed basin located in the weste of Algeria where a dataset was collected and prepared.

Keywords: USLE, erosion, web gis, Algeria

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Authors: Yanto Santosa, Rozza Tri Kwatrina

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High Conservation Value (HCV) is an area with conservation function within oil palm plantation. Despite the important role of HCV area in biodiversity conservation and various studies on HCV, there was a lack of research studying the factors determining its success. A preliminary study was conducted to identify the determinant factor of HCV that affected the diversity. Line transect method was used to calculate the species diversity of butterfly, birds, mammals, and herpetofauna species as well as their richness. Specifically for mammals, camera traps were also used. The research sites comprised of 12 HCV areas in 3 provinces of Indonesia (Central Kalimantan, Riau, and Palembang). The relationship between the HCV biophysical factor with the species number and species diversity for each wildlife class was identified using Chi-Square analysis with Cross tab (contingency table). Results of the study revealed that species diversity varied by research locations. Four factors determining the success of HCV area in relations to the number and diversity of wildlife species are land cover types for mammals, the width of area and distance to rivers for birds, and distance to settlements for butterflies.

Keywords: wildlife diversity, oil palm plantation, high conservation value area, ecological factors

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Authors: Shin-Hyung Cho, Dong-Kyu Kim, Seung-Young Kho

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Truck-involved crashes have higher crash severity than non-truck-involved crashes. There have been many studies about the frequency of crashes and the development of severity models, but those studies only analyzed the relationship between observed variables. To identify why more people are injured or killed when trucks are involved in the crash, we must examine to quantify the complex causal relationship between severity of the crash and risk factors by adopting the latent factors of crashes. The aim of this study was to develop a structural equation or model based on truck-involved and non-truck-involved crashes, including five latent variables, i.e. a crash factor, environmental factor, road factor, driver’s factor, and severity factor. To clarify the unique characteristics of truck-involved crashes compared to non-truck-involved crashes, a confirmatory analysis method was used. To develop the model, we extracted crash data from 10,083 crashes on Korean freeways from 2008 through 2014. The results showed that the most significant variable affecting the severity of a crash is the crash factor, which can be expressed by the location, cause, and type of the crash. For non-truck-involved crashes, the crash and environment factors increase severity of the crash; conversely, the road and driver factors tend to reduce severity of the crash. For truck-involved crashes, the driver factor has a significant effect on severity of the crash although its effect is slightly less than the crash factor. The multiple group analysis employed to analyze the differences between the heterogeneous groups of drivers.

Keywords: crash severity, structural structural equation modeling (SEM), truck-involved crashes, multiple group analysis, crash on freeway

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Authors: Turki Adnan Kamal, Abdulmajeed Ahmad Alsofiany, Nemer Khidhran Husain Alghamdi, Ali Eissa Hassan Al-Rajhi

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Background:- Health care workers are ranked as one of the most vulnerable groups experiencing violence and aggressive behavior compared to other occupational groups. Objectives:- To estimate the prevalence rate and characteristics and assess the avoidance measures, and notification of the violence among medical staff working in primary health care centers in Taif city. Subject and methods:- A cross-sectional study design was applied among all physicians and a representative sample of nurses working in primary health care centers affiliated with the Ministry of Health (MOH) in Taif city. A predesigned Arabic/English validated self-administered questionnaire was used. Results:- In this study, 56 physicians and 145 nurses responded, giving a response rate of 77.6%. Their age ranged from 25 and 60 years (36.2±8.2), with 59.7% of them aged between 25 and 35 years. Males represent 55.7% of them. More than half of them (52.2%) were Saudis. The prevalence of workplace violence was 30.3%. Verbal abuse was the commonest reported type (86.9%). The absence of security, training on the procedures that must be followed and special uniforms at the workplace were significantly associated with workplace violence. We concluded that workplace violence is a significant problem facing a considerable proportion of HCWs in primary health care centers in Taif, Saudi Arabia. Most violence incidents were verbal. Conclusion:- Findings of this study revealed that HCWs who were dealing with male patients only were at high risk of workplace violence and the absence of measures to avoid workplace violence, particularly security, training on the procedures that must be followed and special uniform at the workplace was significantly associated with workplace violence.

Keywords: violence, workplace, primary health care, prevalence, avoidance

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Authors: Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran

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Dengue outbreaks are affected by biological, ecological, socio-economic and demographic factors that vary over time and space. These factors have been examined separately and still require systematic clarification. The present study aimed to investigate the spatial-temporal clustering relationships between these factors and dengue outbreaks in the northern region of Sri Lanka. Remote sensing (RS) data gathered from a plurality of satellites were used to develop an index comprising rainfall, humidity and temperature data. RS data gathered by ALOS/AVNIR-2 were used to detect urbanization, and a digital land cover map was used to extract land cover information. Other data on relevant factors and dengue outbreaks were collected through institutions and extant databases. The analyzed RS data and databases were integrated into geographic information systems, enabling temporal analysis, spatial statistical analysis and space-time clustering analysis. Our present results showed that increases in the number of the combination of ecological factor and socio-economic and demographic factors with above the average or the presence contribute to significantly high rates of space-time dengue clusters.

Keywords: ALOS/AVNIR-2, dengue, space-time clustering analysis, Sri Lanka

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Authors: Hilda Kundai Chikwanda, Lawrence Thabo Mokhadi

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The study aimed to review the factors that lead the freight railway suppliers base in South Africa (SA) to apply the Lean and Six Sigma (L&SS) methodologies. A thorough review of the factors that lead organisations, in the different industries, to implement these methodologies was done. L&SS applications were found to be prominent in the automotive industry. In particular, the railway industry in SA and the region were reviewed in terms of challenges in capturing the freight logistics market and growing market share. Qualitative methods have been used to collect primary data and descriptive statistics was used to calculate, describe, and summarize collected research data. The results show that external factors have a greater influence on the implementation of L&SS. The study drew inferences between freight railway supplier base and the application of Lean and Six Sigma (L&SS) methodologies in the SA context. It identified challenges that leads the SA freight railway to lose market share to road freight users. It further observes and recommends that L&SS methodologies are the ideal strategy required to implement a turnaround in the trajectory of freight railways as a competitive freight transport solution.

Keywords: production, methodology, manufacturing, lean, six sigma

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Authors: Paramet Damchoo

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The purpose of this study is to study the factors that influence the decision making of foreign volunteer tourists in Thailand. A sample size was 400 drawn from 10 provinces of Thailand using cluster sampling method. The factor analysis was used to analysis the data. The findings indicate that volunteer tourism which was based in Thailand contained a total of 45 activities which could be divided into 4 categories. The most of these tourists were from Europe including UK and Scandinavia which was 54.50 percent. Moreover, the tourists were male rather than female and 63.50 Percent of them ware younger than 20 years old. It is also found that there are 67.00 percent of the tourists used website to find where the volunteer tourism was based. Finally, the factors that influence the decision making of foreign volunteer tourists in Thailand consist of a wide variety of activities together with a flexibility in their activities and also low prices.

Keywords: decision making, volunteer tourism, special interest tourism, GAP year

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Authors: Abdullah Abdulsalam, Adamu Balami, Olajide Olubanji Olowe, Maryam Abdu Abdulkadir

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The development and persistence of low back pain may be influenced by several factors which include lifestyle factors, previous pain symptoms, psychological factors, workplace factors as well as socio-demographic variables. The focus of this study was to determine the socio-demographic and work related variables as a predictor of persistence of back pain and disability among civil servants receiving physiotherapy in tertiary health institutions in Kano, Nigeria. One hundred and twenty nine newly referred low back pain patients for physiotherapy participated in the study. This study was a cross sectional study involving patients that were newly diagnosed of back pain, referred and received physiotherapy. The convenience sampling technique was used to select the patients based on the inclusion criteria. The data obtained was analysed using simple percentage and multiple regression for stated hypothesis at 0.05 level of significance. The findings reveal that all the variables are not significant predictor of persistence of back pain and disability. The study recommended that determinants of low back pain recovery by clinician should include other clinical factors not only reduction in pain intensity.

Keywords: socio-demographic, work related variables, Kano state, back pain and disability

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Authors: Halefom Kidane

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This study aims to assess the wind resource potential and characterize the urban area wind patterns in Hawassa City, Ethiopia. The estimation and characterization of wind resources are crucial for sustainable urban planning, renewable energy development, and climate change mitigation strategies. A secondary data collection method was used to carry out the study. The collected data at 2 meters was analyzed statistically and extrapolated to the standard heights of 10-meter and 30-meter heights using the power law equation. The standard deviation method was used to calculate the value of scale and shape factors. From the analysis presented, the maximum and minimum mean daily wind speed at 2 meters in 2016 was 1.33 m/s and 0.05 m/s in 2017, 1.67 m/s and 0.14 m/s in 2018, 1.61m and 0.07 m/s, respectively. The maximum monthly average wind speed of Hawassa City in 2016 at 2 meters was noticed in the month of December, which is around 0.78 m/s, while in 2017, the maximum wind speed was recorded in the month of January with a wind speed magnitude of 0.80 m/s and in 2018 June was maximum speed which is 0.76 m/s. On the other hand, October was the month with the minimum mean wind speed in all years, with a value of 0.47 m/s in 2016,0.47 in 2017 and 0.34 in 2018. The annual mean wind speed was 0.61 m/s in 2016,0.64, m/s in 2017 and 0.57 m/s in 2018 at a height of 2 meters. From extrapolation, the annual mean wind speeds for the years 2016,2017 and 2018 at 10 heights were 1.17 m/s,1.22 m/s, and 1.11 m/s, and at the height of 30 meters, were 3.34m/s,3.78 m/s, and 3.01 m/s respectively/Thus, the site consists mainly primarily classes-I of wind speed even at the extrapolated heights.

Keywords: artificial neural networks, forecasting, min-max normalization, wind speed

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Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha

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Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and time-consuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.

Keywords: soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil, geotechnical engineering

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Authors: Rocio Herrero Romero, Lucie Cluver, James Hall, Janina Steinert

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Educational delay and non-completion are major policy concerns in South Africa. However, little research has focused on predictors for educational delay amongst adolescents in disadvantaged areas. This study has two aims: first, to use data integration approaches to compare the educational delay of 599 adolescents aged 16 to 18 from disadvantaged communities to national and provincial representative estimates in South Africa. Second, the paper also explores predictors for educational delay by comparing adolescents out of school (n=64) and at least one year behind (n=380), with adolescents in the age-appropriate grade or higher (n=155). Multinomial logistic regression models using self-report and administrative data were applied to look for significant associations of risk and protective factors. Significant risk factors for being behind (rather than in age-appropriate grade) were: male gender, past grade repetition, rural location and larger school size. Risk factors for being out of school (rather than in the age-appropriate grade) were: past grade repetition, having experienced problems concentrating at school, household poverty, and food insecurity. Significant protective factors for being in the age-appropriate grade (rather than out of school) were: living with biological parents or grandparents and access to school counselling. Attending school in wealthier communities was a significant protective factor for being in the age-appropriate grade (rather than behind). Our results suggest that both personal and contextual factors –family and school- predicted educational delay. This study provides new evidence to the significant effects of personal, family, and school characteristics on the educational outcomes of adolescents from disadvantaged communities in South Africa. This is the first longitudinal and quantitative study to systematically investigate risk and protective factors for post-compulsory educational outcomes amongst South African adolescents living in disadvantaged communities.

Keywords: disadvantaged communities, quantitative analysis, school delay, South Africa

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Authors: Michael Smalenberger

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Intelligent tutoring systems (ITS) are computer-based platforms which can incorporate artificial intelligence to provide step-by-step guidance as students practice problem-solving skills. ITS can replicate and even exceed some benefits of one-on-one tutoring, foster transactivity in collaborative environments, and lead to substantial learning gains when used to supplement the instruction of a teacher or when used as the sole method of instruction. A common facet of many ITS is their use of Bayesian Knowledge Tracing (BKT) to estimate parameters necessary for the implementation of the artificial intelligence component, and for the probability of mastery of a knowledge component relevant to the ITS. While various techniques exist to estimate these parameters and probability of mastery, none directly and reliably ask the user to self-assess these. In this study, 111 undergraduate students used an ITS in a college-level introductory statistics course for which detailed transaction-level observations were recorded, and users were also routinely asked direct questions that would lead to such a self-assessment. Comparisons were made between these self-assessed values and those obtained using commonly used estimation techniques. Our findings show that such self-assessments are particularly relevant at the early stages of ITS usage while transaction level data are scant. Once a user’s transaction level data become available after sufficient ITS usage, these can replace the self-assessments in order to eliminate the identifiability problem in BKT. We discuss how these findings are relevant to the number of exercises necessary to lead to mastery of a knowledge component, the associated implications on learning curves, and its relevance to instruction time.

Keywords: Bayesian Knowledge Tracing, Intelligent Tutoring System, in vivo study, parameter estimation

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Authors: Fernando Doral

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Family businesses are a key phenomenon within the business landscape. Nevertheless, it involves two terms (“family” and “business”) which are nowadays rapidly evolving. Consequently, it isn't easy to diagnose if a family business will be a growing or decreasing phenomenon, which is the objective of this study. For that purpose, a sample of 50 Spanish-established companies from various sectors was taken. Different factors were identified for each enterprise, related to the profile of the founders, such as age, the number of sons and daughters, or support received from the family at the moment to start it up. That information was taken as an input for a clustering method to identify groups, which could help define the founders' profiles. That characterization was carried as a base to identify three factors whose evolution should be analyzed: family structures, business landscape and entrepreneurs' motivations. The analysis of the evolution of these three factors seems to indicate a negative tendency of family businesses. Therefore the consequent diagnosis of this study is to consider family businesses as a declining phenomenon.

Keywords: business diagnose, business trends, family business, family business founders

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Authors: Yuanyuan Fu

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Background and Purpose: Along with the change of society and economy, the traditional home function of old people has gradually weakened in the contemporary China. Acknowledging these situations, to better meet old people’s needs on formal services and improve the quality of later life, this study seeks to identify patterns of intended service use among frail old people living in the communities and examined determinants that explain heterogeneous variations in old people’s intended service use patterns. Additionally, this study also tested the relationship between culture value and intended service use patterns and the mediating role of enabling factors in terms of culture value and intended service use patterns. Methods：Participants were recruited from Haidian District, Beijing, China in 2015. The multi-stage sampling method was adopted to select sub-districts, communities and old people aged 70 years old or older. After screening, 577 old people with limitations in daily life, were successfully interviewed. After data cleaning, 550 samples were included for data analysis. This study establishes a conceptual framework based on the Anderson Model (including predisposing factors, enabling factors and need factors), and further developed it by adding culture value factors (including attitudes towards filial piety and attitudes towards social face). Using a latent class analysis (LCA), this study classifies overall patterns of old people’s formal service utilization. Fourteen types of formal services were taken into account, including housework, voluntary support, transportation, home-delivered meals, and home-delivery medical care, elderly’s canteen and day-care center/respite care and so on. Structural equation modeling (SEM) was used to examine the direct effect of culture value on service use pattern, and the mediating effect of the enabling factors. Results: The LCA classified a hierarchical structure of service use patterns: multiple intended service use (N=69, 23%), selective intended service use (N=129, 23%), and light intended service use (N=352, 64%). Through SEM, after controlling predisposing factors and need factors, the results showed the significant direct effect of culture value on older people’s intended service use patterns. Enabling factors had a partial mediation effect on the relationship between culture value and the patterns. Conclusions and Implications: Differentiation of formal services may be important for meeting frail old people’s service needs and distributing program resources by identifying target populations for intervention, which may make reference to specific interventions to better support frail old people. Additionally, culture value had a unique direct effect on the intended service use patterns of frail old people in China, enriching our theoretical understanding of sources of culture value and their impacts. The findings also highlighted the mediation effects of enabling factors on the relationship between culture value factors and intended service use patterns. This study suggests that researchers and service providers should pay more attention to the important role of culture value factors in contributing to intended service use patterns and also be more sensitive to the mediating effect of enabling factors when discussing the relationship between culture value and the patterns.

Keywords: frail old people, intended service use pattern, culture value, enabling factors, contemporary China, latent class analysis

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Authors: Shraddha Palikhe, Sunkuk Kim

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The construction industry is the most labor intensive in Nepal. It is obvious that construction is a major sector and any productivity enhancement activity in this sector will have a positive impact in the overall improvement of the national economy. Previous studies have stated that Nepal has poor labor productivity among other south Asian countries. Though considerable research has been done on productivity factors in other countries, no study has addressed labor productivity issues in Nepal. Therefore, the main objective of this study is to identify and hierarchy the influence factors for poor labor productivity. In this study, a questionnaire approach is chosen as a method of the survey from thirty experts involved in the construction industry, such as Architects, Civil Engineers, Project Engineers and Site Engineers. A survey was conducted in Nepal, to identify the major factors impacting construction labor productivity. Analytic Hierarchy Process (AHP) analysis method was used to understand the underlying relationships among the factors, categorized into five groups, namely (1) Labor-management group; (2) Material management group; (3) Human labor group; (4) Technological group and (5) External group and was divided into 33 subfactors. AHP was used to establish the relative importance of the criteria. The AHP makes pairwise comparisons of relative importance between hierarchy elements grouped by labor productivity decision criteria. Respondents were asked to answer based on their experience of construction works. On the basis of the respondent’s response, weight of all the factors were calculated and ranked it. The AHP results were tabulated based on weight and ranking of influence factors. AHP model consists of five main criteria and 33 sub-criteria. Among five main criteria, the scenario assigns a weight of highest influential factor i.e. 26.15% to human labor group followed by 23.01% to technological group, 22.97% to labor management group, 17.61% material management group and 10.25% to external group. While in 33 sub-criteria, the most influential factor for poor productivity in Nepal are lack of monetary incentive (20.53%) for human labor group, unsafe working condition (17.55%) for technological group, lack of leadership (18.43%) for labor management group, unavailability of tools at site (25.03%) for material management group and strikes (35.01%) for external group. The results show that AHP model associated criteria are helpful to predict the current situation of labor productivity. It is essential to consider these influence factors to improve the labor productivity in the construction industry of Nepal.

Keywords: construction, hierarchical analysis, influence factors, labor productivity

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Authors: Madara Apsalone

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Knowledge management and innovation is key to competitive advantage and sustainable business development in advanced economies. Small and medium-sized enterprises (SMEs) have lower capacity and more constrained resources for long-term and high-uncertainty research and development investments. At the same time, SMEs can implement organizational innovation to improve their performance and further foster other types of innovation. The purpose of this study is to analyze, how socio-cultural factors such as shared values, organizational behaviors, work organization and decision making processes can influence knowledge management and help to develop organizational innovation via an empirical study. Surveying 600 SMEs in Latvia, the author explores the contribution of different socio-cultural factors to organizational innovation and the role of knowledge management and organizational learning in this process. A conceptual model, explaining the impact of organizational team, development, result-orientation and structure is created. The study also proposes insights that contribute to theoretical and practical discussions on fostering innovation of small businesses in small economies.

Keywords: knowledge management, organizational innovation, small and medium-sized enterprises, socio-cultural factors

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Authors: Dedah Ahmed Babou, Nicolas Bez

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The Min-Max autocorrelation factor (MAF) approach makes it possible to express in a space formed by spatially independent factors, spatiotemporal observations. These factors are ordered in decreasing order of spatial autocorrelation. The starting observations are thus expressed in the space formed by these factors according to temporal coordinates. Each vector of temporal coefficients expresses the temporal evolution of the weight of the corresponding factor. Applying this approach has enabled us to achieve the following results: (i) Define a spatially orthogonal space in which the projections of the raw data are determined; (ii) Define a limit threshold for the factors with the strongest structures in order to analyze the weight, and the temporal evolution of these different structures (iii) Study the correlation between the temporal evolution of the persistent spatial structures and that of the observed average abundance (iv) Propose prototypes of campaigns reflecting a high vs. low abundance (v) Propose a classification of campaigns that highlights seasonal and/or temporal similarities. These results were obtained by analyzing the octopus yield during the scientific campaigns of the oceanographic vessel Al Awam during the period 1989-2017 in the Mauritanian exclusive economic zone.

Keywords: spatiotemporal , autocorrelation, kriging, variogram, Octopus vulgaris

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Authors: Park, Yoon Hong, Wang, Jung Kab, Choi Seong-Won, Kim, Hong Kyu

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Itaewon-Ro is a special place where the Seoul Metropolitan city designated as the fist are of tourism, specially with the commercial supremacy that foreigners may like. It is the place that grew with regional specialty. Study on the vitalization factors of commercialist were analyzed on consumer shop choice factor, Physical environment based on commercial supremacy vitalization, Functional side of the road and regional specialty. However, since Itaewon seemed to take great place in the cultural factor, Because of its regional specialty, Research was processed. This study is the analysis on the vitalization of Itaewon commercialist that looked for important factors with AHP analysis on consumers use as commercialist. Based on the field study and preceded study, top three factors were distinguished with physical factor, cultural factor, landscape factor, and thirteen detail contents were found. This study focused on the choice of the consumer and with a consumer-based questionnaire, we analyzed the importance of vitalization factors. Results of the research are shown in the following paragraphs. In the Itaewon commercial market, mostly women in the 20~30s were the main consumers for meeting and hopping. Vitalization category that the consumer thinks it most importantly was 'attraction', 'various businesses', and 'convenience of transportation'. 'Attraction that cannot be seen in other places', Which was chosen as the most important factor was judged that Itaewon holds cultural identity that is shown in the process of development, Instead of showing artificial and physical composition.

Keywords: commercialist, vitalization factor, regional specialty, cultural factor, AHP analysis

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Authors: H. Vargova, J. Strecka, N. Tomasovicova

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A rigorous analytical treatment, with the help of a concept of negativity, is used to study the quantum and thermal entanglement in an isotropic mixed spin-(1/2,S) Heisenberg dimer. The effect of the spin-S magnitude, as well as the effect of diversity between Landé g-factors of magnetic constituents on system entanglement, is exhaustively analyzed upon the variation of the external magnetic and electric field, respectively. It was identified that the increasing magnitude of the spin-S species in a mixed spin-(1/2,S) Heisenberg dimer with comparative Landé g-factors have always a reduction effect on a degree of the quantum entanglement, but it strikingly shifts the thermal entanglement to the higher temperatures. Surprisingly, out of the limit of identical Landé g-factors, the increasing magnitude of spin-S entities can enhance the system entanglement in both low and high magnetic fields. Besides this, we identify that the analyzed dimer with a high-enough magnitude of the spin-S entities at a sufficiently high magnetic field can exhibit unconventional thermally driven re-entrance between the entangled and unentangled mixed state. The importance of the electric-field stimuli is also discussed in detail.

Keywords: quantum and thermal entantanglement, mixed spin Heisenberg model, negativity, reentrant phase transition

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Authors: Imali T. Jayamanne, K. P. Asoka Ramanayake

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Transition from tertiary level education to employment is one of the challenges that many fresh university graduates face after graduation. The transition period or the waiting time to obtain the first employment varies with the socio-economic factors and the general characteristics of a graduate. Compared to other fields of study, Arts graduates in Sri Lanka, have to wait a long time to find their first employment. The objective of this study is to identify the determinants of the transition from higher education to employment of these graduates using survival models. The study is based on a survey that was conducted in the year 2016 on a stratified random sample of Arts graduates from Sri Lankan universities who had graduated in 2012. Among the 469 responses, 36 (8%) waiting times were interval censored and 13 (3%) were right censored. Waiting time for the first employment varied between zero to 51 months. Initially, the log-rank and the Gehan-Wilcoxon tests were performed to identify the significant factors. Gender, ethnicity, GCE Advanced level English grade, civil status, university, class received, degree type, sector of first employment, type of first employment and the educational qualifications required for the first employment were significant at 10%. The Cox proportional hazards model was fitted to model the waiting time for first employment with these significant factors. All factors, except ethnicity and type of employment were significant at 5%. However, since the proportional hazard assumption was violated, the lognormal Accelerated failure time (AFT) model was fitted to model the waiting time for the first employment. The same factors were significant in the AFT model as in Cox proportional model.

Keywords: AFT model, first employment, proportional hazard, survey design, waiting time

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Authors: Mohammad Rahim Rahnama, Lia Shaddel

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Today, along with the development of urbanism, its negative consequences on the health of citizens are emerging. Mental disorders are common in the big cities, while mental health enables individuals to become active citizens. Meanwhile, women have a larger share of mental problems. Depression and anxiety disorders have a higher prevalence rate among women and these disorders affect the health of future generations, too. Therefore, improving women’s mental health through the potentials offered by urban spaces are of paramount importance. The present study aims to first, evaluate the spatial autocorrelation of women’s mental health and walkable spaces and then present solutions, based on the findings, to improve the walkability index. To determine the spatial distribution of women’s mental health in Mashhad, Moran's I was used and 1000 questionnaire were handed out in various sub-districts of Mashhad. Moran's I was calculated to be 0.18 which indicates a cluster distribution pattern. The walkability index was calculated using the four variables pertaining to the length of walkable routes, mixed land use, retail floor area ratio, and household density. To determine spatial autocorrelation of mental health and the walkability index, bivariate Moran’s I was calculated. Moran's I was determined to be 0.37 which shows a direct spatial relationship between variables; 4 clusters in 9 sub-districts of Mashhad were created. In High-Low cluster, there was a negative spatial relationship and hence, to identify factors affecting walkability in urban spaces semi-structures interviews were conducted with 21 women in this cluster. The findings revealed that security is the major factor influencing women’s walking behavior in this cluster. In accordance with the findings, some suggestions are offered to improve the presence of women in this sub-district.

Keywords: Mashhad, spatial autocorrelation, women’s mental health, walkability index

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Authors: Fabiana Franceschi, Martha Cobo, Manuel Figueredo

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Bogotá, the capital of Colombia, is its largest city and one of the most polluted in Latin America due to the fast economic growth over the last ten years. Bogotá has been affected by high pollution events which led to the high concentration of PM10 and NO2, exceeding the local 24-hour legal limits (100 and 150 g/m3 each). The most important pollutants in the city are PM10 and PM2.5 (which are associated with respiratory and cardiovascular problems) and it is known that their concentrations in the atmosphere depend on the local meteorological factors. Therefore, it is necessary to establish a relationship between the meteorological variables and the concentrations of the atmospheric pollutants such as PM10, PM2.5, CO, SO2, NO2 and O3. This study aims to determine the interrelations between meteorological variables and air pollutants in Bogotá, using data mining techniques. Data from 13 monitoring stations were collected from the Bogotá Air Quality Monitoring Network within the period 2010-2015. The Principal Component Analysis (PCA) algorithm was applied to obtain primary relations between all the parameters, and afterwards, the K-means clustering technique was implemented to corroborate those relations found previously and to find patterns in the data. PCA was also used on a per shift basis (morning, afternoon, night and early morning) to validate possible variation of the previous trends and a per year basis to verify that the identified trends have remained throughout the study time. Results demonstrated that wind speed, wind direction, temperature, and NO2 are the most influencing factors on PM10 concentrations. Furthermore, it was confirmed that high humidity episodes increased PM2,5 levels. It was also found that there are direct proportional relationships between O3 levels and wind speed and radiation, while there is an inverse relationship between O3 levels and humidity. Concentrations of SO2 increases with the presence of PM10 and decreases with the wind speed and wind direction. They proved as well that there is a decreasing trend of pollutant concentrations over the last five years. Also, in rainy periods (March-June and September-December) some trends regarding precipitations were stronger. Results obtained with K-means demonstrated that it was possible to find patterns on the data, and they also showed similar conditions and data distribution among Carvajal, Tunal and Puente Aranda stations, and also between Parque Simon Bolivar and las Ferias. It was verified that the aforementioned trends prevailed during the study period by applying the same technique per year. It was concluded that PCA algorithm is useful to establish preliminary relationships among variables, and K-means clustering to find patterns in the data and understanding its distribution. The discovery of patterns in the data allows using these clusters as an input to an Artificial Neural Network prediction model.

Keywords: air pollution, air quality modelling, data mining, particulate matter

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

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Authors: H. Afsari, H. Shokouhmand

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When stack is placed in a thermoacoustic resonator in a cryocooler, one extremity of the stack heats up while the other cools down due to the thermoacoustic effect. In the present, with expression a formula by linear theory, will see this temperature difference depends on what factors. The computed temperature difference is compared to the one predicted by the formula. These discrepancies can not be attributed to non-linear effects, rather they exist because of thermal effects. Two correction factors are introduced for close up results among linear theory and computed and use these correction factors to modified linear theory. In fact, this formula, is optimized by GA (Genetic Algorithm). Finally, results are shown at different Mach numbers and stack location in resonator.

Keywords: heat transfer, thermoacoustic cryocooler, stack, resonator, mach number, genetic algorithm

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Authors: Naritphol Boonyakiat

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This research attempts to investigate the effects of corporate social responsibility and knowledge management factors on students’ learning process of the Silpakorn University. The goal of this study is to fill the literature gap by gaining an understanding of corporate social responsibility and the knowledge management factors that fundamentally relate to students’ learning process within the university context. Thus, this study will focus on the outcomes that derive from a set of quantitative data that were obtained using Silpakorn university’s database of 200 students. The results represent the perceptions of students regarding the impact of corporate social responsibility and knowledge management factors on their learning process within the university. The findings indicate that corporate social responsibility and knowledge management have significant effects on students’ learning process. This study may assist us in gaining a better understanding of the integrated aspects of university and learning environments to discover how to allocate optimally university’s resources and management approaches to gain benefits from corporate social responsibility and knowledge management practices toward students’ learning process within the university bodies. Therefore, there is a sufficient reason to believe that the findings can contribute to research in the area of CSR, KM and students’ learning process as an essential aspect of university’s stakeholder.

Keywords: corporate social responsibility, knowledge management, learning process, university’s students

Procedia PDF Downloads 311