Search results for: significant factors

Authors: Ishaq Kashif, Muhammad Younas, Muhammad Riaz, Mubarak Ali

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Poor feeding management during pre-weaning period is one of the factors resulting in compromised growth of Beetal kids fattened for meat purpose. The main reason for this anomaly may be less milk offered to kids and non-serious efforts for its management. This study was planned to find the most appropriate protein level suiting the age of the weaning while shifting animals to high input feeding system. Total of 42 Beetal male kids having 30 (±10), 60 (±10) and 90 (±10) days of age were selected with 16 in each age group. They were designated as G30, G60 and G90, respectively. The weights of animals were; 8±2 kg (G30), 12±2 kg (G60) and 16±2 kg (G90), respectively. All animals were weaned by introducing the total mix feed gradually and withdrawing the milk during the adjustment period of two weeks. The pelleted starter ration (total mix feed) with three various dietary protein levels designated as R1 (16% CP), R2 (20% CP) and R3 (26% CP) were introduced. The control group was reared on the fodder (Maize). The starter rations were iso-caloric and were offered for six-week duration. All animals were exposed to treatment using two-factor factorial (3×3) plus control treatment arrangement under completely randomized design. The data were collected on average daily feed intake (ADFI), average daily gain (ADG), gain to intake ratio, Klieber ratio (KR), body measurements and blood metabolites of kids. The data was analyzed using aov function of R-software. The statistical analysis showed that starter feed protein levels and age of weaning had significant interaction for ADG (P < 0.001), KR (P < 0.001), ADFI (P < 0.05) and blood urea nitrogen (P < 0.05) while serum creatinine and feed conversion had non-significant interaction. The trend analysis revealed that ADG had significant quadratic interaction (P < 0.05) within protein levels and age of weaning. It was found that animals weaned at 30 or 60 days, on R2 diet had better ADG (46.8 gm/day and 87.06 gm/day, respectively) weaned at 60 days of age. The animals weaned at 90 days had best ADG (127 gm/day) with R1. It is concluded that animal weaned at 30 or 40 days required 20% CP for better growth performance while animal at 90 days showed better performance with 16% CP.

Keywords: average daily gain, starter protein levels, weaning age, gain to intake ratio

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Authors: Reza Gheisari, Paulo J. Bartolo, Nicholas Goddard

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Polymeric micro-cantilevers (Cs) are rapidly becoming popular for MEMS applications such as chemo- and bio-sensing as well as purely electromechanical applications such as microrelays. Polymer materials present suitable physical and chemical properties combined with low-cost mass production. Hence, micro-cantilevers made of polymers indicate much more biocompatibility and adaptability of rapid prototyping along with mechanical properties. This research studies the effects of three process and one size factors on the filling behaviour in micro cavity, and the role of each in the replication of micro parts using different polymer materials i.e. polypropylene (PP) SABIC 56M10 and acrylonitrile butadiene styrene (ABS) Magnum 8434. In particular, the following factors are considered: barrel temperature, mould temperature, injection speed and the thickness of micro features. The study revealed that the barrel temperature and the injection speed are the key factors affecting the flow length of micro features replicated in PP and ABS. For both materials, an increase of feature sizes improves the melt flow. However, the melt fill of micro features does not increase linearly with the increase of their thickness.

Keywords: flow length, micro cantilevers, micro injection moulding, microfabrication

Procedia PDF Downloads 378

Authors: Suppara Charoenpoom

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The purposes of this research were to investigate the level of consumers’ awareness of the traditional community retailers in terms of location, service quality, risk, shopping enjoyment, value for money, shopping satisfaction and intention to repurchase as well as to investigate the factors influenced the consumers’ repurchase in Samut Sonkhram Province, Thailand. The findings revealed that consumers had a high level of awareness in terms of location, and intention to repurchase. The factors influenced the consumers’ level of satisfaction included value for money, shopping enjoyment, and service quality. The factors of consumers’ level of satisfaction had an influence to the intention to repurchase. Moreover, the findings also revealed that the majority of respondents wanted traditional community retailers to continue to operate because of these reasons: close location, convenience, credit, as well as provide a place and time for community social gathering and activities.

Keywords: quality management, service quality, traditional retailer, consumers’ awareness

Procedia PDF Downloads 369

Authors: Georgiana Onicescu, Yuqian Shen

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Due to the complex nature of geo-referenced data, multicollinearity of the risk factors in public health spatial studies is a commonly encountered issue, which leads to low parameter estimation accuracy because it inflates the variance in the regression analysis. To address this issue, we proposed a two-stage variable selection method by extending the least absolute shrinkage and selection operator (Lasso) to the Bayesian spatial setting, investigating the impact of risk factors to health outcomes. Specifically, in stage I, we performed the variable selection using Bayesian Lasso and several other variable selection approaches. Then, in stage II, we performed the model selection with only the selected variables from stage I and compared again the methods. To evaluate the performance of the two-stage variable selection methods, we conducted a simulation study with different distributions for the risk factors, using geo-referenced count data as the outcome and Michigan as the research region. We considered the cases when all candidate risk factors are independently normally distributed, or follow a multivariate normal distribution with different correlation levels. Two other Bayesian variable selection methods, Binary indicator, and the combination of Binary indicator and Lasso were considered and compared as alternative methods. The simulation results indicated that the proposed two-stage Bayesian Lasso variable selection method has the best performance for both independent and dependent cases considered. When compared with the one-stage approach, and the other two alternative methods, the two-stage Bayesian Lasso approach provides the highest estimation accuracy in all scenarios considered.

Keywords: Lasso, Bayesian analysis, spatial analysis, variable selection

Procedia PDF Downloads 123

Authors: C. Fernandez-Plaza, I. Abad, E. Diaz, I. Diaz

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Births occurring before the 37th week of gestation are considered preterm births. A threat of preterm is defined as the beginning of regular uterine contractions, dilation and cervical effacement between 23 and 36 gestation weeks. To author's best knowledge, the factors that determine the beginning of the birth are not completely defined yet. In particular, the incidence of sleep habits on preterm births is weekly studied. The aim of this study is to develop a model to predict the factors affecting premature delivery on pregnancy, based on the above potential risk factors, including those derived from sleep habits and light exposure at night (introduced as 12 variables obtained by a telephone survey using two questionnaires previously used by other authors). Thus, three groups of variables were included in the study (maternal, fetal and sleep habits). The study was approved by Research Ethics Committee of the Principado of Asturias (Spain). An observational, retrospective and descriptive study was performed with 481 births between January 1, 2015 and May 10, 2016 in the University Central Hospital of Asturias (Spain). A statistical analysis using SPSS was carried out to compare qualitative and quantitative variables between preterm and term delivery. Chi-square test qualitative variable and t-test for quantitative variables were applied. Statistically significant differences (p < 0.05) between preterm vs. term births were found for primiparity, multi-parity, kind of conception, place of residence or premature rupture of membranes and interruption during nights. In addition to the statistical analysis, machine learning methods to look for a prediction model were tested. In particular, tree based models were applied as the trade-off between performance and interpretability is especially suitable for this study. C5.0, recursive partitioning, random forest and tree bag models were analysed using caret R-package. Cross validation with 10-folds and parameter tuning to optimize the methods were applied. In addition, different noise reduction methods were applied to the initial data using NoiseFiltersR package. The best performance was obtained by C5.0 method with Accuracy 0.91, Sensitivity 0.93, Specificity 0.89 and Precision 0.91. Some well known preterm birth factors were identified: Cervix Dilation, maternal BMI, Premature rupture of membranes or nuchal translucency analysis in the first trimester. The model also identifies other new factors related to sleep habits such as light through window, bedtime on working days, usage of electronic devices before sleeping from Mondays to Fridays or change of sleeping habits reflected in the number of hours, in the depth of sleep or in the lighting of the room. IF dilation < = 2.95 AND usage of electronic devices before sleeping from Mondays to Friday = YES and change of sleeping habits = YES, then preterm is one of the predicting rules obtained by C5.0. In this work a model for predicting preterm births is developed. It is based on machine learning together with noise reduction techniques. The method maximizing the performance is the one selected. This model shows the influence of variables related to sleep habits in preterm prediction.

Keywords: machine learning, noise reduction, preterm birth, sleep habit

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Authors: Sareh Rajabi, Taha Anjamrooz, Ahmed Hassan Almarzooqi

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Employee satisfaction, engagement, and performance are crucial for successful organizations. The performance of the employees now depends on their satisfaction level and whether they are satisfied with the management. Due to this fact, the organizations are now measuring the satisfaction level of their employees to increase profitability, productivity, and turnover. The aim of this research is to inspect the antecedents which direct in the direction of significant employee engagement and good job fit by finding the relationship between employee satisfaction and engagement. Based on an inclusive literature review on the employees’ satisfaction, engagement and performance, this research will conduct a study and survey in the UAE organizations in order to develop a framework for evaluating the impact of factors like employee satisfaction and engagement on the operation as an outcome by using statistical analysis. This study will allow in understanding the advantages of containing satisfied employees and how they perform in their peak motivation to make the company more profitable and competitive.

Keywords: employees’ satisfaction, employees’ engagement, antecedents, outcomes

Procedia PDF Downloads 138

Authors: Mijoh A. Gbededo, Kapila Liyanage, Ilias Oraifige

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Decision making for sustainable manufacturing design and management requires critical considerations due to the complexity and partly conflicting issues of economic, social and environmental factors. Although there are tools capable of assessing the combination of one or two of the sustainability factors, the frameworks have not adequately integrated all the three factors. Case study and review of existing simulation applications also shows the approach lacks integration of the sustainability factors. In this paper we discussed the development of a simulation based framework for support of a holistic assessment of sustainable manufacturing design and management. To achieve this, a strategic approach is introduced to investigate the strengths and weaknesses of the existing decision supporting tools. Investigation reveals that Discrete Event Simulation (DES) can serve as a rock base for other Life Cycle Analysis frameworks. Simio-DES application optimizes systems for both economic and competitive advantage, Granta CES EduPack and SimaPro collate data for Material Flow Analysis and environmental Life Cycle Assessment, while social and stakeholders’ analysis is supported by Analytical Hierarchy Process, a Multi-Criteria Decision Analysis method. Such a common and integrated framework creates a platform for companies to build a computer simulation model of a real system and assess the impact of alternative solutions before implementing a chosen solution.

Keywords: discrete event simulation, life cycle sustainability analysis, manufacturing, sustainability

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Authors: V. M. Mmbengwa, J. R. M. Mabuso, C. P. Du Plooy, S. Laurrie, H. D. van Schalkwyk

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Sweet potato products are necessary for the provision of essential nutrients in every household, regardless of their poverty status. Their consumption appears to be highly influenced by socio-economic factors, such as malnutrition, food insecurity and unemployment. Therefore, market availability is crucial for these cultivars to resolve some of the socio-economic factors. The aim of the study was to investigate market availability of sweet potato cultivars in the North West Province. In this study, both qualitative and quantitative research methodologies were used. Qualitative methodology was used to explain the quantitative outcomes of the variables. On the other hand, quantitative results were used to test the hypothesis. The study used SPSS software to analyse the data. Cross-tabulation and Chi-square statistics were used to obtain the descriptive and inferential analyses, respectively. The study found that the Blesbok cultivar is dominating the markets of the North West Province, with the Monate cultivar dominating in the Bojanala Platinum (75 %) and Dr Ruth Segomotsi Mompati (25 %) districts. It is also found that a unit increase in the supply of sweet potato cultivars in both local and district municipal markets is accompanied by a reduced demand of 28 % and 33 % at district and local markets, respectively. All these results were found to be significant at p<0.05. The results further revealed that in four out of nine local municipality markets, the Blesbok cultivar seems to be solely available in those four local municipal markets of North West Province. It can be concluded that Blesbok, relative to other cultivars, is the most commercialised sweet potato variety and that consumers across this Province are highly aware of it. For other cultivars to assume market prominence in this Province, a well-designed marketing campaign for creating awareness may be required. This campaign may be based on nutritional advantages of different cultivars, of which Blesbok is relatively inferior, compared to orange-fleshed sweet potato varieties.

Keywords: cultivar, malnutrition, markets, sweet potato

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Authors: Ibrahim Mahamid, A. Al-Ghonamy, M. Aichouni

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This study is conducted to identify causes of cost deviations in public construction projects in Saudi Arabia from contractors’ perspective. 41 factors that might affect cost estimating accuracy were identified through literature review and discussion with some construction experts. The factors were tabulated in a questionnaire form and a field survey included 51 contractors from the Northern Province of Saudi Arabia was performed. The results show that the top five important causes are: wrong estimation method, long period between design and time of implementation, cost of labor, cost of machinary and absence of construction-cost data.

Keywords: cost deviation, public construction, cost estimating, Saudi Arabia, contractors

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Authors: Huang Hao, Li Weiwen

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Global biodiversity continues to decline as a result of global climate change and various human activities, such as habitat destruction, pollution, introduction of alien species and overfishing. Although there are connections between global marine organisms more or less, it is better to have clear geographical boundaries in order to facilitate the assessment and management of different biogeographical zones. And so area based management tools (ABMT) are considered as the most effective means for the conservation and sustainable use of marine biodiversity. On a large scale, the geographical gap (or barrier) is the main factor to influence the connectivity, diffusion, ecological and evolutionary process of marine organisms, which results in different distribution patterns. On a small scale, these factors include geographical location, geology, and geomorphology, water depth, current, temperature, salinity, etc. Therefore, the analysis on geographic and environmental factors is of great significance in the study of biodiversity characteristics. This paper summarizes the marine spatial classification and ABMTs used in coastal area, open oceans and deep sea. And analysis principles and methods of marine spatial classification based on biogeographic related factors, and take China Near Sea (CNS) area as case study, and select key biogeographic related factors, carry out marine spatial classification at biological region scale, ecological regionals scale and biogeographical scale. The research shows that CNS is divided into 5 biological regions by climate and geographical differences, the Yellow Sea, the Bohai Sea, the East China Sea, the Taiwan Straits, and the South China Sea. And the bioregions are then divided into 12 ecological regions according to the typical ecological and administrative factors, and finally the eco-regions are divided into 98 biogeographical units according to the benthic substrate types, depth, coastal types, water temperature, and salinity, given the integrity of biological and ecological process, the area of the biogeographical units is not less than 1,000 km². This research is of great use to the coastal management and biodiversity conservation for local and central government, and provide important scientific support for future spatial planning and management of coastal waters and sustainable use of marine biodiversity.

Keywords: spatial classification, marine biodiversity, bio-geographical, conservation

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Authors: Kamaludeen Samaila, Khashyaullah Abdulfattah, Fahimi Ahmad Bin Amir

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The study was conducted to examine the relationship between selected factors (performance expectancy, effort expectancy, social influence and facilitating condition) and students’ intention to use the learning management system (LMS), as well as investigating the factors predicting students’ intention to use the LMS. The study was specifically conducted at the Faculty of Educational Study of University Putra Malaysia. Questionnaires were distributed to 277 respondents using a random sampling technique. SPSS Version 22 was employed in analyzing the data; the findings of this study indicated that performance expectancy (r = .69, p < .01), effort expectancy (r=.60, p < .01), social influence (r = .61, p < .01), and facilitating condition (r=.42, p < .01), were significantly related to students’ intention to use the LMS. In addition, the result also revealed that performance expectancy (β = .436, p < .05), social influence (β=.232, p < .05), and effort expectancy (β = .193, p < .05) were strong predictors of students’ intention to use the LMS. The analysis further indicated that (R2) is 0.054 which means that 54% of variation in the dependent variable is explained by the entire predictor variables entered into the regression model. Understanding the factors that affect students’ intention to use the LMS could help the lecturers, LMS managers and university management to develop the policies that may attract students to use the LMS.

Keywords: LMS, postgraduate students, PutraBlas, students’ intention, UPM, UTAUT model

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Authors: Anna M. Pretorius

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The emerging markets category for portfolio investment was introduced in 1986 in an attempt to promote capital market development in less developed countries. Investors traditionally diversified their portfolios by investing in different developed markets. However, high growth opportunities forced investors to consider emerging markets as well. Examples include the rapid growth of the “Asian Tigers” during the 1980s, growth in Latin America during the 1990s and the increased interest in emerging markets during the global financial crisis. As such, portfolio flows to emerging markets have increased substantially. In 2002 7% of all equity allocations from advanced economies went to emerging markets; this increased to 20% in 2012. The stronger links between advanced and emerging markets led to increased synchronization of asset price movements. This increased level of stock market integration for emerging markets is confirmed by various empirical studies. Against the background of increased interest in emerging market assets and the increasing level of integration of emerging markets, this paper focuses on the determinants of stock market integration of emerging market countries. Various studies have linked the level of financial market integration with specific economic variables. These variables include: economic growth, local inflation, trade openness, local investment, budget surplus/ deficit, market capitalization, domestic bank credit, domestic institutional and legal environment and world interest rates. The aim of this study is to empirically investigate to what extent trade-related determinants have an impact on stock market integration. The panel data sample include data of 16 emerging market countries: Brazil, Chile, China, Colombia, Czech Republic, Hungary, India, Malaysia, Pakistan, Peru, Philippines, Poland, Russian Federation, South Africa, Thailand and Turkey for the period 1998-2011. The integration variable for each emerging stock market is calculated as the explanatory power of a multi-factor model. These factors are extracted from a large panel of global stock market returns. Trade related explanatory variables include: exports as percentage of GDP, imports as percentage of GDP and total trade as percentage of GDP. Other macroeconomic indicators – such as market capitalisation, the size of the budget deficit and the effectiveness of the regulation of the securities exchange – are included in the regressions as control variables. An initial analysis on a sample of developed stock markets could not identify any significant determinants of stock market integration. Thus the macroeconomic variables identified in the literature are much more significant in explaining stock market integration of emerging markets than stock market integration of developed markets. The three trade variables are all statistically significant at a 5% level. The market capitalisation variable is also significant while the regulation variable is only marginally significant. The global financial crisis has highlighted the urgency to better understand the link between the financial and real sectors of the economy. This paper comes to the important finding that, apart from the level of market capitalisation (as financial indicator), trade (representative of the real economy) is a significant determinant of stock market integration of countries not yet classified as developed economies.

Keywords: emerging markets, financial market integration, panel data, trade

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Authors: Steffen Happel

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Non-standard isotopes such as Sc-44/47, Zr-89, and Sn-117mare finding interest is increasing in radiopharmaceutical applications. Methods for the separation of these elements from typical target materials were developed. The methods used in this paper are based on the use of extraction chromatographic resins such as UTEVA, TBP, and DGA resin. Information on the selectivity of the resins (Dw values of selected elements in HCl and HNO3 of varying concentration) will be presented as well as results of the method development such as elution studies, chemical recoveries, and decontamination factors. Developed methods are based on the use of vacuum supported separation allowing for fast and selective separation.

Keywords: elution, extraction chromatography, radiopharmacy, decontamination factors

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Authors: Kyle Burke Pfeiffer, Carmella Burdi, Karen Marsh

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The evacuation and shelter-in-place planning process employed by most jurisdictions within the United States is not informed by a scientifically-derived framework that is inclusive of the behavioral and policy-related indicators of public compliance with evacuation orders. While a significant body of work exists to define these indicators, the research findings have not been well-integrated nor translated into useable planning factors for public safety officials. Additionally, refinement of the planning factors alone is insufficient to support science-based evacuation planning as the behavioral elements of evacuees—even with consideration of policy-related indicators—must be examined in the context of specific regional transportation and shelter networks. To address this problem, the Federal Emergency Management Agency and Argonne National Laboratory developed an agent-based model to support regional analysis of zone-based evacuation in southeastern Georgia. In particular, this model allows public safety officials to analyze the consequences that a range of hazards may have upon a community, assess evacuation and shelter-in-place decisions in the context of specified evacuation and response plans, and predict outcomes based on community compliance with orders and the capacity of the regional (to include extra-jurisdictional) transportation and shelter networks. The intention is to use this model to aid evacuation planning and decision-making. Applications for the model include developing a science-driven risk communication strategy and, ultimately, in the case of evacuation, the shortest possible travel distance and clearance times for evacuees within the regional boundary conditions.

Keywords: agent-based modeling for evacuation, decision-support for evacuation planning, evacuation planning, human behavior in evacuation

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Authors: Terada Pinyo

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This study is a survey research designed to evaluate the quality of graduate students and factors influencing their quality. The sample group consists of 240 students. The data are collected from stratified sampling and are analyzed and calculated by instant computer program. Statistics used are percentage, mean, standard deviation, Pearson correlation coefficient, Cramer’s V and logistic regression analysis. It is found that the graduate students’ opinions regarding their characteristics according to the Thai Qualifications Framework for Higher Education (TQF) are at high score range both overall and specific category. The top categories that received the top score are interpersonal skills and responsibility, ethics and morals, knowledge, cognitive skills, numerical analysis with communication and information technology skills, respectively. On the other hand, factors affecting the quality of graduate students are cognitive skills, numerical analysis with communication and information technology, knowledge, interpersonal skills and responsibility, ethics and morals, and career regarding sales/business, respectively.

Keywords: student quality evaluation, Thai qualifications framework for higher education, graduate school, cognitive skills

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Authors: Razmik Atabekyan, V. Atabekyan

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This article discusses a new alternative method for determination of seismic loads on buildings, based on resistance of structures to deformations of vibrations. The basic principles for determining seismic loads by spectral method were developed in 40… 50ies of the last century and further have been improved to pursuit true assessments of seismic effects. The base of the existing methods to determine seismic loads is response spectrum or dynamicity coefficient β (norms of RF), which are not definitively established. To this day there is no single, universal method for the determination of seismic loads and when trying to apply the norms of different countries, significant discrepancies between the results are obtained. On the other hand there is a contradiction of the results of macro seismic surveys of strong earthquakes with the principle of the calculation based on accelerations. It is well-known, on soft soils there is an increase of destructions (mainly due to large displacements), even though the accelerations decreases. Obviously, the seismic impacts are transmitted to the building through foundation, but paradoxically, the existing methods do not even include foundation data. Meanwhile acceleration of foundation of the building can differ several times from the acceleration of the ground. During earthquakes each building has its own peculiarities of behavior, depending on the interaction between the soil and the foundations, their dynamic characteristics and many other factors. In this paper we consider a new, alternative method of determining the seismic loads on buildings, without the use of response spectrum. The following main conclusions: 1) Seismic loads are revealed at the foundation level, which leads to redistribution and reduction of seismic loads on structures. 2) The proposed method is universal and allows determine the seismic loads without the use of response spectrum and any implicit coefficients. 3) The possibility of taking into account important factors such as the strength characteristics of the soils, the size of the foundation, the angle of incidence of the seismic ray and others. 4) Existing methods can adequately determine the seismic loads on buildings only for first form of vibrations, at an average soil conditions.

Keywords: seismic loads, response spectrum, dynamic characteristics of buildings, momentum

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Authors: Liwen Hou

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The booming mobile business has been penetrating the taxi industry worldwide with P2P (peer to peer) taxi services, as an emerging business model, transforming the industry. Parallel with other mobile businesses, member recommendations and online reviews are believed to be very effective with regard to acquiring new users for P2P taxi services. Based on an empirical dataset of the taxi industry in China, this study aims to reveal which factors influence users’ recommendations and review-writing behaviors. Differing from the existing literature, this paper takes the taxi driver’s perspective into consideration and hence selects a group of variables related to the drivers. We built two models to reflect the factors that influence the number of recommendations and reviews posted on the platform (i.e., the app). Our models show that all factors, except the driver’s score, significantly influence the recommendation behavior. Likewise, only one factor, passengers’ bad reviews, is insignificant in generating more drivers’ reviews. In the conclusion, we summarize the findings and limitations of the research.

Keywords: online recommendation, P2P taxi service, review-writing, word of mouth

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Authors: Isabel Acero, Nuria Alcalde

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The economic crisis and notorious corporate scandals have caused social indignation and sparked the debate concerning the underlying rationality of the compensation that directors receive. In this context, this study examines the determinants of the remuneration of directors in listed Spanish companies using individualized data. A multilevel methodology appropriate for this type of data has been used that allows us to differentiate between inter-company variations and intra-company variations. The results show that company size is the variable (at the company level) that exerts the greatest influence on the level of director´s compensation. One surprising finding is that the presence of independent directors on the board has a positive influence on remuneration. At the individual level, tenure and experience have a significant influence on the level of compensation, while the director´s level of education does not appear to have an effect on it.

Keywords: board of directors, compensation, experience, multilevel, tenure

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Authors: Ali Alsawayeh, Ibrahim Eldanfour

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This paper examines the extent of disclosure of oil and gas reserve quantum in annual reports of international oil and gas exploration and production companies, particularly companies in untested international markets, such as Canada, the UK and the US, and seeks to determine the underlying factors that affect the level of disclosure on oil reserve quantum. The study is concerned with the usefulness of disclosure of oil and gas reserves quantum to investors and other users. Given the primacy of the annual report (10-k) as a source of supplemental reserves data about the company and as the channel through which companies disseminate information about their performance, the annual reports for one year (2009) were the central focus of the study. This comparative study seeks to establish whether differences exist between the sample companies, based on new disclosure requirements by the Securities and Exchange Commission (SEC) in respect of reserves classification and definition. The extent of disclosure of reserve is provided and compared among the selected companies. Statistical analysis is performed to determine whether any differences exist in the extent of disclosure of reserve under the determinant variables. This study shows that some factors would affect the extent of disclosure of reserve quantum in the above-mentioned countries, namely: company’s size, leverage and quality of auditor. Companies that provide reserves quantum in detail appear to display higher size. The findings also show that the level of leverage has affected companies’ reserves quantum disclosure. Indeed, companies that provide detailed reserves quantum disclosure tend to employ a ‘high-quality auditor’. In addition, the study found significant independent variable such as Profit Sharing Contracts (PSC). This factor could explain variations in the level of disclosure of oil reserve quantum between the contractor and host governments. The implementation of SEC oil and gas reporting requirements do not enhance companies’ valuation because the new rules are based only on past and present reserves information (proven reserves); hence, future valuation of oil and gas companies is missing for the market.

Keywords: comparison, company characteristics, disclosure, reserve quantum, regulation

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Authors: Brandy Yee, Dianne Yee

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Through the exploration of the lived experiences, beliefs and values of instructional leaders, teachers and students in Finland, Germany and Canada, we investigated the factors which contribute to developmentally responsive, intellectually engaging middle-level learning environments for early adolescents. Student-centred leadership dimensions, effective instructional practices and student agency were examined through the lens of current policy and research on middle-level learning environments emerging from the Canadian province of Manitoba. Consideration of these three research perspectives in the context of early adolescent learning, placed against an international backdrop, provided a previously undocumented perspective on leading, teaching and learning in the middle years. Aligning with a social constructivist, qualitative research paradigm, the study incorporated collective case study methodology, along with constructivist grounded theory methods of data analysis. Data were collected through semi-structured individual and focus group interviews and document review, as well as direct and participant observation. Three case study narratives were developed to share the rich stories of study participants, who had been selected using maximum variation and intensity sampling techniques. Interview transcript data were coded using processes from constructivist grounded theory. A cross-case analysis yielded a conceptual framework highlighting key factors that were found to be significant in the establishment of developmentally responsive, intellectually engaging middle-level learning environments. Seven core categories emerged from the cross-case analysis as common to all three countries. Within the visual conceptual framework (which depicts the interconnected nature of leading, teaching and learning in middle-level learning environments), these seven core categories were grouped into Essential Factors (student agency, voice and choice), Contextual Factors (instructional practices; school culture; engaging families and the community), Synergistic Factors (instructional leadership) and Cornerstone Factors (education as a fundamental cultural value; preservice, in-service and ongoing teacher development). In addition, sub-factors emerged from recurring codes in the data and identified specific characteristics and actions found in developmentally responsive, intellectually engaging middle-level learning environments. Although this study focused on 12 schools in Finland, Germany and Canada, it informs the practice of educators working with early adolescent learners in middle-level learning environments internationally. The authentic voices of early adolescent learners are the most important resource educators have to gauge if they are creating effective learning environments for their students. Ongoing professional dialogue and learning is essential to ensure teachers are supported in their work and develop the pedagogical practices needed to meet the needs of early adolescent learners. It is critical to balance consistency, coherence and dependability in the school environment with the necessary flexibility in order to support the unique learning needs of early adolescents. Educators must intentionally create a school culture that unites teachers, students and their families in support of a common purpose, as well as nurture positive relationships between the school and its community. A large, urban school district in Canada has implemented a school cohort-based model to begin to bring developmentally responsive, intellectually engaging middle-level learning environments to scale.

Keywords: developmentally responsive learning environments, early adolescents, middle level learning, middle years, instructional leadership, instructional practices, intellectually engaging learning environments, leadership dimensions, student agency

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Authors: Vaibhavi Birle

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Posterior reversible encephalopathy syndrome is a rare clinic-radiological syndrome associated with acute changes in blood pressure during pregnancy. It is characterized symptomatically by headache, seizures, altered mental status, and visual blurring with radiological changes of white matter (vasogenic oedema) affecting the posterior occipital and parietal lobes of the brain. It is being increasingly recognized due to increased institutional deliveries and advances in imaging particularly magnetic resonance imaging (MRI). In spite of the increasing diagnosis the prediction of PRES and patient factors affecting susceptibility is still not clear. Hence, we conducted the retrospective study to analyse the factors associated with PRES at our tertiary centre.

Keywords: pres syndrome, eclampsia, maternal outcome, fetal outcome

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Authors: Awad Elkhadir, Rajab M. Ben Yousef

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Introduction: The production of high-quality medical images by radiology technologists is useful in diagnosing and treating various injuries and diseases. However, the factors affecting the role of radiology technologists in image interpretation in Sudan have not been investigated widely. Methods: Cross-sectional study has been employed by recruiting ten radiology college deans in Sudan. The questionnaire was distributed online, and obtained data were analyzed using Microsoft Excel and IBM-SPSS version 16.0 to generate descriptive statistics. Results: The study results have shown that half of the deans were doubtful about the readiness of Sudan to implement the role of radiology technologist specialist in image interpretation. The majority of them (60%) believed that this issue had been most strongly pushed by researchers over the past decade. The factors affecting the implementation of the radiology technologist specialist role in image interpretation included; education/training (100%), recognition (30%), technical issues (30%), people-related issues (20%), management changes (30%), government role (30%), costs (10%), and timings (20%). Conclusion: The study concluded that there is a need for a change in image interpretation by radiology technologists in Sudan.

Keywords: development, image interpretation, implementation, radiology technologist specialist, Sudan

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Authors: Rachmat Mauludin, Novita R. Kusuma, Diky Mudhakir

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Famotidine (FMT) is one of used substances in the treatment of hiperacidity and peptic ulcer, administered orally and parenterally via intravenous injection. Oral administration, which is more favorable, has been reported to have many obstacles in the process of the treatment, includes decreasing the bioavailability of FMT. This research was aimed to prepare FMT in form of solid lipid nanoparticles (SLN) with size ranging between 100-200 nm. The research was carried out also by optimizing factors that may affect physical stability of SLN. Formulation of Famotidine SLN was carried out by optimizing factors, such as duration of homogenization and sonication, lipid concentration, stabilizer composition and stabilizer concentration. SLN physical stability was evaluated (particle size distribution) for 42 days in 3 diferent temperatures. Entrapment efficiency and drug loading was determined indirectly and directly. The morphology of SLN was visualized by transmission electron microscope (TEM). In vitro release study of FMT was conducted in 2 mediums, at pH of 1.2 and 7.4. Chemical stability of FMT was determined by quantifying the concentration of FMT within 42 days. Famotidin SLN consisted of GMS as lipid and poloxamer 188, lecithin, and polysorbate 80 as stabilizers. Homogenization and sonication was performed for 5 minutes and 10 minutes. Physyical stability of nanoparticles at 3 different temperatures was no significant difference. The best formula was physically stable until 42 days with mean particle size below 200 nm. Nanoparticles produced was able to entrap FMT until 86.6%. Evaluation by TEM showed that nanoparticles was spherical and solid. In medium pH of 1.2, FMT was released only 30% during 4 hour. On the other hand, within 4 hours SLN could release FMT completely in medium pH of 7.4. The FMT concentration in nanoparticles dispersion was maintained until 95% in 42 days (40oC, RH 75%). Famotidine SLN was able to be produced with mean particle size ranging between 100-200 nm and physically stable for 42 days. SLN could be loaded by 86,6% of FMT. Morphologically, obtained SLN was spheric and solid. During 4 hours in medium pH of 1.2 and 7.4, FMT was released until 30% and 100%, respectively.

Keywords: solid lipid nanoparticle (SLN), famotidine (FMT), physicochemical properties, release study

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Authors: Cody Kirby, Kaustav Misra, Arundhati Bagchi Misra, Sharon P. Cox

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This paper focuses on the relationship that dual-enrollment programs have on academic performance and retention. Both performance and retention are significant issues in higher education. The first, performance, is a goal of higher education, having an impact on students’ lives. The second, retention, is key to the viability of any college or university. This paper uses survey research methodology to examine factors that lead to positive student academic performance, which leads to retention, specifically in dual-enrollment programs. The data show several characteristics that lead to a positive impact on GPA. These include the following; age, Caucasian race, full-time status, students in STEM programs, and finally dual enrollment participation.

Keywords: dual enrollment, early college, retention, undergraduate education

Procedia PDF Downloads 135

Authors: Gabriela Silva-Maceda, Silvia Romero-Contreras

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Spanish is a more transparent language than English given that it has more direct correspondences between sounds and letters. It has become important to understand how decoding and linguistic comprehension contribute to reading comprehension in the framework of the widely known Simple View Model. This study aimed to identify the level of prediction by these two components in a sample of 1st to 4th grade children attending two schools in central Mexico (one public and one private). Within each school, ten children were randomly selected in each grade level, and their parents were asked about reading habits and socioeconomic information. In total, 79 children completed three standardized tests measuring decoding (pseudo-word reading), linguistic comprehension (understanding of paragraphs) and reading comprehension using subtests from the Clinical Evaluation of Language Fundamentals-Spanish, Fourth Edition, and the Test de Lectura y Escritura en Español (LEE). The data were analyzed using hierarchical regression, with decoding as a first step and linguistic comprehension as a second step. Results showed that decoding accounted for 19.2% of the variance in reading comprehension, while linguistic comprehension accounted for an additional 10%, adding up to 29.2% of variance explained: F (2, 75)= 15.45, p <.001. Socioeconomic status derived from parental questionnaires showed a statistically significant association with the type of school attended, X2 (3, N= 79) = 14.33, p =.002. Nonetheless when analyzing the Simple View components, only decoding differences were statistically significant (t = -6.92, df = 76.81, p < .001, two-tailed); reading comprehension differences were also significant (t = -3.44, df = 76, p = .001, two-tailed). When socioeconomic status was included in the model, it predicted a 5.9% unique variance, even when already accounting for Simple View components, adding to a 35.1% total variance explained. This three-predictor model was also significant: F (3, 72)= 12.99, p <.001. In addition, socioeconomic status was significantly correlated with the amount of non-textbook books parents reported to have at home for both adults (rho = .61, p<.001) and children (rho= .47, p<.001). Results converge with a large body of literature finding socioeconomic differences in reading comprehension; in addition this study suggests that these differences were also present in decoding skills. Although linguistic comprehension differences between schools were expected, it is argued that the test used to collect this variable was not sensitive to linguistic differences, since it came from a test to diagnose clinical language disabilities. Even with this caveat, results show that the components of the Simple View Model can predict less than a third of the variance in reading comprehension in Spanish. However, the results also suggest that a fuller model of reading comprehension is obtained when considering the family’s socioeconomic status, given the potential differences shown by the socioeconomic status association with books at home, factors that are particularly important in countries where inequality gaps are relatively large.

Keywords: decoding, linguistic comprehension, reading comprehension, simple view model, socioeconomic status, Spanish

Procedia PDF Downloads 313

Authors: Chia-Hao Chang, Geng-Gui Wang, Jee-Cheng Wu

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The prediction of a landslide is a difficult task because it requires a detailed study of past activities using a complete range of investigative methods to determine the changing condition. In this research, first step, LiDAR 1-meter by 1-meter resolution of digital elevation model (DEM) was used to generate six environmental factors of landslide. Then, back-propagation neural networks (BPNN) was adopted to identify scarp, landslide areas and non-landslide areas. The BPNN uses 6 environmental factors in input layer and 1 output layer. Moreover, 6 landslide areas are used as training areas and 4 landslide areas as test areas in the BPNN. The hidden layer is set to be 1 and 2; the hidden layer neurons are set to be 4, 5, 6, 7 and 8; the learning rates are set to be 0.01, 0.1 and 0.5. When using 1 hidden layer with 7 neurons and the learning rate sets to be 0.5, the result of Network training root mean square error is 0.001388. Finally, evaluation of BPNN classification accuracy by the confusion matrix shows that the overall accuracy can reach 94.4%, and the Kappa value is 0.7464.

Keywords: digital elevation model, DEM, environmental factors, back-propagation neural network, BPNN, LiDAR

Procedia PDF Downloads 121

Authors: Jantakan Jullawateelert, Korakod Haonoo, Sutipong Sananseang, Sarun Torpaiboon, Thanunthon Bowornsakulwong, Lalintip Hocharoen

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Process scale-up is essential for the biological process to increase production capacity from bench-scale bioreactors to either pilot or commercial production. Scale-up based on constant volumetric oxygen mass transfer coefficient (KLa) is mostly used as a scale-up factor since oxygen supply is one of the key limiting factors for cell growth. However, to estimate KLa of culture vessels operated with different conditions are time-consuming since it is considerably influenced by a lot of factors. To overcome the issue, this study aimed to establish correlation equations of KLa and operating parameters in 0.5 L and 5 L bioreactor employed with pitched-blade impeller and gas sparger. Temperature, gas flow rate, agitation speed, and impeller position were selected as process parameters and equations were created using response surface methodology (RSM) based on central composite design (CCD). In addition, the effects of these parameters on KLa were also investigated. Based on RSM, second-order polynomial models for 0.5 L and 5 L bioreactor were obtained with an acceptable determination coefficient (R²) as 0.9736 and 0.9190, respectively. These models were validated, and experimental values showed differences less than 10% from the predicted values. Moreover, RSM revealed that gas flow rate is the most significant parameter while temperature and agitation speed were also found to greatly affect the KLa in both bioreactors. Nevertheless, impeller position was shown to influence KLa in only 5L system. To sum up, these modeled correlations can be used to accurately predict KLa within the specified range of process parameters of two different sizes of bioreactors for further scale-up application.

Keywords: response surface methodology, scale-up, stirred-tank bioreactor, volumetric oxygen mass transfer coefficient

Procedia PDF Downloads 186

Authors: Mahnaz Sanjari, Sedigheh Salemi, Mohammad Mirzabeigi

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Nowadays, the world is facing a crisis of workforce and one of the most striking examples is the shortage of nurses. Nursing workforce productivity is related by various factors such as absenteeism, professional effectiveness and quality care. This cross-sectional study was conducted in 700 nurses who work in government hospitals from 35 hospitals of 9 provinces in Iran. The study was approved by the Nursing Council and was carried out with the authorization of the Research Ethics Committee. The questionnaire included 33 questions and 4 sub categories such as human resource, education and management. The reliability was evaluated by Cronbach's alpha (α=0/85). Statistical analyzes were performed, using SPSS version 16. The result showed that nurses emphasized on "respect to nurse-to-bed ratio" and less importance item was "using less experienced nurse". In addition, another important factor in clinical productivity is "Proper physical structure and amenities","good communication with colleagues" and "having good facilities". Also, "human resources at all levels of standard", "promoting on merit" and "well defined relationship in health system" are another important factors in productivity from nurse` view. The main managerial factor is "justice between employees" and the main educational component of productivity is “updating nursing knowledge”. The results show that more than half of the participants emphasized on the management and educational factors. Productivity as one of the main part of the health care quality leads to appropriate use of human and organizational resources, reduce cost services, and organizational development.

Keywords: productivity, nursing services, workforce, cost services

Procedia PDF Downloads 335

Authors: Sherman Ho, Ahmed Cherif Megri

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Headers play a critical role in conveying steam to regulate heating system temperatures. While various materials like steel grades 91 and 92 have been traditionally used for pipes, this research proposes the use of a robust and innovative material, INCONEL Alloy 740H. Boilers in power plant configurations are exposed to cycling conditions due to factors such as daily, seasonal, and yearly variations in weather. These cycling conditions can lead to the deterioration of headers, which are vital components with intricate geometries. Header failures result in substantial financial losses from repair costs and power plant shutdowns, along with significant public inconveniences such as the loss of heating and hot water. To address this issue and seek solutions, a mechanical analysis, as well as a structural analysis, are recommended. Transient analysis to predict heat transfer conditions is of paramount importance, as the direction of heat transfer within the header walls and the passing steam can vary based on the location of interest, load, and operating conditions. The geometry and material of the header are also crucial design factors, and the choice of pipe material depends on its usage. In this context, the heat transfer coefficient plays a vital role in header design and analysis. This research employs ANSYS Fluent, a numerical simulation program, to understand header behavior, predict heat transfer, and analyze mechanical phenomena within the header. Transient simulations are conducted to investigate parameters like heat transfer coefficient, pressure loss coefficients, and heat flux, with the results used to optimize header design.

Keywords: CFD, header, power plant, heat transfer coefficient, simulation using experimental data

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Authors: Syed Toqueer, Omer Younus

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Terrorism, today, has emerged as a global menace with Pakistan being the most adversely affected state. Therefore, the motive behind this study is to empirically establish the linkage of terrorism with socio-economic (uneven income distribution, poverty and unemployment) and political nexuses so that a policy recommendation can be put forth to better approach this issue in Pakistan. For this purpose, the study employs two competing models, namely, the distributed lag model and OLS, so that findings of the model may be consolidated comprehensively, over the reference period of 1984-2012. The findings of both models are indicative of the fact that uneven income distribution of Pakistan is rather a contributing factor towards terrorism when measured through GDP per capita. This supports the hypothesis that immiserizing modernization theory is applicable for the state of Pakistan where the underprivileged are marginalized. Results also suggest that other socio-economic variables (poverty, unemployment and consumer confidence) can condense the brutality of terrorism once these conditions are catered to and improved. The rational of opportunity cost is at the base of this argument. Poor conditions of employment and poverty reduces the opportunity cost for individuals to be recruited by terrorist organizations as economic returns are considerably low and thus increasing the supply of volunteers and subsequently increasing the intensity of terrorism. The argument of political freedom as a means of lowering terrorism stands true. The more the people are politically repressed the more alternative and illegal means they will find to make their voice heard. Also, the argument that politically transitioning economy faces more terrorism is found applicable for Pakistan. Finally, the study contributes to an ongoing debate on which of the two set of factors are more significant with relation to terrorism by suggesting that socio-economic factors are found to be the primary causes of terrorism for Pakistan.

Keywords: terrorism, socioeconomic conditions, political freedom, distributed lag model, ordinary least square

Procedia PDF Downloads 311