Search results for: factor models

Authors: Marcel Chevalier, Léo Dupont, Sylvain Marié, Frédérique Roffet, Elena Stolyarova, William Templier, Costin Vasile

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Industrial end-users are currently facing an increasing need to reduce the risk of unexpected failures and optimize their maintenance. This calls for both short-term analysis and long-term ageing anticipation. At Schneider Electric, we tackle those two issues using both machine learning and first principles models. Machine learning models are incrementally trained from normal data to predict expected values and detect statistically significant short-term deviations. Ageing models are constructed by breaking down physical systems into sub-assemblies, then determining relevant degradation modes and associating each one to the right kinetic law. Validating such anomaly detection and maintenance models is challenging, both because actual incident and ageing data are rare and distorted by human interventions, and incremental learning depends on human feedback. To overcome these difficulties, we propose to simulate physics, systems, and humans -including asset maintenance operations- in order to validate the overall approaches in accelerated time and possibly choose between algorithmic alternatives.

Keywords: degradation models, ageing, anomaly detection, soft sensor, incremental learning

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Authors: Caglayan Pinar Demirtas, Mustafa Koc

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Objective: This study was carried out in order to find out; the methods which are used by primary school teachers to cope with stress, their psychological health, and the direction of controlling focus. The study was carried out by using the ‘school survey’ and ‘society survey’ methods. Method: The study included primary school teachers. The study group was made up of 1066 people; 511 women and 555 men who accepted volunteerly to complete; ‘the inventory for collecting data, ‘the Scale for Attitude of Overcoming Stress’ (SBTE / SAOS), ‘Rotter’s Scale for the Focus of Inner- Outer Control’ (RİDKOÖ / RSFIOC), and ‘the Symptom Checking List’ (SCL- 90). The data was collected by using ‘the Scale for Attitude of Overcoming Stress’, ‘the Scale for the Focus of Inner- Outer Control’, ‘the Symptom Checking List’, and a personal information form developed by the researcher. SPSS for Windows packet programme was used. Result: The age variable is a factor in interpersonal sensitivity, depression, anxciety, hostality symptoms but it is not a factor in the other symptoms. The variable, gender, is a factor in emotional practical escaping overcoming method but it is not a factor in the other overcoming methods. Namely, it has been found out that, women use emotional practical escaping overcoming method more than men. Marital status is a factor in methods of overcoming stress such as trusting in religion, emotional practical escaping and biochemical escaping while it is not a factor in the other methods. Namely, it has been found out that married teachers use trusting in religion method, and emotional practical escaping method more than single ones. Single teachers generally use biochemical escaping method. In primary school teachers’ direction of controlling focus, gender variable is a factor. It has been found out that women are more inner controlled while the men are more outer controlled. The variable, time of service, is a factor in the direction of controlling focus; that is, teachers with 1-5 years of service time are more inner controlled compared with teachers with 16-20 years of service time. The variable, age, is a factor in the direction of controlling focus; that is, teachers in 26-30 age groups are more outer controlled compared with the other age groups and again teachers in 26-30 age group are more inner controlled when compared with the other age groups. Direction of controlling focus is a factor in the primary school teachers’ psychological health. Namely, being outer controlled is a factor but being inner controlled is not. The methods; trusting in religion, active plannıng and biochemical escaping used by primary school teachers to cope with stress act as factors in the direction of controlling focus but not in the others. Namely, it has been found out that outer controlled teachers prefer the methods of trusting in religion and active planning while the inner controlled ones prefer biochemical escaping.

Keywords: coping with, controlling focus, psychological health, stress

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Authors: Ahmed A. Al-Mudhafar, Ali A. Abduljabar, Hayder Jawad Albattat

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This work suggests a new microwave resonator sensor (MRS) device for measuring the oil’s breakdown voltage of high voltage transformers. A precise high-sensitivity sensor is designed and manufactured based on a microstrip split ring resonator (SRR). To improve the sensor sensitivity, a RF amplifier of 30 dB gain is linked through a transmission line of 50Ω.The sensor operates at a microwave band (L) with a quality factor of 1.35x105 when it is loaded with an empty tube. In this work, the sensor has been tested with three samples of high voltage transformer oil of different ages (new, middle, and damaged) where the quality factor differs with each sample. A mathematical model was built to calculate the breakdown voltage of the transformer oils and the accuracy of the results was higher than 90%.

Keywords: active resonator sensor, oil breakdown voltage, transformers oils, quality factor

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Authors: Pauline E. Ngo-Henha

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Existing turnover intention theories are reviewed in this paper. This review was conducted with the help of the search keyword “turnover intention theories” in Google Scholar during the month of July 2017. These theories include: The Theory of Organizational Equilibrium (TOE), Social Exchange Theory, Job Embeddedness Theory, Herzberg’s Two-Factor Theory, the Resource-Based View, Equity Theory, Human Capital Theory, and the Expectancy Theory. One of the limitations of this review paper is that data were only collected from Google Scholar where many papers were sometimes not freely accessible. However, this paper attempts to contribute to the research in clarifying the distinction between theories and models in the context of turnover intention.

Keywords: Literature Review, Theory, Turnover, Turnover intention

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Authors: Jeongmin Kim, Eunju Lee, Kwang Ryel Ryu

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This paper addresses the problem of predictive control for energy management of large-scaled exhibition halls, where a lot of energy is consumed to maintain internal atmosphere under certain required conditions. Predictive control achieves better energy efficiency by optimizing the operation of air-conditioning facilities with not only the current but also some future status taken into account. In this paper, we propose to use predictive models learned from past sensor data of hall environment, for use in optimizing the operating plan for the air-conditioning facilities by simulating future environmental change. We have implemented an emulator of an exhibition hall by using EnergyPlus, a widely used building energy emulation tool, to collect data for learning environment-change models. Experimental results show that the learned models predict future change highly accurately on a short-term basis.

Keywords: predictive control, energy management, machine learning, optimization

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Authors: Sipho Mbatha, Anne Mastament-Mason

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South African manufacturing global competitiveness was ranked 22nd (out of 38 countries), dropped to 24th in 2013 and is expected to drop further to 25th by 2018. These impacts negatively on the industrialisation project of South Africa. For industrialization to be achieved through labour intensive industries like the Apparel Manufacturing Industries of South Africa (AMISA), South Africa needs to identify and respond to factors negatively impacting on the development of competitive advantage This paper applied factor conditions from Porter’s Diamond Model (1990) to understand the various challenges facing the AMISA. Factor conditions highlighted in Porter’s model are grouped into two groups namely, basic and advance factors. Two AMISA associations representing over 10 000 employees were interviewed. The largest Clothing, Textiles and Leather (CTL) apparel retail group was also interviewed with a government department implementing the industrialisation policy were interviewed The paper points out that while AMISA have basic factor conditions necessary for competitive advantage in the clothing and textiles industries, Advance factor coordination has proven to be a challenging task for the AMISA, Higher Education Institutions (HEIs) and government. Poor infrastructural maintenance has contributed to high manufacturing costs and poor quick response as a result of lack of advanced technologies. The use of Porter’s Factor Conditions as a tool to analyse the sector’s competitive advantage challenges and opportunities has increased knowledge regarding factors that limit the AMISA’s competitiveness. It is therefore argued that other studies on Porter’s Diamond model factors like Demand conditions, Firm strategy, structure and rivalry and Related and supporting industries can be used to analyse the situation of the AMISA for the purposes of improving competitive advantage.

Keywords: compliance rule, apparel manufacturing industry, factor conditions, advance skills and South African industrial policy

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Authors: Nahla H. Alaswadko, Rayya A. Hassan, Bayar N. Mohammed

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Empirical deterministic models have been developed to predict roughness progression of heavy duty spray sealed pavements for a dataset representing rural arterial roads. The dataset provides a good representation of the relevant network and covers a wide range of operating and environmental conditions. A sample with a large size of historical time series data for many pavement sections has been collected and prepared for use in multilevel regression analysis. The modelling parameters include road roughness as performance parameter and traffic loading, time, initial pavement strength, reactivity level of subgrade soil, climate condition, and condition of drainage system as predictor parameters. The purpose of this paper is to report the approaches adopted for models development and validation. The study presents multilevel models that can account for the correlation among time series data of the same section and to capture the effect of unobserved variables. Study results show that the models fit the data very well. The contribution and significance of relevant influencing factors in predicting roughness progression are presented and explained. The paper concludes that the analysis approach used for developing the models confirmed their accuracy and reliability by well-fitting to the validation data.

Keywords: roughness progression, empirical model, pavement performance, heavy duty pavement

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Authors: Seyed Habib Shojaei, Reza Eivazi, Mir Sajad Shojaei, Alireza Akbari, Pooria Mazloom, Seyede Mitra Sadati, Mir Zeinalabedin Shojaei, Farnaz Farbakhsh

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To study the genetic diversity in rapeseeds and agronomic traits, an experiment was conducted using multivariate statistical methods at Agricultural Research Station of Kashmar in 2012-2013.In this experiment, ten genotypes of rapeseed in a Randomized Complete Block designs with three replications were evaluated. The following traits were studied: seed yield, number of days to the fifty percent of flowering, plant height, number of pods on main stem, length of the pod, seed yield per plant, number of seed in pod, harvest index, weight of 100 seeds, number of pods on lateral branch, number of lateral branches. In analyzing the variance, differences between cultivars were significant. The average comparative revealed that the most valuable variety was Licord regarding to the traits while the least valuable variety was Opera. In stepwise regression, harvest index, grain yield per plant and number of pods per lateral branches were entering to model. Correlation analysis showed that the grain yield with the number of pods per lateral branches and seed yield per plant have positive and significant correlation. In the factor analysis, the first five components explained more than 83% of the variance in the data. In the first factor, seed yield and the number of pods per lateral branches were of the highest importance. The traits, seed yield per plant, and pod per main stem were of a great significance in the second factor. Moreover, in the third factor, plant height and the number of lateral branches were more important. In the fourth factor, plant height and one hundred seeds weight were of the highest variance. Finally, days to fifty percent of flowering and one hundred seeds weight were more important in fifth factor.

Keywords: rapeseed, variance analysis, regression, factor analysis

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Authors: Josip Vasilj, Petar Sarajcev, Damir Jakus

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One of the major difficulties introduced with wind power penetration is the inherent uncertainty in production originating from uncertain wind conditions. This uncertainty impacts many different aspects of power system operation, especially the balancing power requirements. For this reason, in power system development planing, it is necessary to evaluate the potential uncertainty in future wind power generation. For this purpose, simulation models are required, reproducing the performance of wind power forecasts. This paper presents a wind power forecast error simulation models which are based on the stochastic process simulation. Proposed models capture the most important statistical parameters recognized in wind power forecast error time series. Furthermore, two distinct models are presented based on data availability. First model uses wind speed measurements on potential or existing wind power plant locations, while the seconds model uses statistical distribution of wind speeds.

Keywords: wind power, uncertainty, stochastic process, Monte Carlo simulation

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Authors: Minakshi Jain, Sachin Yadav

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Gram Panchayat is the smallest unit of Democracy in India. Grassroots Democracy has been further strengthened by implementation of the 73rd Constitutional Amendment act (CAA) in 1992. To analyse the impact of grassroots democracy the three villages are selected, which have the representation of each section of the society. The selected villages belongs to the same block and district of Haryana state. Villages are selected to access the marginalized group such as women and other backward class. These groups are isolated and do not participate in the grassroots level development process. The caste continue to be a relevant factor in determining the rural leadership. The earlier models of Panchayati Raj failed to benefit the marginalized groups of the society. The 73rd CAA, advocates a uniform three tier system of Panchayat at District level (Zilla Panchayat), Taluka/Block level (Block Panchayat), and village level (Gram Panchayat). The socio-economic profile of representatives in each village is important factor in rural development. The study will highlight the socio-economic profile of elected members at gram Panchayat level, Block Level and District level. The analysis reveals that there is a need to educate and develop the capacity and capability of the elected representative. Training must be imparted to all of them to enable them to function as per provision in the act. The paper will analyse the impact of act on rural development than propose some measures to further strengthen the Panchayati Raj Institution (PRI’s) at grassroots level.

Keywords: democracy, rural development, marginalized people, function

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Authors: Heny Pratiwi, Niken Silmi Surjandari, Noegroho Djarwanti

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This study was conducted to determine the potential for landslides as a result of monthly rainfall in a watershed. Rainfall data that will be used is rainfall from years 2007-2011. Research methods created by modeling the slope on some variation of angle in a row 30◦, 45◦, and 60◦ with a homogeneous layer of soil. Slope Stability Analysis using Method Fellenius. The results of the slope stability analysis without rain on slope 30◦, 45◦, and 60◦ respectively 1.3846, 1.0115, and 0.7284. Results in the absence of rain showed that the slope on the slope 45◦ are in critical condition and on a slope with a slope 60◦ already avalanche with safety factor value <1. The results in the rainy conditions shows slopes 30◦ are in critical condition with a value factor <1 due to the intensity of monthly rainfall> 250 mm/month.

Keywords: slope stability, monthly rainfall, infiltration, safety factor, Fellenius method

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Authors: Sudip Kumar Kundu, Charu Singh

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As a great physiographic divide, the Himalayas affecting a large system of water and air circulation which helps to determine the climatic condition in the Indian subcontinent to the south and mid-Asian highlands to the north. It creates obstacles by defending chill continental air from north side into India in winter and also defends rain-bearing southwesterly monsoon to give up maximum precipitation in that area in monsoon season. Nowadays extreme weather conditions such as heavy precipitation, cloudburst, flash flood, landslide and extreme avalanches are the regular happening incidents in the region of North Western Himalayan (NWH). The present study has been planned to investigate the suitable model(s) to find out the rainfall pattern over that region. For this investigation, selected models from Coordinated Regional Climate Downscaling Experiment (CORDEX) and Coupled Model Intercomparison Project Phase 5 (CMIP5) has been utilized in a consistent framework for the period of 1976 to 2000 (historical). The ability of these driving models from CORDEX domain and CMIP5 has been examined according to their capability of the spatial distribution as well as time series plot of rainfall over NWH in the rainy season and compared with the ground-based Indian Meteorological Department (IMD) gridded rainfall data set. It is noted from the analysis that the models like MIROC5 and MPI-ESM-LR from the both CORDEX and CMIP5 provide the best spatial distribution of rainfall over NWH region. But the driving models from CORDEX underestimates the daily rainfall amount as compared to CMIP5 driving models as it is unable to capture daily rainfall data properly when it has been plotted for time series (TS) individually for the state of Uttarakhand (UK) and Himachal Pradesh (HP). So finally it can be said that the driving models from CMIP5 are better than CORDEX domain models to investigate the rainfall pattern over NWH region.

Keywords: global warming, rainfall, CMIP5, CORDEX, NWH

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Authors: Balthazar Temu, Zhao Yan, Bogdan-Petrin Ratiu, Sang Soon Oh, Qiang Li

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Photonic Crystal Surface Emitting Lasers (PCSELs) are structures which are made up of a periodically repeating patterns with a unit cell consisting of changes in refractive index. The variation in refractive index can be achieved by etching air holes in a semiconductor material to get hole based PCSELs or by growing nanowires to get nanowire based PCSELs. As opposed to hole based PCSELs, nanowire based PCSELs can be integrated on silicon platform without threading dislocations, thanks to the small area of the nanowire that is in contact with silicon substrate that relaxes the strain. Nanowire based PCSELs reported in the literature have been designed using a triangular, square or honeycomb patterns. The triangular and square pattern PCSELs have limited degrees of freedom in tuning the design parameters which hinders the ability to design high quality factor (Q-factor) and/or variable wavelength devices. Nanowire based PCSELs designed using triangular and square patterns have been reported with the lasing thresholds of 130 kW/〖cm〗^2 and 7 kW/〖cm〗^2 respectively. On the other hand the honeycomb pattern gives more degrees of freedom in tuning the design parameters, which can allow one to design high Q-factor devices. A deformed honeycomb pattern device was reported with lasing threshold of 6.25 W/〖cm〗^2 corresponding to a simulated Q-factor of 5.84X〖10〗^5.Despite this achievement, the design principles which can lead to realization of even higher Q-factor honeycomb pattern PCSELs have not yet been investigated. In this work we study how the resonance wavelength and the Q-factor of three different resonance modes of the device vary when their design parameters are tuned. Through this study we establish the design and simulation of devices operating in 970nm wavelength band, O band and in the C band with quality factors up to 7X〖10〗^7 . We also investigate the quality factors of undeformed device and establish that the band edge close to 970nm can attain high quality factor when the device is undeformed and the quality factor degrades as the device is deformed.

Keywords: honeycomb PCSEL, nanowire laser, photonic crystal laser, simulation of photonic crystal surface emitting laser

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Authors: Fayçal Benyahia, Abdelmohsen Albedah, Bel Abbes Bachir Bouiadjra

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In this study the Finite element method is used to analyse the effect of the thermal residual stresses resulting from adhesive curing on the performances of the bonded composite repair in aircraft structures. The stress intensity factor at the crack tip is chosen as fracture criterion in order to estimate the repair performances. The obtained results show that the presence of the thermal residual stresses reduces considerably the repair performances and consequently decreases the fatigue life of cracked structures. The effects of the curing temperature, the adhesive properties and the adhesive thickness on the Stress Intensity Factor (SIF) variation with thermal stresses are also analysed.

Keywords: bonded composite repair, residual stress, adhesion, stress transfer, finite element analysis

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Authors: Juyeon Lee, Sungeun You

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Experiential avoidance is one’s tendency to avoid painful internal experience, unwanted adverse thoughts, emotions, and physical sensations. The Multidimensional Experiential Avoidance Questionnaire (MEAQ) is a measure of experiential avoidance, and the original scale consisted of 62 items with six subfactors including behavioral avoidance, distress aversion, procrastination, distraction/suppression, repression/denial, and distress endurance. The purpose of this study was to examine the factor structure of the MEAQ in a Korean sample. Three hundred community adults and university students aged 18 to 35 participated in an online survey assessing experiential avoidance (MEAQ and Acceptance and Action Questionnaire-II; AAQ-II), depression (Patient Health Questionnaire-9; PHQ-9), anxiety (Generalized Anxiety Disoder-7; GAD-7), negative affect (Positive and Negative Affect Scale; PANAS), neuroticism (Big Five Inventory; BFI), and quality of life (Satisfaction with Life Scale; SWLS). Factor analysis with principal axis with direct oblimin rotation was conducted to examine subfactors of the MEAQ. Results indicated that the six-factor structure of the original scale was adequate. Eight items out of 62 items were removed due to insufficient factor loading. These items included 3 items of behavior avoidance (e.g., “When I am hurting, I would do anything to feel better”), 2 items of repression/denial (e.g., “I work hard to keep out upsetting feelings”), and 3 items of distress aversion (e.g., “I prefer to stick to what I am comfortable with, rather than try new activities”). The MEAQ was positively associated with the AAQ-II (r = .47, p < .001), PHQ-9 (r = .37, p < .001), GAD-7 (r = .34, p < .001), PANAS (r = .35, p < .001), and neuroticism (r = .24, p < .001), and negatively correlated with the SWLS (r = -.38, p < .001). Internal consistency was good for the MEAQ total (Cronbach’s α = .90) as well as all six subfactors (Cronbach’s α = .83 to .87). The findings of the study support the multidimensional feature of experiential avoidance and validity of the MEAQ in a sample of Korean adults.

Keywords: avoidance, experiential avoidance, factor structure, MEAQ

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Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

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In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: equivalent martingale measure, European put option, girsanov theorem, martingales, monte carlo method, option price valuation formula

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Authors: Adilson Elias Xavier, Otto Corrêa Rotunno Filho, Paulo Canedo De Magalhães

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This paper addresses the issue of automatic parameter estimation in conceptual rainfall-runoff (CRR) models. Due to threshold structures commonly occurring in CRR models, the associated mathematical optimization problems have the significant characteristic of being strongly non-differentiable. In order to face this enormous task, the resolution method proposed adopts a smoothing strategy using a special C∞ differentiable class function. The final estimation solution is obtained by solving a sequence of differentiable subproblems which gradually approach the original conceptual problem. The use of this technique, called Hyperbolic Smoothing Method (HSM), makes possible the application of the most powerful minimization algorithms, and also allows for the main difficulties presented by the original CRR problem to be overcome. A set of computational experiments is presented for the purpose of illustrating both the reliability and the efficiency of the proposed approach.

Keywords: rainfall-runoff models, automatic calibration, hyperbolic smoothing method

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Authors: H. Duggal, G. Singh, G. Singh, A. Bhalla, S. Kumar, J. S. Shahi, D. Mehta

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The total differential cross section for scattering of the 5.895 keV photons by various polymers has been measured at scattering angle of 135o. The experimental measurements were carried out using the energy dispersive setup involving annular source of the 55Fe radioisotope and a low energy germanium (LEGe) detector. The cross section values are measured for 20 polymer targets namely, Paraffin Wax, Polytetrafluoro ethylene (PTFE), Cellulose, Silicone oil, Polyvinyl alcohol (PVA), Polyvinyl purrolidone (PVP), Polymethyl methacrylate (PMMA), Kapton, Mylar, Chitosan, Polyvinyl chloride (PVC), Bakelite, Carbopol, Chlorobutyl rubber (CBR), Polyetylene glycol (PEG), Polysorbate-20, Nylon-6, Cetyl alcohol, Carboxyl methyl sodium cellulose and Sodium starch glucolate. The measurements were performed in vacuum so as to avoid scattering contribution due to air and strong absorption of low energy photons in the air column. In the present investigations, the geometrical factor and efficiency of the detector were determined by measuring the K x-rays emitted from the 22Ti and 23V targets excited by the Mn K x-rays in the same experimental set up. The measured scattering cross sections have been compared with the sum of theoretically calculated elastic and inelastic scattering cross sections. The theoretical elastic (Rayleigh) scattering cross sections based on the various form factor approximations, namely, non-relativistic form factor (NF), relativistic form factor (RF), modified form factor (MF), and MF with anomalous scattering factor (ASF) as well as the second order S-matrix formalisms, and the inelastic scattering differential cross sections based on the Klein-Nishina formula after including the inelastic scattering function (KN+ISF) have been calculated. The experimental results show fairly good agreement with theoretical cross sections.

Keywords: photon, polymers, elastic and inelastic, scattering cross sections

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Authors: Feten Chihi, Gabriella Varga

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The world's most prevalent waste management strategy is landfills. However, it grew more difficult due to a lack of acceptable waste sites. In order to develop larger landfills and extend their lifespan, the purpose of this article is to expand the capacity of the construction by varying the slope's inclination and to examine its effect on the safety factor. The capacity change with tilt is mathematically determined. Using a new probabilistic calculation method that takes into account the heterogeneity of waste layers, the safety factor for various slope angles is examined. To assess the effect of slope variation on the overall safety of landfills, over a hundred computations were performed for each angle. It has been shown that capacity increases significantly with increasing inclination. Passing from 1:3 to 2:3 slope angles and from 1:3 to 1:2 slope angles, the volume of garbage that can be deposited increases by 40 percent and 25 percent, respectively, of the initial volume. The results of the safety factor indicate that slopes of 1:3 and 1:2 are safe when the standard method (homogenous waste) is used for computation. Using the new approaches, a slope with an inclination of 2:3 can be deemed safe, despite the fact that the calculation does not account for the safety-enhancing effect of daily cover layers. Based on the study reported in this paper, the malty layered nonhomogeneous calculating technique better characterizes the safety factor. As it more closely resembles the actual state of landfills, the employed technique allows for more flexibility in design parameters. This work represents a substantial advance in limiting both safe and economical landfills.

Keywords: landfill, municipal solid waste, slope inclination, capacity, safety factor

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Authors: Mohammad Qasim Mohammadi, Mohammad Arif Rohman

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Although socially sustainable building is becoming increasingly popular worldwide, past studies indicate that when policymakers support sustainable building development, the social dimension is often given insufficient attention or entirely disregarded. There are not many studies that focus on the problems of socially sustainable buildings in Afghanistan. This research investigates the factors that may hinder social sustainability implementation in residential building construction. The study will gather data from construction professionals by purposive sampling and employ Exploratory Factor Analysis (EFA) and Varimax for analysis. The results will undergo rigorous examination and thorough discussion. The expected results in this research will analyze the underlying barrier structure (factors) that hinder social sustainability, and each of these factors will represent a set of observed variables. In addition, the factor loadings show which barriers pose the greatest challenges. The primary goal of this study is to provide valuable insights into the impediment factors of social sustainability within the residential building environment, aiming to inform decision-making in the industry and encourage the adoption of more socially sustainable construction practices.

Keywords: social sustainability, residential building, barriers, drivers, afghanistan, factor analysis

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Authors: Mehdi Seifbarghy, Zahra Mansouri

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In this paper a few location-allocation models are developed in a multi-echelon supply chain including suppliers, manufacturers, distributors and retailers. The objectives are maximizing demand coverage, minimizing the total distance of distributors from suppliers, minimizing some facility establishment costs and minimizing the environmental effects. Since nature of the given models is multi-objective, we suggest a number of goal-based solution techniques such L-P metric, goal programming, multi-choice goal programming and goal attainment in order to solve the problems.

Keywords: location, multi-echelon supply chain, covering, goal programming

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Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

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Authors: H. C. Nguyen

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This contribution considers seismic effects on the stability of slope and footing resting on a slope. The seismic force is simply treated as static inertial force through the values of acceleration factor. All domains are assumed to be plasticity deformations approximated using node-based smoothed finite element method (NS-FEM). The failure mechanism and safety factor were then explored using numerical procedure based on upper bound approach in which optimization problem was formed as second order cone programming (SOCP). The data obtained confirm that upper bound procedure using NS-FEM and SOCP can give stable and rapid convergence results of seismic stability factors.

Keywords: upper bound analysis, safety factor, slope stability, footing resting on slope

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Authors: Nodelman V.

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Despite serious difficulties in the assimilation of the conceptual system of Calculus, software in the educational process is used only occasionally, and even then, mainly for illustration purposes. The following are a few reasons: The non-trivial nature of the studied material, Lack of skills in working with software, Fear of losing time working with software, The variety of the software itself, the corresponding interface, syntax, and the methods of working with the software, The need to find suitable models, and familiarize yourself with working with them, Incomplete compatibility of the found models with the content and teaching methods of the studied material. This paper proposes an active use of the developed non-commercial software VusuMatica, which allows removing these restrictions through Broad support for the studied mathematical material (and not only Calculus). As a result - no need to select the right software, Emphasizing the unity of mathematics, its intrasubject and interdisciplinary relations, User-friendly interface, Absence of special syntax in defining mathematical objects, Ease of building models of the studied material and manipulating them, Unlimited flexibility of models thanks to the ability to redefine objects, which allows exploring objects characteristics, and considering examples and counterexamples of the concepts under study. The construction of models is based on an original approach to the analysis of the structure of the studied concepts. Thanks to the ease of construction, students are able not only to use ready-made models but also to create them on their own and explore the material studied with their help. The presentation includes examples of using VusuMatica in studying the concepts of limit and continuity of a function, its derivative, and integral.

Keywords: counterexamples, limitations and requirements, software, teaching and learning calculus, user-friendly interface and syntax

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Authors: Balimu Mwiya, Mundia Muya, Chabota Kaliba, Peter Mukalula

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Factors affecting construction unit cost vary depending on a country’s political, economic, social and technological inclinations. Factors affecting construction costs have been studied from various perspectives. Analysis of cost factors requires an appreciation of a country’s practices. Identified cost factors provide an indication of a country’s construction economic strata. The purpose of this paper is to identify the essential factors that affect unit cost estimation and their breakdown using artificial neural networks. Twenty-five (25) identified cost factors in road construction were subjected to a questionnaire survey and employing SPSS factor analysis the factors were reduced to eight. The 8 factors were analysed using the neural network (NN) to determine the proportionate breakdown of the cost factors in a given construction unit rate. NN predicted that political environment accounted 44% of the unit rate followed by contractor capacity at 22% and financial delays, project feasibility, overhead and profit each at 11%. Project location, material availability and corruption perception index had minimal impact on the unit cost from the training data provided. Quantified cost factors can be incorporated in unit cost estimation models (UCEM) to produce more accurate estimates. This can create improvements in the cost estimation of infrastructure projects and establish a benchmark standard to assist the process of alignment of work practises and training of new staff, permitting the on-going development of best practises in cost estimation to become more effective.

Keywords: construction cost factors, neural networks, roadworks, Zambian construction industry

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Authors: H. Djebar, L. Khene, M. Boucenna, M. R. Djebar, M. N. Khebbeb, M. Djekoun

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Currently in toxicology, use of alternative models permits to understand the mechanisms of toxicity at different levels of cells. Objectives of our research concern the determination of NPs ZnO, TiO2, AlO2, and FeO2 effect on ciliate protist freshwater Paramecium sp and Helix aspersa. The result obtained show that NPs increased antioxidative enzyme activity like catalase, glutathione –S-transferase and level GSH. Also, cells treated with high concentrations of NPs showed a high level of MDA. In conclusion, observations from growth and enzymatic parameters suggest on one hand that treatment with NPs provokes an oxidative stress and on the other that snale and paramecium are excellent alternatives models for ecotoxicological studies.

Keywords: NPs, GST, catalase, GSH, MDA, toxicity, snale and paramecium

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Authors: Abdull Halim Abdul, Muhaimin Sulam

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This paper is about a subsurface study of Taman Pudu Ulu, Cheras, Kuala Lumpur with emphasize of Geo mechanic properties based on stratum index factor in humanities environment. Subsurface drilling and seismic data were used to understand the subsurface condition of the study area such as the type and thickness of the strata. Borehole and soil samples were recovered Geo mechanic properties of the area by conducting number of experiments. Taman Pudu Ulu overlies the Kuala Lumpur Limestone formation that is known for its karstic features such as caves and cavities. Hence by knowing the Geo mechanic properties such as the normal strain and shear strain we can plan a safer and economics construction that is plan at the area in the future.

Keywords: stratum, index factor, geo mechanic properties, humanities environment

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Authors: Mengistu G. Woldu, Hani Y. Zaki, Areeg Faggad, Badreldin E. Abdalla

Abstract:

Background: Type 2 diabetes mellitus (T2DM) is a complex, degenerative, and multi-factorial disease, which is culpable for huge mortality and morbidity worldwide. Even though relatively significant numbers of studies are conducted on the genetics domain of this disease in the developed world, there is huge information gap in the sub-Saharan Africa region in general and in Eritrea in particular. Objective: The principal aim of this study was to investigate the association of common variants of the Insulin Receptor Substrate 1 (IRS1) and Transcription Factor 7-Like 2 (TCF7L2) genes with T2DM in the Eritrean population. Method: In this cross-sectional case control study 200 T2DM patients and 112 non-diabetes subjects were participated and genotyping of the IRS1 (rs13431179, rs16822615, 16822644rs, rs1801123) and TCF7L2 (rs7092484) tag SNPs were carries out using PCR-RFLP method of analysis. Haplotype analyses were carried out using Plink version 1.07, and Haploview 4.2 software. Linkage disequilibrium (LD), and Hardy-Weinberg equilibrium (HWE) analyses were performed using the Plink software. All descriptive statistical data analyses were carried out using SPSS (Version-20) software. Throughout the analysis p-value ≤0.05 was considered statistically significant. Result: Significant association was found between rs13431179 SNP of the IRS1 gene and T2DM under the recessive model of inheritance (OR=9.00, 95%CI=1.17-69.07, p=0.035), and marginally significant association found in the genotypic model (OR=7.50, 95%CI=0.94-60.06, p=0.058). The rs7092484 SNP of the TCF7L2 gene also showed markedly significant association with T2DM in the recessive (OR=3.61, 95%CI=1.70-7.67, p=0.001); and allelic (OR=1.80, 95%CI=1.23-2.62, p=0.002) models. Moreover, eight haplotypes of the IRS1 gene found to have significant association withT2DM (p=0.013 to 0.049). Assessments made on the interactions of genotypes of the rs13431179 and rs7092484 SNPs with various parameters demonstrated that high density lipoprotein (HDL), low density lipoprotein (LDL), waist circumference (WC), and systolic blood pressure (SBP) are the best T2DM onset predicting models. Furthermore, genotypes of the rs7092484 SNP showed significant association with various atherogenic indexes (Atherogenic index of plasma, LDL/HDL, and CHLO/HDL); and Eritreans carrying the GG or GA genotypes were predicted to be more susceptible to cardiovascular diseases onset. Conclusions: Results of this study suggest that IRS1 (rs13431179) and TCF7L2 (rs7092484) gene polymorphisms are associated with increased risk of T2DM in Eritreans.

Keywords: IRS1, SNP, TCF7L2, type 2 diabetes

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Authors: John M. Basey, Clinton D. Francis, Maxwell B. Joseph

Abstract:

After gathering data from experimental procedures, inquiry-oriented-science labs often allow students the freedom to stay and complete the write up in class or leave lab early and complete the write up later. Teachers must decide whether to allow students this freedom to self-regulate this time. Student interviews have indicated four time-target strategies that may influence how students utilize this time: grade-target-A, grade-target-C, time-limited, and proficiency. The hypothesis tested was that variability in class composition relative to the four grade-target strategies has an impact on when students leave class, which in turn may influence their overall learning as exemplified by grades. Students were divided into the four indicated groups with a survey. Class composition and the GTA teaching the class had significant impacts on how long students stayed in class with class composition having the greatest impact. A factor analysis identified two factors. Factor 1 included classes with percentages of grade-target students opposite time-limited/proficiency students and explained 43% of the variance. Factor 2 included classes with percentages of grade-target-A/proficiency students opposite grade-target-C students and explained 33% of the variance. Students who stayed longer received significantly higher grades (P = 0.008) with no significant relationships between grade and Factor 1 or Factor 2 (P > 0.05). The time students stayed in class was significantly positively related to Factor 1 (P = 0.006) and significantly negatively related to Factor 2 (P = 0.008). These results support the hypothesis and indicate that teachers may want to know the composition of student-target strategies before deciding on how to have students allocate study time at the end of inquiry-oriented labs. According to these results, ideal classes for self-regulation have a high proportion of proficiency and time-limited students and a low proportion of grade-target students, or a high proportion of grade-target-A and proficiency students and a low proportion of grade-target-C students. Non-ideal classes for self-regulation were comprised of the inverse proportions.

Keywords: grades, inquiry lab design, synergism in student motivation, class composition

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Authors: Vallence Ngabo M., Leonard Atuhaire, Peter Clever Rutayisire

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The main aim of this study was to establish the differences in both the determinants of stunting and the causal mechanism through which the identified determinants influence stunting amongst male and female under-fives in Uganda. Literature shows that male children below the age of five years are at a higher risk of being stunted than their female counterparts. Specifically, studies in Uganda indicate that being a male child is positively associated with stunting, while being a female is negatively associated with stunting. Data for 904 males and 829 females under-fives was extracted form UDHS-2016 survey dataset. Key variables for this study were identified and used in generating relevant models and paths. Structural equation modeling techniques were used in their generalized form (GSEM). The generalized nature necessitated specifying both the family and link functions for each response variable in the system of the model. The sex of the child (b4) was used as a grouping factor and the height for age (HAZ) scores were used to construct the status for stunting of under-fives. The estimated models and path clearly indicated that the set of underlying factors that influence male and female under-fives respectively was different and the path through which they influence stunting was different. However, some of the determinants that influenced stunting amongst male under-fives also influenced stunting amongst the female under-fives. To reduce the stunting problem to the desirable state, it is important to consider the multifaceted and complex nature of the risk factors that influence stunting amongst the under-fives but, more importantly, consider the different sex-specific factors and their causal mechanism or paths through which they influence stunting.

Keywords: stunting, underfives, sex of the child, GSEM, causal mechanism

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