Search results for: reliable facility location model

Authors: Martin Cermak, Stanislav Sysala

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In this paper we present the efficient parallel implementation of elastoplastic problems based on the TFETI (Total Finite Element Tearing and Interconnecting) domain decomposition method. This approach allow us to use parallel solution and compute this nonlinear problem on the supercomputers and decrease the solution time and compute problems with millions of DOFs. In our approach we consider an associated elastoplastic model with the von Mises plastic criterion and the combination of linear isotropic-kinematic hardening law. This model is discretized by the implicit Euler method in time and by the finite element method in space. We consider the system of nonlinear equations with a strongly semismooth and strongly monotone operator. The semismooth Newton method is applied to solve this nonlinear system. Corresponding linearized problems arising in the Newton iterations are solved in parallel by the above mentioned TFETI. The implementation of this problem is realized in our in-house MatSol packages developed in MATLAB.

Keywords: isotropic-kinematic hardening, TFETI, domain decomposition, parallel solution

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Authors: Renzo Palomino, Alessandra Trujillo, Lidia Pacheco

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The document presents a study based on the incremental bearing capacity of silty clay soil with the incorporation of crushed PET fibers. For a better understanding of the behavior of soil, it is necessary to know its origin. The analyzed samples came from the subgrade layer of a highway that connects the cities of Muniches and Yurimaguas in Loreto, Peru. The material in this area usually has properties such as low support index, medium to high plasticity, and other characteristics that make it considered a ‘problematic’ soil due to factors such as climate, humidity, and geographical location. In addition, PET fibers are obtained from the decomposition of plastic bottles that are polluting agents with a high production rate in our country; in that sense, their use in a construction process represents a considerable reduction in environmental impact. Moreover, to perform a precise analysis of the behavior of this soil mixed with PET, tests such as the hydrometer test, Proctor and CBR with 15%, 10%, 5%, 4%, 3%, and 1% of PET with respect to the mass of the sample of natural soil were carried out. The results show that when a low percentage of PET is used, the support index increases.

Keywords: environmental impact, geotechnics, PET, silty clay soil

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Authors: Nancy Retzlaff, Sarah J. Berkemer, Trudie Strauss

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In the last couple of decades, the advent of digitalization of any kind of data was probably one of the major advances in all fields of study. This paves the way for also analysing these data even though they might come from disciplines where there was no initial computational necessity to do so. Especially in linguistics, one can find a rather manual tradition. Still when considering studies that involve the history of language families it is hard to overlook the striking similarities to bioinformatics (phylogenetic) approaches. Alignments of words are such a fairly well studied example of an application of bioinformatics methods to historical linguistics. In this paper we will not only consider alignments of strings, i.e., words in this case, but also alignments of syntax trees of selected Indo-European languages. Based on initial, crude alignments, a sophisticated scoring model is trained on both letters and syntactic features. The aim is to gain a better understanding on which features in two languages are related, i.e., most likely to have the same root. Initially, all words in two languages are pre-aligned with a basic scoring model that primarily selects consonants and adjusts them before fitting in the vowels. Mixture models are subsequently used to filter ‘good’ alignments depending on the alignment length and the number of inserted gaps. Using these selected word alignments it is possible to perform tree alignments of the given syntax trees and consequently find sentences that correspond rather well to each other across languages. The syntax alignments are then filtered for meaningful scores—’good’ scores contain evolutionary information and are therefore used to train the sophisticated scoring model. Further iterations of alignments and training steps are performed until the scoring model saturates, i.e., barely changes anymore. A better evaluation of the trained scoring model and its function in containing evolutionary meaningful information will be given. An assessment of sentence alignment compared to possible phrase structure will also be provided. The method described here may have its flaws because of limited prior information. This, however, may offer a good starting point to study languages where only little prior knowledge is available and a detailed, unbiased study is needed.

Keywords: alignments, bioinformatics, comparative linguistics, historical linguistics, statistical methods

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Authors: Carolyn Scott, Rachel Nugent

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The agricultural industry in Ireland and worldwide is one of the most dangerous occupations with respect to occupational health and safety accidents and fatalities. Many accident causation models have been developed in safety research to understand the underlying and contributory factors that lead to the occurrence of an accident. Due to the uniqueness of the agricultural sector, current accident causation theories cannot be applied. This paper presents an accident causation model named the Irish Farm Accident Causation Model (IFACM) which has been specifically tailored to the needs of Irish farms. The IFACM is a theoretical and practical model of accident causation that arranges the causal factors into a graphic representation of originating, shaping, and contributory factors that lead to accidents when unsafe acts and conditions are created that are not rectified by control measures. Causes of farm accidents were assimilated by means of a thorough literature review and were collated to form a graphical representation of the underlying causes of a farm accident. The IFACM was validated retrospectively through case study analysis and peer review. Participants in the case study (n=10) identified causes that led to a farm accident in which they were involved. A root cause analysis was conducted to understand the contributory factors surrounding the farm accident, traced back to the ‘root cause’. Experts relevant to farm safety accident causation in the agricultural industry have peer reviewed the IFACM. The accident causation process is complex. Accident prevention requires a comprehensive understanding of this complex process because to prevent the occurrence of accidents, the causes of accidents must be known. There is little research on the key causes and contributory factors of unsafe behaviours and accidents on Irish farms. The focus of this research is to gain a deep understanding of the causality of accidents on Irish farms. The results suggest that the IFACM framework is helpful for the analysis of the causes of accidents within the agricultural industry in Ireland. The research also suggests that there may be international applicability if further research is carried out. Furthermore, significant learning can be obtained from considering the underlying causes of accidents.

Keywords: farm safety, farm accidents, accident causation, root cause analysis

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Authors: P. Singh, R. M. Banik

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Artificial neural network (ANN) was employed to optimize assay parameters viz., time, temperature, pH of reaction mixture, enzyme volume and substrate concentration of L-glutaminase from Bacillus cereus MTCC 1305. ANN model showed high value of coefficient of determination (0.9999), low value of root mean square error (0.6697) and low value of absolute average deviation. A multilayer perceptron neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model and its topology was obtained as 5-3-1 after applying Levenberg Marquardt (LM) training algorithm. The predicted activity of L-glutaminase was obtained as 633.7349 U/l by considering optimum assay parameters, viz., pH of reaction mixture (7.5), reaction time (20 minutes), incubation temperature (35˚C), substrate concentration (40mM), and enzyme volume (0.5ml). The predicted data was verified by running experiment at simulated optimum assay condition and activity was obtained as 634.00 U/l. The application of ANN model for optimization of assay conditions improved the activity of L-glutaminase by 1.499 fold.

Keywords: Bacillus cereus, L-glutaminase, assay parameters, artificial neural network

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Authors: Buket Metin

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Buildings cause a variety of loads on the environment due to activities performed at each stage of the building life cycle. Construction is the first stage that affects both the natural and built environments at different steps of the process, which can be defined as transportation of materials within the construction site, formation and preparation of materials on-site and the application of materials to realize the building subsystems. All of these steps require the use of technology, which varies based on the facilities that contractors and subcontractors have. Hence, environmental consequences of the construction process should be tackled by focusing on construction technology options used in every step of the process. This paper presents an environmental decision-making model for assessing on-site performances of subcontractors based on the construction technology options which they can supply. First, construction technologies, which constitute information, tools and methods, are classified. Then, environmental performance criteria are set forth related to resource consumption, ecosystem quality, and human health issues. Finally, the model is developed based on the relationships between the construction technology components and the environmental performance criteria. The Fuzzy Analytical Hierarchy Process (FAHP) method is used for weighting the environmental performance criteria according to environmental priorities of decision-maker(s), while the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used for ranking on-site environmental performances of subcontractors using quantitative data related to the construction technology components. Thus, the model aims to provide an insight to decision-maker(s) about the environmental consequences of the construction process and to provide an opportunity to improve the overall environmental performance of construction sites.

Keywords: construction process, construction technology, decision making, environmental performance, subcontractor

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Authors: Nicolas Thiers, Romain Gers, Olivier Skurtys

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In this work, we study numerically the effect of a thermal perturbation on the heat transfer in a rectangular differentially heated cavity of aspect ratio 4, filled by air. In order to maintain the center symmetry, the thermal perturbation is imposed by a square wave at both active walls, at the same relative position of the hot or cold boundary layers. The influences of the amplitude and the vertical location of the perturbation are investigated. The air flow is calculated solving the unsteady Boussinesq-Navier-Stokes equations using the PN - PN-2 Spectral Element Method (SEM) programmed in the Nek5000 opencode, at RaH= 9x107, just before the first bifurcation which leads to periodical flow. The results show that the perturbation has a major impact for the highest amplitude, and at about three quarters of the cavity height, upstream, in both hot and cold boundary layers.

Keywords: direct numerical simulation, heat transfer enhancement, localized thermal perturbations, natural convection, rectangular differentially-heated cavity

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Authors: Olfa Kaabia, Ilyes Abid, Khaled Guesmi

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This pioneer paper studies whether and how Bitcoin shocks are transmitted to the U.S economy. We employ a new methodology: TVP FAVAR model with stochastic volatility. We use a large dataset of 111 major U.S variables from 1959:m1 to 2016:m12. The results show that Bitcoin shocks significantly impact the U.S. economy. This significant impact is pronounced in a volatile and increasing U.S economy. The Bitcoin has a positive relationship on the U.S real activity, and a negative one on U.S prices and interest rates. Effects on the Monetary Policy exist via the inter-est rates and the Money, Credit and Finance transmission channels.

Keywords: bitcoin, US economy, FAVAR models, stochastic volatility

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Authors: Jussi Horelli, Salla Niittymäki

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In this acceleratingly developing world, it will be crucial for our students to not only to adapt to continuous change, but to be the driving force of it. This raises the question of how can the educational processes motivate and encourage the students to learn the perhaps most important skill there for their further work career: the ability to learn and absorb more by themselves. In engineering education, the learning contents and methods have traditionally been very substance oriented and teacher-centered. In Häme University of Applied Sciences (HAMK), the pedagogical model has been completely renewed during the past few years. Terms like phenomenon or skills-based learning and collaborative teaching are things which have not very often been related to engineering education, but are now the foundation of HAMK’s pedagogical model in all disciplines, even in engineering studies. In this paper, a new flexible way of executing engineering studies will be introduced. The paper will summarize three years’ experiences and observations of a process where traditional teacher-centric mechanical engineering teaching was converted into a model where teachers work collaboratively in teams supporting the students’ learning processes.

Keywords: team teaching, collaborative learning, engineering education, new pedagogy

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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The aim of this study was to improve the effects of human body 3D reconstruction. The MvP algorithm was adopted to obtain key point information from multiple perspectives. This algorithm allowed the capture of human posture and joint positions from multiple angles, providing more comprehensive and accurate data. The study also incorporated the SMPL-X model, which has been widely used for human body modeling, to achieve more accurate 3D reconstruction results. The use of the MvP algorithm made it possible to observe the reconstructed object from multiple angles, thus reducing the problems of blind spots and missing information. This algorithm was able to effectively capture key point information, including the position and rotation angle of limbs, providing key data for subsequent 3D reconstruction. Compared with traditional single-view methods, the method of multi-view fusion significantly improved the accuracy and stability of reconstruction. By combining the MvP algorithm with the SMPL-X model, we successfully achieved better human body 3D reconstruction effects. The SMPL-X model is highly scalable and can generate highly realistic 3D human body models, thus providing more detail and shape information.

Keywords: 3D human reconstruction, multi-view, joint point, SMPL-X

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Authors: Elyes Zarrouk, Yassine Benayed, Faiez Gargouri

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This paper presents a new hybrid model for isolated Arabic words recognition. To do this, we apply Support Vectors Machine (SVM) as an estimator of posterior probabilities within the Dynamic Bayesian networks (DBN). This paper deals a comparative study between DBN and SVM/DBN systems for multi-dialect isolated Arabic words. Performance using SVM/DBN is found to exceed that of DBNs trained on an identical task, giving higher recognition accuracy for four different Arabic dialects. In fact, the average of recognition rates for the four dialects with SVM/DBN was 87.67% while 83.01% with DBN.

Keywords: dynamic Bayesian networks, hybrid models, supports vectors machine, Arabic isolated words

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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An estimating equation technique is an alternative method of the widely used maximum likelihood methods, which enables us to ease some complexity due to the complex characteristics of time-varying covariates. In the situations, when both the time-varying covariates and left-truncation are considered in the model, the maximum likelihood estimation procedures become much more burdensome and complex. To ease the complexity, in this study, the modified estimating equations those have been given high attention and considerations in many researchers under semiparametric transformation model was proposed. The purpose of this article was to develop the modified estimating equation under flexible and general class of semiparametric transformation models for left-truncated and right censored survival data with time-varying covariates. Besides the commonly applied Cox proportional hazards model, such kind of problems can be also analyzed with a general class of semiparametric transformation models to estimate the effect of treatment given possibly time-varying covariates on the survival time. The consistency and asymptotic properties of the estimators were intuitively derived via the expectation-maximization (EM) algorithm. The characteristics of the estimators in the finite sample performance for the proposed model were illustrated via simulation studies and Stanford heart transplant real data examples. To sum up the study, the bias for covariates has been adjusted by estimating density function for the truncation time variable. Then the effect of possibly time-varying covariates was evaluated in some special semiparametric transformation models.

Keywords: EM algorithm, estimating equation, semiparametric transformation models, time-to-event outcomes, time varying covariate

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Authors: Wilhelmina van den Berg

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Through intentionally developing the Register Continuum and the Functional Model of Language in the secondary history classroom, teachers can effectively build a teaching and learning cycle geared towards literacy improvement and EAL differentiation. Developing an understanding of and engaging students in the field, tenor, and tone of written and spoken language, allows students to build the foundation for greater academic achievement due to integrated literacy skills in the history classroom. Building a variety of scaffolds during lessons within these models means students can improve their academic language and communication skills.

Keywords: academic language, EAL, functional model of language, international baccalaureate, literacy skills

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Authors: Jiajun Wang, Xiaoge Li

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The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree

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Authors: Andrew T. Hendrickson, Liven De Marez, Marijn Martens, Gytha Muller, Tudor Paisa, Koen Ponnet, Catherine Schweizer, Megan Van Meer, Mariek Vanden Abeele

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Quantifying and understanding the myriad ways people use their phones and how that impacts their relationships, cognitive abilities, mental health, and well-being is increasingly important in our phone-centric society. However, most studies on the patterns of phone use have focused on theory-driven tests of specific usage hypotheses using self-report questionnaires or analyses of smaller datasets. In this work we present a series of analyses from a large corpus of over 3000 users that combine data-driven and theory-driven analyses to identify reliable smartphone usage patterns and clusters of similar users. Furthermore, we compare the stability of user clusters across user- and system-initiated sessions, as well as during the hypothesized ritualized behavior times directly before and after sleeping. Our results indicate support for some hypothesized usage patterns but present a more complete and nuanced view of how people use smartphones.

Keywords: data mining, experience sampling, smartphone usage, health and well being

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Authors: Mohammad Beyki, Justus Pawlak, Robert Patzke, Franz Renz

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In the context of planetary exploration, the MIMOS II (miniaturized Mössbauer spectrometer) serves as a proven and reliable measuring instrument. The transmission behaviour of the electronics in the Mössbauer spectroscopy is newly developed and optimized. For this purpose, the overall electronics is split into three parts. This elaboration deals exclusively with the first part of the signal chain for the evaluation of photons in experiments with gamma radiation. Parallel to the analysis of the electronics, a new method for the stability consideration of linear and non-linear systems is presented: The extended method of Lyapunov’s stability criteria. The design helps to weigh advantages and disadvantages against other simulated circuits in order to optimize the MIMOS II for the terestric and extraterestric measurment. Finally, after stability analysis, the controller design according to Ackermann is performed, achieving the best possible optimization of the output variable through a skillful pole assignment.

Keywords: Mössbauer spectroscopy, electronic signal amplifier, light processing technology, photocurrent, trans-impedance amplifier, extended Lyapunov method

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Authors: Wee Tong Liaw, Elaine Wong Yee Sing

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Since 2001, many companies in Singapore have voluntarily participated in the bi-annual Singapore HEALTH Award initiated by the Health Promotion Board of Singapore (HPB). The Singapore HEALTH Award (SHA), is an industry wide award and assessment process. SHA assesses and recognizes employers in Singapore for implementing a comprehensive and sustainable health promotion programme at their workplaces. The rationale for implementing a sustained health promoting workplace and participating in SHA is obvious when company management is convinced that healthier employees, business productivity, and profitability are positively correlated. However, performing research or empirical studies on the impact of a sustained health promoting workplace on stock returns are not likely to yield any interests in the absence of a systematic and independent assessment on the comprehensiveness and sustainability of a health promoting workplace in most developed economies. The principles of diversification and mean-variance efficient portfolio in Modern Portfolio Theory developed by Markowitz (1952) laid the foundation for the works of many financial economists and researchers, and among others, the development of the Capital Asset Pricing Model from the work of Sharpe (1964), Lintner (1965) and Mossin (1966), and the Fama-French Three-Factor Model of Fama and French (1992). This research seeks to support the rationale by studying whether there is a significant relationship or impact of a sustained health promoting workplace on the performance of companies listed on the SGX. The research shall form and test hypotheses pertaining to the impact of a sustained health promoting workplace on company’s performances, including stock returns, of companies that participated in the SHA and companies that did not participate in the SHA. In doing so, the research would be able to determine whether corporate and fund manager should consider the significance of a sustained health promoting workplace as a risk factor to explain the stock returns of companies listed on the SGX. With respect to Singapore’s stock market, this research will test the significance and relevance of a health promoting workplace using the Singapore Health Award as a proxy for non-diversifiable risk factor to explain stock returns. This study will examine the significance of a health promoting workplace on a company’s performance and study its impact on stock price performance and beta and examine if it has higher explanatory power than the traditional single factor asset pricing model CAPM (Capital Asset Pricing Model). To study the significance there are three key questions pertinent to the research study. I) Given a choice, would an investor be better off investing in a listed company with a sustained health promoting workplace i.e. a Singapore Health Award’s recipient? II) The Singapore Health Award has four levels of award starting from Bronze, Silver, Gold to Platinum. Would an investor be indifferent to the level of award when investing in a listed company who is a Singapore Health Award’s recipient? III) Would an asset pricing model combining FAMA-French Three Factor Model and ‘Singapore Health Award’ factor be more accurate than single factor Capital Asset Pricing Model and the Three Factor Model itself?

Keywords: asset pricing model, company's performance, stock prices, sustained health promoting workplace

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Authors: Aysha Zamir

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This study examines to what extent foreign private investment (FPI) affects the clean industrial environment and sustainable economic growth through developed countries investment in China. Moreover, this study investiage an association among FPI, CO2 emission, energy consumption, and sustainable economic growth. This study uses random effects and generalized least squares (GLS) and panel VAR estimators for data analysis. The results indicate that the Chinese economy has a vastly positive influenced regarding the location and choice of emerging and developed countries’ investment in the domestic market. Furthermore, emerging and developed economies investment increases the contribution among domestic firms, environment sustainability toward the national economy. The further results show that foreign private investment and gross domestic investment have a positive impact on sustainable economic growth.

Keywords: clean industrial environment, energy consumption, CO2 emmission, foreign private investment, developed and emerging economies

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Authors: Badreddine Chemali, Boualem Tiliouine

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This article presents the main results of a numerical investigation on the uncertainty of dynamic response of structures with statistically correlated random damping Gamma distributed. A computational method based on a Linear Statistical Model (LSM) is implemented to predict second order statistics for the response of a typical industrial building structure. The significance of random damping with correlated parameters and its implications on the sensitivity of structural peak response in the neighborhood of a resonant frequency are discussed in light of considerable ranges of damping uncertainties and correlation coefficients. The results are compared to those generated using Monte Carlo simulation techniques. The numerical results obtained show the importance of damping uncertainty and statistical correlation of damping coefficients when obtaining accurate probabilistic estimates of dynamic response of structures. Furthermore, the effectiveness of the LSM model to efficiently predict uncertainty propagation for structural dynamic problems with correlated damping parameters is demonstrated.

Keywords: correlated random damping, linear statistical model, Monte Carlo simulation, uncertainty of dynamic response

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Authors: Bishakha Majumdar, Ranjeet Nambudiri

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Considerable dichotomy exists in research regarding the role of optimism and self-efficacy in work and career outcomes. Optimism and self-efficacy are related to performance, commitment and engagement, but also are implicated in seeing opportunities outside the firm and switching jobs. There is absence of research capturing these opposing strands of findings in the same model and providing a holistic understanding of how the expectancy beliefs operate in case of the working professional. We attempt to bridge this gap by proposing that career-decision self-efficacy and career outcome expectations affect intention to quit through the competitive mediation pathways of internal and external marketability. This model provides a holistic picture of the role of career expectancy beliefs on career outcomes, by considering perceived career opportunities both inside and outside one’s present organization. The understanding extends the application of career expectancy beliefs in the context of career decision-making by the employed individual. Further, it is valuable for reconsidering the effectiveness of hiring and retention techniques used by a firm, as selection, rewards and training programs need to be supplemented by interventions that specifically strengthen the stability pathway.

Keywords: career decision self-efficacy, career outcome expectations, marketability, intention to quit, job mobility

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Authors: Sulastriningsih Djumingin

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This study has some objectives. It aims at describing the ability of the second-grade students to write review text without applying the Lesson Study model at SMPN 18 Makassar. Second, it seeks to describe the ability of the second-grade students to write review text by applying the Lesson Study model at SMPN 18 Makassar. Third, it aims at testing the effectiveness of the Lesson Study model in writing review text at SMPN 18 Makassar. This research was true experimental design with posttest Only group design involving two groups consisting of one class of the control group and one class of the experimental group. The research populations were all the second-grade students at SMPN 18 Makassar amounted to 250 students consisting of 8 classes. The sampling technique was purposive sampling technique. The control class was VIII2 consisting of 30 students, while the experimental class was VIII8 consisting of 30 students. The research instruments were in the form of observation and tests. The collected data were analyzed using descriptive statistical techniques and inferential statistical techniques with t-test types processed using SPSS 21 for windows. The results shows that: (1) of 30 students in control class, there are only 14 (47%) students who get the score more than 7.5, categorized as inadequate; (2) in the experimental class, there are 26 (87%) students who obtain the score of 7.5, categorized as adequate; (3) the Lesson Study models is effective to be applied in writing review text. Based on the comparison of the ability of the control class and experimental class, it indicates that the value of t-count is greater than the value of t-table (2.411> 1.667). It means that the alternative hypothesis (H1) proposed by the researcher is accepted.

Keywords: application, lesson study, review text, writing

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Authors: Ebuwa Osagie, Vasilije Manovic

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Exergy analysis provides the identification of the location, sources of thermodynamic inefficiencies, and magnitude in a thermal system. Thus, both the qualitative and quantitative assessment can be evaluated with exergy, unlike energy which is based on quantitative assessment only. The main purpose of exergy analysis is to identify where exergy is destroyed. Thus, reduction of the exergy destruction and losses associated with the capture plant systems can improve work potential. Furthermore, thermodynamic analysis of different configurations of the process helps to identify opportunities for reducing the steam requirements for each of the configurations. This paper presents steady-state simulation and exergy analysis of the 2-amino-2-methyl-1-propanol (AMP)-based post-combustion capture (PCC) plant. Exergy analysis performed for the AMP-based plant and the different configurations revealed that the rich split with intercooling configuration gave the highest exergy efficiency of 73.6%, while that of the intercooling and the reference AMP-based plant were 57.3% and 55.8% respectively.

Keywords: 2-amino-2-methyl-1-propanol, modelling, and simulation, post-combustion capture plant, exergy analysis, flowsheeting configurations

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Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

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Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

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Authors: Ciolomic Ioana Andreea, Farcas Teodora, Tiron-Tudor Adriana

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Investments in research and innovation are widely acknowledged as being crucial drivers for economic growth, for job-creation and to secure social and economic welfare. The aim of this article is to disseminate the results of a Leonardo da Vinci Innovation Transfer project, AdapTykes Adaptation of trainings based up on the Finnish Workplace Development Programme. This project aims to analyses the adaptability of the Finnish model to the economic and political environment of the two emergent countries Romania and Hungary, in order to develop workplace innovation. The focus of this paper is to present the adaptability of the Finnish model to the Romanian context.

Keywords: innovation, human resources, education, tools

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Authors: S. Moustafa El Shanawany, I. Labib Salem, F. Mohamed Magdy Badr El Dine, H. Tag El Deen Abd Allah

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Thermal injuries remain a global health problem and a common issue encountered in forensic pathology. They are a devastating cause of morbidity and mortality in children and adults especially in developing countries, causing permanent disfigurement, scarring and grievous hurt. Burns have always been a matter of legal concern in cases of suicidal burns, self-inflicted burns for false accusation and homicidal attempts. Assessment of burn injuries as well as rating permanent disabilities and disfigurement following thermal injuries for the benefit of compensation claims represents a challenging problem. This necessitates the development of reliable scoring systems to yield an expected likelihood of permanent disability or fatal outcome following burn injuries. The study was designed to identify the risk factors of mortality in acute burn patients and to evaluate the applicability of FLAMES (Fatality by Longevity, APACHE II score, Measured Extent of burn, and Sex) and BOBI (Belgian Outcome in Burn Injury) model scores in predicting the outcome. The study was conducted on 100 adult patients with acute burn injuries admitted to the Burn Unit of Alexandria Main University Hospital, Egypt from October 2014 to October 2015. Victims were examined after obtaining informed consent and the data were collected in specially designed sheets including demographic data, burn details and any associated inhalation injury. Each burn patient was assessed using both BOBI and FLAMES scoring systems. The results of the study show the mean age of patients was 35.54±12.32 years. Males outnumbered females (55% and 45%, respectively). Most patients were accidently burnt (95%), whereas suicidal burns accounted for the remaining 5%. Flame burn was recorded in 82% of cases. As well, 8% of patients sustained more than 60% of total burn surface area (TBSA) burns, 19% of patients needed mechanical ventilation, and 19% of burnt patients died either from wound sepsis, multi-organ failure or pulmonary embolism. The mean length of hospital stay was 24.91±25.08 days. The mean BOBI score was 1.07±1.27 and that of the FLAMES score was -4.76±2.92. The FLAMES score demonstrated an area under the receiver operating characteristic (ROC) curve of 0.95 which was significantly higher than that of the BOBI score (0.883). A statistically significant association was revealed between both predictive models and the outcome. The study concluded that both scoring systems were beneficial in predicting mortality in acutely burnt patients. However, the FLAMES score could be applied with a higher level of accuracy.

Keywords: BOBI, burns, FLAMES, scoring systems, outcome

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Authors: Antonello Troncone, Luigi Pugliese, Andrea Parise, Enrico Conte

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The present study deals with the landslides periodically reactivated by groundwater level fluctuations owing to rainfall. The main type of movement which generally characterizes these landslides consists in sliding with quite small-displacement rates. Another peculiar characteristic of these landslides is that soil deformations are essentially concentrated within a thin shear band located below the body of the landslide, which, consequently, undergoes an approximately rigid sliding. In this context, a simple method is proposed in the present study to forecast the movements of this type of landslides owing to rainfall. To this purpose, the landslide body is schematized by means of a two-block model. Some analytical solutions are derived to relate rainfall measurements with groundwater level oscillations and these latter, in turn, to landslide mobility. The proposed method is attractive for engineering applications since it requires few parameters as input data, many of which can be obtained from conventional geotechnical tests. To demonstrate the predictive capability of the proposed method, the application to a well-documented landslide periodically reactivated by rainfall is shown.

Keywords: rainfall, water level fluctuations, landslide mobility, two-block model

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Authors: Mohammad Zahidul Islam Bhuiyan, Shanyong Wang, Scott William Sloan, Daichao Sheng

Abstract:

Nowadays soil pressure transducers are widely used to measure the soil stress states in laboratory and field experiments. The soil pressure transducers, investigated here, are traditional diaphragm-type earth pressure cells (DEPC) based on strain gauge principle. It is found that the output of these sensors varies with the soil conditions as well as the position of a sensor. Therefore, it is highly recommended to calibrate the pressure sensors based on the similar conditions of their intended applications. The factory calibration coefficients of the EPCs are not reliable to use since they are normally calibrated by applying fluid (a special type of oil) pressure only over load sensing zone, which does not represent the actual field conditions. Thus, the calibration of these sensors is utmost important, and they play a pivotal role for assessing earth pressures precisely. In the present study, TML soil pressure sensor is used to compare its sensitivity under different calibration systems, for example, fluid calibration, and static load calibration with or without soil. The results report that the sensor provides higher sensitivity (more accurate results) under soil calibration system.

Keywords: calibration, soil pressure, earth pressure cell, sensitivity

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Authors: K. G. Sorokozherdyev, E. A. Efimov

Abstract:

The socio-economic development of regions and countries is an important research issue. Today, in the face of many negative events in the global and regional economies, it is especially important to identify those areas that can serve as sources of economic growth and the basis for the well-being of the population. This study aims to identify the most important sectors of the economy of the Arkhangelsk region that can contribute to the socio-economic development of the region as a whole. For research, the Arkhangelsk region was taken as one of the typical Russian regions that do not have significant reserves of hydrocarbons nor there are located any large industrial complexes. In this regard, the question of possible origins of economic growth seems especially relevant. The basis of this study constitutes the distributed lag regression model (ADL model) developed by the authors, which is based on quarterly data on the socio-economic development of the Arkhangelsk region for the period 2004-2016. As a result, we obtained three equations reflecting the dynamics of three indicators of the socio-economic development of the region -the average wage, the regional GRP, and the birth rate. The influencing factors are the shares in GRP of such sectors as agriculture, mining, manufacturing, construction, wholesale and retail trade, hotels and restaurants, as well as the financial sector. The study showed that the greatest influence on the socio-economic development of the region is exerted by such industries as wholesale and retail trade, construction, and industrial sectors. The study can be the basis for forecasting and modeling the socio-economic development of the Arkhangelsk region in the short and medium term. It also can be helpful while analyzing the effectiveness of measures aimed at stimulating those or other industries of the region. The model can be used in developing a regional development strategy.

Keywords: regional economic development, regional sectoral structure, ADL model, Arkhangelsk region

Procedia PDF Downloads 97

Authors: Diqin Qi, Jiaming Li, Siman Li

Abstract:

Based on the use of the three-point smoothing method for selectively processing original data columns, this paper establishes a group of grey GM(1,1) models to predict the concentration ranges of four major air pollutants in Shanghai from 2023 to 2024. The results indicate that PM₁₀, SO₂, and NO₂ maintain the national Grade I standards, while the concentration of PM₂.₅ has decreased but still remains within the national Grade II standards. Combining the forecast results, recommendations are provided for the Shanghai municipal government's efforts in air pollution prevention and control.

Keywords: atmospheric pollutant prediction, Grey GM(1, 1), model group, three-point smoothing method

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Authors: Hamid Goharnejad, Milad Sadeghpoor Moalem, Mahmood Zakeri Niri, Leili Sadeghi Khalegh Abadi

Abstract:

While there are many benefits to using reservoir dams, their break leads to destructive effects. From the viewpoint of International Committee of Large Dams (ICOLD), dam break means the collapse of whole or some parts of a dam; thereby the dam will be unable to hold water. Therefore, studying dam break phenomenon and prediction of its behavior and effects reduces losses and damages of the mentioned phenomenon. One of the most common types of reservoir dams is embankment dam. Overtopping in embankment dams occurs because of flood discharge system inability in release inflows to reservoir. One of the most important issues among managers and engineers to evaluate the performance of the reservoir dam rim when sliding into the storage, creating waves is large and long. In this study, the effects of floods which caused the overtopping of the dam have been investigated. It was assumed that spillway is unable to release the inflow. To determine outflow hydrograph resulting from dam break, numerical model using Flow-3D software and empirical equations was used. Results of numerical models and their comparison with empirical equations show that numerical model and empirical equations can be used to study the flood resulting from dam break.

Keywords: embankment dam break, empirical equations, Taleghan dam, Flow-3D numerical model

Procedia PDF Downloads 317