Search results for: endogenous switching regression model

Authors: Seyed Hamed Hashemi Sohi, Gerald Jo Denoga

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Machining or metal cutting is one of the most widely used production processes in industry. The quality of the process and the resulting machined product depends on parameters like tool geometry, material, and cutting conditions. However, the relationships of these parameters to the cutting process are often based mostly on empirical knowledge. In this study, computer modeling and simulation using LS-DYNA software and a Smoothed Particle Hydrodynamic (SPH) methodology, was performed on the orthogonal metal cutting process to analyze three-dimensional deformation of AISI 1045 medium carbon steel during machining. The simulation was performed using the following constitutive models: the Power Law model, the Johnson-Cook model, and the Zerilli-Armstrong models (Z-A). The outcomes were compared against the simulated results obtained by Cenk Kiliçaslan using the Finite Element Method (FEM) and the empirical results of Jaspers and Filice. The analysis shows that the SPH method combined with the Zerilli-Armstrong constitutive model is a viable alternative to simulating the metal cutting process. The tangential force was overestimated by 7%, and the normal force was underestimated by 16% when compared with empirical values. The simulation values for flow stress versus strain at various temperatures were also validated against empirical values. The SPH method using the Z-A model has also proven to be robust against issues of time-scaling. Experimental work was also done to investigate the effects of friction, rake angle and tool tip radius on the simulation.

Keywords: metal cutting, smoothed particle hydrodynamics, constitutive models, experimental, cutting forces analyses

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Authors: M. F. Wu, F. T. Cheng

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Leather industry is the most important traditional industry to provide the leather products in the world for thousand years. The fierce global competitive environment and common awareness of global carbon reduction make livestock supply quantities falling, salt and wet blue leather material reduces and the price skyrockets significantly. Exchange rate fluctuation led sales revenue decreasing which due to the differences of export exchanges and compresses the overall profitability of leather industry. This paper applies activity-based benefit assessment approach to build up fitness fur input mixed model, fur is Wet Blue, which concerned with four key factors: the output rate of wet blue, unit cost of wet blue, yield rate and grade level of Wet Blue to achieve the low cost strategy under given unit price of leather product condition of the company. The research findings indicate that applying this model may improve the input cost structure, decrease numbers of leather product inventories and to raise the competitive advantages of the enterprise in the future.

Keywords: activity-based benefit assessment approach, input mixed, output rate, wet blue

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Authors: S. J. Yune, S. Y. Lee, S. J. Im, B. S. Kam, S. Y. Baek

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This study aimed to determine the reliability of clinical performance assessments, having been emphasized by ability-based education, and professors overall assessment methods. We addressed the following problems: First, we try to find out whether there is a difference in what we consider to be the main variables affecting the clinical performance test according to the evaluator’s working period and the number of evaluation experience. Second, we examined the relationship among the global rating score (G), analytic global rating score (Gc), and the sum of the analytical checklists (C). What are the main factors affecting clinical performance assessments in relation to the numbers of times the evaluator had administered evaluations and the length of their working period service? What is the relationship between overall assessment score and analytic checklist score? How does analytic global rating with 6 components in OSCE and 4 components in sub-domains (Gc) CPX: aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude overall assessment score and task-specific analytic checklist score sum (C) affect the professor’s overall global rating assessment score (G)? We studied 75 professors who attended a 2016 Bugyeoung Consortium clinical skills performances test evaluating third and fourth year medical students at the Pusan National University Medical school in South Korea (39 prof. in OSCE, 36 prof. in CPX; all consented to participate in our study). Each evaluator used 3 forms; a task-specific analytic checklist, subsequent analytic global rating scale with sub-6 domains, and overall global scale. After the evaluation, the professors responded to the questionnaire on the important factors of clinical performance assessment. The data were analyzed by frequency analysis, correlation analysis, and hierarchical regression analysis using SPSS 21.0. Their understanding of overall assessment was analyzed by dividing the subjects into groups based on experiences. As a result, they considered ‘precision’ most important in overall OSCE assessment, and ‘precise accuracy physical examination’, ‘systemic approaches to taking patient history’, and ‘diagnostic skill capability’ in overall CPX assessment. For OSCE, there was no clear difference of opinion about the main factors, but there was for CPX. Analytic global rating scale score, overall rating scale score, and analytic checklist score had meaningful mutual correlations. According to the regression analysis results, task-specific checklist score sum had the greatest effect on overall global rating. professors regarded task-specific analytic checklist total score sum as best reflecting overall OSCE test score, followed by aseptic practice, precision, systemic approach, proficiency, successfulness, and attitude on a subsequent analytic global rating scale. For CPX, subsequent analytic global rating scale score, overall global rating scale score, and task-specific checklist score had meaningful mutual correlations. These findings support explanations for validity of professors’ global rating in clinical performance assessment.

Keywords: global rating, clinical performance assessment, medical education, analytic checklist

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Authors: Sara Ramos Contioso

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The premiere of Anton Bruckner's Requiem in Dm, in September 1849, represents a turning point in the composer's creative evolution. This Mass of the Dead, which was dedicated to the memory of his esteemed friend and mentor Franz Sailer, establishes the beginning of a new creative aesthetic in the composer´s production and links its liturgical development, which is contextualized in the monastery of St. Florian, to the use of a range of musicals possibilities that are projected by Bruckner on an orchestral texture with choir and organ. Set on a strict tridentine ritual model, this requiem exemplifies the religious aesthetics of a composer that is committed to the Catholic faith and that also links to its structure the reinterpretation of a religious model that, despite being romantic, shows a strong influence derived from the baroque or the Viennese Classicism language. Consequently, the study responds to the need to show the survival of the Requiem Mass within the romantic context of Vienna. Therefore, it draws on a detailed analysis of the score and the creative context of the composer with the intention of linking the work to the tradition of the genre and also specifying the stylistic particularities of its musical model within a variability of possibilities such as the contrasting precedents of Mozart, Haydn, Cherubini or Berlioz´s requiems. Tradition or modernity, liturgy or concert hall are aesthetic references that will condition the development of the Requiem Mass in the middle of the nineteenth century. In this context, this paper tries to recover Bruckner's Requiem in Dm as a musical model of the romantic ritual of deceased and as a stylistic reference of a creative composition that will condition the development of later liturgical works such as Liszt or DeLange (1868) ones.

Keywords: liturgy, religious symbolism, requiem, romanticism

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Authors: Niyongabo Elyse

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Prefabricated building construction is a pioneering approach that combines design, production, and assembly to attain energy efficiency, environmental sustainability, and economic feasibility. Despite continuous development in the industry in China, the low technical maturity of standardized design, factory production, and construction assembly introduces uncertainties affecting prefabricated component production and on-site assembly processes. This research focuses on enhancing project management performance under uncertainty to help enterprises navigate these challenges and optimize project resources. The study introduces a perspective on how uncertain factors influence the implementation of prefabricated building construction projects. It proposes a theoretical model considering project process management ability, adaptability to uncertain environments, and collaboration ability of project participants. The impact of uncertain factors is demonstrated through case studies and quantitative analysis, revealing constraints on implementation time, cost, quality, and safety. To address uncertainties in prefabricated component production scheduling, a fuzzy model is presented, expressing processing times in interval values. The model utilizes a cooperative co-evolution evolution algorithm (CCEA) to optimize scheduling, demonstrated through a real case study showcasing reduced project duration and minimized effects of processing time disturbances. Additionally, the research addresses on-site assembly construction scheduling, considering the relationship between task processing times and assigned resources. A multi-objective model with fuzzy activity durations is proposed, employing a hybrid cooperative co-evolution evolution algorithm (HCCEA) to optimize project scheduling. Results from real case studies indicate improved project performance in terms of duration, cost, and resilience to processing time delays and resource changes. The study also introduces a multistage dynamic process control model, utilizing IoT technology for real-time monitoring during component production and construction assembly. This approach dynamically adjusts schedules when constraints arise, leading to enhanced project management performance, as demonstrated in a real prefabricated housing project. Key contributions include a fuzzy prefabricated components production scheduling model, a multi-objective multi-mode resource-constrained construction project scheduling model with fuzzy activity durations, a multi-stage dynamic process control model, and a cooperative co-evolution evolution algorithm. The integrated mathematical model addresses the complexity of prefabricated building construction project management, providing a theoretical foundation for practical decision-making in the field.

Keywords: prefabricated construction, project management performance, uncertainty, fuzzy scheduling

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Authors: M. Khairudin

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This paper investigates the system identification and design quantitative feedback theory (QFT) for the robust control of a lathe spindle. The dynamic of the lathe spindle is uncertain and time variation due to the deepness variation on cutting process. System identification was used to obtain the dynamics model of the lathe spindle. In this work, real time system identification is used to construct a linear model of the system from the nonlinear system. These linear models and its uncertainty bound can then be used for controller synthesis. The real time nonlinear system identification process to obtain a set of linear models of the lathe spindle that represents the operating ranges of the dynamic system. With a selected input signal, the data of output and response is acquired and nonlinear system identification is performed using Matlab to obtain a linear model of the system. Practical design steps are presented in which the QFT-based conditions are formulated to obtain a compensator and pre-filter to control the lathe spindle. The performances of the proposed controller are evaluated in terms of velocity responses of the the lathe machine spindle in corporating deepness on cutting process.

Keywords: lathe spindle, QFT, robust control, system identification

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Authors: Tiantian Feng

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There is a dearth of research on the literary circle as a teaching strategy in English as a Foreign Language (EFL) classes in Chinese colleges and universities and even fewer empirical studies on its impacts. In this one-quarter, design-based project, the researcher aims to increase students’ engagement, cooperation, and, on top of that, reading comprehension performance by utilizing a researcher-developed, adapted reading circle model in an EFL reading course at a Chinese college. The model also integrated team-based learning and portfolio assessment, with an emphasis on the specialization of individual responsibilities, contributions, and outcomes in reading projects, with the goal of addressing current issues in EFL classes at Chinese colleges, such as passive learning, test orientation, ineffective and uncooperative teamwork, and lack of dynamics. In this quasi-experimental research, two groups of students enrolled in the course were invited to participate in four in-class team projects, with the intervention class following the adapted literature circle model and team members rotating as Leader, Coordinator, Brain trust, and Reporter. The researcher/instructor used a sequential explanatory mixed-methods approach to quantitatively analyze the final grades for the pre-and post-tests, as well as individual scores for team projects and will code students' artifacts in the next step, with the results to be reported in a subsequent paper(s). Initial analysis showed that both groups saw an increase in final grades, but the intervention group enjoyed a more significant boost, suggesting that the adapted reading circle model is effective in improving students’ reading comprehension performance. This research not only closes the empirical research gap of literature circles in college EFL classes in China but also adds to the pool of effective ways to optimize reading comprehension performance and class performance in college EFL classes.

Keywords: literature circle, EFL teaching, college english reading, reading comprehension

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Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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Authors: Amin Ardali, Mohammadreza Khalili, Mohammadreza Rezai

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In this paper, dynamic response of thin smart composite panel subjected to low-velocity transverse impact is investigated. Shape memory wires are used to reinforced curved composite panel in a smart way. One-dimensional thermodynamic constitutive model by Liang and Rogers is used for estimating the structural recovery stress. The two degrees-of-freedom mass-spring model is used for evaluation of the contact force between the curved composite panel and the impactor. This work is benefited from the Hertzian linear contact model which is linearized for the impact analysis of curved composite panel. The governing equations of curved panel are provided by first-order shear theory and solved by Fourier series related to simply supported boundary condition. For this purpose, the equation of doubly curved panel motion included the uniform in-plane forces is obtained. By the present analysis, the curved panel behavior under low-velocity impact, and also the effect of the impact parameters, the shape memory wire and the curved panel dimensions are studied.

Keywords: doubly curved shell, SMA wire, impact response, smart material, shape memory alloy

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Authors: U. Yavas, M. Gokasan

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Control of diesel engine’s air path has drawn a lot of attention due to its multi input-multi output, closed coupled, non-linear relation. Today, precise control of amount of air to be combusted is a must in order to meet with tight emission limits and performance targets. In this study, passenger car size diesel engine is modeled by AVL Boost RT, and then simulated with standard, industry level PID controllers. Finally, linear model predictive control is designed and simulated. This study shows the importance of modeling and control of diesel engines with flexible algorithm development in computer based systems.

Keywords: predictive control, engine control, engine modeling, PID control, feedforward compensation

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Authors: Yusha'u Shu'aibu Baraya, Kah Keng Wong, Nik Soriani Yaacob

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Strobilanthes crispus (S. crispus), is a Malaysian herb locally known as ‘Pecah kaca’ or ‘Jin batu’ which have demonstrated potent anticancer effects in both in vitro and in vivo models. In particular, S. crispus subfraction (SCS) significantly reduced tumor growth in N-methyl-N-Nitrosourea-induced breast cancer rat model. However, there is paucity of information on the effects of SCS in breast cancer metastasis. Thus, in this study, the antimetastatic effects of SCS (100 mg/kg) was investigated following 30 days of treatment in 4T1-induced mammary tumor (n = 5) model. The response to treatment was assessed based on the outcome of the tumour growth, body weight and hematological parameters. The results demonstrated that tumor bearing mice treated with SCS (TM-S) had significant (p<0.05) reduction in the mean tumor number and tumor volume as well as tumor weight compared to the tumor bearing mice (TM), i.e. tumor untreated group. Also, there was no secondary tumor formation or tumor-associated lesions in the major organs of TM-S compared to the TM group. Similarly, comparable body weights were observed among the TM-S, normal (uninduced) mice treated with SCS and normal (untreated/control) mice (NM) groups compared to the TM group (p<0.05). Furthermore, SCS administration does not cause significant changes in the hematological parameters as compared to the NM group, which indicates no sign of anemia and toxicity related effects. In conclusion, SCS significantly inhibited the overall tumor growth and metastasis in 4T1-induced breast cancer mouse model suggesting its promising potentials as therapeutic agent for breast cancer treatment.

Keywords: 4T1-cells, breast cancer, metastasis, Strobilanthes crispus

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Authors: Tingyu Zhang

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The horizontal ecological compensation (HEC) mechanism is the key to stimulating the active participation of the whole basin in ecological protection. In this paper, we construct an evolutionary model for HEC in the Yangtze River Economic Belt (YREB) basin with the introduction of the central government constraint and incentive mechanism (CGCIM) and explore the conditions for the realization of a (Protection and compensation) strategy that meets the social expectations. Further, the water quality-water quantity model is utilized to measure the HEC amount with the characteristic factual data of the YREB in 2020-2022. The results show that the stability of the evolutionary game model of upstream and downstream governments in the YREB is closely related to the CGCIM. If (Protection Compensation) is to be realized as the only evolutionary stable strategy of the evolutionary game system composed of upstream and downstream governments, it is necessary for the CGCIM to satisfy that the sum of the incentives for the protection side and its unilateral or bilateral constraints is greater than twice the input cost of the active strategy, and the sum of the incentives for the compensation side and its unilateral or bilateral constraints is greater than the amount of ecological compensation that needs to be paid by it when it adopts the active strategy. At this point, the total amount of HEC that the downstream government should give to the upstream government of the YREB is 2856.7 million yuan in 2020, 5782.1 million yuan in 2021, and 23166.7 million yuan in 2022. The results of the study can provide a reference for promoting the improvement and refinement of the HEC mechanism in the YREB.

Keywords: horizontal ecological compensation, Yangtze river economic belt, evolutionary game analysis, water quality and quantity model research on territorial ecological restoration in Mianzhu city, Sichuan, under the dual evaluation framework

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Authors: Touhami Tahenni

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Excessively wide cracks are harmful to the serviceability of reinforced concrete (RC) beams and may lead to durability problems in the longer term. They also reduce the rigidity of RC sections, rendering the tensile concrete ineffective structurally. To reduce the negative effects of cracks, steel fibers are added to concrete mixes in the same manner as aggregates. In the present work, steel fibers reinforced concrete (SFRC) beams, made of normal strength and high strength concretes, were tested in a four-point bending test using a digital image correlation technique. The beams had different volume fractions of fibres and different aspect ratios (fiber length/fiber diameter). The evaluation of flexural cracking widths was determined using Gom-Aramis software. The experimental crack widths were compared with theoretical values predicted by the technical document of Rilem TC 162-TDF. The model proposed in this document seems to be the only one that considers the efficiency of steel fibres in restraining the crack widths. However, the model of Rilem takes into account only the aspect ratio of steel fibres to predict the crack width of SFRC beams. It has been reported in several pieces of research that the contribution of steel fibres to the limitation of flexural cracking widths is based on three essential parameters namely, the volume fraction, the orientation and the aspect ratio of fibres. Referring to the literature on the flexural cracking behavior of SFRC beams and the experimental observations of the present work, a correction of the Rilem model by the introduction of these parameters in the formula is proposed. The crack widths predicted by the new empirical model were compared with the experimental results and assessed against other test data on SFRC beams taken from the literature. The modified Rilem model gives better results and is found more satisfactory in predicting the crack widths of fibres concrete.

Keywords: stee fibres, reinforced concrete, flexural cracking, tensile strength, crack width

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Authors: Nana Kojo Ayimadu Baafi, Kwesi Amponsah-Tawiah

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The study investigated the relationship between job-related anxiety and employee creativity. The study further explored the role of job resources in moderating the relationship between job-related anxiety and employee creativity within the oil and gas industries. The study utilized a cross-sectional survey design. A non-probability sampling technique, specifically convenience sampling, was used to sample 1200 participants from multiple companies within the oil and gas industries. The collected data were analyzed using Regression analysis and PROCESS macro for the moderation analysis. The study empirically demonstrated a negative significant relationship between job-related anxiety and employee creativity. It also exhibited that job resources moderated the relationship between job-related anxiety and creativity. This study addresses gaps in previous studies by highlighting the significance of job resources in how job-related anxiety affects employee creativity.

Keywords: employee creativity, job-related anxiety, job resource, human resources

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Authors: F. Boudet, V. Galano, D. Gmira, L. Munoz, A. Reina

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Commodities pricing needs a specific approach as they are often linked to each other and so are expectedly doing their prices. They are called co-integrated when at least one stationary linear combination exists between them. Though widespread in economic literature, and even if many equilibrium relations and co-movements exist in the economy, this principle of co-movement is not developed in derivatives field. The present study focuses on the following problem: How can the price of a forward agreement on a commodity be simulated, when it is co-integrated with other ones? Theoretical analysis is developed from Gibson-Schwartz model and an analytical solution is given for short maturities contracts and under risk-neutral conditions. The application has been made to crude oil and heating oil energy commodities and result confirms the applicability of proposed method.

Keywords: co-integration, commodities, forward pricing, Gibson-Schwartz

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Authors: K. Boumediene, S. E. Belhenniche

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This article presents a numerical analysis of a turbulent flow past DTMB 4119 marine propeller by the means of RANS approach; the propeller designed at David Taylor Model Basin in USA. The purpose of this study is to predict the hydrodynamic performance of the marine propeller, it aims also to compare the results obtained with the experiment carried out in open water tests; a periodical computational domain was created to reduce the unstructured mesh size generated. The standard kw turbulence model for the simulation is selected; the results were in a good agreement. Therefore, the errors were estimated respectively to 1.3% and 5.9% for KT and KQ.

Keywords: propeller flow, CFD simulation, RANS, hydrodynamic performance

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Authors: Betül Özgenç, Soner Kuşlu, Sabri Çolak, Turan Çalban

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The aim of this study was investigate the leaching kinetics of ulexite in disodium hydrogen phosphate solutions in a mechanical agitation system. Reaction temperature, concentration of disodium hydrogen phosphate solutions, stirring speed, solid/liquid ratio and ulexite particle size were selected as parameters. The experimental results were successfully correlated by linear regression using Statistica program. Dissolution curves were evaluated shrinking core models for solid-fluid systems. It was observed that increase in the reaction temperature and decrease in the solid/liquid ratio causes an increase the dissolution rate of ulexite. The activation energy was found to be 63.4 kJ/mol. The leaching of ulexite was controlled by chemical reaction.

Keywords: ulexite, disodium hydrogen phosphate, leaching kinetics

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Authors: Najibullah M, Soumendra Nath Kuiry

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Dams and reservoirs are perceived for their estimable alms to irrigation, water supply, flood control, electricity generation, etc. which civilize the prosperity and wealth of society across the world. Meantime the dam breach could cause devastating flood that can threat to the human lives and properties. Failures of large dams remain fortunately very seldom events. Nevertheless, a number of occurrences have been recorded in the world, corresponding in an average to one to two failures worldwide every year. Some of those accidents have caused catastrophic consequences. So it is decisive to predict the dam break flow for emergency planning and preparedness, as it poses high risk to life and property. To mitigate the adverse impact of dam break, modeling is necessary to gain a good understanding of the temporal and spatial evolution of the dam-break floods. This study will mainly deal with one-dimensional (1D) dam break modeling. Less commonly used in the hydraulic research community, another possible option for modeling the rapidly varied dam-break flows is the extended Boussinesq equations (BEs), which can describe the dynamics of short waves with a reasonable accuracy. Unlike the Shallow Water Equations (SWEs), the BEs taken into account the wave dispersion and non-hydrostatic pressure distribution. To capture the dam-break oscillations accurately it is very much needed of at least fourth-order accurate numerical scheme to discretize the third-order dispersion terms present in the extended BEs. The scope of this work is therefore to develop an 1D fourth-order accurate in both space and time Boussinesq model for dam-break flow analysis by using finite-volume / finite difference scheme. The spatial discretization of the flux and dispersion terms achieved through a combination of finite-volume and finite difference approximations. The flux term, was solved using a finite-volume discretization whereas the bed source and dispersion term, were discretized using centered finite-difference scheme. Time integration achieved in two stages, namely the third-order Adams Basforth predictor stage and the fourth-order Adams Moulton corrector stage. Implementation of the 1D Boussinesq model done using PYTHON 2.7.5. Evaluation of the performance of the developed model predicted as compared with the volume of fluid (VOF) based commercial model ANSYS-CFX. The developed model is used to analyze the risk of cascading dam failures similar to the Panshet dam failure in 1961 that took place in Pune, India. Nevertheless, this model can be used to predict wave overtopping accurately compared to shallow water models for designing coastal protection structures.

Keywords: Boussinesq equation, Coastal protection, Dam-break flow, One-dimensional model

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Authors: Pirakorn Sukonthaman, Paphitchaya Temphattharachok, Warangkana Thammasanya, Kraichart Tantrakarnarpa, Tanongson Tientavorn

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Agriculture is the main occupation in Thailand. Excessive amount of pesticides are used to increase the products but are toxic to human body. In 2009, Bureau of Epidemiology received 1,691 cases reported with pesticides toxicity (2.66:100,000) which 10.61 % of them is caused by Organophosphate. The purposes are to find factors associated with pesticides used and plasma cholinesterase level and other emerging issues that previous studies did not explain among agricultural workers in Baan Na Yao, Chachoengsao, Thailand. This research was an exploratory mixed method study. Qualitative interviews and quantitative questionnaires were used together in order to gather information from the agricultural workers (mainly cassava and rice farming) directly exposed to pesticides within 2 months simultaneously. Qualitative participants were selected by purposive sampling and a total survey for quantitative ones. The quantitative data was statistically analyzed by using multiple logistic regression model. Qualitative data was transcribed verbatim and thematically analyzed. For qualitative study, 15 participants were interviewed and 300/323 participants (92.88%) were given questionnaires, of which were 175 male and 125 female and 113 among them were spraymen. The prevalence of abnormal plasma cholinesterase level was 92.28% (Safe 7.72% Risky 49.33% and Unsafe 42.95%). Participants with inappropriate behaviors during spraying had a significant association with plasma cholinesterase level (95%CI=1.399-14.858) but other factors such as age, gender, education, attitude and knowledge had no association. They also had encountered various symptoms from pesticides such as fatigue (61%), vertigo (59.67%) and headache (58.86%), etc. Although they had high knowledge and attitude they still had poor behaviors. Moreover, our qualitative component showed that though they had worn the personal protective equipment (PPE) regularly, their PPE was not standard. Not only substandard PPE, but also there were obstacles of wearing such as the hot climate and inconvenience. They misunderstood their symptoms from using pesticides as allergy. Therefore, they did not seek for proper medical check-ups and treatment. This research revealed almost all of the participants have abnormal levels of plasma cholinesterase related especially those with poor behaviors. They also wore PPE but inadequately and misunderstood the symptoms produced by organophosphate use as allergy. Therefore, they did not seek for medical treatment. Occupation health education, modification of PPE and periodic medical checking are ways to make agricultural workers concern and know if there is any progression in a long term.

Keywords: pesticides, plasma cholinesterase level, spraymen, agricultural workers

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Authors: Anand Malik

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The Himalayas with high tectonic activities poses a great threat to human life and property. Climate change is another reason which triggering extreme events multiple fold effect on high mountain glacial environment, rock falls, landslides, debris flows, flash flood and snow avalanches. One such extreme event of cloud burst along with breach of moraine dammed Chorabri Lake occurred from June 14 to June 17, 2013, triggered flooding of Saraswati and Mandakini rivers in the Kedarnath Valley of Rudraprayag district of Uttrakhand state of India. As a result, huge volume of water with its high velocity created a catastrophe of the century, which resulted into loss of large number of human/animals, pilgrimage, tourism, agriculture and property. Thus a comprehensive assessment of debris flow hazards requires GIS-based modeling using numerical methods. The aim of present study is to focus on analysis and mapping of debris flow movements using geospatial data with flow-r (developed by team at IGAR, University of Lausanne). The model is based on combined probabilistic and energetic algorithms for the assessment of spreading of flow with maximum run out distances. Aster Digital Elevation Model (DEM) with 30m x 30m cell size (resolution) is used as main geospatial data for preparing the run out assessment, while Landsat data is used to analyze land use land cover change in the study area. The results of the study area show that model can be applied with great accuracy as the model is very useful in determining debris flow areas. The results are compared with existing available landslides/debris flow maps. ArcGIS software is used in preparing run out susceptibility maps which can be used in debris flow mitigation and future land use planning.

Keywords: debris flow, geospatial data, GIS based modeling, flow-R

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Authors: Danika Pieters

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Due to changing societal and economic demands, organizational change has become increasingly prevalent in work life. While a long time change research has focused on the effects of single discrete change events on different employee outcomes such as job satisfaction and organizational commitment, a nascent research stream has begun to look into the potential cumulative effects of change in the context of continuous intense reforms. This case study of a large Belgian public organization aims to add to this growing literature by examining how the frequency and diversity of past changes impact employees’ appraisals of a newly introduced change. Twelve hundred survey results were analyzed using standard ordinary least squares regression. Results showed a correlation between high past change frequency and diversity and a negative appraisal of the new change. Implications for practitioners and future research are discussed.

Keywords: change frequency, change diversity, organizational changes, change appraisal, change evaluation

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Authors: Noha A. Alowedi

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This paper proposes a Translator Career Path (TCP) which is based on the Dreyfus Model of Skills Acquisition as the conceptual framework. In this qualitative study, the methodology to collect and analyze the data takes an inductive approach that draws upon the literature to form the criteria for the different steps in the TCP. This path is based on descriptors of expert translator performance and best employees’ practice documented in the literature. Each translator skill will be graded as novice, advanced beginner, competent, proficient, and expert. Consequently, five levels of translator performance are identified in the TCP as five ranks. The first rank is the intern translator, which is equivalent to the novice level; the second rank is the assistant translator, which is equivalent to the advanced beginner level; the third rank is the associate translator, which is equivalent to the competent level; the fourth rank is the translator, which is equivalent to the proficient level; finally, the fifth rank is the expert translator, which is equivalent to the expert level. The main function of this career path is to guide the processes of translator development in translation organizations. Although it is designed primarily for the need of in-house translators’ supervisors, the TCP can be used in academic settings for translation trainers and teachers.

Keywords: Dreyfus model, translation organization, translator career path, translator development, translator evaluation, translator promotion

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Authors: Sungjun Hong, Yanghon Chung, Nyunbae Park, Sangyong Park

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South Korea, as the 7th largest greenhouse gas emitting country in 2011, announced that the national reduction target of greenhouse gas emissions was 30% based on BAU (Business As Usual) by 2020. And the reduction rate of the transport sector is 34.3% which is the highest figure among all sectors. This paper attempts to analyze the environmental effect on deploying the green cars in Korean road transport sector. In order to calculate the greenhouse gas emissions, the LEAP model is applied in this study.

Keywords: green car, greenhouse gas, LEAP model, road transport sector

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Authors: Ritesh Kumar, Rajendra Pamula

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In this paper, we present our contribution for book recommendation. In our experiment, we combine the results of Sequential Dependence Model (SDM) and exploitation of book information such as reviews, tags and ratings. This social information is assigned by users. For this, we used CLEF-2016 Social Book Search Track Suggestion task. Finally, our proposed method extensively evaluated on CLEF -2015 Social Book Search datasets, and has better performance (nDCG@10) compared to other state-of-the-art systems. Recently we got the good performance in CLEF-2016.

Keywords: sequential dependence model, social information, social book search, query expansion

Procedia PDF Downloads 285

Authors: Rakesh Kumar, A. K. Ghosh

Abstract:

The paper presents the modeling of linear and nonlinear longitudinal aerodynamics using real flight data of Hansa-3 aircraft gathered at low and high angles of attack. The Neural-Gauss-Newton (NGN) method has been applied to model the linear and nonlinear longitudinal dynamics and estimate parameters from flight data. Unsteady aerodynamics due to flow separation at high angles of attack near stall has been included in the aerodynamic model using Kirchhoff’s quasi-steady stall model. NGN method is an algorithm that utilizes Feed Forward Neural Network (FFNN) and Gauss-Newton optimization to estimate the parameters and it does not require any a priori postulation of mathematical model or solving of equations of motion. NGN method was validated on real flight data generated at moderate angles of attack before application to the data at high angles of attack. The estimates obtained from compatible flight data using NGN method were validated by comparing with wind tunnel values and the maximum likelihood estimates. Validation was also carried out by comparing the response of measured motion variables with the response generated by using estimates a different control input. Next, NGN method was applied to real flight data generated by executing a well-designed quasi-steady stall maneuver. The results obtained in terms of stall characteristics and aerodynamic parameters were encouraging and reasonably accurate to establish NGN as a method for modeling nonlinear aerodynamics from real flight data at high angles of attack.

Keywords: parameter estimation, NGN method, linear and nonlinear, aerodynamic modeling

Procedia PDF Downloads 440

Authors: Eda Yakit Ak, Ergül Aslan

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The study was conducted using the quasi-experimental design to determine the influence of the nursing support program prepared according to the Health Belief Model on reproductive health behaviors of orthopedically disabled women in the physical therapy and rehabilitation clinic at a university hospital between August 2019-October, 2020. The research sample included 50 women (35 in the control group and 15 in the experimental group with orthopedic disability). A 3-week nursing support program was applied to the experimental group of women. To collect the data, Introductory Information Form and Scale for Determining the Protective Attitudes of Married Women towards Reproductive Health (SDPAMW) were applied. The evaluation was made with a follow-up form for four months. In the first evaluation, the total SDPAMW scores were 119.93±20.59 for the experimental group and 122.20±16.71 for the control group. In the final evaluation, the total SDPAMW scores were 144.27±11.95 for the experimental group and 118.00±16.43 for the control group. The difference between the groups regarding the first and final evaluations for the total SDPAMW scores was statistically significant (p<0.01). In the experimental group, between the first and final evaluations regarding the sub-dimensions of SDPAMW, an increase was found in the behavior of seeing the doctor on reproductive health issues, protection from reproductive organ and breast cancer, general health behaviors to protect reproductive health, and protection from genital tract infections (p<0.05). Consequently, the nursing support program based on the Health Belief Model applied to orthopedically disabled women positively affected reproductive health behaviors.

Keywords: orthopedically disabled, woman, reproductive health, nursing support program, health belief model

Procedia PDF Downloads 141

Authors: Nada Souissi, Mourad Mroua

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The main purpose of this study is to examine the interaction between financial asset volatility, economic factors and investor's behavioral indicators related to both the company's and the markets stocks for the period from January 2000 to January2020. Using multiple linear regression and Bayesian Networks modeling, results show a positive and negative relationship between investor's psychology index, economic factors and predicted stock market return. We reveal that the application of the Bayesian Discrete Network contributes to identify the different cause and effect relationships between all economic, financial variables and psychology index.

Keywords: Financial asset return predictability, Economic factors, Investor's psychology index, Bayesian approach, Probabilistic networks, Parametric learning

Procedia PDF Downloads 140

Authors: Amornchai Challcharoenwattana, Chanathip Pharino

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Rising amount of MSW every day, maximizing material diversions from landfills via recycling is a prefer method to land dumping. Characteristic of Thai MSW is classified as 40 -60 per cent compostable wastes while potentially recyclable materials in waste streams are composed of plastics, papers, glasses, and metals. However, rate of material recovery from MSW, excluding composting or biogas generation, in Thailand is still low. Thailand’s recycling rate in 2010 was only 20.5 per cent. Central government as well as local governments in Thailand have tried to curb this problem by charging some of MSW management fees at the users. However, the fee is often too low to promote MSW minimization. The objective of this paper is to identify levels of willingness-to-pay (WTP) for MSW recycling in different social structures with expected outcome of sustainable MSW managements for different town settlements to maximize MSW recycling pertaining to each town’s potential. The method of eliciting WTP is a payment card. The questionnaire was deployed using online survey during December 2012. Responses were categorized into respondents living in Bangkok, living in other municipality areas, or outside municipality area. The responses were analysed using descriptive statistics, and multiple linear regression analysis to identify relationships and factors that could influence high or low WTP. During the survey period, there were 168 filled questionnaires from total 689 visits. However, only 96 questionnaires could be usable. Among respondents in the usable questionnaires, 36 respondents lived in within the boundary of Bangkok Metropolitan Administration while 45 respondents lived in the chartered areas that were classified as other municipality but not in BMA. Most of respondents were well-off as 75 respondents reported positive monthly cash flow (77.32%), 15 respondents reported neutral monthly cash flow (15.46%) while 7 respondent reported negative monthly cash flow (7.22%). For WTP data including WTP of 0 baht with valid responses, ranking from the highest means of WTP to the lowest WTP of respondents by geographical locations for good MSW management were Bangkok (196 baht/month), municipalities (154 baht/month), and non-urbanized towns (111 baht/month). In-depth analysis was conducted to analyse whether there are additional room for further increase of MSW management fees from the current payment that each correspondent is currently paying. The result from multiple-regression analysis suggested that the following factors could impacts the increase or decrease of WTP: incomes, age, and gender. Overall, the outcome of this study suggests that survey respondents are likely to support improvement of MSW treatments that are not solely relying on landfilling technique. Recommendations for further studies are to obtain larger sample sizes in order to improve statistical powers and to provide better accuracy of WTP study.

Keywords: MSW, willingness to pay, payment card, waste seperation

Procedia PDF Downloads 284

Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

Procedia PDF Downloads 138

Authors: Yuanhao Gao, Pin Lin, Kees Weijer

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In this paper, we will determine the external body force distribution with analysis of stokes fluid motion using mathematical modelling and numerical approaching. The body force distribution is regarded as the unknown variable and could be determined by the idea of optimal control theory. The Stokes flow motion and its velocity are generated by given forces in a unit square domain. A regularized objective functional is built to match the numerical result of flow velocity with the generated velocity data. So that the force distribution could be determined by minimizing the value of objective functional, which is also the difference between the numerical and experimental velocity. Then after utilizing the Lagrange multiplier method, some partial differential equations are formulated consisting the optimal control system to solve. Finite element method and conjugate gradient method are used to discretize equations and deduce the iterative expression of target body force to compute the velocity numerically and body force distribution. Programming environment FreeFEM++ supports the implementation of this model.

Keywords: optimal control model, Stokes equation, finite element method, conjugate gradient method

Procedia PDF Downloads 397