Search results for: behavioral modeling

Authors: Fawzi Srairi, Abderrahmane Dib

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Recently, the desire for a self-powered micro and nanodevices has attracted a great interest of using sustainable energy sources. Further, the ultimate goal of nanogenerator is to harvest energy from the ambient environment in which a self-powered device based on these generators is needed. With the development of nanogenerator-based circuits design and optimization, the building of new device simulator is necessary for the study and the synthesis of electromechanical parameters of this type of models. In the present article, both numerical modeling and optimization of piezoelectric nanogenerator based on zinc oxide have been carried out. They aim to improve the electromechanical performances, robustness, and synthesis process for nanogenerator. The proposed model has been developed for a systematic study of the nanowire morphology parameters in stretching mode. In addition, heuristic optimization technique, namely, particle swarm optimization has been implemented for an analytic modeling and an optimization of nanogenerator-based process in stretching mode. Moreover, the obtained results have been tested and compared with conventional model where a good agreement has been obtained for excitation mode. The developed nanogenerator model can be generalized, extended and integrated into simulators devices to study nanogenerator-based circuits.

Keywords: electrical potential, heuristic algorithms, numerical modeling, nanogenerator

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Authors: Abeer Samy, Oliver C. Saavedra Valeriano, Abdelazim Negm

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The Blue Nile Basin is the most important tributary of the Nile River. Egypt and Sudan are almost dependent on water originated from the Blue Nile. This multi-dependency creates conflicts among the three countries Egypt, Sudan, and Ethiopia making the management of these conflicts as an international issue. Good assessment of the water resources of the Blue Nile is an important to help in managing such conflicts. Hydrological models are good tool for such assessment. This paper presents a critical review of the nature and variability of the climate and hydrology of the Blue Nile Basin as a first step of using hydrological modeling to assess the water resources of the Blue Nile. Many several attempts are done to develop basin-scale hydrological modeling on the Blue Nile. Lumped and semi distributed models used averages of meteorological inputs and watershed characteristics in hydrological simulation, to analyze runoff for flood control and water resource management. Distributed models include the temporal and spatial variability of catchment conditions and meteorological inputs to allow better representation of the hydrological process. The main challenge of all used models was to assess the water resources of the basin is the shortage of the data needed for models calibration and validation. It is recommended to use distributed model for their higher accuracy to cope with the great variability and complexity of the Blue Nile basin and to collect sufficient data to have more sophisticated and accurate hydrological modeling.

Keywords: Blue Nile Basin, climate change, hydrological modeling, watershed

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Authors: Waqas Mehdi, Muhammad Umar Hassan, Khadeeja Mustafa

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Objective: Post-concussion syndrome (PCS) is a medical term used to point out the complicated combination of physical, emotional, cognitive and behavioral signs and symptoms associated with Mild Traumatic Brain Injury(mTBI). This study was conducted to assess the improvement or debilitating effect of behavioral therapy in addition to the conventional treatment and to document these results for increasing the efficiency of treatment provided to such cases. Method: This was primarily an interventional prospective cohort study which was conducted in the Department of Neurosurgery, Mayo Hospital Lahore. The sample size was 200 patients who were randomly distributed into two groups. The interventional group with Cognitive behavioral therapy was added in addition to the conventional treatment regimen and the Control group receiving only conventional treatment. Results were noted initially as well as after two weeks of the follow-up period. Data were subsequently analyzed by Statistical Package for Social Sciences (SPSS) software and associations worked out. Result and conclusion: Among the patients that were given therapy sessions along with conventional medicine, there was a significant improvement in the symptoms and their overall quality of life. It is also important to notice that the time period taken for these effects to wane is cut down by psychiatric solutions too. So we can conclude that CBT sessions not only speed up recovery in patients with post-concussion syndrome they also aid in the efficiency improvement in functional capability and quality of life.

Keywords: neurosurgery, CBT, PCS, mTBI

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Authors: M. Fathi, Z. Farhaninejad, M. Shahedi, M. Sadeghi

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Drying is one of the oldest preservation methods for food and agriculture products. Appropriate control of operation can be obtained by modeling. Limitation of continues models for complex boundary condition and non-regular geometries leading to appearance of discrete novel methods such as cellular automata, which provides a platform for obtaining fast predictions by rule-based mathematics. In this research a one D dimensional CA was used for simulating thin layer drying of banana. Banana slices were dried with a convectional air dryer and experimental data were recorded for validating of final model. The model was programmed by MATLAB, run for 70000 iterations and von-Neumann neighborhood. The validation results showed a good accordance between experimental and predicted data (R=0.99). Cellular automata are capable to reproduce the expected pattern of drying and have a powerful potential for solving physical problems with reasonable accuracy and low calculating resources.

Keywords: banana, cellular automata, drying, modeling

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Authors: Leal Leonardo, Pires Carlos Augusto de Moraes, Casiraghi Magela

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In this work were realized the modeling and simulation of the catalytic reformer process, of ample form, considering all the equipment that influence the operation performance. Considered it a semi-regenerative reformer, with four reactors in series intercalated with four furnaces, two heat exchanges, one product separator and one recycle compressor. A simplified reactional system was considered, involving only ten chemical compounds related through five reactions. The considered process was the applied to aromatics production (benzene, toluene, and xylene). The models developed to diverse equipment were interconnecting in a simulator that consists of a computer program elaborate in FORTRAN 77. The simulation of the global model representative of reformer unity achieved results that are compatibles with the literature ones. It was then possible to study the effects of operational variables in the products concentration and in the performance of the unity equipment.

Keywords: catalytic reforming, modeling, simulation, petrochemical engineering

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Authors: Nasrin Akter, Prem Chhetri, Shams Rahman

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The present study tested Ajzen’s Theory of Planned Behavior (TPB) model to explain the formation of business customers’ intention to use 3PL services in Bangladesh. The findings show that the TPB model has a good fit to the data. Based on theoretical support and suggested modification indices, a refined TPB model was developed afterwards which provides a better predictive power for intention. Consistent with the theory, the results of a structural equation analysis revealed that the intention to use 3PL services is predicted by attitude and subjective norms but not by perceived behavioral control. Further investigation indicated that the paths between (attitude and intention) and (subjective norms and intention) did not statistically differ between 3PL user and non-user. Findings of this research provide an evidence base to formulate business strategies to increase the use of 3PL services in Bangladesh to enhance productivity and to gain economic efficiency.

Keywords: Bangladesh, intention, third-party logistics, Theory of Planned Behavior

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Authors: Yudhajit Datta

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Will is a phenomenon that has puzzled humanity for a long time. It is a belief that Will Power of an individual affects the success achieved by an individual in life. It is thought that a person endowed with great will power can overcome even the most crippling setbacks of life while a person with a weak will cannot make the most of life even the greatest assets. Behavioral aspects of the human experience such as will are rarely subjected to quantitative study owing to the numerous uncontrollable parameters involved. This work is an attempt to subject the phenomena of will to the test of an artificial neural network. The claim being tested is that will power of an individual largely determines success achieved in life. In the study, an attempt is made to incorporate the behavioral phenomenon of will into a computational model using data pertaining to the success of individuals obtained from an experiment. A neural network is to be trained using data based upon part of the model, and subsequently used to make predictions regarding will corresponding to data points of success. If the prediction is in agreement with the model values, the model is to be retained as a candidate. Ultimately, the best-fit model from among the many different candidates is to be selected, and used for studying the correlation between success and will.

Keywords: will power, will, success, apathy factor, random factor, characteristic function, life story

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Authors: B. S.Akhmetov, S. T. Akhmetova, D. N. Nadeyev, V. Yu. Yegorov, V. V. Smogoonov

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Estimated probabilities of errors of the first and second kind for nonideal biometrics-neural transducers 256 outputs, the construction of nomograms based error probability of 'own' and 'alien' from the mathematical expectation and standard deviation of the normalized measures Hamming.

Keywords: modeling, errors, probability, biometrics, neural network, authentication

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Authors: Xiaoqin Wang, Li Yin

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Background and purpose: In many practices, one estimates causal effects arising from a complex stochastic process, where a sequence of treatments are assigned to influence a certain outcome of interest, and there exist time-dependent covariates between treatments. When covariates are plentiful and/or continuous, statistical modeling is needed to reduce the huge dimensionality of the problem and allow for the estimation of causal effects. Recently, Wang and Yin (Annals of statistics, 2020) derived a new general formula, which expresses these causal effects in terms of the point effects of treatments in single-point causal inference. As a result, it is possible to conduct the modeling via point effects. The purpose of the work is to study the modeling of these causal effects via point effects. Challenges and solutions: The time-dependent covariates often have influences from earlier treatments as well as on subsequent treatments. Consequently, the standard parameters – i.e., the mean of the outcome given all treatments and covariates-- are essentially all different (null paradox). Furthermore, the dimension of the parameters is huge (curse of dimensionality). Therefore, it can be difficult to conduct the modeling in terms of standard parameters. Instead of standard parameters, we have use point effects of treatments to develop likelihood-based parametric approach to the modeling of these causal effects and are able to model the causal effects of a sequence of treatments by modeling a small number of point effects of individual treatment Achievements: We are able to conduct the modeling of the causal effects from a sequence of treatments in the familiar framework of single-point causal inference. The simulation shows that our method achieves not only an unbiased estimate for the causal effect but also the nominal level of type I error and a low level of type II error for the hypothesis testing. We have applied this method to a longitudinal study of COVID-19 mortality among Scandinavian countries and found that the Swedish approach performed far worse than the other countries' approach for COVID-19 mortality and the poor performance was largely due to its early measure during the initial period of the pandemic.

Keywords: causal effect, point effect, statistical modelling, sequential causal inference

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Authors: Najmeh Hamid, Vajiheh Hamedy , Zahra Rostamianasl

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Background: Cancer is one of the medical problems that have been associated with pain. Moreover, the pain is combined with negative emotions such as anxiety, depression and anger. Poor pain management causes negative effects on the quality of life, which results in negative effects that continue a long time after the painful experiences. Objectives: The aim of this research was to compare the effectiveness of Common Cognitive Behavioral Therapy for Pain and its computerized version on the reduction of pain intensity, depression, anger and anxiety in children with cancer. Methods: The research method of this “Randomized Controlled Clinical Trial” was a pre, post-test and follow-up with a control group. In this research, we have examined the effectiveness of Common Cognitive Behavioral Therapy for Pain and its computerized version on the reduction of pain intensity, anxiety, depression and anger in children with cancer in Ahvaz. Two psychological interventions (cognitive behavioral therapy for pain and the computerized version) were compared with the control group. The sample consisted of 60 children aged 8 to 12 years old with different types of cancer at Shafa hospital in Ahwaz. According to the including and excluding criteria such as age, socioeconomic status, clinical diagnostic interview and other criteria, 60 subjects were selected. Then, randomly, 45 subjects were selected. The subjects were randomly divided into three groups of 15 (two experimental and one control group). The research instruments included Spielberger Anxiety Inventory (STAY-2) and International Pain Measurement Scale. The first experimental group received 6 sessions of cognitive-behavioral therapy for 6 weeks, and the second group was subjected to a computerized version of cognitive-behavioral therapy for 6 weeks, but the control group did not receive any interventions. For ethical considerations, a version of computerized cognitive-behavioral therapy was provided to them. After 6 weeks, all three groups were evaluated as post-test and eventually after a one-month follow-up. Results: The findings of this study indicated that both interventions could reduce the negative emotions (pain, anger, anxiety, depression) associated with cancer in children in comparison with a control group (p<0.0001). In addition, there were no significant differences between the two interventions (p<0.01). It means both interventions are useful for reducing the negative effects of pain and enhancing adjustment. Conclusion: we can use CBT in situations in which there is no access to psychologists and psychological services. In addition, it can be a useful alternative to conventional psychological interventions.

Keywords: pain, children, psychological intervention, cancer, anger, anxiety, depression

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Authors: Yen-Ting Chiu, Chia-Ying Lin, Pei-Hsuan Ho

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New technologies can help solve the problem of labor shortage and the decline of birthrate. Technologies can improve human’s life and reduce the burden on the staff and bring convenience to people. That’s why unmanned retail store X-Store was established in Taiwan to create more valuable services and shopping experiences based on smart retailing. The purpose of this study is to examine the impact of unmanned stores, X-Store, on customers’ behavioral intentions. It uses the Unified theory of acceptance and use of technology (UTAUT) model as a basis and adds a perceived value factor to explain customer willingness to use the X-Store. In addition, the study further divided the sample into gender and age groups to compare behavioral differences between different groups. The study collected 214 valid questionnaires through online questionnaires. Using SPSS as a statistical analysis tool, the results of the study show that effort expectancy, social influence, facilitating conditions, and perceived value have a significant impact on behavioral intention to use X-Store. However, performance expectancy is not significant. This research concludes with managerial implications and suggestions for retail practitioners.

Keywords: perceived value, smart retailing, unmanned store, UTAUT, X-Store

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Authors: Maryam Safrai, Tewfik Mahdi

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This article presents the stochastic modeling of the Richelieu River flood in Quebec, Canada, occurred in the spring of 2011. With the aid of the one-dimensional Watershed Modeling System (WMS (v.10.1) and HEC-RAS (v.4.1) as a flood simulator, the delineation of the probabilistic flooded areas was considered. Based on the Monte Carlo method, WMS (v.10.1) delineated the probabilistic flooded areas with corresponding occurrence percentages. Furthermore, results of this one-dimensional model were compared with the results of two-dimensional model (SRH-2D) for the evaluation of efficiency and precision of each applied model. Based on this comparison, computational process in two-dimensional model is longer and more complicated versus brief one-dimensional one. Although, two-dimensional models are more accurate than one-dimensional method, but according to existing modellers, delineation of probabilistic flooded areas based on Monte Carlo method is achievable via one-dimensional modeler. The applied software in this case study greatly responded to verify the research objectives. As a result, flood risk maps of the Richelieu River with the two applied models (1d, 2d) could elucidate the flood risk factors in hydrological, hydraulic, and managerial terms.

Keywords: flood modeling, HEC-RAS, model comparison, Monte Carlo simulation, probabilistic flooded area, SRH-2D, WMS

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Authors: Neslihan Sahin Celik, Ali Eraslan

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As a result of PISA (Program for International Student Assessments) survey that tests how well students can apply the knowledge and skills they have learned at school to real-life challenges, the new and redesigned mathematics education programs in many countries emphasize the necessity for the students to face complex and multifaceted problem situations and gain experience in this sense allowing them to develop new skills and mathematical thinking to prepare them for their future life after school. At this point, mathematical models and modeling approaches can be utilized in the analysis of complex problems which represent real-life situations in which students can actively participate. In particular, model eliciting activities that bring about situations which allow the students to create solutions to problems and which involve mathematical modeling must be used right from primary school years, allowing them to face such complex, real-life situations from early childhood period. A qualitative study was conducted in a university foundation primary school in the city center of a big province in 2013-2014 academic years. The participants were 4th grade students in a primary school. After a four-week preliminary study applied to a fourth-grade classroom, three students included in the focus group were selected using criterion sampling technique. A focus group of three students was videotaped as they worked on the Crime Problem. The conversation of the group was transcribed, examined with students’ written work and then analyzed through the lens of Blum and Ferri’s modeling processing cycle. The results showed that primary fourth-grade students can successfully work with model eliciting problem while they encounter some difficulties in the modeling processes. In particular, they developed new ideas based on different assumptions, identified the patterns among variables and established a variety of models. On the other hand, they had trouble focusing on problems and occasionally had breaks in the process.

Keywords: primary school, modeling, mathematical modeling, crime problem

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Authors: David F. Nettleton, Christian Wasiak, Jonas Dorissen, David Gillen, Alexandr Tretyak, Elodie Bugnicourt, Alejandro Rosales

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In this work, preliminary results are given for the modeling and calibration of two inline processes, pultrusion, and laser ablation, using machine learning techniques. The end product of the processes is the core of a medical guidewire, manufactured to comply with a user specification of diameter and flexibility. An ensemble approach is followed which requires training several models. Two state of the art machine learning algorithms are benchmarked: Kernel Recursive Least Squares (KRLS) and Support Vector Regression (SVR). The final objective is to build a precise digital model of the pultrusion and laser ablation process in order to calibrate the resulting diameter and flexibility of a medical guidewire, which is the end product while taking into account the friction on the forming die. The result is an ensemble of models, whose output is within a strict required tolerance and which covers the required range of diameter and flexibility of the guidewire end product. The modeling and automatic calibration of complex in-line industrial processes is a key aspect of the Industry 4.0 movement for cyber-physical systems.

Keywords: calibration, data modeling, industrial processes, machine learning

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Authors: Mohd Zamri Che Wanik

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This paper presents the management of the Fault Ride Through event within a Solar Farm during a grid fault. The modeling and simulation of a photovoltaic (PV) with battery energy storage connected to the power network will be described. The modeling approach and the study analysis performed are described. The model and operation scenarios are simulated using a digital simulator for different scenarios. The dynamic response of the system when subjected to sudden self-clearance temporary fault is presented. The capability of the PV system and battery storage riding through the power system fault and, at the same time, supporting the local grid by injecting fault current is demonstrated. For each case, the different control methods to achieve the objective of supporting the grid according to grid code requirements are presented and explained. The inverter modeling approach is presented and described.

Keywords: faut ride through, solar farm, grid code, power network

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Authors: A. C. Bennis, F. Dumas, F. Ardhuin, B. Blanke

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The mechanics of rip currents are complex, involving interactions between waves, currents, water levels and the bathymetry, that present particular challenges for numerical models. Here, the effects of a grid-spacing dependent horizontal mixing on the wave-current interactions are studied. Near the shore, wave rays diverge from channels towards bar crests because of refraction by topography and currents, in a way that depends on the rip current intensity which is itself modulated by the horizontal mixing. At low resolution with the grid-spacing dependent horizontal mixing, the wave motion is the same for both coupling modes because the wave deviation by the currents is weak. In high-resolution case, however, classical results are found with the stabilizing effect of the flow by feedback of waves on currents. Lastly, wave-current interactions and the horizontal mixing strongly affect the intensity of the three-dimensional rip velocity.

Keywords: numerical modeling, wave-current interactions, turbulence modeling, rip currents

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Authors: Eti Mizrahi, Gizem İntepe

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The geographical location of Turkey that stretches from Asia to Europe and Russia to Africa makes it an important logistics hub in the region. Although logistics is a developing sector in Turkey, the stock market representation is still low with only two companies listed in Turkey’s stock exchange since 2010. In this paper, we use the daily values of these two listed stocks as a benchmark for the logistics sector. After modeling logistics stock prices, an empirical examination is conducted between the existing logistics indices and these stock prices. The paper investigates whether the measures of logistics stocks are correlated with newly available logistics indices. It also shows the reflection of the economic activity in the logistics sector on the stock exchange market. The results presented in this paper are the first analysis of the behavior of logistics indices and logistics stock prices for Turkey.

Keywords: forecasting, logistic stock exchange, modeling, Africa

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Authors: Amal Alatar

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The architectural legacy is considered a significant factor, which left its features on the shape of buildings and historical and archaeological sites all over the world. In this framework, this paper focuses on Umm Qais town, located in Northern Jordan, which includes archaeological remains of the ancient Decapolis city of Gadara, still the witness of the originality and architectural identity of the city. 3D modeling is a public asset and a valuable resource for cultural heritage. This technique allows the possibility to make accurate representations of objects, structures, and surfaces. Hence, these representations increase valuable assets when thinking about cultural heritage. The Heritage Building Information Modeling (HBIM) is considered an effective tool to represent information on Cultural Heritage (CH) which can be used for documentation, restoration, conservation, presentation, and research purposes. Therefore, this paper focus on the interdisciplinary project of the virtualization of the West Theater in Gadara (Umm Qais) for 3D documentation and structural studies. The derived 3D model of the cultural heritage is the basis for further archaeological studies; the challenges of the work stay in the acquisition, processing, and integration of the multi-resolution data as well as their interactive visualization.

Keywords: archaeology, 3D modeling, Umm Qais, culture heritage, Jordan

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Authors: Wardoyo, Humairoh

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In global competition nowadays, the world economy heavily depends upon high technology and capital intensive industries that are mainly owned by well-established economic and developed countries, such as United States of America, United Kingdom, Japan, and South Korea. Indonesia as a developing country is building its economic activities towards industrial country as well, although a slightly different approach was implemented. For example, similar to the concept of one village one product (OVOP) implemented in Japan, Indonesia also adopted this concept by promoting local traditional products to improve incomes of village people and to enhance local economic activities. Analysis on how OVOP program increase local people’s income and influence customer satisfaction were the objective of this paper. Behavioral intention to purchase and re-purchase, customer satisfaction and promotion are key factors for local products to play significant roles in improving local income and economy of the region. The concepts of OVOP and key factors that influence economic activities of local people and the region will be described and explained in the paper. Results of research, in a case study based on 300 respondents, customers of a local restaurant at Tangerang City, Banten Province of Indonesia, indicated that local product, service quality and behavioral intention individually have significant influence to customer satisfaction; whereas simultaneous tests to the variables indicated positive and significant influence to the behavioral intention through customer satisfaction as the intervening variable.

Keywords: behavioral intention, customer satisfaction, local products, one village one product (OVOP)

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Authors: Yuqing Zou, Chunrui Zou, Yichong Cao

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Previous research has revealed relationships between self-efficacy (SE), engagement, and academic achievement among students in Western countries, but these relationships remain unknown in college math courses among college students in China. In addition, previous research has shown that test anxiety has a direct effect on engagement and academic achievement. However, how test anxiety affects the relationships between SE, engagement, and academic achievement is still unknown. In this study, the authors aimed to explore the mediating roles of behavioral engagement (BE), emotional engagement (EE), and cognitive engagement (CE) in the association between SE and academic achievement and the moderating role of test anxiety in college math courses. Our hypotheses are that the association between SE and academic achievement was mediated by engagement and that test anxiety played a moderating role in the association. To explore the research questions, the authors collected data through self-reported surveys among 147 students at a northwestern university in China. Self-reported surveys were used to collect data. The motivated strategies for learning questionnaire (MSLQ) (Pintrich, 1991), the metacognitive strategies questionnaire (Wolters, 2004), and the engagement versus disaffection with learning scale (Skinner et al., 2008) were used to assess SE, CE, and BE and EE, respectively. R software was used to analyze the data. The main analyses used were reliability and validity analysis of scales, descriptive statistics analysis of measured variables, correlation analysis, regression analysis, and structural equation modeling (SEM) analysis and moderated mediation analysis to look at the structural relationships between variables at the same time. The SEM analysis indicated that student SE was positively related to BE, EE, and CE and academic achievement. BE, EE, and CE were all positively associated with academic achievement. That is, as the authors expected, higher levels of SE led to higher levels of BE, EE, and CE, and greater academic achievement. Higher levels of BE, EE, and CE led to greater academic achievement. In addition, the moderated mediation analysis found that the path of SE to academic achievement in the model was as significant as expected, as was the moderating effect of test anxiety in the SE-Achievement association. Specifically, test anxiety was found to moderate the association between SE and BE, the association between SE and CE, and the association between EE and Achievement. The authors investigated possible mediating effects of BE, EE, and CE in the associations between SE and academic achievement, and all indirect effects were found to be significant. As for the magnitude of mediations, behavioral engagement was the most important mediator in the SE-Achievement association. This study has implications for college teachers, educators, and students in China regarding ways to promote academic achievement in college math courses, including increasing self-efficacy and engagement and lessening test anxiety toward math.

Keywords: academic engagement, self-efficacy, test anxiety, academic achievement, college math courses, behavioral engagement, cognitive engagement, emotional engagement

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Authors: Haijie Li, Xuping Zhang

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This paper presents a computationally efficient method for the modeling of robot manipulators with flexible links and joints. This approach combines the Discrete Time Transfer Matrix Method with the Finite Segment Method, in which the flexible links are discretized by a number of rigid segments connected by torsion springs; and the flexibility of joints are modeled by torsion springs. The proposed method avoids the global dynamics and has the advantage of modeling non-uniform manipulators. Experiments and simulations of a single-link flexible manipulator are conducted for verifying the proposed methodologies. The simulations of a three-link robot arm with links and joints flexibility are also performed.

Keywords: flexible manipulator, transfer matrix method, linearization, finite segment method

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Authors: Ismail Seçer

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The purpose of this study is to analyze the relationship between school burnout and academic motivation in high school students. The working group of the study consists of 455 students from the high schools in Erzurum city center, selected with appropriate sampling method. School Burnout Scale and Academic Motivation Scale were used in the study to collect data. Correlation analysis and structural equation modeling were used in the analysis of the data collected through the study. As a result of the study, it was determined that there are significant and negative relations between school burnout and academic motivation, and the school burnout has direct and indirect significant effects on the getting over himself, using knowledge and exploration dimension through the latent variable of academic motivation. Lastly, it was determined that school burnout is a significant predictor of academic motivation.

Keywords: school burnout, motivation, structural equation modeling, university

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Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

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With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: machine learning, imbalanced data, data mining, big data

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Authors: Serge Provost, Abdous Saboor

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A q-analogue of the generalized extreme value distribution which includes the Gumbel distribution is introduced. The additional parameter q allows for increased modeling flexibility. The resulting distribution can have a finite, semi-infinite or infinite support. It can also produce several types of hazard rate functions. The model parameters are determined by making use of the method of maximum likelihood. It will be shown that it compares favourably to three related distributions in connection with the modeling of a certain hydrological data set.

Keywords: extreme value theory, generalized extreme value distribution, goodness-of-fit statistics, Gumbel distribution

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Authors: Ridha Fethi Mechlouch, Ahlem Ayadi, Ammar Ben Brahim

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Given the importance of the preservation of polyphenols and carotenoids during thermal processing, we attempted in this study to investigate the variation of these two parameters in faba beans during microwave treatment using different power densities (1; 2; and 3W/g), then to perform a mathematical modeling by using non-linear regression analysis to evaluate the models constants. The variation of the carotenoids and polyphenols ratio of faba beans and the models are tested to validate the experimental results. Exponential models were found to be suitable to describe the variation of caratenoid ratio (R²= 0.945, 0.927 and 0.946) for power densities (1; 2; and 3W/g) respectively, and polyphenol ratio (R²= 0.931, 0.989 and 0.982) for power densities (1; 2; and 3W/g) respectively. The effect of microwave power density Pd(W/g) on the coefficient k of models were also investigated. The coefficient is highly correlated (R² = 1) and can be expressed as a polynomial function.

Keywords: microwave treatment, power density, carotenoid, polyphenol, modeling

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Authors: An-Na Li, Ying-Yu Chen, Yu-Lung Lin

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Food tourism is one of the growing industries in the tourism industry today. The Destination Marketing Organizations (DMOs) are aware of the importance of gastronomy to stimulate local and regional economic development. From the heritage and cultural aspects, gastronomy is becoming a more important part of the cultural heritage of the region. Heritage destinations provide culinary heritage, which fits the current interest in traditional food, and cuisine is a part of a general desire for authentic experience. However, few studies have empirically examined antecedents of food tourists’ behavioral intentions. This study examined the effects of cuisine experience; emotions, place attachment and tourists’ revisit behavioral intentions. A total of 408 individuals responded to the on-site survey in the historic town of Lu-Kang in Taiwan. The results indicated that tourists’ cuisine experience include place flavor, media recommendation, local learning, life transfer and interpersonal share. In addition, cuisine experience had significant impacts on emotions and place attachment, emotions had significant effects on place attachment, furthermore, which in turn place attachment had significant effects on tourists’ revisit behavioral intentions. The findings suggested that the cuisine experience is a multi-dimensions construct. On the other hands, the good quality of cuisine experience could evoke tourists’ positive emotions and it could play a significant role in promoting tourist revisit intentions or word of mouth. Implications for theory and practice are discussed.

Keywords: culinary tourism, cuisine experiences, emotions, revisit intentions

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Authors: David G. Maxinez, Andrés Ferreyra Ramírez, Liliana Castillo Sánchez, Nancy Adán Mendoza, Carlos Aviles Cruz

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This research describes the use of fuzzy logic in detection, assessment, analysis and evaluation of children with behavioral disorders. It shows how to acquire and analyze ambiguous, vague and full of uncertainty data coming from the input variables to get an accurate assessment result for each of the typologies presented by children with behavior problems. Behavior disorders analyzed in this paper are: hyperactivity (H), attention deficit with hyperactivity (DAH), conduct disorder (TD) and attention deficit (AD).

Keywords: alteration, behavior, centroid, detection, disorders, economic, fuzzy logic, hyperactivity, impulsivity, social

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Authors: Prakash Persad, Kelvin Loutan, Trichelle Seepersad

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The Finite Element Method is commonly used in the analysis of flexible manipulators to predict elastic displacements and develop joint control schemes for reducing positioning error. In order to preserve simplicity, regular geometries, ideal joints and connections are assumed. This paper presents the dynamic FE analysis of a 4- degrees of freedom open chain manipulator, intended for striking a curved 3D surface percussion musical instrument. This was done utilizing the new MultiBody Dynamics Module in COMSOL, capable of modeling the elastic behavior of a body undergoing rigid body type motion.

Keywords: dynamic modeling, entertainment robots, finite element method, flexible robot manipulators, multibody dynamics, musical robots

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Authors: Elizabeth Hoyos, Hernán Alvarez, Diana Lopez, Yesid Montoya

Abstract:

The main goal of this research relates to the modeling of FSW from a different or unusual perspective coming from mechanical engineering, particularly looking for a way to establish process windows by assessing soundness of the joints as a priority and with the added advantage of lower computational time. This paper presents the use of a previously developed model applied to specific aspects of soundness evaluation of AA7075 FSW welds. EMSO software (Environment for Modeling, Simulation, and Optimization) was used for simulation and an adapted CNC machine was used for actual welding. This model based approach showed good agreement with the experimental data, from which it is possible to set a window of operation for commercial aluminum alloy AA7075, all with low computational costs and employing simple quality indicators that can be used by non-specialized users in process modeling.

Keywords: aluminum AA7075, friction stir welding, phenomenological based semiphysical model, processing map

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Authors: Malgorzata Wojcik

Abstract:

Groups are a powerful and significant part of human development. They serve as major emergent microsocial structures in children’s and youth’s ecological system. During middle and secondary school, peer groups become a particularly salient influence. While they promote a range of prosocial and positive emotional and behavioral attributes, they can also elicit negative or antisocial attributes, effectively “bringing out the worst” in some individuals. The grounded theory approach was employed to guide data collection and analysis, as it allows for a deeper understanding of the group processes and students’ perspectives on complex intragroup relations. Students’ perspectives on bullying cases were investigated by observing daily interactions among those involved and interviewing 47 students. The results complement theories of labeling in bullying by showing that all students self-label themselves and find it difficult to break patterns of behaviors related to bullying, such as supporting the bully or not defending the victim. In terms of the practical implications, the findings indicate that it could be beneficial to use non-punitive, restorative anti-bullying interventions that implement peer influence to transform bullying relations by removing behavioral labels.

Keywords: bullying, peer group, victimization, class reputation

Procedia PDF Downloads 117