Search results for: virtual physical model

Authors: Kais Ben-Ahmed, Mhamed Ali-El-Aroui

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This paper develops a Local Generalized Linear Spatial Model (LGLSM) to describe the spatial variation of Visceral Leishmaniasis (VL) infection risk in northern and central Tunisia. The response from each region is a number of affected children less than five years of age recorded from 1996 through 2006 from Tunisian pediatric departments and treated as a poison county level data. The model includes climatic factors, namely averages of annual rainfall, extreme values of low temperatures in winter and high temperatures in summer to characterize the climate of each region according to each continentality index, the pluviometric quotient of Emberger (Q2) to characterize bioclimatic regions and component for residual extra-poison variation. The statistical results show the progressive increase in the number of affected children in regions with high continentality index and low mean yearly rainfull. On the other hand, an increase in pluviometric quotient of Emberger contributed to a significant increase in VL incidence rate. When compared with the original GLSM, Bayesian locally modeling is improvement and gives a better approximation of the Tunisian VL risk estimation. According to the Bayesian approach inference, we use vague priors for all parameters model and Markov Chain Monte Carlo method.

Keywords: generalized linear spatial model, local model, extra-poisson variation, continentality index, visceral leishmaniasis, Tunisia

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Authors: Farhad Salek, Shahaboddin Resalati

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The production of electric vehicles (EVs) featuring lithium-ion battery technology has substantially escalated over the past decade, demonstrating a steady and persistent upward trajectory. The imminent retirement of electric vehicle (EV) batteries after approximately eight years underscores the critical need for their redirection towards recycling, a task complicated by the current inadequacy of recycling infrastructures globally. A potential solution for such concerns involves extending the operational lifespan of electric vehicle (EV) batteries through their utilization in stationary energy storage systems during secondary applications. Such adoptions, however, require addressing the safety concerns associated with batteries’ knee points and thermal runaways. This paper develops an accurate mathematical model representative of the second-life battery packs from a cell-to-pack scale using an equivalent circuit model (ECM) methodology. Neural network algorithms are employed to forecast the degradation parameters based on the EV batteries' aging history to develop a degradation model. The degradation model is integrated with the ECM to reflect the impacts of the cycle aging mechanism on battery parameters during operation. The developed model is tested under real-life load profiles to evaluate the life span of the batteries in various operating conditions. The methodology and the algorithms introduced in this paper can be considered the basis for Battery Management System (BMS) design and techno-economic analysis of such technologies.

Keywords: second life battery, electric vehicles, degradation, neural network

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Authors: Rohini Hariharan, Yazhini R., Blessy Maria Mathew

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The task of detecting email spam is a very important one in the era of digital technology that needs effective ways of curbing unwanted messages. This paper presents an approach aimed at making email spam categorization algorithms transparent, reliable and more trustworthy by incorporating Local Interpretable Model-agnostic Explanations (LIME). Our technique assists in providing interpretable explanations for specific classifications of emails to help users understand the decision-making process by the model. In this study, we developed a complete pipeline that incorporates LIME into the spam classification framework and allows creating simplified, interpretable models tailored to individual emails. LIME identifies influential terms, pointing out key elements that drive classification results, thus reducing opacity inherent in conventional machine learning models. Additionally, we suggest a visualization scheme for displaying keywords that will improve understanding of categorization decisions by users. We test our method on a diverse email dataset and compare its performance with various baseline models, such as Gaussian Naive Bayes, Multinomial Naive Bayes, Bernoulli Naive Bayes, Support Vector Classifier, K-Nearest Neighbors, Decision Tree, and Logistic Regression. Our testing results show that our model surpasses all other models, achieving an accuracy of 96.59% and a precision of 99.12%.

Keywords: text classification, LIME (local interpretable model-agnostic explanations), stemming, tokenization, logistic regression.

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Authors: Xinghui Wu, Chun Yang

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Inertial microfluidics is a competitive fluidic method with applications in separation of particles, cells and bacteria. In contrast to traditional microfluidic devices with low Reynolds number, inertial microfluidics works in the intermediate Re number range which brings about several intriguing inertial effects on particle separation/focusing to meet the throughput requirement in the real-world. Geometric modifications to make channels become irregular shapes can leverage fluid inertia to create complex secondary flow for adjusting the particle equilibrium positions and thus enhance the separation resolution and throughput. Although inertial microfluidics has been extensively studied by experiments, our current understanding of its mechanisms is poor, making it extremely difficult to build rational-design guidelines for the particle focusing locations, especially for irregularly shaped microfluidic channels. Inertial particle microfluidics in irregularly shaped channels were investigated in our group. There are several fundamental issues that require us to address. One of them is about the balance between the inertial lift forces and the secondary drag forces. Also, it is critical to quantitatively describe the dependence of the life forces on particle-particle interactions in irregularly shaped channels, such as a rectangular one. To provide physical insights into the inertial microfluidics in channels of irregular shapes, in this work the immersed boundary-lattice Boltzmann method (IB-LBM) was introduced and validated to explore the transport characteristics and the underlying mechanisms of an inertial focusing single particle in a rectangular microchannel. The transport dynamics of a finitesized particle were investigated over wide ranges of Reynolds number (20 < Re < 500) and particle size. The results show that the inner equilibrium positions are more difficult to occur in the rectangular channel, which can be explained by the secondary flow caused by the presence of a finite-sized particle. Furthermore, force decoupling analysis was utilized to study the effect of each type of lift force on the inertia migration, and a theoretical model for the lateral lift force of a finite-sized particle in the rectangular channel was established. Such theoretical model can be used to provide theoretical guidance for the design and operation of inertial microfluidics.

Keywords: inertial microfluidics, particle focuse, life force, IB-LBM

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Authors: Fadwa Haraka, Ahmad Elouatouati, Mourad Taha Janan

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In this study, we propose a neural network based method in order to calculate the heat source temperature of isotropic plate with lower surface forced cooling. To validate the proposed model, the heat source temperatures values will be compared to the analytical method -variables separation- and finite element model. The mathematical simulation is done through 3D numerical simulation by COMSOL software considering three different materials: Aluminum, Copper, and Graphite. The proposed method will lead to a formulation of the heat source temperature based on the thermal and geometric properties of the base plate.

Keywords: thermal model, thermal resistance, finite element simulation, neural network

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Authors: Natalia Sáez, Dina Shulfman

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There is an important research gap regarding accessible pedagogical techniques for teaching foreign languages to adults with visual impairments. English as a foreign language (EFL), in particular, is needed in many countries to expand occupational opportunities and improve living standards. Within EFL research, teaching and learning prepositions have only recently gained momentum, considering that they constitute one of the most difficult structures to learn in a foreign language and are fundamental for communicating about spatial relations in the world, both on the physical and imaginary levels. Learning to use prepositions would not only facilitate communication when referring to the surrounding tangible environment but also when conveying ideas about abstract topics (e.g., justice, love, society), for which students’ sociocultural knowledge about space could play an important role. By potentiating visually impaired students’ ability to construe mental spatial imagery, this study made efforts to explore pedagogical techniques that cater to their strengths, helping them create new worlds by welcoming and expanding their sociocultural funds of knowledge as they learn to use English prepositions. Fifteen visually impaired adults living in Chile participated in the study. Their first language was Spanish, and they were learning English at the intermediate level of proficiency in an EFL workshop at La Biblioteca Central para Ciegos (The Central Library for the Blind). Within this workshop, a series of activities and interviews were designed and implemented with the intention of uncovering students’ spatial funds of knowledge when learning literal/physical uses of three English prepositions, namely “in,” “at,” and “on”. The activities and interviews also explored whether students used their original spatial funds of knowledge when learning metaphorical uses of these prepositions and if their use of spatial imagery changed throughout the learning activities. Over the course of approximately half a year, it soon became clear that the students construed mental images of space when learning both literal/physical and metaphorical uses of these prepositions. This research could inform a new approach to inclusive language education using pedagogical methods that are relevant and accessible to students with visual impairments.

Keywords: EFL, funds of knowledge, prepositions, spatial cognition, visually impaired students

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Authors: Sung-Won Seo, Jang-Young Choi

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The rare earth magnets used in synchronous generators offer many advantages, including high efficiency, greatly reduced the size, and weight. The permanent magnet linear synchronous generator (PMLSG) allows for direct drive without the need for a mechanical device. Therefore, the PMLSG is well suited to translational applications, such as wave energy converters and free piston energy converters. This manuscript compares the effects of different magnetization patterns on the characteristics of double-sided PMLSGs in slotless stator structures. The Halbach array has a higher flux density in air-gap than the Vertical array, and the advantages of its performance and efficiency are widely known. To verify the advantage of Halbach array, we apply a finite element method (FEM) and analytical method. In general, a FEM and an analytical method are used in the electromagnetic analysis for determining model characteristics, and the FEM is preferable to magnetic field analysis. However, the FEM is often slow and inflexible. On the other hand, the analytical method requires little time and produces accurate analysis of the magnetic field. Therefore, the flux density in air-gap and the Back-EMF can be obtained by FEM. In addition, the results from the analytical method correspond well with the FEM results. The model of the Halbach array reveals less copper loss than the model of the Vertical array, because of the Halbach array’s high output power density. The model of the Vertical array is lower core loss than the model of Halbach array, because of the lower flux density in air-gap. Therefore, the current density in the Vertical model is higher for identical power output. The completed manuscript will include the magnetic field characteristics and structural features of both models, comparing various results, and specific comparative analysis will be presented for the determination of the best model for application in a wave energy converting system.

Keywords: wave energy converter, permanent magnet linear synchronous generator, finite element method, analytical method

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Authors: Rebin Mzhda Mohammed, Hoshmand Ali Hama Agha

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Excess skin, often consequential to substantial weight loss or the aging process, introduces physical discomfort, obstructs daily activities, and undermines an individual's self-esteem. As these challenges become increasingly prevalent, the need to explore viable solutions grows in significance. Extra skin removal surgery, colloquially known as body contouring surgery, has emerged as a compelling intervention to ameliorate the physical and psychological burdens of excess skin. This study undertakes a comprehensive review to illuminate the intricacies of extra skin removal surgery, encompassing its diverse procedures, associated risks, benefits, and psychological implications on patients. The methodological approach adopted involves a systematic and exhaustive review of pertinent scholarly literature sourced from reputable databases, including PubMed, Google Scholar, and specialized cosmetic surgery journals. Articles are meticulously curated based on their relevance, credibility, and recency. Subsequently, data from these sources are synthesized and categorized, facilitating a comprehensive understanding of the subject matter. Qualitative analysis serves to unravel the nuanced psychological effects, while quantitative data, where available, are harnessed to underpin the study's conclusions. In terms of major findings, the research underscores the manifold advantages of extra skin removal surgery. Patients experience a notable improvement in physical comfort, amplified mobility, enhanced self-confidence, and a newfound ability to don clothing comfortably. Nonetheless, the benefits are juxtaposed with potential risks, encompassing infection, scarring, hematoma, delayed healing, and the challenge of achieving symmetry. A salient discovery is the profound psychological impact of the surgery, as patients consistently report elevated body image satisfaction, heightened self-esteem, and a substantial enhancement in overall quality of life. In summation, this research accentuates the pivotal role of extra skin removal surgery in ameliorating the intricate interplay of physical and psychological difficulties posed by excess skin. By elucidating the diverse procedures, associated risks, and psychological outcomes, the study contributes to a comprehensive and informed comprehension of the surgery's multifaceted effects. Therefore, individuals contemplating this transformative surgical option are equipped with comprehensive insights, ultimately fostering informed decision-making, guided by the expertise of medical professionals.

Keywords: extra skin removal surgery, body contouring, abdominoplasty, brachioplasty, thigh lift, body lift, benefits, risks, psychological effects

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Authors: R. Hellmuth

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The method of factory planning has changed a lot, especially when it is about planning the factory building itself. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity and Ambiguity) lead to more frequent restructuring measures within a factory. A digital factory model is the planning basis for rebuilding measures and becomes an indispensable tool. Furthermore, digital building models are increasingly being used in factories to support facility management and manufacturing processes. The main research question of this paper is, therefore: What kind of digital factory model is suitable for the different areas of application during the operation of a factory? First, different types of digital factory models are investigated, and their properties and usabilities for use cases are analysed. Within the scope of investigation are point cloud models, building information models, photogrammetry models, and these enriched with sensor data are examined. It is investigated which digital models allow a simple integration of sensor data and where the differences are. Subsequently, possible application areas of digital factory models are determined by means of a survey and the respective digital factory models are assigned to the application areas. Finally, an application case from maintenance is selected and implemented with the help of the appropriate digital factory model. It is shown how a completely digitalized maintenance process can be supported by a digital factory model by providing information. Among other purposes, the digital factory model is used for indoor navigation, information provision, and display of sensor data. In summary, the paper shows a structuring of digital factory models that concentrates on the geometric representation of a factory building and its technical facilities. A practical application case is shown and implemented. Thus, the systematic selection of digital factory models with the corresponding application cases is evaluated.

Keywords: building information modeling, digital factory model, factory planning, maintenance

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Authors: Abdennabi Alitane, Ali Essahlaoui, Ahmed M. Saqr, Sabine Sauvage, José-Miguel Sánchez-Pérez, Ann Van Griensven

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Climate change effect of on water resources in semi-arid regions can be serious, it is essential to understand the effects of climate change on the water balance in order to develop sustainable adaptation strategies. This research project examined the impact of climate change on the components of the water balance in a R'Dom hydrological watershed in the Mediterranean region. The assessment of climate change impact on the future hydrology is done by using the SDSM (Statistical DownScaling Model) and SWAT+ (The Soil and Water Assessment Tool) hydrological model during the baseline period (2002–2013), the data was analyzed and compared to future climate projections . The future projections of the global circulation model canEMS2 under the RCP 2.6, RCP 4.5 and RCP 8.5 scenarios were statically downscaled for a period (2014–2100). Afterwards, the SWAT+ model is simulated for the period from 2000 to 2013, calibrated from 2002 to 2007, and validated from 2008 to 2013 using monthly streamflow data. The model results showed good performance with an NSE of 0.72 and R2 of 0.71 during the validation period. The future precipitation shows a decreasing tendency under all scenarios, with -6.59%, -2.86%, and -2.57% for RCPaveg 2.6, RCPaveg 4.5, and RCPaveg 8.5, respectively. On other hand, the average monthly streamflow of R’Dom river in the near future (2014–2043) will decrease by 44–48%, decrease by 36–48% in the Medium period (2044–2071) and decrease by 43–52% in the period (2072–2100) under the three RCP scenarios. Regarding the water balance components changes, the average annual of actual evapotranspiration is predicted to increase from 5% to 9% under the three RCP scenarios for the three future study periods. Projected average annual flows are expected to decrease by 37% to 90% under the three RCP scenarios over the three future periods. In general, the current scientific research context and the results obtained from the methodology applied will help to optimize future water planning in semi-arid regions in the face of climate change.

Keywords: climate change, water balance, R'Dom watershed, SDSM, SWAT+ model

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Authors: Sungzoon Cho, Hye Jin Lee, Sungwhan Jeon, Dongyoung Min, Sungwon Lyu

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Major public corporations worldwide use conference calls to report their quarterly earnings. These 'earnings' conference calls allow for questions from stock analysts. We investigated if it is possible to identify sentiment from the call script and use it to predict stock price movement. We analyzed call scripts from six companies, two each from Korea, China and Indonesia during six years 2011Q1 – 2017Q2. Random forest with Frequency-based sentiment scores using Loughran MacDonald Dictionary did better than control model with only financial indicators. When the stock prices went up 20 days from earnings release, our model predicted correctly 77% of time. When the model predicted 'up,' actual stock prices went up 65% of time. This preliminary result encourages us to investigate advanced sentiment scoring methodologies such as topic modeling, auto-encoder, and word2vec variants.

Keywords: earnings call script, random forest, sentiment analysis, stock price prediction

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Authors: Maesoomeh Khorshidi Mehr, Mohammad Sajadian, Shadi Alipour

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The purpose of the present study was to compare the effects of eight weeks of continuous and periodic aerobic exercises on serum levels of CRP in overweight woman. 36 woman aged between 20 and 35 years from the city of Ahwaz were randomly selected as the sample of the study. This sample was further divided into three groups (n= 12) of continuous aerobic exercise, periodic aerobic exercise, and control. Subjects of the groups of continuous and periodic aerobic exercise participated in 8 weeks of specialized exercises while the control group subjects did not take part in any regular physical activity program. Blood samples were collected from subjects in 24 hours prior to and 48 hours past to the intervention period. Afterwards, the serum level of CRP was measured for each blood sample. Results showed that BMI and serum level of CRP both significantly reduced as a result of aerobic exercises. However, no statistically significant difference was recorded between the extent of effects of the former and latter aerobic exercise types. Eight weeks of aerobic exercise will probably result in reduced inflammation and cardiovascular diseases risk in overweight women. The reason for lack of difference between effects of continuous and periodic aerobic exercise may lie in the similarity of average intensity and length of physical administered activities.

Keywords: heart diseases, aerobic exercise, inflammation, CRP, overweight

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Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Piedad Garrido, Fernando Repulles, Andy Bloor, Julio A. Sanguesa, Jesus Gallardo, Vicente Torres, Jesus Tramullas

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With the emergence and development of Information and Communications Technologies (ICTs), Higher Education is experiencing rapid changes, not only in its teaching strategies but also in student’s learning skills. However, we have noticed that students often have difficulty when seeking innovative, useful, and interesting learning resources for their work. This is due to the lack of supervision in the selection of good query tools. This paper presents AINA, an Information Retrieval (IR) computer system aimed at providing motivating and stimulating content to both students and teachers working on different areas and at different educational levels. In particular, our proposal consists of an open virtual resource environment oriented to the vast universe of Disney comics and cartoons. Our test suite includes Disney’s long and shorts films, and we have performed some activities based on the Just In Time Teaching (JiTT) methodology. More specifically, it has been tested by groups of university and secondary school students.

Keywords: information retrieval, animation, educational resources, JiTT

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Authors: Davoud Maleki, Neda Zamani

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The present study aims at exploring the effective accountability model of Islamic Azad University using a qualitative approach of grounded theory. The data of this study were obtained from semi-structured interviews with 25 professors and scholars in Islamic Azad University of Tehran who were selected by theoretical sampling method. In the data analysis, the stepwise method and Strauss and Corbin analytical methods (1992) were used. After identification of the main component (balanced response to stakeholders’ needs) and using it to bring the categories together, expressions and ideas representing the relationships between the main and subcomponents, and finally, the revealed components were categorized into six dimensions of the paradigm model, with the relationships among them, including causal conditions (7 components), main component (balanced response to stakeholders’ needs), strategies (5 components), environmental conditions (5 components), intervention features (4 components), and consequences (3 components). Research findings show an exploratory model for describing the relationships between causal conditions, main components, accountability strategies, environmental conditions, university environmental features, and that consequences.

Keywords: accountability, effectiveness, Islamic Azad University, grounded theory

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Authors: Song Zhang, Hui Wang, Johannes Henrich Schleifenbaum

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Due to the increasing demand for quality assurance and reliability for additive manufacturing, the development of an advanced in-situ monitoring system is required to monitor the process anomalies as input for further process control. Optical-based monitoring systems, such as CMOS cameras and NIR cameras, are proved as effective ways to monitor the geometrical distortion and exceptional thermal distribution. Therefore, many studies and applications are focusing on the availability of the optical-based monitoring system for detecting varied types of defects. However, the capability of the monitoring setup is not quantified. In this study, a quantification model to evaluate the capability of the monitoring setups for the LPBF machine based on acquired monitoring data of a designed test artifact is presented, while the design of the relevant test artifacts is discussed. The monitoring setup is evaluated based on its hardware properties, location of the integration, and light condition. Methodology of data processing to quantify the capacity for each aspect is discussed. The minimal capability of the detectable size of the monitoring set up in the application is estimated by quantifying its resolution and accuracy. The quantification model is validated using a CCD camera-based monitoring system for LPBF machines in the laboratory with different setups. The result shows the model to quantify the monitoring system's performance, which makes the evaluation of monitoring systems with the same concept but different setups possible for the LPBF process and provides the direction to improve the setups.

Keywords: data processing, in-situ monitoring, LPBF process, optical system, quantization model, test artifact

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Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: Henok Hailemariam, Frank Wuttke

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Collapsible soils are weak soils that appear to be stable in their natural state, normally dry condition, but rapidly deform under saturation (wetting), thus generating large and unexpected settlements which often yield disastrous consequences for structures unwittingly built on such deposits. In this study, a prediction model for the relative subsidence of stressed collapsible soils based on dielectric permittivity measurement is presented. Unlike most existing methods for soil subsidence prediction, this model does not require moisture content as an input parameter, thus providing the opportunity to obtain accurate estimation of the relative subsidence of collapsible soils using dielectric measurement only. The prediction model is developed based on an existing relative subsidence prediction model (which is dependent on soil moisture condition) and an advanced theoretical frequency and temperature-dependent electromagnetic mixing equation (which effectively removes the moisture content dependence of the original relative subsidence prediction model). For large scale sub-surface soil exploration purposes, the spatial sub-surface soil dielectric data over wide areas and high depths of weak (collapsible) soil deposits can be obtained using non-destructive high frequency electromagnetic (HF-EM) measurement techniques such as ground penetrating radar (GPR). For laboratory or small scale in-situ measurements, techniques such as an open-ended coaxial line with widely applicable time domain reflectometry (TDR) or vector network analysers (VNAs) are usually employed to obtain the soil dielectric data. By using soil dielectric data obtained from small or large scale non-destructive HF-EM investigations, the new model can effectively predict the relative subsidence of weak soils without the need to extract samples for moisture content measurement. Some of the resulting benefits are the preservation of the undisturbed nature of the soil as well as a reduction in the investigation costs and analysis time in the identification of weak (problematic) soils. The accuracy of prediction of the presented model is assessed by conducting relative subsidence tests on a collapsible soil at various initial soil conditions and a good match between the model prediction and experimental results is obtained.

Keywords: collapsible soil, dielectric permittivity, moisture content, relative subsidence

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Authors: M. Cardenas-Garcia, P. P. Gonzalez-Perez

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Intercellular communication is a necessary condition for cellular functions and it allows a group of cells to survive as a population. Throughout this interaction, the cells work in a coordinated and collaborative way which facilitates their survival. In the case of cancerous cells, these take advantage of intercellular communication to preserve their malignancy, since through these physical unions they can send signs of malignancy. The Wnt/β-catenin signaling pathway plays an important role in the formation of intercellular communications, being also involved in a large number of cellular processes such as proliferation, differentiation, adhesion, cell survival, and cell death. The modeling and simulation of cellular signaling systems have found valuable support in a wide range of modeling approaches, which cover a wide spectrum ranging from mathematical models; e.g., ordinary differential equations, statistical methods, and numerical methods– to computational models; e.g., process algebra for modeling behavior and variation in molecular systems. Based on these models, different simulation tools have been developed from mathematical ones to computational ones. Regarding cellular and molecular processes in cancer, its study has also found a valuable support in different simulation tools that, covering a spectrum as mentioned above, have allowed the in silico experimentation of this phenomenon at the cellular and molecular level. In this work, we simulate and explore the complex interaction patterns of intercellular communication in cancer cells using the Cellulat bioinformatics tool, a computational simulation tool developed by us and motivated by two key elements: 1) a biochemically inspired model of self-organizing coordination in tuple spaces, and 2) the Gillespie’s algorithm, a stochastic simulation algorithm typically used to mimic systems of chemical/biochemical reactions in an efficient and accurate way. The main idea behind the Cellulat simulation tool is to provide an in silico experimentation environment that complements and guides in vitro experimentation in intra and intercellular signaling networks. Unlike most of the cell signaling simulation tools, such as E-Cell, BetaWB and Cell Illustrator which provides abstractions to model only intracellular behavior, Cellulat is appropriate for modeling both intracellular signaling and intercellular communication, providing the abstractions required to model –and as a result, simulate– the interaction mechanisms that involve two or more cells, that is essential in the scenario discussed in this work. During the development of this work we made evident the application of our computational simulation tool (Cellulat) for the modeling and simulation of intercellular communication between normal and cancerous cells, and in this way, propose key molecules that may prevent the arrival of malignant signals to the cells that surround the tumor cells. In this manner, we could identify the significant role that has the Wnt/β-catenin signaling pathway in cellular communication, and therefore, in the dissemination of cancer cells. We verified, using in silico experiments, how the inhibition of this signaling pathway prevents that the cells that surround a cancerous cell are transformed.

Keywords: cancer cells, in silico approach, intercellular communication, key molecules, modeling and simulation

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Authors: J. Tamosaitiene

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The article focuses on the identification and classification of key risk management criteria that represent the most important sustainability aspects of the construction industry. The construction sector is one of the most important sectors in Lithuania. Nowadays, the assessment of the risk level of a construction project is especially important for the quality of construction projects, the growth of enterprises and the sector. To establish the most important criteria for successful growth of the sector, a questionnaire for experts was developed. The analytic hierarchy process (AHP), the expert judgement method and other multicriteria decision making (MCDM) methods were used to develop the hybrid model. The results were used to develop an integrated knowledge system for the measurement of a risk level particular to construction projects. The article presents a practical case that details the developed system, sustainable aspects, and risk assessment.

Keywords: risk, system, model, construction

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Authors: Jiying Han

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Teaching is widely known to be an emotional endeavor, and teachers’ ability to regulate their emotions is important for their well-being and the effectiveness of their classroom management. Considering that teachers’ emotion regulation is an underexplored issue in the field of educational research, some studies have attempted to explore the role of emotion regulation in teachers’ work and to explore the links between teachers’ emotion regulation, job characteristics, and well-being, based on the Job Demands-Resources (JD-R) model. However, those studies targeted primary or secondary teachers. So far, very little is known about the relationships between university teachers’ emotion regulation and its antecedents and effects on teacher well-being. Based on the job demands-resources model and emotion regulation theory, this study examined the relationships between job characteristics of university teaching (i.e., emotional job demands and teaching support), emotion regulation strategies (i.e., reappraisal and suppression), and university teachers’ well-being. Data collected from a questionnaire survey of 643 university teachers in China were analysed. The results indicated that (1) both emotional job demands and teaching support had desirable effects on university teachers’ well-being; (2) both emotional job demands and teaching support facilitated university teachers’ use of reappraisal strategies; and (3) reappraisal was beneficial to university teachers’ well-being, whereas suppression was harmful. These findings support the applicability of the job demands-resources model to the contexts of higher education and highlight the mediating role of emotion regulation.

Keywords: emotional job demands, teaching support, emotion regulation strategies, the job demands-resources model

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Authors: Alireza Mirrashid, Mohammad Khoshbin, Ali Atghaei, Hassan Shahbazi

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In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is the use of infrared thermal and smoke sensors, which cannot be used in outdoor applications. Therefore, the use of vision-based methods seems necessary. The problem of smoke and fire detection is spatiotemporal and requires spatiotemporal solutions. This paper presents a method that uses spatial features along with temporal-based features to detect smoke and fire in the scene. It consists of three main parts; the task of each part is to reduce the error of the previous part so that the final model has a robust performance. This method also uses transformer modules to increase the accuracy of the model. The results of our model show the proper performance of the proposed approach in solving the problem of smoke and fire detection and can be used to increase workplace safety.

Keywords: attention, fire detection, smoke detection, spatio-temporal

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Authors: Chisomo Patrick Kumbuyo, Katsuyuki Shimizu, Hiroshi Yasuda, Yoshinobu Kitamura

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This study deals with a way of predicting Malawi rainfall from global sea surface temperature (SST) using a simple multiple regression model. Monthly rainfall data from nine stations in Malawi grouped into two zones on the basis of inter-station rainfall correlations were used in the study. Zone 1 consisted of Karonga and Nkhatabay stations, located in northern Malawi; and Zone 2 consisted of Bolero, located in northern Malawi; Kasungu, Dedza, Salima, located in central Malawi; Mangochi, Makoka and Ngabu stations located in southern Malawi. Links between Malawi rainfall and SST based on statistical correlations were evaluated and significant results selected as predictors for the regression models. The predictors for Zone 1 model were identified from the Atlantic, Indian and Pacific oceans while those for Zone 2 were identified from the Pacific Ocean. The correlation between the fit of predicted and observed rainfall values of the models were satisfactory with r=0.81 and 0.54 for Zone 1 and 2 respectively (significant at less than 99.99%). The results of the models are in agreement with other findings that suggest that SST anomalies in the Atlantic, Indian and Pacific oceans have an influence on the rainfall patterns of Southern Africa.

Keywords: Malawi rainfall, forecast model, predictors, SST

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Authors: Thendo Mafame

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There is a need for academic research to focus on solving or contributing to solving real-world societal problems. Transdisciplinary research (TDR) provides a way to produce functional and applicable research findings, which can be used to advance developmental causes. This TDR study explores ways in which South Africa’s spatial divide, entrenched through decades of discriminatory planning policies, can be restructured to bring about equitable access to places of employment, business, leisure, and service for previously marginalised South Africans. It does by exploring the potential of the transit-orientated development (TOD) model to restructure and revitalise urban spaces in a collaborative model. The study focuses, through a case study, on the Du Toit station precinct in the town of Stellenbosch, on the peri-urban edge of the city of Cape Town, South Africa. The TOD model is increasingly viewed as an effective strategy for creating sustainable urban redevelopment initiatives, and it has been deployed successfully in other parts of the world. The model, which emphasises development density, diversity of land-use and infrastructure and transformative design, is customisable to a variety of country contexts. This study made use of case study approach with mixed methods to collect and analyse data. Various research methods used include the above-mentioned focus group discussions and interviews, as well as observation, transect walks This research contributes to the professional development of TDR studies that are focused on urbanisation issues.

Keywords: case study, integrated urban development, land-use, stakeholder collaboration, transit-oriented development, transdisciplinary research

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Authors: Sandeep Das

Abstract:

Terminal post is one of the most important features of a Battery. The design and manufacturing of post are very much critical especially when threaded inserts (Bolt-on type) are used since all the collected energy is delivered from the lead part to the threaded insert (Cu or Cu alloy). Any imperfection at the interface may cause Voltage drop, high resistance, high heat generation, etc. This may be because of sudden change of material properties from lead to Cu alloys. To avoid this problem, a scheme of material gradation is proposed for achieving continuous variation of material properties for the Post used in commercially available lead acid battery. The Functionally graded (FG) material for the post is considered to be composed of different layers of homogeneous material. The volume fraction of the materials used corresponding to each layer is calculated by considering its variation along the direction of current flow (z) according to a power law. Accordingly, the effective properties of the homogeneous layers are estimated and the Post composed of this FG material is modeled using the commercially available ANSYS software. The solid 186 layered structural solid element has been used for discretization of the model of the FG Post. A thermal electric analysis is performed on the layered FG model. The model developed has been validated by comparing the results of the existing Post model& experimental analysis

Keywords: ANSYS, functionally graded material, lead-acid battery, terminal post

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Authors: T. Bouchabchoub, A. Bendahmane, A. Haouriqui, N. Attou

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This paper presents simulation results of Forex predicting model equations in order to give approximately a prevision of interest rates. First, Hall-Taylor (HT) equations have been used with Taylor rule (TR) to adapt them to European and American Forex Markets. Indeed, initial Taylor Rule equation is conceived for all Forex transactions in every States: It includes only one equation and six parameters. Here, the model has been used with Hall-Taylor equations, initially including twelve equations which have been reduced to only three equations. Analysis has been developed on the following base macroeconomic variables: Real change rate, investment wages, anticipated inflation, realized inflation, real production, interest rates, gap production and potential production. This model has been used to specifically study the impact of an inflation shock on macroeconomic director interest rates.

Keywords: interest rate, Forex, Taylor rule, production, European Central Bank (ECB), Federal Reserve System (FED).

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Authors: Zdravko Trivic, John Chye Fung, Ruzica Bozovic-Stamenovic

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Within the context of rapidly ageing population in Singapore and the pressing demands on both caregivers and care providers, an integrated approach to ageing-friendly and ability-sensitive enabling environment becomes an imperative. This particularly applies to nursing home environments and their immediate surroundings, as they are becoming one of the main available options of long-term care for many senior adults who are unable to age at home. Yet, despite the considerable efforts to break the still predominant clinical approach to eldercare and to introduce more home-like design and person-centric care model, nursing homes keep being stigmatised and perceived as not so desirable environments to grow old in. The challenges are further emphasised by the associated physical, sensorial, psychological and cognitive declines that are the common consequences of ageing. Such declines have an immense impact on almost all aspects of older adults’ daily functioning, including problems with mobility and spatial orientation, difficulties in communication, withdrawal from social interaction, higher level of depression and decreased sense of independence and autonomy. However, typical nursing home designs tend to neglect the full capacities of balanced and carefully integrated multisensory stimuli as active component of care and ability building. This paper outlines part of a larger multi-disciplinary study of six nursing homes in Singapore, with overarching objectives to create new models of supportive nursing home environments that go beyond the clinical care model and encourage community integration with the nursing home settings. The paper focuses on the largely neglected aspects of sensorial comfort and multi-sensorial properties of nursing homes, including both indoor and immediate outdoor spaces (boundaries). The objective was to investigate the sensory rhythms and explore their role in nursing home users’ daily routine and therapeutic capacities. Socio-sensory rhythms were captured and analysed through a combination of on-site sensory recordings of “objective” quantitative sensory data (air temperature and humidity, sound level and luminance) using multi-function environment meter, perceived experienced data, spatial mapping, first-person observations of nursing home users’ activity patterns, and interviews. This was done in addition to employment of available assessment tools, such as Wisconsin Person Directed Care assessment tool, Dementia Quality of Life [DQoL] instrument, and Resident Environment Impact Scale [REIS], as these tools address the issues of sensorial experience insufficiently and selectively. Key findings indicate varied levels of sensory comfort, as well as diversity, intensity, and customisation of multi-sensory conditions within different nursing home spaces. Sensory stimulation is typically concentrated in communal living areas of the nursing homes or in the areas that often provide controlled or limited access, including specifically designed sensory rooms and outdoor green spaces (gardens and terraces). Opportunities for sensory stimulation are particularly limited for bed-bound senior residents and within more functional areas, such as corridors. This suggests that the capacities of nursing home designs to provide more diverse and better integrated pleasant sensory conditions as integrated “therapeutic devices” to build nursing home residents’ physical and mental abilities, encourage activity and improve wellbeing are far from exhausted.

Keywords: ageing-supportive environment, enabling design, multi-sensory assessment, nursing home environment

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Authors: Mehrnoosh Pirhayati

Abstract:

Translation can be affected by different meta-textual factors of target context such as ideology, politics, and culture. So, the rule of fidelity, or being faithful to the source text, can be ignored by the translator. On the other hand, critical discourse analysis, derived from applied linguistics, is entered into the field of translation studies and used by scholars for revealing hidden deviations and possible roots of manipulations. This study focused on the famous Persian translation of the bestseller book, “A**hole No More,” written by XavierCrement 1990, performed by Mahmud Farjami to comparatively and critically analyze it with its corresponding English original book. The researcher applied Pirhayati’s model and framework of translation criticism at the textual and semiotic levels for this qualitative study. It should be noted that Kress and Van Leeuwen’s semiotic model, along with Machin’s model of typographical analysis, was also used at the semiotic level. The results of the comparisons and analyses indicate thatthis Persian translation of the book is affected by the factors of ideology and economics and reveal that the Islamic attitude causes the translator to employ some strategies such as substitution and deletion. Those who may benefit from this research are translation trainers, students of translation studies, critics, and scholars.

Keywords: farjami (2013), Ideology, manipulation, pirhayati's (2013) model of translation criticism, Xavier crement (1990)

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Authors: Barenten Suciu

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In order to explain the damping mechanism, related to the hunting motion of the wheel axle of a high-speed railway vehicle, a generalized dynamic model is proposed. Based on such model, analytic expressions for the damping coefficient and damped natural frequency are derived, without imposing restrictions on the ratio between the lateral and vertical creep coefficients. Influence of the travelling speed, wheel conicity, dimensionless mass of the wheel axle, ratio of the creep coefficients, ratio of the track span to the yawing diameter, etc. on the damping coefficient and damped natural frequency, is clarified.

Keywords: high-speed railway vehicle, hunting motion, wheel axle, damping, creep, vibration model, analysis.

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Authors: Yenesew Mengiste Yihun, Abraham Mehari Haile, Teklu Erkossa, Bart Schultz

Abstract:

Teff (Eragrostic tef) is a staple food in Ethiopia. The local and international demand for the crop is ever increasing pushing the current price five times compared with that in 2006. To meet this escalating demand increasing production including using irrigation is imperative. Optimum application of irrigation water, especially in semi-arid areas is profoundly important. AquaCrop model application in irrigation water scheduling and simulation of water productivity helps both irrigation planners and agricultural water managers. This paper presents simulation and evaluation of AquaCrop model in optimizing the yield and biomass response to variation in timing and rate of irrigation water application. Canopy expansion, canopy senescence and harvest index are the key physiological processes sensitive to water stress. For full irrigation water application treatment there was a strong relationship between the measured and simulated canopy and biomass with r2 and d values of 0.87 and 0.96 for canopy and 0.97 and 0.74 for biomass, respectively. However, the model under estimated the simulated yield and biomass for higher water stress level. For treatment receiving full irrigation the harvest index value obtained were 29%. The harvest index value shows generally a decreasing trend under water stress condition. AquaCrop model calibration and validation using the dry season field experiments of 2010/2011 and 2011/2012 shows that AquaCrop adequately simulated the yield response to different irrigation water scenarios. We conclude that the AquaCrop model can be used in irrigation water scheduling and optimizing water productivity of Teff grown under water scarce semi-arid conditions.

Keywords: AquaCrop, climate smart agriculture, simulation, teff, water security, water stress regions

Procedia PDF Downloads 409