Search results for: path loss model

Authors: P. G. Siddheshwar, B. N. Veena

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Rayleigh-B´enard convection of a nanoliquid in shallow, square and tall enclosures is studied using the Khanafer-Vafai-Lightstone single-phase model. The thermophysical properties of water, copper, copper-oxide, alumina, silver and titania at 3000 K under stagnant conditions that are collected from literature are used in calculating thermophysical properties of water-based nanoliquids. Phenomenological laws and mixture theory are used for calculating thermophysical properties. Free-free, rigid-rigid and rigid-free boundary conditions are considered in the study. Intractable Lorenz model for each boundary combination is derived and then reduced to the tractable Ginzburg-Landau model. The amplitude thus obtained is used to quantify the heat transport in terms of Nusselt number. Addition of nanoparticles is shown not to alter the influence of the nature of boundaries on the onset of convection as well as on heat transport. Amongst the three enclosures considered, it is found that tall and shallow enclosures transport maximum and minimum energy respectively. Enhancement of heat transport due to nanoparticles in the three enclosures is found to be in the range 3% - 11%. Comparison of results in the case of rigid-rigid boundaries is made with those of an earlier work and good agreement is found. The study has limitations in the sense that thermophysical properties are calculated by using various quantities modelled for static condition.

Keywords: enclosures, free-free, rigid-rigid, rigid-free boundaries, Ginzburg-Landau model, Lorenz model

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Authors: Nebila Lichiheb, LaToya Myles, William Pendergrass, Bruce Hicks, Dawson Cagle

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Atmospheric transport of hazardous materials in urban areas is increasingly under investigation due to the potential impact on human health and the environment. In response to health and safety concerns, several dispersion models have been developed to analyze and predict the dispersion of hazardous contaminants. The models of interest usually rely on meteorological information obtained from the meteorological models of NOAA’s National Weather Service (NWS). However, due to the complexity of the urban environment, NWS forecasts provide an inadequate basis for dispersion computation in urban areas. A dense meteorological network in Washington, DC, called DCNet, has been operated by NOAA since 2003 to support the development of urban monitoring methodologies and provide the driving meteorological observations for atmospheric transport and dispersion models. This study focuses on the comparison of wind observations from the DCNet station on the U.S. Department of Commerce Herbert C. Hoover Building against the North American Mesoscale (NAM) model outputs for the period 2017-2019. The goal is to develop a simple methodology for modifying NAM outputs so that the dispersion requirements of the city and its urban area can be satisfied. This methodology will allow us to quantify the prediction errors of the NAM model and propose adjustments of key variables controlling dispersion model calculation.

Keywords: meteorological data, Washington D.C., DCNet data, NAM model

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Authors: Sahar Shahsavaripour Ghazanfarpour

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As our daily life depends on quality of built services by systems and using devices in our environment; so education and model of software′s quality will be so important. By daily growth in software′s systems and using them so much, progressing process and requirements′ evaluation in primary level of progress especially architecture level in software get more important. Modern driver architecture changes an in dependent model of a level into some specific models that their purpose is reducing number of software changes into an executive model. Process of designing software engineering is mid-automated. The needed quality attribute in designing architecture and quality attribute in representation are in architecture models. The main problem is the relationship between needs, and elements in some aspect with implicit models and input sources in process. It’s because there is no detection ability. The MART profile is use to describe real-time properties and perform plat form modeling.

Keywords: MDA, DW, OMG, UML, AKB, software architecture, ontology, evaluation

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Authors: K. Djellabi, M. E. H. Latreche

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The induction heating phenomenon depends on various factors, making the problem highly nonlinear. The mathematical analysis of this problem in most cases is very difficult and it is reduced to simple cases. Another knowledge of induction heating systems is generated in production environments, but these trial-error procedures are long and expensive. The numerical models of induction heating problem are another approach to reduce abovementioned drawbacks. This paper deals with the simulation model of induction heating problem. The simulation model of induction heating system in COMSOL Multiphysics is created. In this work we present results of numerical simulations of induction heating process in pieces of cylindrical shapes, in an inductor with four coils. The modeling of the inducting heating process was made with the software COMSOL Multiphysics Version 4.2a, for the study we present the temperature charts.

Keywords: induction heating, electromagnetic field, inductor, numerical simulation, finite element

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Authors: A. S. Salimzhanova, J. C. Sardinas, O. A. Yanovskaya

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The objective of this research work is to discuss the concept of green growth in the Republic of Kazakhstan introduced by its government in the National Sustainable Development Strategy with the objective of transition to a resource-efficient, green economy. We believe that emerging economies like Kazakhstan can pursue a cleaner and more efficient development path by introducing an environmental tax system based on resource consumption rather than only income and labor. The key issues discussed in this article are the eco-efficiency, which refers to closing the gap between economic and ecological efficiencies, and the structural change of the economy toward green growth. We also strongly believe that studying the experience of East Asian countries on green reform including eco-innovation and green solutions in business is essential to the case of Kazakhstan. All of these will raise the status of Kazakhstan to the level of one of the thirty developed countries over the next decades.

Keywords: economic strategy, green growth, green solutions, natural resource management, environmental tax system

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Authors: Yiğit Gürler, İbrahim Şimşek, Müge Savaştaer, Ayberk Karakuş, Alper Taşdemirci

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316L steel is frequently used in the industry due to its easy formability and accessibility in sheet metal forming processes. Numerical and experimental studies are frequently encountered in the literature to examine the mechanical behavior of 316L stainless steel during the forming process. 316L stainless steel is the most common material used in the production of plate heat exchangers and plate heat exchangers are produced by plastic deformation of the stainless steel. The motivation in this study is to determine the appropriate material model during the simulation of the sheet metal forming process. For this reason, two different material models were examined and Ls-Dyna material cards were created using material test data. These are MAT133_BARLAT_YLD2000 and MAT093_SIMPLIFIED_JOHNSON_COOK. In order to compare results of the tensile test & hydraulic bulge test performed both numerically and experimentally. The obtained results were evaluated comparatively and the most suitable material model was selected for the forming simulation. In future studies, this material model will be used in the numerical modeling of the sheet metal forming process.

Keywords: 316L, mechanical characterization, metal forming, Ls-Dyna

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Authors: Adela Penesova, Zofia Radikova, Boris Bajer, Andrea Havranova, Miroslav Vlcek

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Background: The aim of our study was to compare the effect of intensified lifestyle intervention on insulin resistance (HOMA-IR), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and Fibroblast growth factor (FGF) 21 after 8 weeks of lifestyle intervention. Methods: A group of 43 obese patients (13M/30F; 43.0±12.4 years; BMI (body mass index) 31.2±6.3 kg/m2 participated in a weight loss interventional program (NCT02325804) following an 8-week hypocaloric diet (-30% energy expenditure) and physical activity 150 minutes/week. Insulin sensitivity was evaluated according to the homeostasis model assessment of insulin resistance (HOMA-IR) and insulin sensitivity indices according to Matsuda and Cederholm were calculated (ISImat and ISIced). Plasma ALT, AST, Fetuin-A, FGF 21, and physical fitness were measured. Results: The average reduction of body weight was 6.8±4.9 kg (0-15 kg; p=0.0006), accompanied with a significant reduction of body fat amount of fat mass (p=0.03), and waist circumference (p=0.02). Insulin sensitivity has been improved (IR HOMA 2.71±3.90 vs 1.24±0.83; p=0.01; ISIMat 6.64±4.38 vs 8.93±5.36 p ≤ 0.001). Total, LDL cholesterol, and triglycerides decreased (p=0.05, p=0.04, p=0.04, respectively). Physical fitness significantly improved after intervention (as measure VO2 max (maximal oxygen uptake) (p ≤ 0.001). ALT decreased significantly (0.44±0.26 vs post 0.33±0.18 ukat/l, p=0.004); however, AST not (pre 0.40±0.15 vs 0.35±0.09 ukat/l, p=0.07). Hepatokine Fetuin-A significantly decreased after intervention (43.1±10.8 vs 32.6±8.6 ng/ml, p < 0.001); however, FGF 21 levels tended to decrease (146±152 vs 132±164 pg/ml, p=0.07). Conclusion: 8-weeks of diet and physical activity intervention program in obese otherwise healthy subjects led to an improvement of insulin resistance parameters and liver marker profiles, as well as increased physical fitness. This study was supported by grants APVV 15-0228; VEGA 2/0161/16.

Keywords: obesity, diet, exercice, insulin sensitivity

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Authors: Adnan A. Y. Mustafa

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Image matching is a fundamental problem that arises frequently in many aspects of robot and computer vision. It can become a time-consuming process when matching images to a database consisting of hundreds of images, especially if the images are big. One approach to reducing the time complexity of the matching process is to reduce the search space in a pre-matching stage, by simply removing dissimilar images quickly. The Probabilistic Matching Model for Binary Images (PMMBI) showed that dissimilarity detection between binary images can be accomplished quickly by random pixel mapping and is size invariant. The model is based on the gamma binary similarity distance that recognizes an image and its inverse as containing the same scene and hence considers them to be the same image. However, in many applications, an image and its inverse are not treated as being the same but rather dissimilar. In this paper, we present a comparative analysis of dissimilarity detection between PMMBI based on the gamma binary similarity distance and a modified PMMBI model based on a similarity distance that does distinguish between an image and its inverse as being dissimilar.

Keywords: binary image, dissimilarity detection, probabilistic matching model for binary images, image mapping

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Authors: J. Das, T. S. Mahule, V. V. Srinivasu

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Electron spin resonance (ESR) study at 9.45 GHz and a field modulation frequency of 100Hz was performed on bulk polycrystalline samples of Mn:TM (Fe/Ni) and Mn:RE (Gd/Sm) co doped ZnO samples with composition Zn1-xMn:TM/RE)xO synthesised by solid state reaction route and sintered at 500 0C temperature. The room temperature microwave absorption data collected by sweeping the DC magnetic field from -500 to 9500 G for the Mn:Fe and Mn:Ni co doped ZnO samples exhibit a rarely reported non resonant low field absorption (NRLFA) in addition to a strong absorption at around 3350G, usually associated with ferromagnetic resonance (FMR) satisfying Larmor’s relation due to absorption in the full saturation state. Observed low field absorption is distinct to ferromagnetic resonance even at low temperature and shows hysteresis. Interestingly, it shows a phase opposite with respect to the main ESR signal of the samples, which indicates that the low field absorption has a minimum value at zero magnetic field whereas the ESR signal has a maximum value. The major resonance peak as well as the peak corresponding to low field absorption exhibit asymmetric nature indicating magnetic anisotropy in the sample normally associated with intrinsic ferromagnetism. Anisotropy parameter for Mn:Ni codoped ZnO sample is noticed to be quite higher. The g values also support the presence of oxygen vacancies and clusters in the samples. These samples have shown room temperature ferromagnetism in the SQUID measurement. However, in rare earth (RE) co doped samples (Zn1-x (Mn: Gd/Sm)xO), which show paramagnetic behavior at room temperature, the low field microwave signals are not observed. As microwave currents due to itinerary electrons can lead to ohmic losses inside the sample, we speculate that more delocalized 3d electrons contributed from the TM dopants facilitate such microwave currents leading to the loss and hence absorption at the low field which is also supported by the increase in current with increased micro wave power. Besides, since Fe and Ni has intrinsic spin polarization with polarisability of around 45%, doping of Fe and Ni is expected to enhance the spin polarization related effect in ZnO. We emphasize that in this case Fe and Ni doping contribute to polarized current which interacts with the magnetization (spin) vector and get scattered giving rise to the absorption loss.

Keywords: co-doping, electron spin resonance, hysteresis, non-resonant microwave absorption

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Authors: M. Nekri, A. Khelladi

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The world wide web network is a network with a complex topology, the main properties of which are the distribution of degrees in power law, A low clustering coefficient and a weak average distance. Modeling the web as a graph allows locating the information in little time and consequently offering a help in the construction of the research engine. Here, we present a model based on the already existing probabilistic graphs with all the aforesaid characteristics. This work will consist in studying the web in order to know its structuring thus it will enable us to modelize it more easily and propose a possible algorithm for its exploration.

Keywords: clustering coefficient, preferential attachment, small world, web community

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Authors: Harald Lang, Michael Bader, A. Buchroithner

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Holistic methods covering the development process as a whole – e.g. systems engineering – have established themselves in product design. However, technical product optimization, representing improvements in efficiency and/or minimization of loss, usually applies to single components of a system. A holistic approach is being defined based on a hierarchical point of view of systems engineering. This is subsequently presented using the example of an electromechanical flywheel energy storage system for automotive applications.

Keywords: design, product development, product optimization, systems engineering

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

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Authors: James Katungyi

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The Steady State thermal comfort model which dominates thermal comfort practice and which posits the ideal thermal conditions in a narrow range of thermal conditions does not deliver the expected comfort levels among occupants. Furthermore, the buildings where this model is applied consume a lot of energy in conditioning. This paper reviews significant literature about thermal comfort in dynamic indoor conditions including the adaptive thermal comfort model and alliesthesia. A major finding of the paper is that the adaptive thermal comfort model is part of a trend from static to dynamic indoor environments in aspects such as lighting, views, sounds and ventilation. Alliesthesia or thermal delight is consistent with this trend towards dynamic thermal conditions. It is within this trend that the two fold goal of increased thermal comfort and reduced energy consumption lies. At the heart of this trend is a rediscovery of the link between the natural environment and human well-being, a link that was partially severed by over-reliance on mechanically dominated artificial indoor environments. The paper concludes by advocating thermal conditioning solutions that integrate mechanical with natural thermal conditioning in a balanced manner in order to meet occupant thermal needs without endangering the environment.

Keywords: adaptive thermal comfort, alliesthesia, energy, natural environment

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Authors: Ayhan Ince

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In this paper, an analytical simplified method for calculating elasto-plastic stresses strains of notched bodies subject to non-proportional loading paths is discussed. The method was based on the Neuber notch correction, which relates the incremental elastic and elastic-plastic strain energy densities at the notch root and the material constitutive relationship. The validity of the method was presented by comparing computed results of the proposed model against finite element numerical data of notched shaft. The comparison showed that the model estimated notch-root elasto-plastic stresses strains with good accuracy using linear-elastic stresses. The prosed model provides more efficient and simple analysis method preferable to expensive experimental component tests and more complex and time consuming incremental non-linear FE analysis. The model is particularly suitable to perform fatigue life and fatigue damage estimates of notched components subjected to non-proportional loading paths.

Keywords: elasto-plastic, stress-strain, notch analysis, nonprortional loadings, cyclic plasticity, fatigue

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Authors: Tatsuya Otoshi, Masayuki Murata

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With the development and diversification of applications on the Internet, applications that require high responsiveness, such as video streaming, are becoming mainstream. Application responsiveness is not only a matter of communication delay but also a matter of time required to grasp changes in network conditions. The tradeoff between accuracy and measurement time is a challenge in network control. We people make countless decisions all the time, and our decisions seem to resolve tradeoffs between time and accuracy. When making decisions, people are known to make appropriate choices based on relatively small samples. Although there have been various studies on models of human decision-making, a model that integrates various cognitive biases, called ”quantum decision-making,” has recently attracted much attention. However, the modeling of small samples has not been examined much so far. In this paper, we extend the model of quantum decision-making to model decision-making with a small sample. In the proposed model, the state is updated by value-based probability amplitude amplification. By analytically obtaining a lower bound on the number of samples required for decision-making, we show that decision-making with a small number of samples is feasible.

Keywords: quantum decision making, small sample, MPEG-DASH, Grover's algorithm

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Authors: E. Karimi-Sibaki, A. Kharicha, M. Wu, A. Ludwig

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The standard electroslag remelting (ESR) process can ideally control the solidification of an ingot and produce homogeneous structure with minimum defects. However, the melt rate of electrode is rather low that makes the whole process uneconomical especially to produce small ingot sizes. In contrast, continuous casting is an economical process to produce small ingots such as billets at high casting speed. Unfortunately, deep liquid melt pool forms in the billet ingot of continuous casting that leads to center porosity and segregation. As such, continuous casting is not suitable to produce segregation prone alloys like tool steel or several super alloys. On the other hand, the electro slag rapid remelting (ESRR) process has advantages of both traditional ESR and continuous casting processes to produce billets. In the ESRR process, a T-shaped mold is used including a graphite ring that takes major amount of current through the mold. There are only a few reports available in the literature discussing about this topic. The research on the ESRR process is currently ongoing aiming to improve the design of the T-shaped mold, to decrease overall heat loss in the process, and to obtain a higher temperature at metal meniscus. In the present study, a 3D model is proposed to investigate the electromagnetic, thermal, and flow fields in the whole process as well as solidification of the billet ingot. We performed a fully coupled numerical simulation to explore the influence of the electromagnetically driven flow (MHD) on the thermal field in the slag and ingot. The main goal is to obtain some fundamental understanding of the formation of melt pool of the solidifying billet ingot in the ESRR process.

Keywords: billet ingot, magnetohydrodynamics (mhd), numerical simulation, remelting, solidification, t-shaped mold.

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Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

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The 1MWth PUSPATI TRIGA Reactor (RTP) in Malaysia Nuclear Agency has been operating more than 35 years. The existing core power control is using conventional controller known as Feedback Control Algorithm (FCA). It is technically challenging to keep the core power output always stable and operating within acceptable error bands for the safety demand of the RTP. Currently, the system could be considered unsatisfactory with power tracking performance, yet there is still significant room for improvement. Hence, a new design core power control is very important to improve the current performance in tracking and regulating reactor power by controlling the movement of control rods that suit the demand of highly sensitive of nuclear reactor power control. In this paper, the proposed Model Predictive Control (MPC) law was applied to control the core power. The model for core power control was based on mathematical models of the reactor core, MPC, and control rods selection algorithm. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The proposed MPC was presented in a transfer function model of the reactor core according to perturbations theory. The transfer function model-based predictive control (TFMPC) was developed to design the core power control with predictions based on a T-filter towards the real-time implementation of MPC on hardware. This paper introduces the sensitivity functions for TFMPC feedback loop to reduce the impact on the input actuation signal and demonstrates the behaviour of TFMPC in term of disturbance and noise rejections. The comparisons of both tracking and regulating performance between the conventional controller and TFMPC were made using MATLAB and analysed. In conclusion, the proposed TFMPC has satisfactory performance in tracking and regulating core power for controlling nuclear reactor with high reliability and safety.

Keywords: core power control, model predictive control, PUSPATI TRIGA reactor, TFMPC

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Authors: Zhao Hong

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When international students study Chinese as a foreign or second language, it is important for them to form constructive viewpoints and possess an open mindset on Chinese culture. This helps them to make faster progress in their language acquisition. Observations from African students at Liaoning Institute of Science and Technology show that by integrating video-focused social networking apps such as Tiktok (“Douyin”) on a controlled basis, students raise their interest not only in making an effort in learning the Chinese language, but also in the understanding of the Chinese culture. During the last twelve months, our research group explored a teaching model using selected contents in certain classroom settings, including virtual classrooms during lockdown periods due to the COVID-19 pandemic. Using interviews, a survey was conducted on international students from African countries at the Liaoning Institute of Science and Technology in Chinese language courses. Based on the results, a teaching model was built for Chinese language acquisition by entering the "mobile Chinese culture".

Keywords: Chinese as a foreign language, cultural education, social networking apps, teaching model

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Authors: Mojtaba Esmaeilzad Limoudehi

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To evaluate the model ORYZA2000, under the management of irrigation and nitrogen fertilization experiment, a split plot with a randomized complete block design with three replications on hybrid cultivars (spring) in the 1388-1387 crop year was conducted at the Rice Research Institute. Permanent flood irrigation as the main plot in the fourth level, around 5 days, from 11 days to 8 days away, and the four levels of nitrogen fertilizer as the subplots 0, 90, 120, and 150 kg N Ha were considered. Simulated and measured values of leaf area index, grain yield, and biological parameters using the regression coefficient, t-test, the root mean square error (RMSE), and normalized root mean square error (RMSEn) were performed. Results, the normalized root mean square error of 10% in grain yield, the biological yield of 9%, and 23% of maximum LAI was determined. The simulation results show that grain yield and biological ORYZA2000 model accuracy are good but do not simulate maximum LAI well. The results show that the model can support ORYZA2000 test results and can be used under conditions of nitrogen fertilizer and irrigation management.

Keywords: evaluation, rice, nitrogen fertilizer, model ORYZA2000

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Authors: Sabyasachi Biswas, Indrajit Ghosh

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The random and heterogeneous behavior of vehicles in India puts up a greater challenge for researchers. Stop-and-go modeling at signalized intersections under heterogeneous traffic conditions has remained one of the most sought-after fields. Vehicles are often caught up in the dilemma zone and are unable to take quick decisions whether to stop or cross the intersection. This hampers the traffic movement and may lead to accidents. The purpose of this work is to develop a stop and go prediction model that depicts the drivers’ decision during the yellow time at signalised intersections. To accomplish this, certain traffic parameters were taken into account to develop surrogate model. This research investigated the Stop and Go behavior of the drivers by collecting data from 4-signalized intersections located in two major Indian cities. Model was developed to predict the drivers’ decision making during the yellow phase of the traffic signal. The parameters used for modeling included distance to stop line, time to stop line, speed, and length of the vehicle. A Kriging base surrogate model has been developed to investigate the drivers’ decision-making behavior in amber phase. It is observed that the proposed approach yields a highly accurate result (97.4 percent) by Gaussian function. It was observed that the accuracy for the crossing probability was 95.45, 90.9 and 86.36.11 percent respectively as predicted by the Kriging models with Gaussian, Exponential and Linear functions.

Keywords: decision-making decision, dilemma zone, surrogate model, Kriging

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Authors: Yong Min You

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The study on the torque ripple of Permanent Magnet Synchronous Motors (PMSMs) has been rapidly progressed, which effects on the noise and vibration of the electric vehicle. There are several ways to reduce torque ripple, which are the increase in the number of slots and poles, the notch of the rotor and stator teeth, and the skew of the rotor and stator. However, the conventional methods have the disadvantage in terms of material cost and productivity. The demagnetization characteristic of PMSMs must be attained for electric vehicle application. Due to rare earth supply issue, the demand for Dy-free permanent magnet has been increasing, which can be applied to PMSMs for the electric vehicle. Dy-free permanent magnet has lower the coercivity; the demagnetization characteristic has become more significant. To improve the torque ripple as well as the demagnetization characteristics, which are significant parameters for electric vehicle application, an unequal air-gap model is proposed for a PMSM. A shape optimization is performed to optimize the design variables of an unequal air-gap model. Optimal design variables are the shape of an unequal air-gap and the angle between V-shape magnets. An optimization process is performed by Latin Hypercube Sampling (LHS), Kriging Method, and Genetic Algorithm (GA). Finite element analysis (FEA) is also utilized to analyze the torque and demagnetization characteristics. The torque ripple and the demagnetization temperature of the initial model of 45kW PMSM with unequal air-gap are 10 % and 146.8 degrees, respectively, which are reaching a critical level for electric vehicle application. Therefore, the unequal air-gap model is proposed, and then an optimization process is conducted. Compared to the initial model, the torque ripple of the optimized unequal air-gap model was reduced by 7.7 %. In addition, the demagnetization temperature of the optimized model was also increased by 1.8 % while maintaining the efficiency. From these results, a shape optimized unequal air-gap PMSM has shown the usefulness of an improvement in the torque ripple and demagnetization temperature for the electric vehicle.

Keywords: permanent magnet synchronous motor, optimal design, finite element method, torque ripple

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Authors: Muhammet Baldan, Emel Timuçin

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Generally, absorption and bioavailability increase if solubility increases; therefore, it is crucial to predict them in drug discovery applications. Molecular descriptors and Molecular properties are traditionally used for the prediction of water solubility. There are various key descriptors that are used for this purpose, namely Drogan Descriptors, Morgan Descriptors, Maccs keys, etc., and each has different prediction capabilities with differentiating successes between different data sets. Another source for the prediction of solubility is structural features; they are commonly used for the prediction of solubility. However, there are little to no studies that combine three or more properties or descriptors for prediction to produce a more powerful prediction model. Unlike available models, we used a combination of those features in a random forest machine learning model for improved solubility prediction to better predict and, therefore, contribute to drug discovery systems.

Keywords: solubility, random forest, molecular descriptors, maccs keys

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Authors: Tlou J. Ramabu

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Programming is one of the challenging subjects in the field of computing. In the higher education sphere, some programming novices’ performance, retention rate, and success rate are not improving. Most of the time, the problem is caused by the slow pace of learning, difficulty in grasping the syntax of the programming language and poor logical skills. More importantly, programming forms part of major subjects within the field of computing. As a result, specialized pedagogical methods and innovation are highly recommended. Little research has been done on the potential productivity of the WhatsApp platform as part of a blended learning model. In this article, the authors discuss the WhatsApp group as a part of blended learning model incorporated for a group of programming novices. We discuss possible administrative activities for productive utilisation of the WhatsApp group on the blended learning overview. The aim is to take advantage of the popularity of WhatsApp and the time students spend on it for their educational purpose. We believe that blended learning featuring a WhatsApp group may ease novices’ cognitive load and strengthen their foundational programming knowledge and skills. This is a work in progress as the proposed blended learning model with WhatsApp incorporated is yet to be implemented.

Keywords: blended learning, higher education, WhatsApp, programming, novices, lecturers

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Authors: Ron Cottam, Nils Langloh, Willy Ranson, Roger Vounckx

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We start by formally describing the requirements for environmental-reaction survival computation in a natural temporally-demanding medium, and develop this into a more general model of the evolutionary context as a computational machine. The effect of this development is to replace deterministic logic by a modified form which exhibits a continuous range of dimensional fractal diffuseness between the isolation of perfectly ordered localization and the extended communication associated with nonlocality as represented by pure causal chaos. We investigate the appearance of life and consciousness in the derived general model, and propose a representation of Nature within which all localizations have the character of quasi-quantal entities. We compare our conclusions with Heisenberg’s uncertainty principle and nonlocal teleportation, and maintain that computability is the principal influence on evolution in the model we propose.

Keywords: computability, evolution, life, localization, modeling, nonlocality

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Authors: Maarten J. Van der Burgt

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A universe containing matter and antimatter can only exist when matter and antimatter repel each other. Such a system, where like attracts like and like repels unlike, will always expand. Calculations made for such a symmetric universe demonstrate that the expansion is consistent with Hubble’s law, the observed increase in the expansion velocity with time, the initial high acceleration and the foam structure of the universe. Conversely, these observations can be considered as proof for a symmetrical universe and for antimatter possessing a negative gravitational mass. A second proof can be found by reinterpreting the behavior of relativistic moving charged particles. Attributing their behavior to a charge defect of √(1-v2/c2) instead of to a mass defect of 1/√(1-v2/c2) makes it plausible that gravitation is an electromagnetic force, as already suggested by Feynman. This would automatically imply that antimatter has a negative gravitational mass. These proofs underpin the untenability of the Weak Equivalence Principle which states that in a gravitational field all structure less point-like particles follow the same path.

Keywords: celestial mechanics, cosmology, gravitation astrophysics, origin of structure, miscellaneous (matter and antimatter)

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Authors: Toshitaka Higashino, Naoki Wakamiya

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Human beings perform a task by perceiving information from outside, recognizing them, and responding them. There have been various attempts to analyze and understand internal processes behind the reaction to a given stimulus by conducting psychological experiments and analysis from multiple perspectives. Among these, we focused on Model Human Processor (MHP). However, it was built based on psychological experiments and thus the relation with brain activity was unclear so far. To verify the validity of the MHP and propose our model from a viewpoint of neuroscience, EEG (Electroencephalography) measurements are performed during experiments in this study. More specifically, first, experiments were conducted where Latin alphabet characters were used as visual stimuli. In addition to response time, ERPs (event-related potentials) such as N100 and P300 were measured by using EEG. By comparing cycle time predicted by the MHP and latency of ERPs, it was found that N100, related to perception of stimuli, appeared at the end of the perceptual processor. Furthermore, by conducting an additional experiment, it was revealed that P300, related to decision making, appeared during the response decision process, not at the end. Second, by experiments using Japanese Hiragana characters, i.e. Japan's own phonetic symbols, those findings were confirmed. Finally, Japanese Kanji characters were used as more complicated visual stimuli. A Kanji character usually has several readings and several meanings. Despite the difference, a reading-related task and a meaning-related task exhibited similar results, meaning that they involved similar information processing processes of the brain. Based on those results, our model was proposed which reflects response time and ERP latency. It consists of three processors: the perception processor from an input of a stimulus to appearance of N100, the cognitive processor from N100 to P300, and the decision-action processor from P300 to response. Using our model, an application system which reflects brain activity can be established.

Keywords: brain activity, EEG, information processing model, model human processor

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Authors: Frederic Fovet

Abstract:

Inclusive provisions have been statutorily mandated in North America for now over two decades. Despite a growing body of literature around inclusive practices, many in-service teachers continue to express difficulties when it comes to tangible implementation of inclusion in the everyday classroom. While there is debate around the various forms inclusion can take (UDL, differentiation, personalization, etc.), there appears to be a more significant hurdle in getting in-service teachers to fully embrace inclusion both as a goal and a practice. This paper investigates teachers’ degree of awareness around the Social Model of Disability. It argues that teachers often lack basic awareness of disability studies, more particularly of the Social Model of Disability, and that this has a direct impact on their capacity to conceptualize and embrace inclusion. The paper draws from the researcher’s experience as a graduate instructor with in-service teachers, as well as from his experience as a consultant working with schools and school boards. The methodology chosen here is phenomenology, and it draws on tools such as auto-ethnography. The paper opens a discussion around the reform and transformation of pre-service teacher training. It argues that disability studies should be integrated into teacher training as it plays a key role in having teachers develop a theoretical understanding of disability as a social construct.

Keywords: disability, K-12, inclusion, social model, in-service teachers

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Authors: D. Rama Krishna, Y. Pandu Rangaiah

Abstract:

This paper presents the design of multiband reconfigurable antenna using PIN diodes for four iterations and all the four iterations have been validated by measuring return loss and pattern measurements of developed prototype antenna. The simulated and experimental data have demonstrated the concepts of a multiband reconfigurable antenna by switching OFF and ON of PIN diodes for multiple band frequencies. The technique has taken the advantage of a different number of radiating lengths with the use of PIN diode switches, each configuration resonating at multiband frequencies.

Keywords: frequency reconfigurable, meandered line multiband antenna, PIN diode, multiband frequencies

Procedia PDF Downloads 381

Authors: Ehsan Mehryaar, Reza Bushehri

Abstract:

One of the principal parameters defining the clay soil dynamic response is the strain-shear modulus relation. Predicting the strain and, subsequently, shear modulus reduction of the soil is essential for performance analysis of structures exposed to earthquake and dynamic loadings. Many soil properties affect soil’s dynamic behavior. In order to capture those effects, in this study, a database containing 1193 data points consists of maximum shear modulus, strain, moisture content, initial void ratio, plastic limit, liquid limit, initial confining pressure resulting from dynamic laboratory testing of 21 clays is collected for predicting the shear modulus vs. strain curve of soil. A model based on an extreme gradient boosting technique is proposed. A tree-structured parzan estimator hyper-parameter tuning algorithm is utilized simultaneously to find the best hyper-parameters for the model. The performance of the model is compared to the existing empirical equations using the coefficient of correlation and root mean square error.

Keywords: XGBoost, hyper-parameter tuning, soil shear modulus, dynamic response

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Authors: Bruno Gontijo Batista

Abstract:

This paper analyzes how the Socially Aware Design (SAwD) and the Value-oriented and Culturally Informed Approach (VCIA) design model can be used to develop an edutainment game for children with Attention Deficit Hyperactivity Disorder (ADHD). The SAwD approach seeks a design that considers new dimensions in human-computer interaction, such as culture, aesthetics, emotional and social aspects of the user's everyday experience. From this perspective, the game development was VCIA model-based, including the users in the design process through participatory methodologies, considering their behavioral patterns, culture, and values. This is because values, beliefs, and behavioral patterns influence how technology is understood and used and the way it impacts people's lives. This model can be applied at different stages of design, which goes from explaining the problem and organizing the requirements to the evaluation of the prototype and the final solution. Thus, this paper aims to understand how this model can be used in the development of an edutainment game for children with ADHD. In the area of education and learning, children with ADHD have difficulties both in behavior and in school performance, as they are easily distracted, which is reflected both in classes and on tests. Therefore, they must perform tasks that are exciting or interesting for them, once the pleasure center in the brain is activated, it reinforces the center of attention, leaving the child more relaxed and focused. In this context, serious games have been used as part of the treatment of ADHD in children aiming to improve focus and attention, stimulate concentration, as well as be a tool for improving learning in areas such as math and reading, combining education and entertainment (edutainment). Thereby, as a result of the research, it was developed, in a participatory way, applying the VCIA model, an edutainment game prototype, for a mobile platform, for children between 8 and 12 years old.

Keywords: ADHD, edutainment, SAwD, VCIA

Procedia PDF Downloads 181