Search results for: intelligent computational techniques

Authors: Mirzahmedov Ismoiljon Karimjon Ugli, Juraeva Shakhnoza Abdumalik Kizi

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The article deals with the current scientific problems of natural geography related to the development of new pedagogical technologies and their implementation in the educational process. The use of recommended interactive methods in independent study is considered very effective and is a very useful method for students, especially for students who work more on themselves. Today's demand is to make young people talented, intelligent, innovative, as well as mature and well-rounded individuals, as a result of the work carried out in the field of education today. This is how creating tables of different contents and filling them out shows the student's talent and desire for innovation. Also, the techniques and methods necessary for today's student are shown, the role of the teacher in conducting lessons meaningfully, the suitability of the method used by the teacher for the lesson, factors affecting the quality of education, and natural issues of the use of methods based on the specific features of geography are highlighted.

Keywords: teaching methods, educational process, educational technologies, education, problem, didactics, natural geography

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Authors: Zaenal Mutaqin

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The level of erosion that occurs in the upsteam watersheed will lead to limited infiltrattion, land degradation and river trivialisation and estuaries in the body. One of the watesheed that has been degraded caused by using land is the DA Ci Liwung Upstream. The high degradation that occurs in the DA Ci Liwung upstream is indicated by the hugher rate of erosion on the region, especially in the area of agriculture. In this case, agriculture cultivation intent to the agricultural land that has been applied conservation techniques. This study is applied to determine the quantity of erosion by reviewing Hidrologic Response Unit (HRU) in agricuktural cultivation land which is contained in DA Ci Liwung upstream by using the Soil and Water Assessmen Tool (SWAT). Conservation techniques applied are terracing, agroforestry and gulud terrace. It was concluded that agroforestry conservation techniques show the best value of erosion (lowest) compared with other conservation techniques with the contribution of erosion of 25.22 tonnes/ha/year. The results of the calibration between the discharge flow models with the observation that R²=0.9014 and NS=0.79 indicates that this model is acceptable and feasible applied to the Ci Liwung Hulu watershed.

Keywords: conservation, erosion, SWAT analysis, watersheed

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Authors: Nurul Bin Ibrahim

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Advancements in neural networks have offered valuable insights into Fluid Dynamics, notably in addressing turbulence-related challenges. In this research, we introduce multiple applications of models of neural networks, namely Feed-Forward and Recurrent Neural Networks, to explore the relationship between jet formations and stratified turbulence within stochastically excited Boussinesq systems. Using machine learning tools like TensorFlow and PyTorch, the study has created models that effectively mimic and show the underlying features of the complex patterns of jet formation and stratified turbulence. These models do more than just help us understand these patterns; they also offer a faster way to solve problems in stochastic systems, improving upon traditional numerical techniques to solve stochastic differential equations such as the Euler-Maruyama method. In addition, the research includes a thorough comparison with the Statistical State Dynamics (SSD) approach, which is a well-established method for studying chaotic systems. This comparison helps evaluate how well neural networks can help us understand the complex relationship between jet formations and stratified turbulence. The results of this study underscore the potential of neural networks in computational physics and fluid dynamics, opening up new possibilities for more efficient and accurate simulations in these fields.

Keywords: neural networks, machine learning, computational fluid dynamics, stochastic systems, simulation, stratified turbulence

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Authors: Jinwooung Kim, Jae-Hwan Jung, Seong-Jun Kim, Sung-Ah Kim

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Because the building envelope has a significant impact on the operation and maintenance stage of the building, designing the facade considering the performance can improve the performance of the building and lower the maintenance cost of the building. In general, however, optimizing two or more performance factors confronts the limits of time and computational tools. The optimization phase typically repeats infinitely until a series of processes that generate alternatives and analyze the generated alternatives achieve the desired performance. In particular, as complex geometry or precision increases, computational resources and time are prohibitive to find the required performance, so an optimization methodology is needed to deal with this. Instead of directly analyzing all the alternatives in the optimization process, applying experimental techniques (heuristic method) learned through experimentation and experience can reduce resource waste. This study proposes and verifies a method to optimize the double envelope of a building composed of a perforated panel using machine learning to the design geometry and quantitative performance. The proposed method is to achieve the required performance with fewer resources by supplementing the existing method which cannot calculate the complex shape of the perforated panel.

Keywords: building envelope, machine learning, perforated metal, multi-factor optimization, façade

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Authors: B. S. Akhmetov, P. T.Kharitonov, L. Sh. Balgabayeva, O. V. Kisseleva, T. S. Kartbayev

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This article analyzes the applicability of known renewable energy technical means as mobile power sources under the field and extreme conditions. The requirements are determined for the parameters of mobile micro-HPP. The application prospectively of the mobile micro-HPP with intelligent control systems is proved for this purpose. Variants of low-speed electric generators for micro HPP are given. Variants of designs for mobile micro HPP are presented with the direct (gearless) transfer of torque from the hydraulic drive to the rotor of the electric generator. Variant of the hydraulic drive for micro HPP is described workable at low water flows. A general structure of the micro HPP intelligent system control is offered that implements the principle of maximum energy efficiency. The legitimacy of construction and application of mobile micro HPP is proved as electrical power sources for life safety of people under the field and extreme conditions.

Keywords: mobile micro-hydro powerplants, information management systems, hydraulic drive, computer science

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Authors: Gurubasavaraju T. M.

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The magnetorheological (MR) damper could provide variable damping force with respect to the different input magnetic field. The damping force could be estimated through computational analysis using finite element and computational fluid dynamics analysis. The double-ended damper operates without changing the total volume of fluid. In this paper, damping force of double ended damper under different magnetic field is computed. Initially, the magneto-statics analysis carried out to evaluate the magnetic flux density across the fluid flow gap. The respective change in the rheology of the MR fluid is computed by using the experimentally fitted polynomial equation of shear stress versus magnetic field plot of MR fluid. The obtained values are substituted in the Herschel Buckley model to express the non-Newtonian behavior of MR fluid. Later, using computational fluid dynamic (CFD) analysis damping characteristics in terms of force versus velocity and force versus displacement for the respective magnetic field is estimated. The purpose of the present approach is to characterize the preliminary designed MR damper before fabricating.

Keywords: MR fluid, double ended MR damper, CFD, FEA

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Authors: Getaneh Berie Tarekegn

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Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.

Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles

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Authors: Abdul Rashid Ahmadi, Samiullah Paracha, Hamidullah Sokout, Mohammad Hanif Gharana

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Conventional educational practices, do not offer all the required skills for teachers to successfully survive in today’s workplace. Due to poor professional training, a big gap exists across the curriculum plan and the teacher practices in the classroom. As such, raising the quality of teaching through ICT-enabled training and professional development of teachers should be an urgent priority. ‘Mobile Learning’, in that vein, is an increasingly growing field of educational research and practice across schools and work places. In this paper, we propose a novel Mobile learning system that allows the users to learn through an intelligent mobile learning in cooperatively every-time and every-where. The system will reduce the training cost and increase consistency, efficiency, and data reliability. To establish that our system will display neither functional nor performance failure, the evaluation strategy is based on formal observation of users interacting with system followed by questionnaires and structured interviews.

Keywords: computer assisted learning, intelligent tutoring system, learner centered design, mobile mediated learning and teacher education

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Authors: Mohamad Bagher Heidari, Hefzollah Mohammadian

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New discoveries in materials on the nanometer-length scale are expected to play an important role in addressing ongoing and future challenges in the field of communication. Devices and systems for ultra-high speed short and long range communication links, portable and power efficient computing devices, high-density memory and logics, ultra-fast interconnects, and autonomous and robust energy scavenging devices for accessing ambient intelligence and needed information will critically depend on the success of next-generation emerging nonmaterials and devices. This article presents some exciting recent developments in nonmaterials that have the potential to play a critical role in the development and transformation of future intelligent communication and telecom networks in the gas refinery. The industry is benefiting from nanotechnology advances with numerous applications including those in smarter sensors, logic elements, computer chips, memory storage devices, optoelectronics.

Keywords: nonmaterial, intelligent communication, nanoscale, nanophotonic, telecom

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Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasi

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Demand Side Management (DSM) is an essential characteristic of current and future smart grid systems. As one of DSM functions, load management aims to control customers’ total electric consumption and utility’s load factor by using various load shaping techniques. However, applying load shaping techniques such as load shifting, peak clipping, or strategic conservation individually does not provide the desired level of improvement for load factor increment and/or customer’s bill reduction. In this paper, two load shaping techniques will be simulated as constrained optimization problems. The purpose is to reflect the application of combined load shifting and strategic conservation model together at the same time, and the application of combined load shifting and peak clipping model as well. The problem will be formulated and solved by using disciplined convex programming (CVX) based MATLAB® R2013b. Simulation results will be evaluated and compared for studying the most impactful multi-techniques model in improving load curve.

Keywords: convex programing, demand side management, load shaping, multiple, building energy optimization

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Authors: Asmaa M. Fahim

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In this investigation, the (E)-2-cyano-3-(dimethylamino)-N-(2,4-dioxo-1,2,3,4-tetrahydropyrimidin-5-yl)acrylam-ide (4) which used TAM as a template which interacts with Methacrylic Acid (MAA) monomer, in the presence of CH₃CN as progen. The TAM-MMA complex interactions are dependent on stable hydrogen bonding interaction between the carboxylic acid group of TAM(Template) and the hydroxyl group of MMA(methyl methacrylate) with minimal interference of porogen CH₃CN. The physical computational studies were used to optimize their structures and frequency calculations. The binding energies between TAM with different monomers showed the most stable molar ratio of 1:4, which was confirmed through experimental analysis. The optimized polymers were investigated in industrial applications.

Keywords: molecular imprinted polymer, computational studies, SEM, spectral analysis, industrial applications

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Authors: Vipan Kumar Sohpal, Rajesh K Sharma

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Diminishing of conventional fuels and hysterical vehicles emission leads to deterioration of the environment, which emphasize the research to work on biofuels. Biofuels from different sources attract the attention of research due to low emission and biodegradability. Emission of carbon monoxide, carbon dioxide and H-C reduced drastically using Biofuels (B-20) combustion. Contrary to the conventional fuel, engine emission results indicated that nitrous oxide emission is higher in Biofuels. So this paper examines and compares the nitrogen oxide emission of Jatropha Curcus (JCO) B-20% blends with the vegetable oil. In addition to that computational analysis of crude non edible oil performed to assess the impact of composition on emission quality. In conclusion, JCO have the potential feedstock for the biodiesel production after the genetic modification in the plant.

Keywords: jatropha curcus, computational analysis, emissions, NOx biofuels

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Authors: Hashem Al Argha

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Cerebral Aneurysms are the ballooning and defect that occurs in the arteries of the brain. This ballooning might enlarge in size due to mechanical forces and could lead to rupture and death. Computational Fluid Dynamics has been used in the recent years in creating a link between engineering sciences and medical sciences. In this paper, the effects of mechanical forces on cerebral aneurysms will be studied. Results of this study show that mechanical forces could lead to rupture of the aneurysm and could lead to death. High mechanical forces including stresses up to 1.7 MPa could pop aneurysms and lead to a brain hemorrhage.

Keywords: computational fluid dynamics, numerical, aneurysm, mechanical forces

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Authors: Sherif O. Zain Elabideen, Ahmed A. Helal, Ibrahim F. El-Arabawy

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Due to the drastic increase of the wind turbines installed capacity; the grid codes are increasing the restrictions aiming to treat the wind turbines like other conventional sources sooner. In this paper, an intensive review has been presented for different techniques used to add low voltage ride through capability to Doubly Fed Induction Generator (DFIG) wind turbine. A system model with 1.5 MW DFIG wind turbine is constructed and simulated using MATLAB/SIMULINK to explore the effectiveness of the reviewed techniques.

Keywords: DFIG, grid side converters, low voltage ride through, wind turbine

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Authors: Dana Craciun, Daniela Dascalu, Adriana Isvoran

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Phthalates are a class of plastic additives that are used to enhance the physical properties of plastics and as solvents in paintings and some of them proved to be of particular concern for the human health. There are insufficient data concerning the health risks of phthalates and further research on evaluating their effects in humans is needed. As humans are not volunteers for such experiments, computational analysis may be used to predict the biological effects of phthalates in humans. Within this study we have used some computational approaches (SwissADME, admetSAR, FAFDrugs) for predicting the absorption, distribution, metabolization, excretion and toxicity (ADME-Tox) profiles and pharmacokinetics for the most common used phthalates. These computational tools are based on quantitative structure-activity relationship modeling approach. The predictions are further compared to the known effects of each considered phthalate in humans and correlations between computational results and experimental data are discussed. Our data revealed that phthalates are a class of compounds reflecting high toxicity both when ingested and when inhaled, but by inhalation their toxicity is even greater. The predicted harmful effects of phthalates are: toxicity and irritations of the respiratory and gastrointestinal tracts, dyspnea, skin and eye irritations and disruption of the functions of liver and of the reproductive system. Many of investigated phthalates are predicted to be able to inhibit some of the cytochromes involved in the metabolism of numerous drugs and consequently to affect the efficiency of administrated treatments for many diseases and to intensify the adverse drugs reactions. The obtained predictions are in good agreement with clinical data concerning the observed effects of some phthalates in cases of acute exposures. Our study emphasizes the possible health effects of numerous phthalates and underlines the applicability of computational methods for predicting the biological effects of xenobiotics.

Keywords: phthalates, ADME-Tox, pharmacokinetics, biological effects

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Authors: Ajay Wadhwa

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A Laboratory course on computational physics is different from the conventional lab course on other topics of physics like Mechanics, Heat, Optics, etc. because it involves active participation of the teacher as well as one-to-one interaction between teacher and the student. The course content requires the teacher to teach programming language as well as numerical methods along with their applications in physics. The task becomes more daunting when about 90% of the students in the class have no previous experience of any programming language. In the presented work, we have described a methodology for conducting the computational physics course by using the Google Drive and Dropitto.me cloud storage services. We have evaluated the performance in a class of sixty students by dividing them equally into four groups. One of the groups was made the peer group on whom the presented methodology was tested. The other groups were taught by using conventional method of classroom lectures. In order to assess our methodology, we analyzed the performance of students in four class tests. A study of certain statistical parameters like the mean, standard deviation, and Z-test hypothesis revealed that the cyber methodology based on cloud storage is more efficient than the conventional method of teaching.

Keywords: computational Physics, Z-test hypothesis, cloud storage, Google drive

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Authors: Varsha Hemant Patil, Swati A. Bhavsar, Abolee H. Patil

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Image quality assessment plays an important role in image evaluation. This paper aims to present an investigation of classic techniques in use for image quality assessment, especially for super-resolution imaging. Researchers have contributed a lot towards the development of super-resolution imaging techniques. However, not much attention is paid to the development of metrics for testing the performance of developed techniques. In this paper, the study report of existing image quality measures is given. The paper classifies reviewed approaches according to functionality and suitability for super-resolution imaging. Probable modifications and improvements of these to suit super-resolution imaging are presented. The prime goal of the paper is to provide a comprehensive reference source for researchers working towards super-resolution imaging and suggest a better framework for measuring the performance of super-resolution imaging techniques.

Keywords: interpolation, MSE, PSNR, SSIM, super resolution

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Authors: Michael D. Vinod, Hadi Khabbaz

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Construction of infrastructure above or adjacent to landfills is becoming more common to capitalize on the limited space available within urban areas. However, development above landfills is a challenging task due to large voids, the presence of organic matter, heterogeneous nature of waste and ambiguity surrounding landfill settlement prediction. Prior to construction of infrastructure above landfills, ground improvement techniques are being employed to improve the geotechnical properties of landfill material. Although the ground improvement techniques have little impact on long term biodegradation and creep related landfill settlement, they have shown some notable short term success with a variety of techniques, including methods for verifying the level of effectiveness of ground improvement techniques. This paper provides geotechnical and landfill engineers a guideline for selection of landfill ground improvement techniques and their suitability to project-specific sites. Ground improvement methods assessed and compared in this paper include concrete injected columns (CIC), dynamic compaction, rapid impact compaction (RIC), preloading, high energy impact compaction (HEIC), vibro compaction, vibro replacement, chemical stabilization and the inclusion of geosynthetics such as geocells. For each ground improvement technique a summary of the existing theory, benefits, limitations, suitable modern ground improvement monitoring methods, the applicability of ground improvement techniques for landfills and supporting case studies are provided. The authors highlight the importance of implementing cost-effective monitoring techniques to allow observation and necessary remediation of the subsidence effects associated with long term landfill settlement. These ground improvement techniques are primarily for the purpose of construction above closed landfills to cater for transport infrastructure loading.

Keywords: closed landfills, ground improvement, monitoring, settlement, transport infrastructure

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Authors: A. Şahinoğlu, R. Gürbüz, A. Güllü, M. Karhan

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This study in production machines, it is aimed that machine will automatically perceive cutting data and alter cutting parameters. The two most important parameters have to be checked in machine control unit are progress feed rate and speeds. These parameters are aimed to be controlled by sounds of machine. Optimum sound’s features introduced to computer. During process, real time data is received and converted by Matlab software. Data is converted into numerical values. According to them progress and speeds decreases/increases at a certain rate and thus optimum sound is acquired. Cutting process is made in respect of optimum cutting parameters. During chip remove progress, features of cutting tools, kind of cut material, cutting parameters and used machine; affects on various parameters. Instead of required parameters need to be measured such as temperature, vibration, and tool wear that emerged during cutting process; detailed analysis of the sound emerged during cutting process will provide detection of various data that included in the cutting process by the much more easy and economic way. The relation between cutting parameters and sound is being identified.

Keywords: cutting process, sound processing, intelligent late, sound analysis

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Authors: Raghad A. Altowairgi

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With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

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Authors: Yasmin Othman Mydin

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When one experiences problems, this may lead to negative thoughts. These thoughts may occur repetitively. The present study investigates the effectiveness of cognitive and behavioural techniques to reduce negative thoughts. 20 undergraduate university students participated as the sample in these experimental therapy sessions. Ten students received the intervention while the other ten students were in control group. 15 items Perseverative Thinking Questionnaire was administered before and after the intervention to test the effectiveness of the techniques. The behavioural techniques applied were such as, write down the negative thoughts, crumple it and throw it away. While the cognitive technique was to imagine that the thoughts are being taken out of the mind while throwing it away. Paired samples t-test analysis revealed that there were significant reductions (t=4.245,df=9, p .003) in the negative thoughts in the group that received the intervention compared to the control group. This indicates that these techniques are effective to reduce the repetitive negative thoughts.

Keywords: behaviour and cognitive intervention, negative thoughts, writing, psychology

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Authors: Abhiyan Paudel, Maheshwaran M Pillai

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This paper deals with the optimization and comparison of slender delta wing and blended wing body. The objective is to study the difference between the two wing types and analyze the various aerodynamic characteristics of both of these types.The blended-wing body is an aircraft configuration that has the potential to be more efficient than conventional large transport aircraft configurations with the same capability. The purported advantages of the BWB approach are efficient high-lift wings and a wide airfoil-shaped body. Similarly, symmetric separation vortices over slender delta wing may become asymmetric as the angle of attack is increased beyond a certain value, causing asymmetric forces even at symmetric flight conditions. The transition of the vortex pattern from being symmetric to asymmetric over symmetric bodies under symmetric flow conditions is a fascinating fluid dynamics problem and of major importance for the performance and control of high-maneuverability flight vehicles that favor the use of slender bodies. With the use of Star CCM, we analyze both the fluid properties. The CL, CD and CM were investigated in steady state CFD of BWB at Mach 0.3 and through wind tunnel experiments on 1/6th model of BWB at Mach 0.1. From CFD analysis pressure variation, Mach number contours and turbulence area was observed.

Keywords: Coefficient of Lift, Coefficient of Drag, CFD=Computational Fluid Dynamics, BWB=Blended Wing Body, slender delta wing

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Zarine Avetisyan

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Paper presents the discussion of scholars concerning speech impact, peculiarities of its realization, speech strategies, and techniques. Departing from the viewpoints of many prominent linguists, the paper suggests manipulative argumentation be viewed as a most pervasive speech strategy with a certain set of techniques which are to be found in modern American political discourse. The precedence of their occurrence allows us to regard them as pragmatic patterns of speech impact realization in effective public speaking.

Keywords: speech impact, manipulative argumentation, political discourse, technique

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Authors: Worrapol Koranuntachai, Tonkid Chantrasmi, Udomkiat Nontakaew

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Medical latex gloves are made from the latex compound in production lines. Latex dipping is considered one of the most important processes that directly affect the final product quality. In a continuous production line, a chain conveyor carries the formers through the process and partially submerges them into an open channel flow in a latex dipping tank. In general, the conveyor speed is determined by the desired production capacity, and the latex-dipping tank can then be designed accordingly. It is important to understand the flow behavior in the dipping tank in order to achieve high quality in the process. In this work, Computational Fluid Dynamics (CFD) was used to simulate the flow past an array of formers in a simplified latex dipping process. The computational results showed both the flow structure and the vortex generation between two formers. The maximum shear stress over the surface of the formers was used as the quality metric of the latex-dipping process when adjusting operation parameters.

Keywords: medical latex gloves, latex dipping, dipping tank, computational fluid dynamics

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Authors: Abdullah Bajelan, Adel Akbarimajd

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Object manipulation techniques in robotics can be categorized in two major groups including manipulation with grasp and manipulation without grasp. The original aim of this paper is to develop an object manipulation method where in addition to being grasp-less, the manipulation task is done in a passive approach. In this method, linear and angular positions of the object are changed and its manipulation path is controlled. The manipulation path is a helix track with constant radius and incline. The method presented in this paper proposes a system which has not the actuator and the active controller. So this system requires a passive mechanical intelligence to convey the object from the status of the source along the specified path to the goal state. This intelligent is created based on utilizing the geometry of the system components. A general set up for the components of the system is considered to satisfy the required conditions. Then after kinematical analysis, detailed dimensions and geometry of the mechanism is obtained. The kinematical results are verified by simulation in ADAMS.

Keywords: mechanical intelligence, object manipulation, passive mechanism, passive non-prehensile manipulation

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Authors: Mahdi Akhbardeh

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Synchronization of neuronal firing is a hallmark of several neurological diseases. Recently, stimulation techniques have been developed which make it possible to desynchronize oscillatory neuronal activity in a mild and effective way, without suppressing the neurons' firing. As yet, these techniques are being used to establish demand-controlled deep brain stimulation (DBS) techniques for the therapy of movement disorders like severe Parkinson's disease or essential tremor. We here present a first conceptualization suggesting that the nucleus accumbens is a promising target for the standard, that is, permanent high-frequency, DBS in patients with severe and chronic obsessive-compulsive disorder (OCD). In addition, we explain how demand-controlled DBS techniques may be applied to the therapy of OCD in those cases that are refractory to behavioral therapies and pharmacological treatment.

Keywords: stereotactic neurosurgery, deep brain stimulation, obsessive-compulsive disorder, phase resetting

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Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

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Authors: Ahmed E. Hodaib, Mohamed A. Hashem

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In engineering applications, a design has to be as fully perfect as possible in some defined case. The designer has to overcome many challenges in order to reach the optimal solution to a specific problem. This process is called optimization. Generally, there is always a function called “objective function” that is required to be maximized or minimized by choosing input parameters called “degrees of freedom” within an allowed domain called “search space” and computing the values of the objective function for these input values. It becomes more complex when we have more than one objective for our design. As an example for Multi-Objective Optimization Problem (MOP): A structural design that aims to minimize weight and maximize strength. In such case, the Pareto Optimal Frontier (POF) is used, which is a curve plotting two objective functions for the best cases. At this point, a designer should make a decision to choose the point on the curve. Engineers use algorithms or iterative methods for optimization. In this paper, we will discuss the Evolutionary Algorithms (EA) which are widely used with Multi-objective Optimization Problems due to their robustness, simplicity, suitability to be coupled and to be parallelized. Evolutionary algorithms are developed to guarantee the convergence to an optimal solution. An EA uses mechanisms inspired by Darwinian evolution principles. Technically, they belong to the family of trial and error problem solvers and can be considered global optimization methods with a stochastic optimization character. The optimization is initialized by picking random solutions from the search space and then the solution progresses towards the optimal point by using operators such as Selection, Combination, Cross-over and/or Mutation. These operators are applied to the old solutions “parents” so that new sets of design variables called “children” appear. The process is repeated until the optimal solution to the problem is reached. Reliable and robust computational fluid dynamics solvers are nowadays commonly utilized in the design and analyses of various engineering systems, such as aircraft, turbo-machinery, and auto-motives. Coupling of Computational Fluid Dynamics “CFD” and Multi-Objective Evolutionary Algorithms “MOEA” has become substantial in aerospace engineering applications, such as in aerodynamic shape optimization and advanced turbo-machinery design.

Keywords: mathematical optimization, multi-objective evolutionary algorithms "MOEA", computational fluid dynamics "CFD", aerodynamic shape optimization

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Authors: Ibrahim Elnour Abdelrahman Eltayeb

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Computational modelling is a method used to investigate joint forces during a movement. It can get high accuracy in the joint forces via subject-specific models. However, the construction of subject-specific models remains time-consuming and expensive. The purpose of this paper was to identify what alterations we can make to generic computational models to get a better estimation of the joint forces. It appraised the impact of these alterations on the accuracy of the estimated joint forces. It found different strategies of alterations: joint model, muscle model, and an optimisation problem. All these alterations affected joint contact force accuracy, so showing the potential for improving the model predictions without involving costly and time-consuming medical images.

Keywords: joint force, joint model, optimisation problem, validation

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