Search results for: cooling methods

Authors: Reyhaneh Soltanshah, Hamid R. Zarandi

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In order to be more efficient in industries that are related to computer systems, software testing is necessary despite spending time and money. In the embedded system software test, complete knowledge of the embedded system architecture is necessary to avoid significant costs and damages. Software tests increase the price of the final product. The aim of this article is to provide a method to reduce time and cost in tests based on program structure. First, a complete review of eleven white box test methods based on ISO/IEC/IEEE 29119 2015 and 2021 versions has been done. The proposed algorithm is designed using two versions of the 29119 standards, and some white-box testing methods that are expensive or have little coverage have been removed. On each of the functions, white box test methods were applied according to the 29119 standard and then the proposed algorithm was implemented on the functions. To speed up the implementation of the proposed method, the Unity framework has been used with some changes. Unity framework can be used in embedded software testing due to its open source and ability to implement white box test methods. The test items obtained from these two approaches were evaluated using a mathematical ratio, which in various software mining reduced between 50% and 80% of the test cost and reached the desired result with the minimum number of test items.

Keywords: embedded software, reduce costs, software testing, white-box testing

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Authors: M. Aherrahrou

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Moroccan education is currently facing many difficulties and problems due to traditional methods of teaching. Neuro -Linguistic Programming (NLP) appears to hold much potential for education at all levels. In this paper, the major aim is to explore the effect of certain Neuro -Linguistic Programming techniques in one educational institution in Morocco. Quantitative and Qualitative methods are used. The findings prove the effectiveness of this new approach regarding Moroccan education, and it is a promising tool to improve the quality of learning.

Keywords: learning and teaching environment, Neuro- Linguistic Programming, education, quality of learning

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Authors: Tso-Yen Mao, De-Yen Liu, Chun-Feng Huang

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Purpose: This research intends to investigate the reliability and validity of ventilatory threshold (VT) and respiratory compensation point (RCP) determined by skeletal muscle hemodynamic status. Methods: One hundred healthy male (age: 22±3 yrs; height: 173.1±6.0 cm; weight: 67.1±10.5 kg) performed graded cycling exercise test which ventilatory and skeletal muscle hemodynamic data were collected simultaneously. VT and RCP were determined by combined V-slope (VE vs. VCO2) and ventilatory efficiency (VE/VO2 vs. VE/VCO2) methods. Pearson correlation, paired t-test, and Bland-Altman plots were used to analyze reliability, validity, and similarities. Statistical significance was set at α =. 05. Results: There are high test-retest correlations of VT and RCP in ventilatory or near-infrared spectroscopy (NIRS) methods (VT vs. VTNIRS: 0.95 vs. 0.94; RCP vs. RCPNIRS: 0.93 vs. 0.93, p<. 05). There are high coefficient of determination at the first timing point of O2Hb decreased (R2 = 0.88, p<. 05) with VT, and high coefficient of determination at the second timing point of O2Hb declined (R2 = 0.89, p< .05) with RCP. VO2 of VT and RCP are not significantly different between ventilatory and NIRS methods (p>. 05). Conclusion: Using NIRS method to determine VT and RCP is reliable and valid in male individuals during graded exercise. Non-invasive skeletal muscle hemodynamics monitor also can be used for controlling training intensity in the future.

Keywords: anaerobic threshold, exercise intensity, hemodynamic, NIRS

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Authors: Ahmet Kayabasi, Ali Akdagli

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In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.

Keywords: a-shaped compact microstrip antenna, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM)

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Authors: Sanjeev Kumar, S. K. Nath

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Proper selection of welding parameters for getting excellent weld is a challenge. HAZ simulation helps in identifying suitable welding parameters like heating rate, cooling rate, peak temperature, and energy input. In this study, the influence of weld thermal cycle of heat affected zone (HAZ) is simulated for Submerged Arc Welding (SAW) using Gleeble ® 3800 thermomechanical simulator. A (Micro-alloyed) MA steel plate of thickness 18 mm having yield strength 450MPa is used for making test specimens. Determination of the mechanical properties of weld simulated specimens including Charpy V-notch toughness and hardness is performed. Peak temperatures of 1300°C, 1150°C, 1000°C, 900°C, 800°C, heat energy input of 22KJ/cm and preheat temperatures of 30°C have been used with Rykalin-3D simulation model. It is found that the impact toughness (75J) is the best for the simulated HAZ specimen at the peak temperature 900ºC. For parent steel, impact toughness value is 26.8J at -50°C in transverse direction.

Keywords: HAZ simulation, mechanical properties, peak temperature, ship hull steel, weldability

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Authors: Drissi Mokhtaria, Chouaih Abdelkader, Fodil Hamzaoui

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Our work is about a comparison of experimental and theoretical results of the electron charge density distribution and the electrostatic potential around the M-Nitrophenol Molecule (m-NPH) kwon for its interesting physical characteristics. The molecular experimental results have been obtained from a high-resolution X-ray diffraction study. Theoretical investigations were performed under the Gaussian program using the Density Functional Theory at B3LYP level of theory at 6-31G*. The multipolar model of Hansen and Coppens was used for the experimental electron charge density distribution around the molecule, while we used the DFT methods for the theoretical calculations. The electron charge density obtained in both methods allowed us to find out the different molecular properties such us the electrostatic potential and the dipole moment which were finally subject to a comparison leading to an outcome of a good matching results obtained in both methods.

Keywords: electron charge density, m-nitrophenol, nonlinear optical compound, electrostatic potential, optimized geometric

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Authors: Shawn Michael Condon

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Current research on teaching expressivity mainly involves instrumentalists. This study focuses on choral singers’ preference of priming techniques based on four methods for teaching expressivity. 112 choral singers answered the survey about their preferred methods for priming expressivity (vocal modelling, using metaphor, tapping into felt emotions, and drawing on past experiences) in three conditions (active, passive, and instructor). Analysis revealed higher preference for drawing on past experience among more experienced singers. The most preferred technique in the passive and instructor roles was vocal modelling, with metaphors and tapping into felt emotions favoured in an active role. Priming techniques are often used in combination with other methods to enhance singing technique or expressivity and are dependent upon the situation, repertoire, and the preferences of the instructor and performer.

Keywords: emotion, expressivity, performance, singing, teaching

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Authors: S. Perera, T. R. Walsh, M. Solvang

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The structure-property relationships of calcium aluminosilicate (CAS) glass surfaces are of scientific and technological interest regarding dissolution phenomena. Molecular dynamics (MD) simulations can provide atomic-scale insights into the structure and properties of the CAS interfaces in vacuo as the first step to conducting computational dissolution studies on CAS surfaces. However, one limitation to date is that although the bulk properties of CAS glasses have been well studied by MD simulation, corresponding efforts on CAS surface properties are relatively few in number (both theoretical and experimental). Here, a systematic computational protocol to create CAS surfaces in vacuo is developed by evaluating the sensitivity of the resultant surface structure with respect to different factors. Factors such as the relative thickness of the surface layer, the relative thickness of the bulk region, the cooling rate, and the annealing schedule (time and temperature) are explored. Structural features such as ring size distribution, defect concentrations (five-coordinated aluminium (AlV), non-bridging oxygen (NBO), and tri-cluster oxygen (TBO)), and linkage distribution are identified as significant features in dissolution studies.

Keywords: MD simulation, CAS glasses, surface structure, structure-property, CAS interface

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Authors: Masood Karamoozian, Zhang Hong

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The necessity and complexity of the decision-making process and the interference of the various factors to make decisions and consider all the relevant factors in a problem are very obvious nowadays. Hence, researchers show their interest in multi-criteria decision-making methods. In this research, the Analytical Hierarchy Process (AHP), Simple Additive Weighting (SAW), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods of multi-criteria decision-making have been used to solve the problem of optimal construction systems. Systems being evaluated in this problem include; Light Steel Frames (LSF), a case study of designs by Zhang Hong studio in the Southeast University of Nanjing, Insulating Concrete Form (ICF), Ordinary Construction System (OCS), and Prefabricated Concrete System (PRCS) as another case study designs in Zhang Hong studio in the Southeast University of Nanjing. Crowdsourcing was done by using a questionnaire at the sample level (200 people). Questionnaires were distributed among experts, university centers, and conferences. According to the results of the research, the use of different methods of decision-making led to relatively the same results. In this way, with the use of all three multi-criteria decision-making methods mentioned above, the Prefabricated Concrete System (PRCS) was in the first rank, and the Light Steel Frame (LSF) system ranked second. Also, the Prefabricated Concrete System (PRCS), in terms of performance standards and economics, was ranked first, and the Light Steel Frame (LSF) system was allocated the first rank in terms of environmental standards.

Keywords: multi-criteria decision making, AHP, SAW, TOPSIS

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Authors: H. Khanfari, M. Johari Fard

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Dealing with carbonate reservoirs can be mind-boggling for the reservoir engineers due to various digenetic processes that cause a variety of properties through the reservoir. A good estimation of the reservoir heterogeneity which is defined as the quality of variation in rock properties with location in a reservoir or formation, can better help modeling the reservoir and thus can offer better understanding of the behavior of that reservoir. Most of reservoirs are heterogeneous formations whose mineralogy, organic content, natural fractures, and other properties vary from place to place. Over years, reservoir engineers have tried to establish methods to describe the heterogeneity, because heterogeneity is important in modeling the reservoir flow and in well testing. Geological methods are used to describe the variations in the rock properties because of the similarities of environments in which different beds have deposited in. To illustrate the heterogeneity of a reservoir vertically, two methods are generally used in petroleum work: Dykstra-Parsons permeability variations (V) and Lorenz coefficient (L) that are reviewed briefly in this paper. The concept of Lorenz is based on statistics and has been used in petroleum from that point of view. In this paper, we correlated the statistical-based Lorenz method to a petroleum concept, i.e. Kozeny-Carman equation and derived the straight line plot of Lorenz graph for a homogeneous system. Finally, we applied the two methods on a heterogeneous field in South Iran and discussed each, separately, with numbers and figures. As expected, these methods show great departure from homogeneity. Therefore, for future investment, the reservoir needs to be treated carefully.

Keywords: carbonate reservoirs, heterogeneity, homogeneous system, Dykstra-Parsons permeability variations (V), Lorenz coefficient (L)

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Authors: M. Rodionov, Z. Dedovets

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The article analyses the composition and structure of the motivationally oriented methodological system of teaching mathematics (purpose, content, methods, forms, and means of teaching), viewed through the prism of the student as the subject of the learning process. Particular attention is paid to the problem of methods of teaching mathematics, which are represented in the form of an ordered triad of attributes corresponding to the selected characteristics. A systematic analysis of possible options and their methodological interpretation enriched existing ideas about known methods and technologies of training, and significantly expanded their nomenclature by including previously unstudied combinations of characteristics. In addition, examples outlined in this article illustrate the possibilities of enhancing the motivational capacity of a particular method or technology in the real learning practice of teaching mathematics through more free goal-setting and varying the conditions of the problem situations. The authors recommend the implementation of different strategies according to their characteristics in teaching and learning mathematics in secondary schools.

Keywords: education, methodological system, the teaching of mathematics, students motivation

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Authors: Min Gao

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In the past year, the advent of large language models (LLMs) has brought about a revolution in the language service industry, making it possible to efficiently produce more satisfactory and higher-quality translations. This is groundbreaking news for commercial companies involved in language services since much of a translator's work can now be completed by machines. However, it may be bad news for universities that provide translation training programs. They need to confront the challenges posed by AI in education by reconsidering issues such as the reform of traditional teaching methods, the translation ethics of students, and the new demands of the job market for their graduates. This article is an exploratory study of these issues based on the author's experiences in translation teaching. The research combines methods in the form of questionnaires and interviews. The findings include: (1) students may lose their motivation to learn in the AI era, but this can be compensated for by encouragement from the lecturer; (2) Translation ethics are not a serious problem in schools, considering the strict policies and regulations in place; (3) The role of translators has evolved in the new era, necessitating a reform of the traditional teaching methods.

Keywords: job market of translation, large language model, translation ethics, translation training

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Authors: Krzysztof Plesiewicz, Izabela Plesiewicz, Krzysztof Chiżyński, Marzenna Zielińska

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Background: Obesity is an independent risk factor for cardiovascular diseases. There are several anthropometric parameters proposed to estimate the level of obesity, but until now there is no agreement which one is the best predictor of cardiometabolic risk. Scientists defined metabolically obese normal weight, who suffer from metabolic abnormalities, the same as obese individuals, and defined this syndrome as normal weight obesity (NWO). Aim of the study: The aim of our study was to determine the occurrence of overweight and obesity in a cohort of young, adult women, using standard and complementary methods of obesity assessment and to indicate those, who are at risk of obesity. The second aim of our study was to test additional methods of obesity assessment and proof that body mass index using alone is not sufficient parameter of obesity assessment. Materials and methods: 384 young women, aged 18-32, were enrolled into the study. Standard anthropometric parameters (waist to hips ratio (WTH), waist to height ratio (WTHR)) and two other methods of body fat percentage measurement (BFPM) were used in the study: electrical bioimpendance analysis (BIA) and skinfold measurement test by digital fat body mass clipper (SFM). Results: In the study group 5% and 7% of participants had waist to hips ratio and accordingly waist to height ratio values connected with visceral obesity. According to BMI 14% participants were overweight and obese. Using additional methods of body fat assessment, there were 54% and 43% of obese for BIA and SMF method. In the group of participants with normal BMI and underweight (not overweight, n =340) there were individuals with the level of BFPM above the upper limit, for the BIA 49% (n =164) and for the SFM 36 % (n=125). Statistical analysis revealed strong correlation between BIA and SFM methods. Conclusion: BMI using alone is not a sufficient parameter of obesity assessment. High percentage of young women with normal BMI values seem to be normal weight obese.

Keywords: electrical bioimpedance, normal weight obesity, skin-fold measurement test, women

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Authors: Wang Zhanquan, Yang Zeping, Gu Chunhua, Zhu Fazhi, Guo Weibin

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Recently, Massive Open Online Courses (MOOCs) are becoming the new trend of education. There are many problems under the environment of Database Principle curriculum teaching process in MOOCs, such as teaching ideas and theories which are out of touch with the reality, how to carry out the technical teaching and interactive practice in the MOOCs environment, thus the methods of database course under the environment of MOOCs are proposed. There are three processes to deal with problem solving in the research, which are problems proposed, problems solved, and inductive analysis. The present research includes the design of teaching contents, teaching methods in classroom, flipped classroom teaching mode under the environment of MOOCs, learning flow method and large practice homework. The database designing ability is systematically improved based on the researching methods.

Keywords: problem solving-driven, MOOCs, teaching art, learning flow;

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Authors: Hrishi Rakshit, Pooneh Bagheri Zadeh

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This paper investigates the performance of drone classification methods using conventional DCNN with different hyperparameters, when additional drone audio data is embedded in the dataset for training and further classification. In this paper, first a custom dataset is created using different images of drones from University of South California (USC) datasets and Leeds Beckett university datasets with embedded drone audio signal. The three well-known DCNN architectures namely, Resnet50, Darknet53 and Shufflenet are employed over the created dataset tuning their hyperparameters such as, learning rates, maximum epochs, Mini Batch size with different optimizers. Precision-Recall curves and F1 Scores-Threshold curves are used to evaluate the performance of the named classification algorithms. Experimental results show that Resnet50 has the highest efficiency compared to other DCNN methods.

Keywords: drone classifications, deep convolutional neural network, hyperparameters, drone audio signal

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, unsupervised training, text retrieval

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Authors: Murat Demir Aydin, Elanur Celebi

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Adhesively bonded joints are used as an alternative to traditional joining methods due to the important advantages they provide. The most important consideration in the use of adhesively bonded joints is that these joints have appropriate requirements for their use in terms of safety. In order to ensure control of this condition, damage analysis of the adhesively bonded joints should be performed by determining the mechanical properties of the adhesives. When the literature is investigated; it is generally seen that the mechanical properties of adhesives are determined by traditional measurement methods. In this study, to determine the mechanical properties of adhesives, the Digital Image Correlation (DIC) method, which can be an alternative to traditional measurement methods, has been used. The DIC method is a new optical measurement method which is used to determine the parameters of displacement and strain in an appropriate and correct way. In this study, tensile tests of Thick Adherent Shear Test (TAST) samples formed using DP410 liquid structural adhesive and steel materials and bulk tensile specimens formed using and DP410 liquid structural adhesive was performed. The displacement and strain values of the samples were determined by DIC method and the shear stress-strain curves of the adhesive for TAST specimens and the tensile strain curves of the bulk adhesive specimens were obtained. Various methods such as numerical methods are required as conventional measurement methods (strain gauge, mechanic extensometer, etc.) are not sufficient in determining the strain and displacement values of the very thin adhesive layer such as TAST samples. As a result, the DIC method removes these requirements and easily achieves displacement measurements with sufficient accuracy.

Keywords: structural adhesive, adhesively bonded joints, digital image correlation, thick adhered shear test (TAST)

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Authors: Yixun Shi

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Many interior point methods for convex programming solve an (n+m)x(n+m)linear system in each iteration. Many implementations solve this system in each iteration by considering an equivalent mXm system (4) as listed in the paper, and thus the job is reduced into solving the system (4). However, the system(4) has to be solved exactly since otherwise the error would be entirely passed onto the last m equations of the original system. Often the Cholesky factorization is computed to obtain the exact solution of (4). One Cholesky factorization is to be done in every iteration, resulting in higher computational costs. In this paper, two iterative methods for solving linear systems using vector division are combined together and embedded into interior point methods. Instead of computing one Cholesky factorization in each iteration, it requires only one Cholesky factorization in the entire procedure, thus significantly reduces the amount of computation needed for solving the problem. Based on that, a hybrid algorithm for solving convex programming problems is proposed.

Keywords: convex programming, interior point method, linear systems, vector division

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Authors: Abdelhamid Zerroug, Mlle Ismahene Sehili

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Spectral methods are usually applied to solve uni-dimensional boundary value problems. With the advantage of the creation of multidimensional basis, we propose a new spectral method for bi-dimensional problems. In this article, we start by creating bi-spectral basis by different ways, we developed also a new relations to determine the expressions of spectral coefficients in different partial derivatives expansions. Finally, we propose the principle of a new bi-spectral method for the bi-dimensional problems.

Keywords: boundary value problems, bi-spectral methods, bi-dimensional Legendre basis, spectral method

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Authors: Namubiru Zula, Janice Desire Busingue

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Pro-active educational approaches have lately been adapted Globally in the Conservation of Natural Resources. This led to the introduction of the co-management system, which worked for some European Countries on the conservation of sharks and other Natural resources. However, this approach has drastically failed in the Fishery sector on Lake Victoria; and the punitive education approach has been re-instated. Literature is readily available about the punitive educational approaches and scanty with the pro-active one. This article analyses the pro-active approach adopted by the Department of Fisheries for the orientation of BMU leaders in a co-management system. The study is interpreted using the social constructivist lens for co-management of the fishery resource to ensure that fishers are also back to fishing sustainably. It highlights some of the education methods used, methodological challenges that included the power and skills gap of the facilitators and program designers, and some implications to practice.

Keywords: beach management units, fishers, education methods, proactive approach, punitive approach

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Authors: Demet Ozgur-Unluakin, Busenur Turkali, S. Caglar Aksezer

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Since the age of industrialization, maintenance has always been a very crucial element for all kinds of factories and plants. With today’s increasingly developing technology, the system structure of such facilities has become more complicated, and even a small operational disruption may return huge losses in profits for the companies. In order to reduce these costs, effective maintenance planning is crucial, but at the same time, it is a difficult task because of the complexity of systems. The most important aspect of correct maintenance planning is to understand the structure of the system, not to ignore the dependencies among the components and as a result, to model the system correctly. In this way, it will be better to understand which component improves the system more when it is maintained. Undoubtedly, proactive maintenance at a scheduled time reduces costs because the scheduled maintenance prohibits high losses in profits. But the necessity of corrective maintenance, which directly affects the situation of the system and provides direct intervention when the system fails, should not be ignored. When a fault occurs in the system, if the problem is not solved immediately and proactive maintenance time is awaited, this may result in increased costs. This study proposes various maintenance methods with different efficiency measures under corrective maintenance strategy on a subsystem of a thermal power plant. To model the dependencies between the components, dynamic Bayesian Network approach is employed. The proposed maintenance methods aim to minimize the total maintenance cost in a planning horizon, as well as to find the most appropriate component to be attacked on, which improves the system reliability utmost. Performances of the methods are compared under corrective maintenance strategy. Furthermore, sensitivity analysis is also applied under different cost values. Results show that all fault effect methods perform better than the replacement effect methods and this conclusion is also valid under different downtime cost values.

Keywords: dynamic Bayesian networks, maintenance, multi-component systems, reliability

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Authors: Eman M. Morgan, Hayam M. Lotfy, Yasmin M. Fayez, Mohamed Abdelkawy, Engy Shokry

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Two simple, selective, economic, safe, accurate, precise and environmentally friendly methods were developed and validated for the quantitative determination of valaciclovir (VAL) in the presence of its related substances R1 (acyclovir), R2 (guanine) in bulk powder and in the commercial pharmaceutical product containing the drug. Method A is a colorimetric method where VAL selectively reacts with ferric hydroxamate and the developed color was measured at 490 nm over a concentration range of 0.4-2 mg/mL with percentage recovery 100.05 ± 0.58 and correlation coefficient 0.9999. Method B is a reversed phase ultra performance liquid chromatographic technique (UPLC) which is considered superior in technology to the high-performance liquid chromatography with respect to speed, resolution, solvent consumption, time, and cost of analysis. Efficient separation was achieved on Agilent Zorbax CN column using ammonium acetate (0.1%) and acetonitrile as a mobile phase in a linear gradient program. Elution time for the separation was less than 5 min and ultraviolet detection was carried out at 256 nm over a concentration range of 2-50 μg/mL with mean percentage recovery 100.11±0.55 and correlation coefficient 0.9999. The proposed methods were fully validated as per International Conference on Harmonization specifications and effectively applied for the analysis of valaciclovir in pure form and tablets dosage form. Statistical comparison of the results obtained by the proposed and official or reported methods revealed no significant difference in the performance of these methods regarding the accuracy and precision respectively.

Keywords: hydroxamic acid, related substances, UPLC, valaciclovir

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Authors: Sergei Zhevnenko

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Сontinuous layer of tantalum boride is formed on the surface as a result of reactive wetting of oxidized tantalum by copper melt with boron at a temperatures above 1150 °C. An increase in the wetting temperature above 1400 °C leads to a change in the formation mechanism of tantalum borides, they are formed in the nanosized flakes. In the presented work, we studied the process of copper-based in-situ composite formation, strengthened by the particles of tantalum borides. We investigated the structure of the formed particles, the conditions, and the kinetics of their formation. Dissolving boride particles do not have time to mix uniformly in the melt upon sufficiently rapid cooling and form a macrostructure, partly repeating the shape of the metallic tantalum. This allows to set different gradient structures in the copper alloy. Such macrostructures have been obtained. Boride particles and microstructures were studied by scanning and transmission electron microscopy, and regions with particles were investigated by nanoindentation. In this work, we also measured the kinetics of impregnation of porous tantalum with copper-boron melt and studied the structures of the composite, in which the melt filling the interpore space is saturated with boride particles.

Keywords: copper, tantalum borides, in-situ composites, wetting, imbibition

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Authors: Shital Patil, Surendra Bhosale

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Cardiac diseases are the leading causes of mortality and morbidity in the world, from recent few decades accounting for a large number of deaths have emerged as the most life-threatening disorder globally. Machine learning and Artificial intelligence have been playing key role in predicting the heart diseases. A relevant set of feature can be very helpful in predicting the disease accurately. In this study, we proposed a comparative analysis of 4 different features selection methods and evaluated their performance with both raw (Unbalanced dataset) and sampled (Balanced) dataset. The publicly available Z-Alizadeh Sani dataset have been used for this study. Four feature selection methods: Data Analysis, minimum Redundancy maximum Relevance (mRMR), Recursive Feature Elimination (RFE), Chi-squared are used in this study. These methods are tested with 8 different classification models to get the best accuracy possible. Using balanced and unbalanced dataset, the study shows promising results in terms of various performance metrics in accurately predicting heart disease. Experimental results obtained by the proposed method with the raw data obtains maximum AUC of 100%, maximum F1 score of 94%, maximum Recall of 98%, maximum Precision of 93%. While with the balanced dataset obtained results are, maximum AUC of 100%, F1-score 95%, maximum Recall of 95%, maximum Precision of 97%.

Keywords: cardio vascular diseases, machine learning, feature selection, SMOTE

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Authors: Hao-Hsi Tseng, Hsin-Yun Lee

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The Most Advantageous Tender (MAT) has been criticized for its susceptibility to dictatorial situations and for its processing of same score, same rank issues. This study applies the four criteria from Arrow's Impossibility Theorem to construct a mechanism for revealing illegitimate scores in scoring methods. While commonly be used to improve on problems resulting from extreme scores, ranking methods hide significant defects, adversely affecting selection fairness. To address these shortcomings, this study relies mainly on the overall evaluated score method, using standardized scores plus normal cumulative distribution function conversion to calculate the evaluation of vender preference. This allows for free score evaluations, which reduces the influence of dictatorial behavior and avoiding same score, same rank issues. Large-scale simulations confirm that this method outperforms currently used methods using the Impossibility Theorem.

Keywords: Arrow’s impossibility theorem, cumulative normal distribution function, most advantageous tender, scoring method

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Authors: Salsabeel F. M. Alfalah, Jannat F. Falah, Nadia Muhaidat, Amjad Hudaib, Diana Koshebye, Sawsan AlHourani

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Educational technology is changing the way how students engage and interact with learning materials. This improved the learning process amongst various subjects. Virtual Reality (VR) applications are considered one of the evolving methods that have contributed to enhancing medical education. This paper utilizes VR to provide a solution to improve the delivery of the subject of Embryology to medical students, and facilitate the teaching process by providing a useful aid to lecturers, whilst proving the effectiveness of this new technology in this particular area. After evaluating the current teaching methods and identifying students ‘needs, a VR system was designed that demonstrates in an interactive fashion the development of the human embryo from fertilization to week ten of intrauterine development. This system aims to overcome some of the problems faced by the students’ in the current educational methods, and to increase the efficacy of the learning process.

Keywords: virtual reality, student assessment, medical education, 3D, embryology

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Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

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Authors: Brahim Boukabcha, Amar Rebbouh

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The bootstrap method based on the idea of exploiting all the information provided by the initial sample, allows us to study the properties of estimators. In this article we will present a theoretical study on the different methods of bootstrapping and using the technique of re-sampling in statistics inference to calculate the standard error of means of an estimator and determining a confidence interval for an estimated parameter. We apply these methods tested in the regression models and Pareto model, giving the best approximations.

Keywords: bootstrap, error standard, bias, jackknife, mean, median, variance, confidence interval, regression models

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Authors: Abdul Basit, Gildas Lhostis, Bernard Durand

Abstract:

Shape memory polymers (SMPs) are replacing shape memory alloys (SMAs) in many applications as SMPs have certain superior properties than SMAs. However, SMAs possess some properties like recovery under stress that SMPs lack. SMPs cannot give complete recovery even under a small load. SMPs are initially heated close to their transition temperature (glass transition temperature or the melting temperature). Then force is applied to deform the heated SMP to a specific position. Subsequently, SMP is allowed to cool keeping it deformed. After cooling, SMP gets the temporary shape. This temporary shape can be recovered by heating it again at the same temperature that was given it while heating it initially. As a result, it will recover its original position. SMP can perform unconstrained recovery and constrained recovery, however; under the load, it only recovers partially. In this work, the recovery under the load of an asymmetrical shape memory composite called as CBCM-SMPC has been investigated. It is found that it has the ability to recover under different loads. Under different loads, it shows powerful complete recovery in reference to initial position. This property can be utilized in many applications.

Keywords: shape memory, polymer composite, thermo-mechanical testing, recovery under load

Procedia PDF Downloads 438

Authors: Nicoleta Simona Vedeanu, Rares Stiufiuc, Dana Alina Magdas

Abstract:

A detailed knowledge of the teeth structure is mandatory to understand and explain the defects and the dental pathology, but especially to take a correct decision regarding dental prophylaxis and treatment. The present work is an alternative study to the traditional investigation methods used in dentistry, a study based on the use of modern, sensitive physical methods to investigate human enamel and dentin. For the present study, several teeth collected from patients of different ages were used for structural and dietary investigation. The samples were investigated by Raman spectroscopy for the molecular structure analysis of dentin and enamel, atomic force microscopy (AFM) to view the dental topography at the micrometric size and mass spectrometry for isotopic ratios as a fingerprint of patients’ personal diet. The obtained Raman spectra and their interpretation are in good correlation with the literature and may give medical information by comparing affected dental structures with healthy ones. AFM technique gave us the possibility to study in details the dentin and enamel surface to collect information about dental hardness or dental structural changes. δ¹³C values obtained for the studied samples can be classified in C4 category specific to young people and children diet (sweets, cereals, juices, pastry). The methods used in this attempt furnished important information about dentin and enamel structure and dietary habits and each of the three proposed methods can be extended at a larger level in the study of the teeth structure.

Keywords: AFM, dentine, enamel, Raman spectroscopy

Procedia PDF Downloads 145