Search results for: computational analysis

Authors: N. Hamzah, M.A. Khoiry, I. Arshad, W.H.W. Badaruzzaman, N. M. Tawil

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Construction delay is unavoidable in developing countries including Malaysia. It is defined as time overrun or extension of time for completion of a project. The purpose of the study is to determine the causes of delay in Malaysian construction industries based on previous worldwide research. The field survey conducted includes the experienced developers, consultants and contractors in Malaysia. 34 causes of the construction delay have been determined and 24 have been selected using the Rasch model analysis. The analysis result will be used as the baseline for the next research to find the causes of delay in the Malaysian construction industry taking place in Malaysian higher learning institutions.

Keywords: Causes of construction delay, construction projects, Malaysian construction industry, Rasch model analysis.

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Authors: Hasan Çiçekli, Ahmet Gökçen, Uğur Çam

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In this paper, a comparative performance analysis of mostly used four nonlinearity cancellation techniques used to realize the passive resistor by MOS transistors, is presented. The comparison is done by using an integrator circuit which is employing sequentially Op-amp, OTRA and ICCII as active element. All of the circuits are implemented by MOS-C realization and simulated by PSPICE program using 0.35μm process TSMC MOSIS model parameters. With MOS-C realization, the circuits became electronically tunable and fully integrable which is very important in IC design. The output waveforms, frequency responses, THD analysis results and features of the nonlinearity cancellation techniques are also given.

Keywords: Integrator circuits, MOS-C realization, nonlinearity cancellation, tunable resistors.

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Authors: Funda Erdem Şahnali, Ş. Özgür Atayılmaz, Tolga N. Aynur

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Almost all of the domestic refrigerators operate on the principle of the vapor compression refrigeration cycle and removal of heat from the refrigerator cabinets is done via one of the two methods: natural convection or forced convection. In this study, airflow and temperature distributions inside a 375L no-frost type larder cabinet, in which cooling is provided by forced convection, are evaluated both experimentally and numerically. Airflow rate, compressor capacity and temperature distribution in the cooling chamber are known to be some of the most important factors that affect the cooling performance and energy consumption of a refrigerator. The objective of this study is to evaluate the original temperature distribution in the larder cabinet, and investigate for better temperature distribution solutions throughout the refrigerator domain via system optimizations that could provide uniform temperature distribution. The flow visualization and airflow velocity measurements inside the original refrigerator are performed via Stereoscopic Particle Image Velocimetry (SPIV). In addition, airflow and temperature distributions are investigated numerically with Ansys Fluent. In order to study the heat transfer inside the aforementioned refrigerator, forced convection theories covering the following cases are applied: closed rectangular cavity representing heat transfer inside the refrigerating compartment. The cavity volume has been represented with finite volume elements and is solved computationally with appropriate momentum and energy equations (Navier-Stokes equations). The 3D model is analyzed as transient, with k-ε turbulence model and SIMPLE pressure-velocity coupling for turbulent flow situation. The results obtained with the 3D numerical simulations are in quite good agreement with the experimental airflow measurements using the SPIV technique. After Computational Fluid Dynamics (CFD) analysis of the baseline case, the effects of three parameters: compressor capacity, fan rotational speed and type of shelf (glass or wire) are studied on the energy consumption; pull down time, temperature distributions in the cabinet. For each case, energy consumption based on experimental results is calculated. After the analysis, the main effective parameters for temperature distribution inside a cabin and energy consumption based on CFD simulation are determined and simulation results are supplied for Design of Experiments (DOE) as input data for optimization. The best configuration with minimum energy consumption that provides minimum temperature difference between the shelves inside the cabinet is determined.

Keywords: Air distribution, CFD, DOE, energy consumption, larder cabinet, refrigeration, uniform temperature.

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Authors: Maged A. Mossallam

Abstract:

The objective from this paper is to design a solar thermal engine for space vehicles orbital control and electricity generation. A computational model is developed for the prediction of the solar thermal engine performance for different design parameters and conditions in order to enhance the engine efficiency. The engine is divided into two main subsystems. First, the concentrator dish which receives solar energy from the sun and reflects them to the cavity receiver. The second one is the cavity receiver which receives the heat flux reflected from the concentrator and transfers heat to the fluid passing over. Other subsystems depend on the application required from the engine. For thrust application, a nozzle is introduced to the system for the fluid to expand and produce thrust. Hydrogen is preferred as a working fluid in the thruster application. Results model developed is used to determine the thrust for a concentrator dish 4 meters in diameter (provides 10 kW of energy), focusing solar energy to a 10 cm aperture diameter cavity receiver. The cavity receiver outer length is 50 cm and the internal cavity is 47 cm in length. The suggested design material of the internal cavity is tungsten to withstand high temperature. The thermal model and analysis shows that the hydrogen temperature at the plenum reaches 2000oK after about 250 seconds for hot start operation for a flow rate of 0.1 g/sec.Using solar thermal engine as an electricity generation device on earth is also discussed. In this case a compressor and turbine are used to convert the heat gained by the working fluid (air) into mechanical power. This mechanical power can be converted into electrical power by using a generator.

Keywords: Concentrated Solar Energy, Orbital Control, Power Generation, Solar Thermal Engine, Space Vehicles Propulsion

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Authors: E. Platzer

Abstract:

This paper introduces a framework that aims to support the design and development of mobile services. The traditional innovation process and its supporting instruments in form of creativity tools, acceptance research and user-generated content analysis are screened for potentials for improvement. The result is a reshaped innovation process where acceptance research and usergenerated content analysis are fully integrated within a creativity tool. Advantages of this method are the enhancement of design relevant information for developers and designers and the possibility to forecast market success.

Keywords: design support, innovation support, technology acceptance, user-generated content analysis.

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Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

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In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent transportation systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning.

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Authors: M.Zadshakouyan, E.Abdi Sobbouhi, H.Jafarzadeh

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In this study, the precision heading process of spur gears has been investigated by means of numerical analysis. The effect of some parameters such as teeth number and module on the forming force and material flow were presented. The simulation works were performed rigid-plastic finite element method using DEFORM 3D software. In order to validate the estimated numerical results, they were compared with those obtained experimentally during heading of spur gear using lead as a model material. Results showed that the optimum number of gear teeth is between 10 to 20, that is because of being the specific pressure in its minimum value.

Keywords: Heading, spur gear, numerical analysis, experiments.

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Authors: Smah Doeban Almotiri

Abstract:

One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2021, until April 4, 2021. Natural language processing (NLP), which is a form of Artificial intelligent was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applied machine learning sentimental method such as Crystal Feel and extended the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

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Authors: Meng-Lung Lin, Qiubing Wang, Fujun Sun, Tzu-How Chu, Yi-Shiang Shiu

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The normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI) derived from the moderate resolution imaging spectroradiometer (MODIS) have been widely used to identify spatial information of drought condition. The relationship between NDVI and NDMI has been analyzed using Pearson correlation analysis and showed strong positive relationship. The drought indices have detected drought conditions and identified spatial extents of drought. A comparison between normal year and drought year demonstrates that the amplitude analysis considered both vegetation and moisture condition is an effective method to identify drought condition. We proposed the amplitude analysis is useful for quick spatial assessment of drought information at a regional scale.

Keywords: NDVI, NDMI, Drought, remote sensing, spatialassessment.

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Authors: Sunyoung Bu, Wonkyu Chung, Philsu Kim

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In this paper, we introduce a method for improving the embedded Runge-Kutta-Fehlberg4(5) method. At each integration step, the proposed method is comprised of two equations for the solution and the error, respectively. These solution and error are obtained by solving an initial value problem whose solution has the information of the error at each integration step. The constructed algorithm controls both the error and the time step size simultaneously and possesses a good performance in the computational cost compared to the original method. For the assessment of the effectiveness, EULR problem is numerically solved.

Keywords: Embedded Runge-Kutta-Fehlberg method, Initial value problem.

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Authors: D. Muley, H. S. Al-Mandhari

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This paper evaluates the performance of a multi-lane four legged modern roundabout operating in Muscat using SIDRA model. The performance measures include Degree of Saturation (DOS), average delay, and queue lengths. The geometric and traffic data were used for model preparation. Gap acceptance parameters, critical gap and follow up headway, were used for calibration of SIDRA model. The results from the analysis showed that currently the roundabout is experiencing delays up to 610 seconds per vehicle with DOS 1.67 during peak hour. Further, sensitivity analysis for general and roundabout parameters was performed, amongst lane width, cruise speed, inscribed diameter, entry radius and entry angle showed that inscribed diameter is most crucial factor affecting delay and DOS. Up gradation of roundabout to fully signalized junction was found as the suitable solution which will serve for future years with LOS C for design year having DOS of 0.9 with average control delay of 51.9 seconds per vehicle.

Keywords: Performance analysis, roundabout, sensitivity analysis, SIDRA.

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Authors: Byeong-Sam Kim, Kangsu Lee, Kyoungwoo Park, Samir Ben Chaabane

Abstract:

A Vehicle-s door wireing harness arrangement structure is provided. In vehicle-s door wiring harness(W/H) system is more toward to arrange a passenger compartment than a hinge and a weatherstrip. This article gives some insight into the dimensioning process, with special focus on large deflection analysis of wiring harness(W/H) in vehicle-s door structures for durability problem. An Finite elements analysis for door wiring harness(W/H) are used for residual stresses and dimensional stability with bending flexible. Durability test data for slim test specimens were compared with the numerical predicted fatigue life for verification. The final lifing of the component combines the effects of these microstructural features with the complex stress state arising from the combined service loading and residual stresses.

Keywords: Large deflection, wiring harness system, finite element analysis, vehicle's door.

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Authors: Branislav Vuksanović, Dragana Nikolić

Abstract:

This paper describes the implementation and testing of a multichannel active noise control system (ANCS) based on the filtered-inverse LMS (FILMS) algorithm. The FILMS algorithm is derived from the well-known filtered-x LMS (FXLMS) algorithm with the aim to improve the rate of convergence of the multichannel FXLMS algorithm and to reduce its computational load. Laboratory setup and techniques used to implement this system efficiently are described in this paper. Experiments performed in order to test the performance of the FILMS algorithm are discussed and the obtained results presented.

Keywords: Active noise control, adaptive filters, inverse filters, LMS algorithm, FILMS algorithm.

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Authors: A. D. Parekh, P. R. Tailor

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The Montreal protocol and Kyoto protocol underlined the need of substitution of CFC’s and HCFC’s due to their adverse impact on atmospheric ozone layer which protects earth from U.V rays. The CFCs have been entirely ruled out since 1995 and a long-term basis HCFCs must be replaced by 2020. All this events motivated HFC refrigerants which are harmless to ozone layer. In this paper thermodynamic analysis of cascade refrigeration system has been done using three different refrigerant pairs R13-R12, R290-R23, and R404A-R23. Effect of various operating parameters i.e. evaporator temperature, condenser temperature, temperature difference in cascade condenser and low temperature cycle condenser temperature on performance parameters viz. COP, exergetic efficiency and refrigerant mass flow ratio have been studied. Thermodynamic analysis shows that out of three refrigerant pairs R12-R13, R290-R23 and R404A-R23 the COP of R290-R23 refrigerant pair is highest.

Keywords: Thermodynamic analysis, cascade refrigeration system, COP, exergetic efficiency.

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Authors: Muhammad Mehran Arshad Khan, Chengliang Wang, Zou Minhui, Danyal Badar Soomro

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Security of the smart home in terms of behavior activity pattern recognition is a totally dissimilar and unique issue as compared to the security issues of other scenarios. Sensor devices (low capacity and high capacity) interact and negotiate each other by detecting the daily behavior activity of individuals to execute common tasks. Once a device (e.g., surveillance camera, smart phone and light detection sensor etc.) is compromised, an adversary can then get access to a specific device and can damage daily behavior activity by altering the data and commands. In this scenario, a group of common instruction processes may get involved to generate deadlock. Therefore, an effective suitable security solution is required for smart home architecture. This paper proposes seamless distributed Scheme which fortifies low computational wireless devices for secure communication. Proposed scheme is based on lightweight key-session process to upheld cryptic-link for trajectory by recognizing of individual’s behavior activities pattern. Every device and service provider unit (low capacity sensors (LCS) and high capacity sensors (HCS)) uses an authentication token and originates a secure trajectory connection in network. Analysis of experiments is revealed that proposed scheme strengthens the devices against device seizure attack by recognizing daily behavior activities, minimum utilization memory space of LCS and avoids network from deadlock. Additionally, the results of a comparison with other schemes indicate that scheme manages efficiency in term of computation and communication.

Keywords: Authentication, key-session, security, wireless sensors.

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Authors: H. Alves, J. T. Assis, M. Geraldes, I. Lima, R. T. Lopes

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Microtomographic images and thin section (TS) images were analyzed and compared against some parameters of geological interest such as porosity and its distribution along the samples. The results show that microtomography (CT) analysis, although limited by its resolution, have some interesting information about the distribution of porosity (homogeneous or not) and can also quantify the connected and non-connected pores, i.e., total porosity. TS have no limitations concerning resolution, but are limited by the experimental data available in regards to a few glass sheets for analysis and also can give only information about the connected pores, i.e., effective porosity. Those two methods have their own virtues and flaws but when paired together they are able to complement one another, making for a more reliable and complete analysis.

Keywords: Microtomography, petrographical microscopy, sediments, thin sections.

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Authors: H. B. Kekre, Tanuja K. Sarode

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Mostly transforms are used for speech data compressions which are lossy algorithms. Such algorithms are tolerable for speech data compression since the loss in quality is not perceived by the human ear. However the vector quantization (VQ) has a potential to give more data compression maintaining the same quality. In this paper we propose speech data compression algorithm using vector quantization technique. We have used VQ algorithms LBG, KPE and FCG. The results table shows computational complexity of these three algorithms. Here we have introduced a new performance parameter Average Fractional Change in Speech Sample (AFCSS). Our FCG algorithm gives far better performance considering mean absolute error, AFCSS and complexity as compared to others.

Keywords: Vector Quantization, Data Compression, Encoding, , Speech coding.

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Authors: Sadaf Nawaz, Adnan Ahmed Khan, Asad Mahmood, Chaudhary Farrukh Javed

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Classically, an energy detector is implemented in time domain (TD). However, frequency domain (FD) based energy detector has demonstrated an improved performance. This paper presents a comparison between the two approaches as to analyze their pros and cons. A detailed performance analysis of the classical TD energy-detector and the periodogram based detector is performed. Exact and approximate mathematical expressions for probability of false alarm (Pf) and probability of detection (Pd) are derived for both approaches. The derived expressions naturally lead to an analytical as well as intuitive reasoning for the improved performance of (Pf) and (Pd) in different scenarios. Our analysis suggests the dependence improvement on buffer sizes. Pf is improved in FD, whereas Pd is enhanced in TD based energy detectors. Finally, Monte Carlo simulations results demonstrate the analysis reached by the derived expressions.

Keywords: Cognitive radio, energy detector, periodogram, spectrum sensing.

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Authors: Rosalyn R. Porle, Ali Chekima, Farrah Wong, G. Sainarayanan

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Arms detection is one of the fundamental problems in human motion analysis application. The arms are considered as the most challenging body part to be detected since its pose and speed varies in image sequences. Moreover, the arms are usually occluded with other body parts such as the head and torso. In this paper, histogram-based skin colour segmentation is proposed to detect the arms in image sequences. Six different colour spaces namely RGB, rgb, HSI, TSL, SCT and CIELAB are evaluated to determine the best colour space for this segmentation procedure. The evaluation is divided into three categories, which are single colour component, colour without luminance and colour with luminance. The performance is measured using True Positive (TP) and True Negative (TN) on 250 images with manual ground truth. The best colour is selected based on the highest TN value followed by the highest TP value.

Keywords: image colour analysis, image motion analysis, skin, wavelet transform.

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Authors: V Krishnaveni, S Jayaraman, K Ramadoss

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The electrical potentials generated during eye movements and blinks are one of the main sources of artifacts in Electroencephalogram (EEG) recording and can propagate much across the scalp, masking and distorting brain signals. In recent times, signal separation algorithms are used widely for removing artifacts from the observed EEG data. In this paper, a recently introduced signal separation algorithm Mutual Information based Least dependent Component Analysis (MILCA) is employed to separate ocular artifacts from EEG. The aim of MILCA is to minimize the Mutual Information (MI) between the independent components (estimated sources) under a pure rotation. Performance of this algorithm is compared with eleven popular algorithms (Infomax, Extended Infomax, Fast ICA, SOBI, TDSEP, JADE, OGWE, MS-ICA, SHIBBS, Kernel-ICA, and RADICAL) for the actual independence and uniqueness of the estimated source components obtained for different sets of EEG data with ocular artifacts by using a reliable MI Estimator. Results show that MILCA is best in separating the ocular artifacts and EEG and is recommended for further analysis.

Keywords: Electroencephalogram, Ocular Artifacts (OA), Independent Component Analysis (ICA), Mutual Information (MI), Mutual Information based Least dependent Component Analysis(MILCA)

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Authors: Wang Lin, Li Zhiqiang

Abstract:

The purpose of this paper is to analyze the cooperative learning behavior pattern based on the data of students' movement. The study firstly reviewed the cooperative learning theory and its research status, and briefly introduced the k-means clustering algorithm. Then, it used clustering algorithm and mathematical statistics theory to analyze the activity rhythm of individual student and groups in different functional areas, according to the movement data provided by 10 first-year graduate students. It also focused on the analysis of students' behavior in the learning area and explored the law of cooperative learning behavior. The research result showed that the cooperative learning behavior analysis method based on movement data proposed in this paper is feasible. From the results of data analysis, the characteristics of behavior of students and their cooperative learning behavior patterns could be found.

Keywords: Behavior pattern, cooperative learning, data analyze, K-means clustering algorithm.

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Authors: M. Jarocka

Abstract:

The paper contains a review of the literature in terms of the critical analysis of methodologies of university ranking systems. Furthermore, the initiatives supported by the European Commission (U-Map, U-Multirank) and CHE Ranking are described. Special attention is paid to the tendencies in the development of ranking systems. According to the author, the ranking organizations should abandon the classic form of ranking, namely a hierarchical ordering of universities from “the best" to “the worse". In the empirical part of this paper, using one of the method of cluster analysis called k-means clustering, the author presents university classifications of the top universities from the Shanghai Jiao Tong University-s (SJTU) Academic Ranking of World Universities (ARWU).

Keywords: Classification, cluster analysis, ranking, university.

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Authors: Hassan Manouzi

Abstract:

We present in this paper a useful strategy to solve stochastic partial differential equations (SPDEs) involving stochastic coefficients. Using the Wick-product of higher order and the Wiener-Itˆo chaos expansion, the SPDEs is reformulated as a large system of deterministic partial differential equations. To reduce the computational complexity of this system, we shall use a decomposition-coordination method. To obtain the chaos coefficients in the corresponding deterministic equations, we use a least square formulation. Once this approximation is performed, the statistics of the numerical solution can be easily evaluated.

Keywords: Least squares, Wick product, SPDEs, finite element, Wiener chaos expansion, gradient method.

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Authors: Danielle Shackley, Yetunde Folajimi

Abstract:

As more people turn to the internet seeking health related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores of text, ranging from positive, neutral and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing, tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process, and substituting the Naive Bayes for a deep learning neural network model.

Keywords: Sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model.

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Authors: H. Shamoradifar, B. Teimuri, P. Parvaresh, S. Mohammadi

Abstract:

One of the main characteristics of Heavy Water Moderated Reactors is their high production of plutonium. This article demonstrates the possibility of reduction of plutonium and other actinides in Heavy Water Research Reactor. Among the many ways for reducing plutonium production in a heavy water reactor, in this research, changing the fuel from natural Uranium fuel to Thorium-Uranium mixed fuel was focused. The main fissile nucleus in Thorium-Uranium fuels is U-233 which would be produced after neutron absorption by Th-232, so the Thorium-Uranium fuels have some known advantages compared to the Uranium fuels. Due to this fact, four Thorium-Uranium fuels with different compositions ratios were chosen in our simulations; a) 10% UO₂-90% THO₂ (enriched= 20%); b) 15% UO₂-85% THO₂ (enriched= 10%); c) 30% UO₂-70% THO₂ (enriched= 5%); d) 35% UO₂-65% THO₂ (enriched= 3.7%). The natural Uranium Oxide (UO₂) is considered as the reference fuel, in other words all of the calculated data are compared with the related data from Uranium fuel. Neutronic parameters were calculated and used as the comparison parameters. All calculations were performed by Monte Carol (MCNPX2.6) steady state reaction rate calculation linked to a deterministic depletion calculation (CINDER90). The obtained computational data showed that Thorium-Uranium fuels with four different fissile compositions ratios can satisfy the safety and operating requirements for Heavy Water Research Reactor. Furthermore, Thorium-Uranium fuels have a very good proliferation resistance and consume less fissile material than uranium fuels at the same reactor operation time. Using mixed Thorium-Uranium fuels reduced the long-lived α emitter, high radiotoxic wastes and the radio toxicity level of spent fuel.

Keywords: Burn-up, heavy water reactor, minor actinides, Monte Carlo, proliferation resistance.

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Authors: Kyaw Myo Lin

Abstract:

This paper presents small signal stability study carried over the 140-Bus, 31-Machine, 5-Area MEPE system and validated on free and open source software: PSAT. Well-established linearalgebra analysis, eigenvalue analysis, is employed to determine the small signal dynamic behavior of test system. The aspects of local and interarea oscillations which may affect the operation and behavior of power system are analyzed. Eigenvalue analysis is carried out to investigate the small signal behavior of test system and the participation factors have been determined to identify the participation of the states in the variation of different mode shapes. Also, the variations in oscillatory modes are presented to observe the damping performance of the test system.

Keywords: Eigenvalue analysis, Mode shapes, MEPE test system, Participation factors, Power System oscillations.

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Authors: Hideki Yoshikawa, Masahiro Kaminaga, Arimitsu Shikoda, Toshinori Suzuki

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Round addition differential fault analysis using operation skipping for lightweight block ciphers with on-the-fly key scheduling is presented. For 64-bit KLEIN, it is shown that only a pair of correct and faulty ciphertexts can be used to derive the secret master key. For PRESENT, one correct ciphertext and two faulty ciphertexts are required to reconstruct the secret key. Furthermore, secret key extraction is demonstrated for the LBlock Feistel-type lightweight block cipher.

Keywords: Differential Fault Analysis (DFA), round addition, block cipher, on-the-fly key schedule.

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Authors: Hemant Kumar

Abstract:

Brahmaputra River is known according to the Hindu mythology the son of the Lord Brahma. According to this name, the river Brahmaputra creates mass destruction during the monsoon season in Assam, India. It is a state situated in North-East part of India. This is one of the essential states out of the seven countries of eastern India, where almost all entire Brahmaputra flow carried out. The other states carry their tributaries. In the present case study, the spatial analysis performed in this specific case the number of MODIS data are acquired. In the method of detecting the change, the spray content was found during heavy rainfall and in the flooded monsoon season. By this method, particularly the analysis over the Brahmaputra outflow determines the flooded season. The charged particle-associated in aerosol content genuinely verifies the heavy water content below the ground surface, which is validated by trend analysis through rainfall spectrum data. This is confirmed by in-situ sampled view data from a different position of Brahmaputra River. Further, a Hyperion Hyperspectral 30 m resolution data were used to scan the sediment deposits, which is also confirmed by in-situ sampled view data from a different position.

Keywords: Spatial analysis, change detection, aerosol, trend analysis.

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Authors: Ahmed Mahmoudi, Imen Mejri, Mohamed A. Abbassi, Ahmed Omri

Abstract:

A numerical study based on the Lattice Boltzmann Method (LBM) is proposed to solve one, two and three dimensional heat and mass transfer for isothermal carbonization of thick wood particles. To check the validity of the proposed model, computational results have been compared with the published data and a good agreement is obtained. Then, the model is used to study the effect of reactor temperature and thermal boundary conditions, on the evolution of the local temperature and the mass distributions of the wood particle during carbonization

Keywords: Lattice Boltzmann Method, pyrolysis conduction, carbonization, Heat and mass transfer.

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Authors: Akram G., Jasmy Y.

Abstract:

The finite-difference time-domain (FDTD) method is one of the most widely used computational methods in electromagnetic. This paper describes the design of two-dimensional (2D) FDTD simulation software for transverse magnetic (TM) polarization using Berenger's split-field perfectly matched layer (PML) formulation. The software is developed using Matlab programming language. Numerical examples validate the software.

Keywords: Finite difference time domain (FDTD) method, perfectly matched layer (PML), split-filed formulation, transverse magnetic (TM) polarization.

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