Search results for: Performance of system

Authors: Apoorva Vinod, Archana Mathur, Snehanshu Saha

Abstract:

Though there exists a plethora of Activation Functions (AFs) used in single and multiple hidden layer Neural Networks (NN), their behavior always raised curiosity, whether used in combination or singly. The popular AFs – Sigmoid, ReLU, and Tanh – have performed prominently well for shallow and deep architectures. Most of the time, AFs are used singly in multi-layered NN, and, to the best of our knowledge, their performance is never studied and analyzed deeply when used in combination. In this manuscript, we experiment on multi-layered NN architecture (both on shallow and deep architectures; Convolutional NN and VGG16) and investigate how well the network responds to using two different AFs (Sigmoid-Tanh, Tanh-ReLU, ReLU-Sigmoid) used alternately against a traditional, single (Sigmoid-Sigmoid, Tanh-Tanh, ReLU-ReLU) combination. Our results show that on using two different AFs, the network achieves better accuracy, substantially lower loss, and faster convergence on 4 computer vision (CV) and 15 Non-CV (NCV) datasets. When using different AFs, not only was the accuracy greater by 6-7%, but we also accomplished convergence twice as fast. We present a case study to investigate the probability of networks suffering vanishing and exploding gradients when using two different AFs. Additionally, we theoretically showed that a composition of two or more AFs satisfies Universal Approximation Theorem (UAT).

Keywords: Activation Function, Universal Approximation function, Neural Networks, convergence.

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Authors: S. Z. Sarwar, N. Ehsan , I, Mirza, J. L. Piracha, M. Azeem, A. Ishaque

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The public sector losses are the major cause of stagnant growth of Pakistan. Public sector automotive manufacturing industry is one of the major contributors of these losses. This research has been carried out in order to identify the major barriers of productivity of this industry and suggest measures for improvement. This qualitative and quantitative research consisted of informal interviews, discussions augmented by closed ended questionnaire. Three major manufacturing units were chosen for this research and responses from 103 employees were collected. It was found out in this research that numerous productivity flaws exist in the system which requires immediate attention. Besides highlighting flaws this research also suggests corrective actions and areas for future research to overcome these problems.

Keywords: Automotive manufacturing industry, barriers ofproductivity, Public sector losses.

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Authors: Shahriar Farzam, Maryam Rastgarpour

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Image denoising plays extremely important role in digital image processing. Enhancement of clinical image research based on Curvelet has been developed rapidly in recent years. In this paper, we present a method for image contrast enhancement for cone beam CT (CBCT) images based on fast discrete curvelet transforms (FDCT) that work through Unequally Spaced Fast Fourier Transform (USFFT). These transforms return a table of Curvelet transform coefficients indexed by a scale parameter, an orientation and a spatial location. Accordingly, the coefficients obtained from FDCT-USFFT can be modified in order to enhance contrast in an image. Our proposed method first uses a two-dimensional mathematical transform, namely the FDCT through unequal-space fast Fourier transform on input image and then applies thresholding on coefficients of Curvelet to enhance the CBCT images. Consequently, applying unequal-space fast Fourier Transform leads to an accurate reconstruction of the image with high resolution. The experimental results indicate the performance of the proposed method is superior to the existing ones in terms of Peak Signal to Noise Ratio (PSNR) and Effective Measure of Enhancement (EME).

Keywords: Curvelet transform, image enhancement, CBCT, image denoising.

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Authors: I. Djefour, M. Saidi, I. Tlemsani, S. Toubal

Abstract:

Lignin is a molecule derived from wood and also generated as waste from the paper industry. With a view to its valorization and protection of the environment, we are interested in its use as a superplasticizer-type adjuvant in mortars and concretes to improve their mechanical strengths. The additives of the concrete have a very strong influence on the properties of the fresh and / or hardened concrete. This study examines the development and use of industrial waste and lignin extracted from a renewable natural source (wood) in cementitious materials. The use of these resources is known at present as a definite resurgence of interest in the development of building materials. Physicomechanical characteristics of mortars are determined by optimization quantity of the natural superplasticizer. The results show that the mechanical strengths of mortars based on natural adjuvant have improved by 20% (64 MPa) for a W/C ratio = 0.4, and the amount of natural adjuvant of dry extract needed is 40 times smaller than commercial adjuvant. This study has a scientific impact (improving the performance of the mortar with an increase in compactness and reduction of the quantity of water), ecological use of the lignin waste generated by the paper industry) and economic reduction of the cost price necessary to elaboration of self-compacting mortars and concretes).

Keywords: Biopolymer, lignin, industrial waste, mechanical resistances, self-compacting mortars.

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Authors: M. Zeydan, G. Toğa

Abstract:

This study deals with a multi-criteria optimization problem which has been transformed into a single objective optimization problem using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Grey Relational Analyses (GRA) approach. Grey-RSM and Grey-ANN are hybrid techniques which can be used for solving multi-criteria optimization problem. There have been two main purposes of this research as follows. 1. To determine optimum and robust fiber dyeing process conditions by using RSM and ANN based on GRA, 2. To obtain the best suitable model by comparing models developed by different methodologies. The design variables for fiber dyeing process in textile are temperature, time, softener, anti-static, material quantity, pH, retarder, and dispergator. The quality characteristics to be evaluated are nominal color consistency of fiber, maximum strength of fiber, minimum color of dyeing solution. GRA-RSM with exact level value, GRA-RSM with interval level value and GRA-ANN models were compared based on GRA output value and MSE (Mean Square Error) performance measurement of outputs with each other. As a result, GRA-ANN with interval value model seems to be suitable reducing the variation of dyeing process for GRA output value of the model.

Keywords: Artificial Neural Network, Grey Relational Analysis, Optimization, Response Surface Methodology

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Authors: A. Panacek, M. Kilianova, R. Prucek, V. Husickova, R. Vecerova, M. Kolar, L. Kvitek, R. Zboril

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In this work we describe the preparation of NanoSilver/methylcellulose hydrogel containing silver nanoparticles (NPs) for topical bactericidal applications. Highly concentrated dispersion of silver NPs as high as of 5g/L of silver with diameter of 10nm was prepared by reduction of AgNO₃ via strong reducing agent NaBH₄. Silver NPs were stabilized by addition of sodium polyacrylate in order to prevent their aggregation at such high concentration. This way synthesized silver NPs were subsequently incorporated into methylcellulose suspension at elevated temperature resulting in formation of NanoSilver/methylcellulose hydrogel when temperature cooled down to laboratory conditions. In vitro antibacterial activity assay proved high bactericidal and fungicidal efficiency of silver NPs alone in the form of dispersion as well as in the form of hydrogel against broad spectrum of bacteria and yeasts including highly multiresistant strains such as methicillin-resistant Staphylococcus aureus. A very low concentrations of silver as low as 0.84mg/L Ag in as-prepared dispersion gave antibacterial performance. NanoSilver/methylcellulose hydrogel showed antibacterial action at the lowest used silver concentration equal to 25mg/L. Such prepared NanoSilver/methylcellulose hydrogel represent promising topical antimicrobial formulation for treatment of burns and wounds.

Keywords: Antimicrobial, burn, hydrogel, silver NPs.

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Authors: S. Tangjitsitcharoen

Abstract:

The chatter is one of the major limitations of the productivity in the ball end milling process. It affects the surface roughness, the dimensional accuracy and the tool life. The aim of this research is to propose the new system to detect the chatter during the ball end milling process by using the wavelet transform. The proposed method is implemented on the 5-axis CNC machining center and the new three parameters are introduced from three dynamic cutting forces, which are calculated by taking the ratio of the average variances of dynamic cutting forces to the absolute variances of themselves. It had been proved that the chatter can be easier to detect during the in-process cutting by using the new parameters which are proposed in this research. The experimentally obtained results showed that the wavelet transform can provide the reliable results to detect the chatter under various cutting conditions.

Keywords: Ball end milling, wavelet transform, fast fourier transform, chatter.

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Authors: Safwan Kanan, Jonathan Dewsbury, Gregory Lane-Serff

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A salinity gradient solar pond is a free energy source system for collecting, convertingand storing solar energy as heat. In thispaper, the principles of solar pond are explained. A mathematical model is developed to describe and simulate heat and mass transferbehaviour of salinity gradient solar pond. MATLAB codes are programmed to solve the one dimensional finite difference method for heat and mass transfer equations. Temperature profiles and concentration distributions are calculated. The numerical results are validated with experimental data and the results arefound to be in good agreement.

Keywords: Finite Difference method, Salt-gradient solar-pond, Solar energy, Transient heat and mass transfer.

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Authors: Nurul Azma Zakaria, Masahiro Kimura, Noriko Matsumoto, Norihiko Yoshida

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The fast growth in complexity coupled with requests for shorter development periods for embedded systems are bringing demands towards a more effective, i.e. higher-abstract, design process for hardaware/software integrated design. In Software Engineering area, Model Driven Architecture (MDA) and Executable UML (xUML) has been accepted to bring further improvement in software design. This paper constructs MDA and xUML stepwise transformations from an abstract specification model to a more concrete implementation model using the refactoring technique for hardaware/software integrated design. This approach provides clear and structured models which enables quick exploration and synthesis, and early stage verification.

Keywords: Hardware/software integrated design, model driven architecture, executable UML, refactoring.

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Authors: Attila Balogh, Eszter Varga, István Varjasi

Abstract:

Nowadays there are several grid connected converter in the grid system. These grid connected converters are generally the converters of renewable energy sources, industrial four quadrant drives and other converters with DC link. These converters are connected to the grid through a three phase bridge. The standards prescribe the maximal harmonic emission which could be easily limited with high switching frequency. The increased switching losses can be reduced to the half with the utilization of the wellknown Flat-top modulation. The suggested control method is the expansion of the Flat-top modulation with which the losses could be also reduced to the half compared to the Flat-top modulation. Comparing to traditional control these requirements can be simultaneously satisfied much better with the DLF (DC Link Floating) method.

Keywords: DC link floating, high efficiency, PV converter, control method.

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Authors: Daniel Icaza, Federico Córdova, Chiristian Castro, Fernando Icaza, Juan Portoviejo

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In this article, the mathematical model is presented, and simulations were carried out using specialized software such as MATLAB before the construction of a 900-W wind turbine. The present study was conducted with the intention of taking advantage of the rotation of the blades of the wind generator after going through a process of amplification of speed by means of a system of gears to finally mechanically couple two electric generators of similar characteristics. This coupling allows generating a maximum voltage of 6 V in DC for each generator and putting in series the 12 V DC is achieved, which is later stored in batteries and used when the user requires it. Laboratory tests were made to verify the level of power generation produced based on the wind speed at the entrance of the blades.

Keywords: Smart grids, wind turbine, modeling, renewable energy, robust control.

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Authors: Sandu L., Topală F., Porojan S.

Abstract:

Cast metal inlays can be used on molars requiring a class II restoration instead amalgam and offer a durable alternative. Because it is known that class II inlays may increase the susceptibility to fracture, it is important to ensure optimal performance in selection of the adequate preparation design to reduce stresses in teeth structures and also in the restorations. The aim of the study was to investigate the influence of preparation design on stress distribution in molars with different class II preparations and in cast metal inlays. The first step of the study was to achieve 3D models in order to analyze teeth and cast metal class II inlays. The geometry of the intact tooth was obtained by 3D scanning using a manufactured device. With a NURBS modeling program the preparations and the appropriately inlays were designed. 3D models of first upper molars of the same shape and size were created. Inlay cavities designs were created using literature data. The geometrical model was exported and the mesh structure of the solid 3D model was created for structural simulations. Stresses were located around the occlusal contact areas. For the studied cases, the stress values were not significant influenced by the taper of the preparation. it was demonstrated stresses are higher in the cast metal restorations and therefore the strength of the teeth is not affected.

Keywords: cast metal inlays, class II restoration, molars, 3D models, structural simulations.

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: Speech recognition, acoustic phonetic, artificial intelligence, Hidden Markov Models (HMM), statistical models of speech recognition, human machine performance.

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Authors: Kahraman Ayyildiz, Stefan Conrad

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In this paper we illuminate a frequency domain based classification method for video scenes. Videos from certain topical areas often contain activities with repeating movements. Sports videos, home improvement videos, or videos showing mechanical motion are some example areas. Assessing main and side frequencies of each repeating movement gives rise to the motion type. We obtain the frequency domain by transforming spatio-temporal motion trajectories. Further on we explain how to compute frequency features for video clips and how to use them for classifying. The focus of the experimental phase is on transforms utilized for our system. By comparing various transforms, experiments show the optimal transform for a motion frequency based approach.

Keywords: action recognition, frequency, transform, motion recognition, repeating movement, video classification

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Authors: Aleem Khalid Alvi, M. Yousuf Bin Azhar, Mehmood Usman, Suleman Mumtaz, Sameer Rafiq, RaziUr Rehman, Israr Ahmed

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Sign language recognition has been a topic of research since the first data glove was developed. Many researchers have attempted to recognize sign language through various techniques. However none of them have ventured into the area of Pakistan Sign Language (PSL). The Boltay Haath project aims at recognizing PSL gestures using Statistical Template Matching. The primary input device is the DataGlove5 developed by 5DT. Alternative approaches use camera-based recognition which, being sensitive to environmental changes are not always a good choice.This paper explains the use of Statistical Template Matching for gesture recognition in Boltay Haath. The system recognizes one handed alphabet signs from PSL.

Keywords: Gesture Recognition, Pakistan Sign Language, DataGlove, Human Computer Interaction, Template Matching, BoltayHaath

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Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

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Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.

Keywords: IDS, DDoS, MLP, KDD.

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.

Keywords: Human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, Prior distribution and approximate posterior distribution, KTH dataset.

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Authors: Bhausaheb L. Pangarkar, M. G. Sane, Saroj B. Parjane, Rajendra M. Abhang, Mahendra Guddad

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Vacuum membrane distillation (VMD) process can be used for water purification or the desalination of salt water. The process simply consists of a flat sheet hydrophobic micro porous PTFE membrane and diaphragm vacuum pump without a condenser for the water recovery or trap. The feed was used aqueous NaCl solution. The VMD experiments were performed to evaluate the heat and mass transfer coefficient of the boundary layer in a membrane module. The only operating parameters are feed inlet temperature, and feed flow rate were investigated. The permeate flux was strongly affected by the feed inlet temperature, feed flow rate, and boundary layer heat transfer coefficient. Since lowering the temperature polarization coefficient is essential enhance the process performance considerable and maximizing the heat transfer coefficient for maximizes the mass flux of distillate water. In this paper, the results of VMD experiments are used to measure the boundary layer heat transfer coefficient, and the experimental results are used to reevaluate the empirical constants in the Dittus- Boelter equation.

Keywords: Desalination, heat and mass transfer coefficient, temperature polarization, membrane distillation

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Authors: A.Shokri, A.Faraahi

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Here are many methods for designing and implementation of virtual laboratories, because of their special features. The most famous architectural designs are based on the events. This model of architecting is so efficient for virtual laboratories implemented on a local network. Later, serviceoriented architecture, gave the remote access ability to them and Peer-To-Peer architecture, hired to exchanging data with higher quality and more speed. Other methods, such as Agent- Based architecting, are trying to solve the problems of distributed processing in a complicated laboratory system. This study, at first, reviews the general principles of designing a virtual laboratory, and then compares the different methods based on EDA, SOA and Agent-Based architecting to present weaknesses and strengths of each method. At the end, we make the best choice for design, based on existing conditions and requirements.

Keywords: Virtual Laboratory, Software Engineering, Simulation, EDA, SOA, Agent-Based Architecting.

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Authors: Tomas Makaras, Gintaras Svecevičius

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Landfill waste is a common problem as it has an economic and environmental impact even if it is closed. Landfill waste contains a high density of various persistent compounds such as heavy metals, organic and inorganic materials. As persistent compounds are slowly-degradable or even non-degradable in the environment, they often produce sublethal or even lethal effects on aquatic organisms. The aims of the present study were to estimate sublethal effects of the Kairiai landfill (WGS: 55°55‘46.74“, 23°23‘28.4“) leachate on the locomotor activity of rainbow trout Oncorhynchus mykiss juveniles using the original system package developed in our laboratory for automated monitoring, recording and analysis of aquatic organisms’ activity, and to determine patterns of fish behavioral response to sublethal effects of leachate. Four different concentrations of leachate were chosen: 0.125; 0.25; 0.5 and 1.0 mL/L (0.0025; 0.005; 0.01 and 0.002 as part of 96-hour LC50, respectively). Locomotor activity was measured after 5, 10 and 30 minutes of exposure during 1-minute test-periods of each fish (7 fish per treatment). The threshold-effect-concentration amounted to 0.18 mL/L (0.0036 parts of 96-hour LC50). This concentration was found to be even 2.8-fold lower than the concentration generally assumed to be “safe” for fish. At higher concentrations, the landfill leachate solution elicited behavioral response of test fish to sublethal levels of pollutants. The ability of the rainbow trout to detect and avoid contaminants occurred after 5 minutes of exposure. The intensity of locomotor activity reached a peak within 10 minutes, evidently decreasing after 30 minutes. This could be explained by the physiological and biochemical adaptation of fish to altered environmental conditions. It has been established that the locomotor activity of juvenile trout depends on leachate concentration and exposure duration. Modeling of these parameters showed that the activity of juveniles increased at higher leachate concentrations, but slightly decreased with the increasing exposure duration. Experiment results confirm that the behavior of rainbow trout juveniles is a sensitive and rapid biomarker that can be used in combination with the system for fish behavior monitoring, registration and analysis to determine sublethal concentrations of pollutants in ambient water. Further research should be focused on software improvement aimed to include more parameters of aquatic organisms’ behavior and to investigate the most rapid and appropriate behavioral responses in different species. In practice, this study could be the basis for the development and creation of biological early-warning systems (BEWS).

Keywords: Fish behavior biomarker, landfill leachate, locomotor activity, rainbow trout juveniles, sublethal effects.

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Authors: A. Suleng, T. Jelstad Olsen, J. Šindler, P. Bárta

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A dead leg is a typical subsea production system component. CFD is required to model heat transfer within the dead leg. Unfortunately its solution is time demanding and thus not suitable for fast prediction or repeated simulations. Therefore there is a need to create a thermal FEA model, mimicking the heat flows and temperatures seen in CFD cool down simulations. This paper describes the conventional way of tuning and a new automated way using parametric model order reduction (PMOR) together with an optimization algorithm. The tuned FE analyses replicate the steady state CFD parameters within a maximum error in heat flow of 6 % and 3 % using manual and PMOR method respectively. During cool down, the relative error of the tuned FEA models with respect to temperature is below 5% comparing to the CFD. In addition, the PMOR method obtained the correct FEA setup five times faster than the manually tuned FEA.

Keywords: CFD, convective heat, FEA, model tuning, subseaproduction

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Authors: N. Ould Cherchali, A. Tlemçani, M. S. Boucherit, A. Morsli

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Nature-inspired metaheuristic algorithms, particularly those founded on swarm intelligence, have attracted much attention over the past decade. Firefly algorithm has appeared in approximately seven years ago, its literature has enlarged considerably with different applications. It is inspired by the behavior of fireflies. The aim of this paper is the application of firefly algorithm for solving a nonlinear algebraic system. This resolution is needed to study the Selective Harmonic Eliminated Pulse Width Modulation strategy (SHEPWM) to eliminate the low order harmonics; results have been applied on multilevel inverters. The final results from simulations indicate the elimination of the low order harmonics as desired. Finally, experimental results are presented to confirm the simulation results and validate the efficaciousness of the proposed approach.

Keywords: Firefly algorithm, metaheuristic algorithm, multilelvel inverter, SHEPWM.

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Authors: Ramin Vafadary, Maryam Khanbaghi

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Forecasting electricity load is important for various purposes like planning, operation and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria namely, the Mean Absolute Error and Root Mean Square Error. The National Renewable Energy Laboratory (NREL) residential energy consumption data are used to train the models. The results of this study show that SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts we can improve the robustness of the models for 24 hour ahead electricity load forecasting.

Keywords: Bagging, Fbprophet, Holt-Winters, LSTM, Load Forecast, SARIMA, tensorflow probability, time series.

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Authors: Adriana Alexandru, Cristian Tantareanu, Elena Jitaru

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The paper presents the potential for RES in Romania and the results of the Romanian national research project “Romania contribution to the European targets regarding the development of renewable energy sources - PROMES". The objective of the project is the development of energy generation from renewable energy sources (RES) in Romania by drawing up scenarios and prognosis harmonized with national and European targets, RES development effects modeling (environmental, economic, social etc.), research of the impact of the penetration of RES into the main, implementation of an advanced software system tool for RES information recording and communication, experimental research based on demonstrative applications. The expected results are briefly presented, as well as the social, economic and environmental impact.

Keywords: Energy policy, Internet, renewable energy sources, potential.

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Authors: Zixin Liu, Huawei Yang, Fangwei Chen

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This paper studies the mean square exponential synchronization problem of a class of stochastic neutral type chaotic neural networks with mixed delay. On the Basis of Lyapunov stability theory, some sufficient conditions ensuring the mean square exponential synchronization of two identical chaotic neural networks are obtained by using stochastic analysis and inequality technique. These conditions are expressed in the form of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using Matlab LMI Toolbox. The feedback controller used in this paper is more general than those used in previous literatures. One simulation example is presented to demonstrate the effectiveness of the derived results.

Keywords: Exponential synchronization, stochastic analysis, chaotic neural networks, neutral type system.

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Authors: X. Wang, J. S. Kuang

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The Fixed-angle Softened Truss Model with Tension-stiffening (FASTMT) has a superior performance in predicting the shear behaviour of reinforced concrete (RC) membrane elements, especially for the post-cracking behaviour. Nevertheless, massive computational work is inevitable due to the multiple transcendental equations involved in the stress-strain relationship. In this paper, an iterative root-finding technique is introduced to FASTMT for solving quickly the transcendental equations of the tension-stiffening effect of RC membrane elements. This fast FASTMT, which performs in MATLAB, uses the bisection method to calculate the tensile stress of the membranes. By adopting the simplification, the elapsed time of each loop is reduced significantly and the transcendental equations can be solved accurately. Owing to the high efficiency and good accuracy as compared with FASTMT, the fast FASTMT can be further applied in quick prediction of shear behaviour of complex large-scale RC structures.

Keywords: Bisection method, fixed-angle softened truss model with tension-stiffening, iterative root-finding technique, reinforced concrete membrane.

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Authors: Ramón Cruzat, Sergio F. Ochoa, Ignacio Casas, Luis A. Guerrero, José Bravo

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Patients under health treatments that involve long  stays at a hospital or health center (e.g. cancer, organ transplants and  severe burns), tend to get bored or depressed because of the lack of  social interaction with family and friends. Such a situation also  affects the evolution and effectiveness of their treatments. In many  cases, the solution to this problem involves extra challenges, since  many patients need to rest quietly (or remain in bed) to their being  contagious. Considering the weak health condition in which usually  are these kinds, keeping them motivated and quiet represents an  important challenge for nurses and caregivers. This article presents a  mobile ubiquitous game called MagicRace, which allows hospitalized  kinds to interact socially with one another without putting to risk  their sensitive health conditions. The game does not require a  communication infrastructure at the hospital, but instead, it uses a  mobile ad hoc network composed of the handheld devices used by  the kids to play. The usability and performance of this application  was tested in two different sessions. The preliminary results show  that users experienced positive feelings from this experience.

 

Keywords: Ubiquitous game, children's emotional support, social isolation, mobile collaborative interactions.

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Authors: Mohsin T. Mohammed, Zahid A. Khan, Arshad N. Siddiquee

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The field of biomedical materials plays an imperative requisite and a critical role in manufacturing a variety of biological artificial replacements in a modern world. Recently, titanium (Ti) materials are being used as biomaterials because of their superior corrosion resistance and tremendous specific strength, free- allergic problems and the greatest biocompatibility compared to other competing biomaterials such as stainless steel, Co-Cr alloys, ceramics, polymers, and composite materials. However, regardless of these excellent performance properties, Implantable Ti materials have poor shear strength and wear resistance which limited their applications as biomaterials. Even though the wear properties of Ti alloys has revealed some improvements, the crucial effectiveness of biomedical Ti alloys as wear components requires a comprehensive deep understanding of the wear reasons, mechanisms, and techniques that can be used to improve wear behavior. This review examines current information on the effect of thermal and thermomechanical processing of implantable Ti materials on the long-term prosthetic requirement which related with wear behavior. This paper focuses mainly on the evolution, evaluation and development of effective microstructural features that can improve wear properties of bio grade Ti materials using thermal and thermomechanical treatments.

Keywords: Wear Resistance, Heat Treatment, Thermomechanical Processing, Biomedical Titanium Materials.

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Authors: Weena Eiamprapai

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The growth of Thai society in western style in the middle of Rattanakosin period can be defined as modernization /civilization. These terms had an influence on the development of the country in the reign of King Rama V owing to the governance reform, and cultures influenced by the West. Those were passed on until the reign of King Rama VI. The preference was not only for the renovation of architecture and arts based on Thai customs reflecting the prosperity and beauty of handicrafts but also for the acceptance of westernization. The remain of this acceptance includes the concept of such value as gentlemanly behavior like that in Victorian Era of the United Kingdom, and the support of women’s status. Moreover, the wide spread of modernization leads to the movement to change the country’s governance system from absolute monarchy to democracy by a group of people called Rattanakosin Era (R.E.) 130 party.

Keywords: Art and culture, development period, modernization, King Rama VI.

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Authors: Fitria Rahmawati, Nuryani, Liviana Wijayanti

Abstract:

This research study the application of the immobilized TiO2 layer and Cu-TiO2 layer on graphite substrate as a negative electrode or anode for Li-ion battery. The titania layer was produced through chemical bath deposition method, meanwhile Cu particles were deposited electrochemically. A material can be used as an electrode as it has capability to intercalates Li ions into its crystal structure. The Li intercalation into TiO2/Graphite and Cu- TiO2/Graphite were analyzed from the changes of its XRD pattern after it was used as electrode during discharging process. The XRD patterns were refined by Le Bail method in order to determine the crystal structure of the prepared materials. A specific capacity and the cycle ability measurement were carried out to study the performance of the prepared materials as negative electrode of the Li-ion battery. The specific capacity was measured during discharging process from fully charged until the cut off voltage. A 300 was used as a load. The result shows that the specific capacity of Li-ion battery with TiO2/Graphite as negative electrode is 230.87 ± 1.70mAh.g-1 which is higher than the specific capacity of Li-ion battery with pure graphite as negative electrode, i.e 140.75 ±0.46mAh.g-1. Meanwhile deposition of Cu onto TiO2 layer does not increase the specific capacity, and the value even lower than the battery with TiO2/Graphite as electrode. The cycle ability of the prepared battery is only two cycles, due to the Li ribbon which was used as cathode became fragile and easily broken.

Keywords: Cu-TiO2, electrode, graphite substrate, Li-ion battery, TiO2 layer.

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