Search results for: electron back scattered diffraction.

Authors: A. Udayakumar, M. Rizvan Basha, M. Stalin, V.V Bhanu Prasad

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Three dimensional non-Interlaced carbon fibre reinforced silicon carbide (3-D-Cf/SiC) composites with pyrocarbon interphase were fabricated using isothermal chemical vapor infiltration (ICVI) combined with polymer impregnation pyrolysis (PIP) process. Polysilazane (PSZ) is used as a preceramic polymer to obtain silicon carbide matrix. Thermo gravimetric analysis (TGA), Infrared spectroscopic analysis (IR) and X-ray diffraction (XRD) analysis were carried out on PSZ pyrolysed at different temperatures to understand the pyrolysis and obtaining the optimum pyrolysing condition to yield β-SiC phase. The density of the composites was 1.94 g cm-3 after the 3-D carbon preform was SiC infiltrated for 280 h with one intermediate polysilazane pre-ceramic PIP process. Mechanical properties of the composite materials were investigated under tensile, flexural, shear and impact loading. The values of tensile strength were 200 MPa at room temperature (RT) and 195 MPa at 500°C in air. The average RT flexural strength was 243 MPa. The lower flexural strength of these composites is because of the porosity. The fracture toughness obtained from single edge notched beam (SENB) technique was 39 MPa.m1/2. The work of fracture obtained from the load-displacement curve of SENB test was 22.8 kJ.m-2. The composites exhibited excellent impact resistance and the dynamic fracture toughness of 44.8 kJ.m-2 is achieved as determined from instrumented Charpy impact test. The shear strength of the composite was 93 MPa, which is significantly higher compared 2-D Cf/SiC composites. Microstructure evaluation of fracture surfaces revealed the signatures of fracture processes and showed good support for the higher toughness obtained.

Keywords: 3-D-Cf/SiC, charpy impact test, composites, dynamic fracture toughness, polysilazane, pyrocarbon, Interphase.

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Authors: Foad Nazari, Seyed Mahmood Hosseini, Mohammad Hossein Abolbashari, Mohammad Hassan Abolbashari

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The present study is concerned with the optimal design of functionally graded plates using particle swarm optimization (PSO) algorithm. In this study, meshless local Petrov-Galerkin (MLPG) method is employed to obtain the functionally graded (FG) plate’s natural frequencies. Effects of two parameters including thickness to height ratio and volume fraction index on the natural frequencies and total mass of plate are studied by using the MLPG results. Then the first natural frequency of the plate, for different conditions where MLPG data are not available, is predicted by an artificial neural network (ANN) approach which is trained by back-error propagation (BEP) technique. The ANN results show that the predicted data are in good agreement with the actual one. To maximize the first natural frequency and minimize the mass of FG plate simultaneously, the weighted sum optimization approach and PSO algorithm are used. However, the proposed optimization process of this study can provide the designers of FG plates with useful data.

Keywords: Optimal design, natural frequency, FG plate, hybrid meshless method, MLPG method, ANN approach, particle swarm optimization.

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Authors: Ghzlan Mahmoud Abdel Aziz

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This case study aims to identify the intrastate conflicts between the nation state and armed groups. Nowadays, most wars weaken states against armed groups. Thus, it is very important to negotiate with such groups in order to reinforce the law for the protection of victims. These armed groups are the cause of conflicts and they are related with many of humanitarian issues that result out of conflicts. In this age of rivalry; terrorists, insurgents, or transnational criminal parties have surfaced to the top as a reaction to these armed groups in an effort to set up a new world order. Moreover, the intra state conflicts became increasingly treacherous than the interstate conflicts, particularly when nation state systems deal with armed groups which try to influence the state. The unexpected upraising of the Arab Spring during 2011 in parts of the Middle East and North Africa formed various patterns of conflicts. The events of the Arab Spring resulted in current and long term change across the region. Significant modifications in the level, strength and period of armed conflict around the world have been made. Egypt was in the center of these events. It has fought back the armed groups under the name of terrorism and spread common disorder and violence among civilians. On this note, this study focuses on the problem of the transformation in the methods of organized violence within one state rather than between two state or more and analyzes the objectives, strategies, and internal composition of armed groups and the environments that foster them, with a focus on the Egyptian case.

Keywords: Armed groups, conflicts, Egyptian armed forces, intrastate conflicts.

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Authors: L. Major, J. M. Lackner, M. Dyner, B. Major

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Development of new generation bio-tribological, multilayer coatings opens an avenue for fabrication of future hightech functional surfaces. In the presented work, nano-composite, Cr/CrN+[Cr/ a-C:H implanted by metallic nanocrystals] multilayer coatings have been developed for surface protection of medical tools. Thin films were fabricated by a hybrid Pulsed Laser Deposition technique. Complex microstructure analysis of nanomultilayer coatings, subjected to mechanical and biological tests, were performed by means of transmission electron microscopy (TEM). Microstructure characterization revealed the layered arrangement of Cr23C6 nanoparticles in multilayer structure. Influence of deposition conditions on bio-tribological properties of the coatings was studied. The bio-tests were used as a screening tool for the analyzed nanomultilayer coatings before they could be deposited on medical tools. Bio-medical tests were done using fibroblasts. The mechanical properties of the coatings were investigated by means of a ball-ondisc mechanical test. The micro hardness was done using Berkovich indenter. The scratch adhesion test was done using Rockwell indenter. From the bio-tribological point of view, the optimal properties had the C106_1 material.

Keywords: Bio-tribological coatings, cell-material interaction, hybrid PLD, tribology.

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Authors: Paria Soleimani, Arezoo Neshati

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Myocardial infarction is one of the leading causes of death in the world. Some of these deaths occur even before the patient reaches the hospital. Myocardial infarction occurs as a result of impaired blood supply. Because the most of these deaths are due to coronary artery disease, hence the awareness of the warning signs of a heart attack is essential. Some heart attacks are sudden and intense, but most of them start slowly, with mild pain or discomfort, then early detection and successful treatment of these symptoms is vital to save them. Therefore, importance and usefulness of a system designing to assist physicians in early diagnosis of the acute heart attacks is obvious. The main purpose of this study would be to enable patients to become better informed about their condition and to encourage them to seek professional care at an earlier stage in the appropriate situations. For this purpose, the data were collected on 711 heart patients in Iran hospitals. 28 attributes of clinical factors can be reported by patients; were studied. Three logistic regression models were made on the basis of the 28 features to predict the risk of heart attacks. The best logistic regression model in terms of performance had a C-index of 0.955 and with an accuracy of 94.9%. The variables, severe chest pain, back pain, cold sweats, shortness of breath, nausea and vomiting, were selected as the main features.

Keywords: Coronary heart disease, acute heart attacks, prediction, logistic regression.

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Authors: Jaibir Sharma, Lee JaeWung, Merugu Srinivas, Navab Singh

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This paper presents thermal annealing de-wetting technique for the preparation of porous metal membrane for Thin Film Encapsulation (TFE) application. Thermal annealing de-wetting experimental results reveal that pore size formation in porous metal membrane depend upon i.e. 1. The substrate at which metal is deposited, 2. Melting point of metal used for porous metal cap layer membrane formation, 3. Thickness of metal used for cap layer, 4. Temperature used for formation of porous metal membrane. In order to demonstrate this technique, Silver (Ag) was used as a metal for preparation of porous metal membrane on amorphous silicon (a-Si) and silicon oxide. The annealing of the silver thin film of various thicknesses was performed at different temperature. Pores in porous silver film were analyzed using Scanning Electron Microscope (SEM). In order to check the usefulness of porous metal film for TFE application, the porous silver film prepared on amorphous silicon (a- Si) and silicon oxide was released using XeF2 and VHF, respectively. Finally, guide line and structures are suggested to use this porous membrane for robust TFE application.

Keywords: De-wetting, thermal annealing, metal, melting point, porous.

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Authors: Pradyumna Kumar Sahoo, Prasanta Kumar Satpathy

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This paper aims at finding a suitable neural network for monitoring congestion level in electrical power systems. In this paper, the input data has been framed properly to meet the target objective through supervised learning mechanism by defining normal and abnormal operating conditions for the system under study. The congestion level, expressed as line congestion index (LCI), is evaluated for each operating condition and is presented to the NN along with the bus voltages to represent the input and target data. Once, the training goes successful, the NN learns how to deal with a set of newly presented data through validation and testing mechanism. The crux of the results presented in this paper rests on performance comparison of a multi-layered feed forward neural network with eleven types of back propagation techniques so as to evolve the best training criteria. The proposed methodology has been tested on the standard IEEE-14 bus test system with the support of MATLAB based NN toolbox. The results presented in this paper signify that the Levenberg-Marquardt backpropagation algorithm gives best training performance of all the eleven cases considered in this paper, thus validating the proposed methodology.

Keywords: Line congestion index, critical bus, contingency, neural network.

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Authors: Mohammad T. Shervani-Tabar, Navid Shervani-Tabar

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Tip vortex cavitation is one of well known patterns of cavitation phenomenon which occurs in axial pumps. This pattern of cavitation occurs due to pressure difference between the pressure and suction sides of blades of an axial pump. Since the pressure in the pressure side of the blade is higher than the pressure in its suction side, thus a very small portion of liquid flow flows back from pressure side to the suction side. This fact is cause of tip vortex cavitation and gap cavitation that may occur in axial pumps. In this paper the results of our experimental investigation about movement of tip vortex cavitation along blade edge due to reduction of pump flow rate in an axial pump is reported. Results show that reduction of pump flow rate in conjunction with increasing of outlet pressure causes movement of tip vortex cavitation along blade edge towards the blade tip. Results also show that by approaching tip vortex cavitation to the blade tip, vortex tip pattern of cavitation replaces with a cavitation phenomenon on the blade tip. Furthermore by further reduction of pump flow rate and increasing of outlet pressure, an unstable cavitation phenomenon occurs between each blade leading edge and the next blade trailing edge.

Keywords: Axial Flow Pump, Cavitation, Gap Cavitation, Tip Vortex Cavitation.

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Authors: Axay J Mehta, Hema A Mehta, T.C.Manjunath, C. Ardil

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In this paper, the modelling and design of artificial neural network architecture for load forecasting purposes is investigated. The primary pre-requisite for power system planning is to arrive at realistic estimates of future demand of power, which is known as Load Forecasting. Short Term Load Forecasting (STLF) helps in determining the economic, reliable and secure operating strategies for power system. The dependence of load on several factors makes the load forecasting a very challenging job. An over estimation of the load may cause premature investment and unnecessary blocking of the capital where as under estimation of load may result in shortage of equipment and circuits. It is always better to plan the system for the load slightly higher than expected one so that no exigency may arise. In this paper, a load-forecasting model is proposed using a multilayer neural network with an appropriately modified back propagation learning algorithm. Once the neural network model is designed and trained, it can forecast the load of the power system 24 hours ahead on daily basis and can also forecast the cumulative load on daily basis. The real load data that is used for the Artificial Neural Network training was taken from LDC, Gujarat Electricity Board, Jambuva, Gujarat, India. The results show that the load forecasting of the ANN model follows the actual load pattern more accurately throughout the forecasted period.

Keywords: Power system, Load forecasting, Neural Network, Neuron, Stabilization, Network structure, Load.

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Authors: Sadegh Masoudi, Ali Asghar Yousefi, Somayeh Nourollahi, Fatemeh Noughani

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Two different testicular tissues have to be distinguished in regard to radiation damage: first the seminiferous tubules, corresponding to the sites of spermatogenesis, which are extremely radiosensitive. Second the testosterone secreting Leydig cells, which are considered to be less radiosensitive. This study aims to estimate testicular dose and the associated risks for infertility and hereditary effects from Abdominal and pelvic irradiation. Radiotherapy was simulated on a humanoid phantom using a 15 MV photon beam. Testicular dose was measured for various field sizes and tissue thicknesses along beam axis using an ionization chamber and TLD. For transmission Factor Also common method of measuring the absorbed dose distribution and electron contamination in the build-up region of high-energy beams for radiation therapy is by means of parallel-plate Ionisation chambers. Gonadal dose was reduced by placing lead cups around the testes supplemented by a field edge block. For a tumor dose of 100 cGy, testicular dose was 2.96-8.12 cGy depending upon the field size and the distance from the inferior field edge. The treatment at parameters, the presence of gonad shield and the somatometric characteristics determine whether testicular dose can exceed 1 Gy which allows a complete recovery of spermatogenesis.

Keywords: Absorbed Dose, Abdominal and pelvic, gonads men, Radiotherapy.

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Authors: M. J. Shivaram, Shashi Bhushan Arya, Jagannath Nayak, Bharat Bhooshan Panigrahi

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Titanium and its alloys have become more significant implant materials due to their mechanical properties, excellent biocompatibility and high corrosion resistance. Biomaterials can be produce by using the powder metallurgy (PM) methods and required properties can tailored by varying the processing parameters, such as ball milling time, space holder particles, and sintering temperature. The desired properties such as, structural and mechanical properties can be obtained by powder metallurgy method.  In the present study, deals with fabrication of solid and porous Ti-20Nb-5Ag alloy using high energy ball milling for different times (5 and 20 h). The resultant powder particles were used to fabricate solid and porous Ti-20Nb-5Ag alloy by adding space holder particles (NH₄HCO₃). The resultant powder particles, fabricated solid and porous samples were characterized by scanning electron microscopy (SEM). The compressive strength, elastic modulus and microhardness properties were investigated. Solid and porous Ti-20Nb-5Ag alloy samples showed good mechanical properties for 20 h ball milling time as compare to 5 h ball milling.

Keywords: Ball Milling, compressive strengths, microstructure, porous Titanium alloy.

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Authors: Mikhail Vladimirovich Deryabin, Morten Willatzen

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In this work, we address theoretically the influence of red and white Gaussian noise for electronic energies and eigenstates of cylindrically shaped quantum dots. The stochastic effect can be imagined as resulting from crystal-growth statistical fluctuations in the quantum-dot material composition. In particular we obtain analytical expressions for the eigenvalue shifts and electronic envelope functions in the k . p formalism due to stochastic variations in the confining band-edge potential. It is shown that white noise in the band-edge potential leaves electronic properties almost unaffected while red noise may lead to changes in state energies and envelopefunction amplitudes of several percentages. In the latter case, the ensemble-averaged envelope function decays as a function of distance. It is also shown that, in a stochastic system, constant ensembleaveraged envelope functions are the only bounded solutions for the infinite quantum-wire problem and the energy spectrum is completely discrete. In other words, the infinite stochastic quantum wire behaves, ensemble-averaged, as an atom.

Keywords: cylindrical quantum dots, electronic eigen energies, red and white Gaussian noise, ensemble averaging effects.

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Authors: Rishabh Garg

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Traditionally, business parties build trust with a centralized operating mechanism, such as payment by letter of credit. However, the increase in cyber-attacks and malicious hacking has jeopardized business operations and finance practices. Emerging markets, due to their high banking risks and the large presence of digital financing, are looking for technology that enables transparency and traceability of any transaction in trade, finance or supply chain management. Blockchain systems, in the absence of any central authority, enable transactions across the globe with the help of decentralized applications. DApps consist of a front-end, a blockchain back-end, and middleware, that is, the code that connects the two. The front-end can be a sophisticated web app or mobile app, which is used to implement the functions/methods on the smart contract. Web apps can employ technologies such as HTML, CSS, React and Express. In this wake, fintech and blockchain products are popping up in brokerages, digital wallets, exchanges, post-trade clearance, settlement, middleware, infrastructure and base protocols. The present paper provides a technology driven solution, financial inclusion and innovative working paradigm for business and finance.

Keywords: Authentication, blockchain, channel, cryptography, DApps, data portability, Decentralized Public Key Infrastructure, Ethereum, hash function, Hashgraph, Privilege creep, Proof of Work algorithm, revocation, storage variables, Zero Knowledge Proof.

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Authors: H. D. Ibrahim, H. C. Chinwenyi, A. H. Usman

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Valuing derivatives (options, futures, swaps, forwards, etc.) is one uneasy task in financial mathematics. The two ways this problem can be effectively resolved in finance is by the use of two methods (Martingales and Partial Differential Equations (PDEs)) to obtain their respective options price valuation formulas. This research paper examined two different stochastic financial models which are Constant Elasticity of Variance (CEV) model and Black-Karasinski term structure model. Assuming their respective option price valuation formulas, we proved the analogous of the Martingales and PDEs options price valuation formulas for the two different Stochastic Differential Equation (SDE) models. This was accomplished by using the applications of Girsanov theorem for defining an Equivalent Martingale Measure (EMM) and the Feynman-Kac theorem. The results obtained show the systematic proof for analogous of the two (Martingales and PDEs) options price valuation formulas beginning with the Martingales option price formula and arriving back at the Black-Scholes parabolic PDEs and vice versa.

Keywords: Option price valuation, Martingales, Partial Differential Equations, PDEs, Equivalent Martingale Measure, Girsanov Theorem, Feyman-Kac Theorem, European Put Option.

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Authors: Shin-Jer Yang, Kai-Tai Yang

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In response to a changing world and the fast growth of the Internet, more and more enterprises are replacing web-based services with cloud-based ones. Multi-tenancy technology is becoming more important especially with Software as a Service (SaaS). This in turn leads to a greater focus on the application of Identity and Access Management (IAM). Conventional Near-Field Communication (NFC) based verification relies on a computer browser and a card reader to access an NFC tag. This type of verification does not support mobile device login and user-based access management functions. This study designs an NFC-based third-party cloud identity and access management scheme (NFC-IAM) addressing this shortcoming. Data from simulation tests analyzed with Key Performance Indicators (KPIs) suggest that the NFC-IAM not only takes less time in identity identification but also cuts time by 80% in terms of two-factor authentication and improves verification accuracy to 99.9% or better. In functional performance analyses, NFC-IAM performed better in salability and portability. The NFC-IAM App (Application Software) and back-end system to be developed and deployed in mobile device are to support IAM features and also offers users a more user-friendly experience and stronger security protection. In the future, our NFC-IAM can be employed to different environments including identification for mobile payment systems, permission management for remote equipment monitoring, among other applications.

Keywords: Cloud service, multi-tenancy, NFC, IAM, mobile device.

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Authors: Xiaochuan Chen, Jianguo Yang, Beizhi Li

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Design for cost (DFC) is a method that reduces life cycle cost (LCC) from the angle of designers. Multiple domain features mapping (MDFM) methodology was given in DFC. Using MDFM, we can use design features to estimate the LCC. From the angle of DFC, the design features of family cars were obtained, such as all dimensions, engine power and emission volume. At the conceptual design stage, cars- LCC were estimated using back propagation (BP) artificial neural networks (ANN) method and case-based reasoning (CBR). Hamming space was used to measure the similarity among cases in CBR method. Levenberg-Marquardt (LM) algorithm and genetic algorithm (GA) were used in ANN. The differences of LCC estimation model between CBR and artificial neural networks (ANN) were provided. ANN and CBR separately each method has its shortcomings. By combining ANN and CBR improved results accuracy was obtained. Firstly, using ANN selected some design features that affect LCC. Then using LCC estimation results of ANN could raise the accuracy of LCC estimation in CBR method. Thirdly, using ANN estimate LCC errors and correct errors in CBR-s estimation results if the accuracy is not enough accurate. Finally, economically family cars and sport utility vehicle (SUV) was given as LCC estimation cases using this hybrid approach combining ANN and CBR.

Keywords: case-based reasoning, life cycle cost (LCC), artificialneural networks (ANN), family cars

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Authors: Rizwan Nasir, Hilmi Mukhtar, Zakaria Man, Dzeti Farhah Mohshim

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Carbon dioxide has been well associated with greenhouse effect, and due to its corrosive nature it is an undesirable compound. A variety of physical-chemical processes are available for the removal of carbon dioxide. Previous attempts in this field have established alkanolamine group has the capability to remove carbon dioxide. So, this study combined the polymeric membrane and alkanolamine solutions to fabricate the amine polymeric membrane (APM) to remove carbon dioxide (CO₂). This study entails the effect of three types of amines, monoethanolamine (MEA), diethanolamine (DEA), and methyldiethanolamine (MDEA). The effect of each alkanolamine group on the morphology and performance of polyether sulfone (PES) polymeric membranes was studied. Flat sheet membranes were fabricated by solvent evaporation method by adding polymer and different alkanolamine solutions in the N-Methyl-2-pyrrolidone (NMP) solvent. The final membranes were characterized by using Field Emission Electron Microscope (FESEM), Fourier Transform Infrared (FTIR), and Thermo-Gravimetric Analysis (TGA). The membrane separation performance was studied. The PES-DEA and PES-MDEA membrane has good ability to remove carbon dioxide. 

Keywords: Amine Polymeric membrane, Alkanolamine solution, CO2 Removal, Characterization.

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Authors: Karchung, S. Ruangsinchaiwanich

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This paper presents open-loop vector control method of induction motor with space vector pulse width modulation (SVPWM) technique. Normally, the closed loop speed control is preferred and is believed to be more accurate. However, it requires a position sensor to track the rotor position which is not desirable to use it for certain workspace applications. This paper exhibits the performance of three-phase induction motor with the simplest control algorithm without the use of a position sensor nor an estimation block to estimate rotor position for sensorless control. The motor stator currents are measured and are transformed to synchronously rotating (d-q-axis) frame by use of Clarke and Park transformation. The actual control happens in this frame where the measured currents are compared with the reference currents. The error signal is fed to a conventional PI controller, and the corrected d-q voltage is generated. The controller outputs are transformed back to three phase voltages and are fed to SVPWM block which generates PWM signal for the voltage source inverter. The open loop vector control model along with SVPWM algorithm is modeled in MATLAB/Simulink software and is experimented and validated in TMS320F28335 DSP board.

Keywords: Electric drive, induction motor, open-loop vector control, space vector pulse width modulation technique.

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Authors: Sabita Rani Sahoo, A.Mishra

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Delamination between layers in composite materials is a major structural failure. The delamination resistance is quantified by the critical strain energy release rate (SERR). The present investigation deals with the strain energy release rate of two woven fabric composites. Materials used are made of two types of glass fiber (360 gsm and 600 gsm) of plain weave and epoxy as matrix. The fracture behavior is studied using the mode I, double cantilever beam test and the mode II, end notched flexure test, in order to determine the energy required for the initiation and growth of an artificial crack. The delamination energy of these two materials is compared in order to study the effect of weave and reinforcement on mechanical properties. The fracture mechanism is also analyzed by means of scanning electron microscopy (SEM). It is observed that the plain weave fabric composite with lesser strand width has higher inter laminar fracture properties compared to the plain weave fabric composite with more strand width.

Keywords: Glass- epoxy composites, Fracture Tests: mode I (DCB) and mode II (ENF), Delamination, Calculation of strain energy release rate, SEM Analysis

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Authors: Indradip Banerjee, Souvik Bhattacharyya, Gautam Sanyal

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Encrypted messages sending frequently draws the attention of third parties, perhaps causing attempts to break and reveal the original messages. Steganography is introduced to hide the existence of the communication by concealing a secret message in an appropriate carrier like text, image, audio or video. Quantum steganography where the sender (Alice) embeds her steganographic information into the cover and sends it to the receiver (Bob) over a communication channel. Alice and Bob share an algorithm and hide quantum information in the cover. An eavesdropper (Eve) without access to the algorithm can-t find out the existence of the quantum message. In this paper, a text quantum steganography technique based on the use of indefinite articles (a) or (an) in conjunction with the nonspecific or non-particular nouns in English language and quantum gate truth table have been proposed. The authors also introduced a new code representation technique (SSCE - Secret Steganography Code for Embedding) at both ends in order to achieve high level of security. Before the embedding operation each character of the secret message has been converted to SSCE Value and then embeds to cover text. Finally stego text is formed and transmits to the receiver side. At the receiver side different reverse operation has been carried out to get back the original information.

Keywords: Quantum Steganography, SSCE (Secret SteganographyCode for Embedding), Security, Cover Text, Stego Text.

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Authors: Hasan Furkan Kurt, Tugba Nur Atabey, Onat Cavit Dereli, Ahmad Salmanogli, H. Selcuk Gecim

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In the article, the main goal is to study the effect of the plasmonic properties on the photocurrent generated by a photodetector. Fundamentally, a typical photodetector is designed and simulated using the finite element methods. To utilize the plasmonic effect, gold nanoparticles with different shape, size and morphology are buried into the intrinsic region. Plasmonic effect is arisen through the interaction of the incoming light with nanoparticles by which electrical properties of the photodetector are manipulated. In fact, using plasmonic nanoparticles not only increases the absorption bandwidth of the incoming light, but also generates a high intensity near-field close to the plasmonic nanoparticles. Those properties strongly affect the generated photocurrent. The simulation results show that using plasmonic nanoparticles significantly enhances the electrical properties of the photodetectors. More importantly, one can easily manipulate the plasmonic properties of the gold nanoparticles through engineering the nanoparticles' size, shape and morphology. Another important phenomenon is plasmon-plasmon interaction inside the photodetector. It is shown that plasmon-plasmon interaction improves the electron-hole generation rate by which the rate of the current generation is severely enhanced. This is the key factor that we want to focus on, to improve the photodetector electrical properties.

Keywords: Nanoparticles, plasmonic, plasmon-plasmon interaction, plasmonic photodetector.

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Authors: Luen Chow Chan

Abstract:

With the advocacy of green transportation and green traveling, cycling has become increasingly popular nowadays. Physiology and bike design are key factors for the influence of cycling efficiency. Therefore, this study aimed to investigate the significance of bike-frame geometric factors on cycling efficiency and muscle activation for different body sizes of non-professional Asian male cyclists. Participants who represented various body sizes, as measured by leg and back lengths, carried out cycling tests using a tailor-assembled road bike with different ergonomic design configurations including seat-height adjustments (i.e., 96%, 100%, and 104% of trochanteric height) and bike frame sizes (i.e., small and medium frames) for an assessable distance of 1 km. A specific power meter and self-developed adaptable surface electromyography (sEMG) were used to measure average pedaling power and cadence generated and muscle activation, respectively. The results showed that changing the seat height was far more significant than the body and bike frame sizes. The sEMG data evidently provided a better understanding of muscle activation as a function of different seat heights. Therefore, the interpretation of this study is that the major bike ergonomic design factor dominating the cycling efficiency of Asian participants with different body sizes was the seat height.

Keywords: Bike frame sizes, cadence rate, pedaling power, seat height.

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Authors: Lenka Hurtalová, Eva Tillová, Mária Chalupová, Juraj Belan, Milan Uhríčik

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The secondary alloy A226 is used for many automotive casting produced by mould casting and high pressure die casting. This alloy has excellent castability, good mechanical properties and cost-effectiveness. Production of primary aluminium alloys belong to heavy source fouling of life environs. The European Union calls for the emission reduction and reduction in energy consumption therefore increase production of recycled (secondary) aluminium cast alloys. The contribution is deal with influence of recycling on the quality of the casting made from A226 in automotive industry. The properties of the casting made from secondary aluminium alloys were compared with the required properties of primary aluminium alloys. The effect of recycling on microstructure was observed using combination different analytical techniques (light microscopy upon black-white etching, scanning electron microscopy - SEM upon deep etching and energy dispersive X-ray analysis - EDX). These techniques were used for the identification of the various structure parameters, which was used to compare secondary alloy microstructure with primary alloy microstructure.

Keywords: A226 secondary aluminium alloy, deep etching, mechanical properties, recycling foundry aluminium alloy.

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Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: Lateral bearing capacity, short pile, clayey soil, artificial neural network, Imperialist competition algorithm.

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Authors: Satadal Das, Parthasarathi Sengupta

Abstract:

With millions of livestock wealth in India including cattle, and buffaloes, the National Animal Disease Control Program targeted a massive Brucella vaccination program. As a part of it in the state of West Bengal Veterinary healthcare assistants participated in the program in 2021. The aim of this study was to elucidate the burden of brucellosis in those healthcare assistants and to pinpoint the main causes of such infection. We contacted the healthcare assistants to find out whether they were infected during the vaccination program. Our findings indicated many Veterinary healthcare assistants who participated in the program developed symptoms and signs suggestive of brucellosis. Laboratory tests indicated many confirmed Brucellosis cases. However, this may not include many asymptomatic cases. Detailed analysis revealed that in most of them there was a history of needle prick injury about a month back during the vaccination program, which was mainly due to ferocious or disturbed animals. Few also complained that they were not properly trained or proper personal protective types of equipment were not provided. All of them were treated in referral hospitals following a standard protocol of the Government Health Department and now they are followed up. Thus we conclude that proper care during the vaccination of animals should be followed, prophylactic treatment for needle prick injuries should be given, and training and supply of personal protective equipment should be monitored.

Keywords: Occupational brucellosis, needle prick injury, brucella vaccination, personal protective equipment.

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Authors: Sotirios Raptis

Abstract:

Linking social needs to social classes using different criteria may lead to social services misuse. The paper discusses using ML and Neural Networks (NNs) in linking public services in Scotland in the long term and advocates, this can result in a reduction of the services cost connecting resources needed in groups for similar services. The paper combines typical regression models with clustering and cross-correlation as complementary constituents to predict the demand. Insurance companies and public policymakers can pack linked services such as those offered to the elderly or to low-income people in the longer term. The work is based on public data from 22 services offered by Public Health Services (PHS) Scotland and from the Scottish Government (SG) from 1981 to 2019 that are broken into 110 years series called factors and uses Linear Regression (LR), Autoregression (ARMA) and 3 types of back-propagation (BP) Neural Networks (BPNN) to link them under specific conditions. Relationships found were between smoking related healthcare provision, mental health-related health services, and epidemiological weight in Primary 1(Education) Body Mass Index (BMI) in children. Primary component analysis (PCA) found 11 significant factors while C-Means (CM) clustering gave 5 major factors clusters.

Keywords: Probability, cohorts, data frames, services, prediction.

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Authors: J. K. Adedeji, S. T. Ijatuyi

Abstract:

The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: Neural network, gravitational resistance, pattern recognition, non-linear.

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Authors: N. Basanta Singh, Sanjoy Deb, G. P Mishra, Subir Kumar Sarkar

Abstract:

Carrier mobility has become the most important characteristic of high speed low dimensional devices. Due to development of very fast switching semiconductor devices, speed of computer and communication equipment has been increasing day by day and will continue to do so in future. As the response of any device depends on the carrier motion within the devices, extensive studies of carrier mobility in the devices has been established essential for the growth in the field of low dimensional devices. Small-signal ac transport of degenerate two-dimensional hot electrons in GaAs quantum wells is studied here incorporating deformation potential acoustic, polar optic and ionized impurity scattering in the framework of heated drifted Fermi-Dirac carrier distribution. Delta doping is considered in the calculations to investigate the effects of double delta doping on millimeter and submillimeter wave response of two dimensional hot electrons in GaAs nanostructures. The inclusion of delta doping is found to enhance considerably the two dimensional electron density which in turn improves the carrier mobility (both ac and dc) values in the GaAs quantum wells thereby providing scope of getting higher speed devices in future.

Keywords: Carrier mobility, Delta doping, Hot carriers, Quantum wells.

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Authors: Nthabiseng Portia Mahumapelo, Andre van Niekerk, Ndabenhle Sosibo, Nirdesh Singh

Abstract:

The foundry industry generates large quantities of solid waste in the form of waste foundry sand. The ever-increasing quantities of this type of industrial waste put pressure on land-filling space and its proper management has become a global concern. The South African foundry industry is not different when it comes to this solid waste generation. Utilizing the foundry waste sand in other applications has become an attractive avenue to deal with this waste stream. In the present paper, an evaluation was done on the suitability of foundry waste sand as an additive in clay masonry products. Purchased clay was added to the foundry waste sand sample in a 50/50 ratio. The mixture was named FC sample. The FC sample was mixed with water in a pan mixer until the mixture was consistent and suitable for extrusion. The FC sample was extruded and cut into briquettes. Water absorption, shrinkage and modulus of rupture tests were conducted on the resultant briquettes. Foundry waste sand and FC samples were respectively characterized mineralogically using X-Ray Diffraction, and the major and trace elements were determined using Inductively Coupled Plasma Optical Emission Spectroscopy. Adding purchased clay to the foundry waste sand positively influenced the workability of the test sample. Another positive characteristic was the low linear shrinkage, which indicated that products manufactured from the FC sample would not be susceptible to cracking. The water absorption values were acceptable and the unfired and fired strength values of the briquette’s samples were acceptable. In conclusion, tests showed that foundry waste sand can be used as an additive in masonry clay bricks, provided it is blended with good quality clay.

Keywords: Foundry waste sand, masonry clay bricks, modulus of rupture, shrinkage.

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Authors: Naoto Suzuki

Abstract:

Many ophthalmologists can examine declines in visual sensitivity at arbitrary points on the retina using a precise perimetry device with a fundus camera function. However, the retinal layer causing the decline in visual sensitivity cannot be identified by this method. We studied an electroretinogram (ERG) function that can move the center of the multifocal hexagonal stimulus array in order to investigate cryptogenic diseases, such as macular dystrophy, acute zonal occult outer retinopathy, and multiple evanescent white dot syndrome. An electroretinographic optical system, specifically a perimetric optical system, was added to an experimental device carrying the same optical system as a fundus camera. We also added an infrared camera, a cold mirror, a halogen lamp, and a monitor. The software was generated to show the multifocal hexagonal stimulus array on the monitor using C++Builder XE8 and to move the center of the array up and down as well as back and forth. We used a multifunction I/O device and its design platform LabVIEW for data retrieval. The plate electrodes were used to measure electrodermal activities around the eyes. We used a multifocal hexagonal stimulus array with 37 elements in the software. The center of the multifocal hexagonal stimulus array could be adjusted to the same position as the examination target of the precise perimetry. We successfully added the moving ERG function to the experimental ophthalmologic device.

Keywords: Moving ERG, precise perimetry, retinal layers, visual sensitivity.

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