Search results for: SIFT combination

Authors: Djendi Mohmaed

Abstract:

In this paper, we propose a dual adaptive algorithm, which is based on the combination between the forward blind source separation (FBSS) structure and the affine projection algorithm (APA). This proposed algorithm combines the advantages of the source separation properties of the FBSS structure and the fast convergence characteristics of the APA algorithm. The proposed algorithm needs two noisy observations to provide an enhanced speech signal. This process is done in a blind manner without the need for ant priori information about the source signals. The proposed dual forward blind source separation affine projection algorithm is denoted (DFAPA) and used for the first time in an airplane cockpit context to enhance the communication from- and to- the airplane. Intensive experiments were carried out in this sense to evaluate the performance of the proposed DFAPA algorithm.

Keywords: adaptive algorithm, speech enhancement, system mismatch, SNR

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Authors: Sawsan Eissa, Momen Gharib, Omnia Kabbany

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A flushing numerical study has been performed for intended artificial islands on the Persian Gulf coast in Abu Dhabi, UAE. The island masterplan was tested for flushing using the DELFT 3D hydrodynamic model, and it was found that its residence time exceeds the acceptable PIANC flushing Criteria. Therefore, a number of mitigation measures were applied and tested one by one using the flushing model. Namely, changing the location of the entrance opening, dredging, removing part of the mangrove existing in the near vicinity to create a channel, removing the mangrove altogether, using culverts of different numbers and locations, and pumping at selected points. The pumping option gave the best solution, but it was disregarded due to high capital and running costs. Therefore, it opted for a combination of other solutions, including removing mangroves, introducing culverts, and adjusting island boundaries and types of protection.

Keywords: hydrodynamics, flushing, delft 3d, Persian Gulf, artificial islands.

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Authors: Mustafa Arda, Metin Aydogdu

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Carbon nanotubes (CNTs) have many possible application areas because of their superior physical properties. Nonlocal Theory, which unlike the classical theories, includes the size dependency. Nonlocal Stress and Strain Gradient approaches can be used in nanoscale static and dynamic analysis. In the present study, torsional vibration of CNTs was investigated according to nonlocal stress and strain gradient theories. Effects of the small scale parameters to the non-dimensional frequency were obtained. Results were compared with the Molecular Dynamics Simulation and Lattice Dynamics. Strain Gradient Theory has shown more weakening effect on CNT according to the Stress Gradient Theory. Combination of both theories gives more acceptable results rather than the classical and stress or strain gradient theory according to Lattice Dynamics.

Keywords: torsional vibration, carbon nanotubes, nonlocal gradient theory, stress, strain

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Authors: Selcuk Comlekci, Mohammed Aboajmaa

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Orthogonal frequency division multiplexing (OFDM) is promising technique for the modern wireless communications systems due to its robustness against multipath environment. The high peak to average power ratio (PAPR) of the transmitted signal is one of the major drawbacks of OFDM system, PAPR degrade the performance of bit error rate (BER) and effect on the linear characteristics of high power amplifier (HPA). In this paper, we proposed DHT-Clipping reduction technique to reduce the high PAPR by the combination between discrete Hartley transform (DHT) and Clipping techniques. From the simulation results, we notified that DHT-Clipping technique offers better PAPR reduction than DHT and Clipping, as well as DHT-Clipping introduce improved BER performance better than clipping.

Keywords: ISI, cyclic prefix, BER, PAPR, HPA, DHT, subcarrier

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Authors: Abbas Al-Refaie

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This study optimized the performance of plastic extrusion process of drip irrigation pipes using fuzzy goal programming. Two main responses were of main interest; roll thickness and hardness. Four main process factors were studied. The L₁₈ array was then used for experimental design. The individual-moving range control charts were used to assess the stability of the process, while the process capability index was used to assess process performance. Confirmation experiments were conducted at the obtained combination of optimal factor setting by fuzzy goal programming. The results revealed that process capability was improved significantly from -1.129 to 0.8148 for roll thickness and from 0.0965 to 0.714 and hardness. Such improvement results in considerable savings in production and quality costs.

Keywords: fuzzy goal programming, extrusion process, process capability, irrigation plastic pipes

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Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: Stavros Poulopoulos, Aphrodite Tetorou, Constantine Philippopoulos

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Day after day more pharmaceutical compounds that are not efficiently removed by conventional treatment methods are found in treated wastewaters and drinking waters. Due to their refractory nature, they escape conventional wastewater treatment facilities, and thus advanced oxidation processes have to be utilized to effectively eliminate them. In the present study, the removal of Ibuprofen from aqueous solutions containing the commercial drug Algofren (non-steroidal, anti-inflammatory) using UV irradiation, hydrogen peroxide, titanium dioxide and ferric ions was examined. All experiments were conducted in a batch photoreactor operated for 120 min. The main target was to select the most effective operating conditions for the mineralization of the solutions treated. The combination of Fe(III)/ H₂O₂/UV proved to be very efficient in terms of total organic carbon removal and ibuprofen conversion. For solutions containing 5 mg/L ibuprofen and initial total carbon 51.1 mg/L, complete mineralization was achieved by means of 2.2 ppm Fe(III) and 333 mg/L H₂O₂.

Keywords: pharmaceuticals, photocatalytic, photo-Fenton, TiO₂

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Authors: I. Slim, H. Akkari, A. Ben Abdallah, I. Bhouri, M. Hedi Bedoui

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Osteoporosis is a common disease characterized by low bone mass and deterioration of micro-architectural bone tissue, which provokes an increased risk of fracture. This work treats the texture characterization of trabecular bone radiographs. The aim was to analyze according to clinical research a group of 174 subjects: 87 osteoporotic patients (OP) with various bone fracture types and 87 control cases (CC). To characterize osteoporosis, Fractal and MultiFractal (MF) methods were applied to images for features (attributes) extraction. In order to improve the results, a new method of MF spectrum based on the q-stucture function calculation was proposed and a combination of Fractal and MF attributes was used. The Support Vector Machines (SVM) was applied as a classifier to distinguish between OP patients and CC subjects. The features fusion (fractal and MF) allowed a good discrimination between the two groups with an accuracy rate of 96.22%.

Keywords: fractal, micro-architecture analysis, multifractal, osteoporosis, SVM

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Authors: Debneil Saha Roy

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Weather forecasting is a complex topic and is well suited for analysis by deep learning approaches. With the wide availability of weather observation data nowadays, these approaches can be utilized to identify immediate comparisons between historical weather forecasts and current observations. This work explores the application of deep learning techniques to weather forecasting in order to accurately predict the weather over a given forecast hori­zon. Three deep neural networks are used in this study, namely, Multi-Layer Perceptron (MLP), Long Short Tunn Memory Network (LSTM) and a combination of Convolutional Neural Network (CNN) and LSTM. The predictive performance of these models is compared using two evaluation metrics. The results show that forecasting accuracy increases with an increase in the complexity of deep neural networks.

Keywords: convolutional neural network, deep learning, long short term memory, multi-layer perceptron

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Authors: S. O. Ologe, U. P. Anaidhuno, Duru C. A.

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This research investigated the design and analysis of a rear bumper of an automobile with a hybrid polymer composite of OPEBF/Banana fibre. OPEBF/Banana fibre hybrid polymers composite is of low cost, lightweight, as well as possesses satisfactory mechanical properties. In this research work, hybrid composites have been developed using the hand layup technique based on the percentage combination of OPEBF/Banana fibre at 10:90, 20:80, 30:70, 40:60, 50:50. 60:40, 70:30. 20:80, 90:10, 95:5. The mechanical properties in the context of compressive strength of 65MPa, a flexural strength of 20MPa, and impact strength of 3.25Joule were observed, and the simulation analysis on the induction of 500N load at the factor of safety of 3 was observed to have displayed a good strength suitable for automobile bumper with the advantages of weight reduction.

Keywords: OPEBF, Banana, fibre, hybrid

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Authors: Hamza Nejib, Okba Taouali

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This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS

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Authors: Mosab Alrashed, Wei Xu, Stephen Abineri, Yifan Zhao, Jörn Mehnen

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Thermographic inspection is a relatively new technique for Non-Destructive Testing (NDT) which has been gathering increasing interest due to its relatively low cost hardware and extremely fast data acquisition properties. This technique is especially promising in the area of rapid automated damage detection and quantification. In collaboration with a major industry partner from the aerospace sector advanced thermography-based NDT software for impact damaged composites is introduced. The software is based on correlation analysis of time-temperature profiles in combination with an image enhancement process. The prototype software is aiming to a) better visualise the damages in a relatively easy-to-use way and b) automatically and quantitatively measure the properties of the degradation. Knowing that degradation properties play an important role in the identification of degradation types, tests and results on specimens which were artificially damaged have been performed and analyzed.

Keywords: NDT, correlation analysis, image processing, damage, inspection

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Authors: R. M. Dodo, Z. Musa, K. A. Bello, U. Abdullahi, G. A. Faruna

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Temperature depended austempering of high carbon steel using epoxidized-transesterified cotton seed oil (ETO) was examined. Five set of samples were heated to 850oC and held for one hour then quenched in oil bath of ETO at 250oC at one hour holding time. The same procedure was performed on the rest of the samples and austempered at 270oC, 290oC, 310oC and 330oC. Next, mechanical properties’ tests conducted. The austempered samples were then analyzed for microstructure using scanning electron microscope (SEM). The results indicate that tensile strength and hardness dip with increase in the temperature. Again, impact strength improved with rise in the temperature. It was observed that 270oC is the best austempering temperature, since it produces austempered sample with the best combination of mechanical properties.

Keywords: epoxidized transesterified cotton seed oil, austempering temperature, high carbon steel, bainitic structure

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Authors: Samane Sharifi Monfared, Lavdie Rada

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Nowadays, autonomous vehicles are developing rapidly toward facilitating human car driving. One of the main issues is road lane detection for a suitable guidance direction and car accident prevention. This paper aims to improve and optimize road line detection based on a combination of camera calibration, the Hough transform, and Canny edge detection. The video processing is implemented using the Open CV library with the novelty of having a scale able region masking. The aim of the study is to introduce automatic road lane detection techniques with the user’s minimum manual intervention.

Keywords: hough transform, canny edge detection, optimisation, scaleable masking, camera calibration, improving the quality of image, image processing, video processing

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Authors: Jun Gil Ahn, Jong Kang Park, Jong Tae Kim

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In this paper, we analyze major components of activity recognition (AR) in wearable device with 9-axis sensors and sensor fusion filters. 9-axis sensors commonly include 3-axis accelerometer, 3-axis gyroscope and 3-axis magnetometer. We chose sensor fusion filters as Kalman filter and Direction Cosine Matrix (DCM) filter. We also construct sensor fusion data from each activity sensor data and perform classification by accuracy of AR using Naïve Bayes and SVM. According to the classification results, we observed that the DCM filter and the specific combination of the sensing axes are more effective for AR in wearable devices while classifying walking, running, ascending and descending.

Keywords: accelerometer, activity recognition, directiona cosine matrix filter, gyroscope, Kalman filter, magnetometer

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Authors: M. Louise Humbert, Karen E. Chad, Natalie E. Houser, Marta E. Erlandson

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Physical literacy is the motivation, confidence, physical competence, knowledge, and understanding to value and takes responsibility for engagement in physical activities for life. In recent years, physical literacy has emerged as a determinant of health, promoting a positive lifelong physical activity trajectory. Physical literacy’s holistic approach and emphasis on the intrinsic valuation of movement provide an encouraging avenue for intervention among children to develop competent and confident movers. Although there is research on physical literacy interventions, no evidence exists on the outcomes of multi-sectoral interventions involving a combination of home, school, and community contexts. Since children interact with and in a wide range of contexts (home, school, community) daily, interventions designed to address a combination of these contexts are critical to the development of physical literacy. Working with school administrators and teachers, sports and recreation leaders, and community members, our team of university and community researchers conducted and evaluated one of the first multi-contextual and multi-sectoral physical literacy interventions in Canada. Schools played a critical role in this multi-sector intervention, and in this project, teachers and administrators focused their actions on developing physical literacy in students 10 to 14 years of age through the instruction of physical literacy-focused physical education lessons. Little is known about the experiences of educators when they work alongside an array of community representatives to develop physical literacy in school-aged children. Given the uniqueness of this intervention, we sought to answer the question, ‘What were the experiences of school-based educators involved in a multi-sectoral partnership focused on creating a physical literacy enriched community intervention?’ A thematic analysis approach was used to analyze data collected from interviews with educators and administrators, informal conversations, documents, and observations at workshops and meetings. Results indicated that schools and educators played the largest role in this multi-sector intervention. Educators initially reported a limited understanding of physical literacy and expressed a need for resources linked to the physical education curriculum. Some anxiety was expressed by the teachers as their students were measured, and educators noted they wanted to increase their understanding and become more involved in the assessment of physical literacy. Teachers reported that the intervention’s focus on physical literacy positively impacted the scheduling and their instruction of physical education. Administrators shared their desire for school and division-level actions targeting physical literacy development like the current focus on numeracy and literacy, treaty education, and safe schools. As this was one of the first multi-contextual and multi-sectoral physical literacy interventions, it was important to document creation and delivery experiences to encourage future growth in the area and develop suggested best practices.

Keywords: physical literacy, multi sector intervention, physical education, teachers

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Authors: A. Elnady

Abstract:

This paper presents an improved Direct Power Control (DPC) scheme applied to the multilevel inverter that forms a Distributed Generation Unit (DGU). This paper demonstrates the performance of active and reactive power injected by the DGU to the smart grid. The DPC is traditionally operated by the hysteresis controller with the Space Vector Modulation (SVM) which is applied on the 2-level inverters or 3-level inverters. In this paper, the DPC is operated by the PI controller with the Phase-Disposition Pulse Width Modulation (PD-PWM) applied to the 5-level diode clamped inverter. The new combination of the DPC, PI controller, PD-PWM and multilevel inverter proves that its performance is much better than the conventional hysteresis-SVM based DPC. Simulations results have been presented to validate the performance of the suggested control scheme in the grid-connected mode.

Keywords: direct power control, PI controller, PD-PWM, and power control

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Authors: Jatinderkumar R. Saini

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E-mail has become a key mechanism of electronic communication. This is truer for professional organizations that like to communicate with their subjects online and are slowly shifting to paper-less office. The current paper focuses specifically on academic institutions offering Engineering course in Gujarat state and attempts for textual analysis of the usernames of the institutional e-mail addresses. We found that the institutions tend to design the username segment of their e-mail addresses by choosing words or combination of words from specific categories. The paper also highlights the use of special characters, digits and random words in designing the usernames. On the sidelines, the paper lists the style of employing department names and designations for the design process. To the best of our knowledge, this is the first formal attempt to analyze the selection of words employed for designing username segment of e-mail addresses of Engineering institutions.

Keywords: e-mail address, institute, engineering, username

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Authors: Zhao Pengcheng, Yin Siyuan

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Fintech is the new hot topic of the 21st century, a discipline that combines financial theory with computer modelling. It can provide both digital analysis methods for investment banks and investment decisions for users. Given the variety of services available, it is necessary to provide a superior method of requirements elicitation to ensure that users' needs are addressed in the software development process. The accuracy of traditional software requirements elicitation methods is not sufficient, so this study attempts to use a multi-perspective based requirements heuristic framework. Methods such as interview and questionnaire combination, card sorting, and model driven are proposed. The collection results from PCA show that the new methods can better help with requirements elicitation. However, the method has some limitations and, there are some efficiency issues. However, the research in this paper provides a good theoretical extension that can provide researchers with some new research methods and perspectives viewpoints.

Keywords: requirement elicitation, FinTech, mobile application, survey, interview, model-driven

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Authors: Roberta Martino, Viviana Ventre

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Every day we face choices whose consequences are deferred in time. These types of choices are the intertemporal choices and play an important role in the social, economic, and financial world. The Discounted Utility Model is the mathematical model of reference to calculate the utility of intertemporal prospects. The discount rate is the main element of the model as it describes how the individual perceives the indeterminacy of subsequent periods. Empirical evidence has shown a discrepancy between the behavior expected from the predictions of the model and the effective choices made from the decision makers. In particular, the term temporal inconsistency indicates those choices that do not remain optimal with the passage of time. This phenomenon has been described with hyperbolic models of the discount rate which, unlike the linear or exponential nature assumed by the discounted utility model, is not constant over time. This paper explores the problem of inconsistency by tracing the decision-making process through the concept of impatience. The degree of impatience and the degree of decrease of impatience are two parameters that allow to quantify the weight of emotional factors and cognitive limitations during the evaluation and selection of alternatives. In fact, although the theory assumes perfectly rational decision makers, behavioral finance and cognitive psychology have made it possible to understand that distortions in the decision-making process and emotional influence have an inevitable impact on the decision-making process. The degree to which impatience is diminished is the focus of the first part of the study. By comparing consistent and inconsistent preferences over time, it was possible to verify that some anomalies in the discounted utility model are a result of the combination of cognitive bias and emotional factors. In particular: the delay effect and the interval effect are compared through the concept of misperception of time; starting from psychological considerations, a criterion is proposed to identify the causes of the magnitude effect that considers the differences in outcomes rather than their ratio; the sign effect is analyzed by integrating in the evaluation of prospects with negative outcomes the psychological aspects of loss aversion provided by Prospect Theory. An experiment implemented confirms three findings: the greatest variation in the degree of decrease in impatience corresponds to shorter intervals close to the present; the greatest variation in the degree of impatience occurs for outcomes of lower magnitude; the variation in the degree of impatience is greatest for negative outcomes. The experimental phase was implemented with the construction of the hyperbolic factor through the administration of questionnaires constructed for each anomaly. This work formalizes the underlying causes of the discrepancy between the discounted utility model and the empirical evidence of preference reversal.

Keywords: decreasing impatience, discount utility model, hyperbolic discount, hyperbolic factor, impatience

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Authors: Afshin J. Ghajar, Swanand M. Bhagwat

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The main purpose of this work is to experimentally investigate the effect of pipe orientation on two phase flow phenomenon. Flow pattern, void fraction and two phase pressure drop is measured in a polycarbonate pipe with an inside diameter of 12.7mm for inclination angles ranging from -20° to +20° using air-water fluid combination. The experimental data covers all flow patterns and the entire range of void fraction typically observed in two phase flow. The effect of pipe orientation on void fraction and two phase pressure drop is justified with reference to the change in flow structure and two phase flow behavior. In addition to this, the top performing void fraction and two phase pressure drop correlations available in the literature are presented and their performance is assessed against the experimental data in the present study and that available in the literature.

Keywords: flow patterns, inclined two phase flow, pressure drop, void fraction

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Authors: Yu Li, Jingwu He, Yuexi Xiong

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The spar layout will affect the wing’s stiffness characteristics, and irrational spar arrangement will reduce the overall bending and twisting resistance capacity of the wing. In this paper, the active structural stiffness design theory is used to match the stiffness-center axis position and load-cases under the corresponding multiple flight conditions, in order to achieve better stiffness properties of the wing. The combination of active stiffness method and principle of stiffness distribution is proved to be reasonable supplying an initial reference for wing designing. The optimized layout of spars is eventually obtained, and the high-aspect-ratio wing will have better stiffness characteristics.

Keywords: active structural stiffness design theory, high-aspect-ratio wing, flight load cases, layout of spars

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Authors: Lotfi Hedi Khezami, Mohamed Ben Rabha, N. Sboui, Mounir Gaidi, B. Bessais

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Metal-nano particle-assisted Chemical Etching is an extraordinary developed wet etching method of producing uniform semiconductor nano structure (nano wires) from patterned metallic film on crystalline silicon surface. The metal films facilitate the etching in HF and H2O2 solution and produce silicon nanowires (SiNWs). Creation of different SiNWs morphologies by changing the etching time and its effects on optical and opto electronic properties was investigated. Combination effect of formed SiNWs and stain etching treatment in acid (HF/HNO3/H2O) solution on the surface morphology of Si wafers as well as on the optical and opto electronic properties are presented in this paper.

Keywords: stain etching, porous silicon, silicon nanowires, reflectivity, lifetime, solar cells

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Authors: K. Subbaiah

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Friction stir welding is a solid state welding process. Friction stir welding process eliminates the defects found in fusion welding processes. It is environmentally friend process. 5000 and 6000 series aluminum alloys are widely used in the transportation industries. The Al-Mg-Mn (5000) and Al-Mg-Si (6000) alloys are preferably offer best combination of use in Marine construction. The medium strength and high corrosion resistant 5000 series alloys are the aluminum alloys, which are found maximum utility in the world. In this review, the tool pin profile, process parameters such as hardness, yield strength and tensile strength, and microstructural evolution of friction stir welding of Al-Mg alloys 5000 Series and 6000 series have been discussed.

Keywords: 5000 series and 6000 series Al alloys, friction stir welding, tool pin profile, microstructure and properties

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Authors: Jamuna Konda, Umamaheswara Reddy Karumuri, Sriramya Muthugi, Varun Pishati, Ravi Shakya,

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This paper investigates the challenges involved in mathematical modeling of plant simulation models ensuring the performance of the plant models much closer to the real time physical model. The paper includes the analysis performed and investigation on different methods of modeling, design and development for plant model. Issues which impact the design time, model accuracy as real time model, tool dependence are analyzed. The real time hardware plant would be a combination of multiple physical models. It is more challenging to test the complete system with all possible test scenarios. There are possibilities of failure or damage of the system due to any unwanted test execution on real time.

Keywords: model based design (MBD), MATLAB, Simulink, stateflow, plant model, real time model, real-time workshop (RTW), target language compiler (TLC)

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Authors: Maryam Abata, Moulhime El Bekkali, Said Mazer, Catherine Algani, Mahmoud Mehdi

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One major problem of most electronic systems operating in the millimeter wave band is the signal generation with a high purity and a stable carrier frequency. This problem is overcome by using the combination of a signal with a low frequency local oscillator (LO) and several stages of frequency multipliers. The use of these frequency multipliers to create millimeter-wave signals is an attractive alternative to direct generation signal. Therefore, the isolation problem of the local oscillator from the other stages is always present, which leads to have various mechanisms that can disturb the oscillator performance, thus a buffer amplifier is often included in oscillator outputs. In this paper, we present the study and design of a buffer amplifier in the mm-wave band using a 0.15μm pHEMT from UMS foundry. This amplifier will be used as a part of a frequency quadrupler at 60 GHz.

Keywords: Mm-wave band, local oscillator, frequency quadrupler, buffer amplifier

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Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

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Wireless sensor network was formed by a combination of nodes, systematically it transmitting the data to their base stations, this transmission data can be easily compromised if the limited processing power and the data consistency from these nodes are kept in mind; there is always a discussion to address the secure data transfer or transmission in actual time. This will present a mechanism to securely transmit the data over a chain of sensor nodes without compromising the throughput of the network by utilizing available battery resources available in the sensor node. Our methodology takes many different advantages of Z-MAC protocol for its efficiency, and it provides a unique key by sharing the mechanism using neighbor node MAC address. We present a light weighted data integrity layer which is embedded in the Z-MAC protocol to prove that our protocol performs well than Z-MAC when we introduce the different attack scenarios.

Keywords: hybrid MAC protocol, data integrity, lightweight encryption, neighbor based key sharing, sensor node dataprocessing, Z-MAC

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Authors: Ming-Chu Yin, Ping-An Du

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The shielding ability of a shielding cavity is affected greatly by its resonances, which include resonance modes and frequencies. The equivalent circuit method and numerical method of transmission line matrix (TLM) are used to analyze the effect of aperture-cavity coupling on electromagnetic resonances of a cavity with an aperture in this paper. Both theoretical and numerical results show that the resonance modes of a shielding cavity with an aperture can be considered as the combination of cavity and aperture inherent resonance modes with resonance frequencies shifting, and the reason of this shift is aperture-cavity coupling. Because aperture sizes are important parameters to aperture-cavity coupling, variation rules of electromagnetic resonances of a shielding cavity with its aperture sizes are given, which will be useful for the design of shielding cavities.

Keywords: aperture-cavity coupling, equivalent circuit method, resonances, shielding equipment

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Authors: Rui Mao, Heming Ji, Xiaoyu Wang

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Keystroke dynamics are widely used in identity recognition. It has the advantage that the individual typing rhythm is difficult to imitate. It also supports continuous authentication through the keyboard without extra devices. The existing keystroke dynamics authentication methods based on machine learning have a drawback in supporting relatively complex scenarios with massive data. There are drawbacks to both feature extraction and model optimization in these methods. To overcome the above weakness, an authentication model of keystroke dynamics based on deep learning is proposed. The model uses feature vectors formed by keystroke content and keystroke time. It ensures efficient continuous authentication by cooperating attention mechanisms with the combination of CNN and Bi-LSTM. The model has been tested with Open Data Buffalo dataset, and the result shows that the FRR is 3.09%, FAR is 3.03%, and EER is 4.23%. This proves that the model is efficient and accurate on continuous authentication.

Keywords: keystroke dynamics, identity authentication, deep learning, CNN, LSTM

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Authors: Elly Usman, S. Dante, Diah Purnamasari

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Type 2 diabetes mellitus ( T2DM ) is a syndrome characterized by a state of increased blood sugar levels due to chronic disorders of insulin secretion by pancreatic beta cells and insulin action or a combination of both. The organic cation transporter 1, encoded by the SLC22A1 gene, responsible for the uptake of the antihyperglycemic drug, metformin, in the hepatocyte. We assessed whether a genetic variation in the SLC22A1 gene was associated with the glucose - lowering effect of metformin. Method case study research design. Samples are children with type 2 diabetes mellitus who meet the inclusion criteria. The results proportions SLC22A1 gene polymorphisms in children with diabetes mellitus type 2 amounted to 52.04 % at position 400T/C, there is one heterozygous and one at position 595T/C Conclusion The presence of SLC22A1 gene polymorphisms in children with diabetes mellitus type 2.

Keywords: diabetes Mellitus type 2, metformin, organic cation transporter 1, pharmacogenomics

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