Search results for: selection of multi attributegoods

Authors: Hossein Ahmadi, Ogholgol Nazari

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The necessity of grading and sequencing tasks has led to the development of different criteria in this regard. However, appropriateness of these criteria in different situations is less discussed. This paper attempts to shed more light on the priority of different criteria in relation with different factors including learners, teachers, educational, and cultural factors.

Keywords: Criteria, Grading, Sequencing, Language learning tasks.

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Authors: Sameru Sharma, Sanjay Sharma, Derick Engles

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Multiple-input multiple-output (MIMO) systems are widely in use to improve quality, reliability of wireless transmission and increase the spectral efficiency. However in MIMO systems, multiple copies of data are received after experiencing various channel effects. The limitations on account of complexity due to number of antennas in case of conventional decoding techniques have been looked into. Accordingly we propose a modified sphere decoder (MSD-1) algorithm with lower complexity and give rise to system with high spectral efficiency. With the aim to increase signal diversity we apply rotated quadrature amplitude modulation (QAM) constellation in multi dimensional space. Finally, we propose a new architecture involving space time trellis code (STTC) concatenated with space time block code (STBC) using MSD-1 at the receiver for improving system performance. The system gains have been verified with channel state information (CSI) errors.

Keywords: Channel State Information , Diversity, Multi-Antenna, Rotated Constellation, Space Time Codes.

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Authors: M. M. Doroodmand, Z.Tahvildar, M. H.Sheikhi

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novel and simple method is introduced for rapid and highly efficient water treatment by reverse osmosis (RO) method using multi-walled carbon nanotubes (MWCNTs) / polyacrylonitrile (PAN) polymer as a flexible, highly efficient, reusable and semi-permeable mixed matrix membrane (MMM). For this purpose, MWCNTs were directly synthesized and on-line purified by chemical vapor deposition (CVD) process, followed by directing the MWCNT bundles towards an ultrasonic bath, in which PAN polymer was simultaneously suspended inside a solid porous silica support in water at temperature to ~70 οC. Fabrication process of MMM was finally completed by hot isostatic pressing (HIP) process. In accordance with the analytical figures of merit, the efficiency of fabricated MMM was ~97%. The rate of water treatment process was also evaluated to 6.35 L min-1. The results reveal that, the CNT-based MMM is suitable for rapid treatment of different forms of industrial, sea, drinking and well water samples.

Keywords: Mixed Matrix Membrane, Carbon Nanostructures, Chemical Vapour Deposition, Hot Isostatic Pressing

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Authors: Mohamed R. Mhereeg

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The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). The Microsoft's .NET widows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Keywords: MACS, Implementation, Multi-Agent, SOA, Autonomous, WCF.

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Authors: Srinivasa Reddy Mallampati, Byoung Ho Lee, Yoshiharu Mitoma, Simion Cristian

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In recent years, environmental nanotechnology has risen to the forefront and the new properties and enhanced reactivates offered by nanomaterial may offer a new, low-cost paradigm to solving complex environmental pollution problems. This study assessed the synthesis and application of multi-functioned nano-size metallic calcium (nMC) composite for detoxification of hazardous inorganic (heavy metals (HMs)/organic chlorinated/brominated compound (CBCs) contaminants in automobile shredder residue (ASR). ASR residues ball milled with nMC composite can achieve about 90-100% of HMs immobilization and CBCs decomposition. The results highlight the low quantity of HMs leached from ASR residues after treatment with nMC, which was found to be lower than the standard regulatory limit for hazardous waste landfills. The use of nMC composite in a mechanochemical process to treat hazardous ASR (dry conditions) is a simple and innovative approach to remediate hazardous inorganic/organic cross-contaminates in ASR.

Keywords: Nano-sized metallic calcium, automobile shredder residue, organic/inorganic contaminants, immobilization, detoxification.

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Authors: Raghad Jawad Ahmed

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Segmentation of a color image composed of different kinds of regions can be a hard problem, namely to compute for an exact texture fields. The decision of the optimum number of segmentation areas in an image when it contains similar and/or un stationary texture fields. A novel neighborhood-based segmentation approach is proposed. A genetic algorithm is used in the proposed segment-pass optimization process. In this pass, an energy function, which is defined based on Markov Random Fields, is minimized. In this paper we use an adaptive threshold estimation method for image thresholding in the wavelet domain based on the generalized Gaussian distribution (GGD) modeling of sub band coefficients. This method called Normal Shrink is computationally more efficient and adaptive because the parameters required for estimating the threshold depend on sub band data energy that used in the pre-stage of segmentation. A quad tree is employed to implement the multi resolution framework, which enables the use of different strategies at different resolution levels, and hence, the computation can be accelerated. The experimental results using the proposed segmentation approach are very encouraging.

Keywords: Color image segmentation, Genetic algorithm, Markov random field, Scale space filter.

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Authors: Israa Al-Neami, Ali J. Al-Askery, Martin Johnston, Charalampos Tsimenidis

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In this paper, we focus on the design of a multi-line copper wire (MLCW) communication system. First, we construct our proposed MLCW channel and verify its characteristics based on the Kolmogorov-Smirnov test. In addition, we apply Middleton class A impulsive noise (IN) to the copper channel for further investigation. Second, the MIMO G.fast system is adopted utilizing the proposed MLCW channel model and is compared to a single line G-fast system. Second, the performance of the coded system is obtained utilizing concatenated interleaved Reed-Solomon (RS) code with four-dimensional trellis-coded modulation (4D TCM), and compared to the single line G-fast system. Simulations are obtained for high quadrature amplitude modulation (QAM) constellations that are commonly used with G-fast communications, the results demonstrate that the bit error rate (BER) performance of the coded MLCW system shows an improvement compared to the single line G-fast systems.

Keywords: G.fast, Middleton Class A impulsive noise, mitigation techniques, copper channel Model.

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Authors: Min Ye Koo, Gyo Woo Lee

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In this study, epoxy composite specimens reinforced with multi-walled carbon nanotube filler were fabricated using shear mixer and ultra-sonication processor. The mechanical and thermal properties of the fabricated specimens were measured and evaluated. From the electron microscope images and the results from the measurements of tensile strengths, the specimens having 0.6 wt% nanotube content show better dispersion and higher strength than those of the other specimens. The Young’s moduli of the specimens increased as the contents of the nanotube filler in the matrix were increased. The specimen having a 0.6 wt% nanotube filler content showed higher thermal conductivity than that of the other specimens. While, in the measurement of thermal expansion, specimens having 0.4 and 0.6 wt% filler contents showed a lower value of thermal expansion than that of the other specimens. On the basis of the measured and evaluated properties of the composites, we believe that the simple and time-saving fabrication process used in this study was sufficient to obtain improved properties of the specimens.

Keywords: Carbon Nanotube Filler, Epoxy Composite, Ultra-Sonication, Shear Mixer, Mechanical Property, Thermal Property.

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Authors: Saba Shams Bidhendi, Steven Goh, Andrew Wandel

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The implementation of lean manufacturing initiatives has produced significant impacts in improving operational performance and reducing manufacturing wastes in the production process. However, selecting an appropriate set of lean strategies is critical to avoid misapplication of the lean manufacturing techniques and consequential increase in non-value-adding activities. To the author’s best knowledge, there is currently no methodology to select lean strategies that considers their impacts on manufacturing wastes and performance metrics simultaneously. In this research, a multi-objective methodology is proposed that suggests an appropriate set of lean initiatives based on their impacts on performance metrics and manufacturing wastes and within manufacturers’ resource limitation. The proposed methodology in this research suggests the best set of lean initiatives for implementation that have highest impacts on identified critical performance metrics and manufacturing wastes. Therefore, manufacturers can assure that implementing suggested lean tools improves their production performance and reduces manufacturing wastes at the same time. A case study was conducted to show the effectiveness and validate the proposed model and methodologies.

Keywords: Lean manufacturing, Lean strategies, manufacturing wastes, manufacturing performance metrics, decision making, optimisation.

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Authors: Ehab F. Badran, Guoxiang Gu

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We consider optimal channel equalization for MIMO (multi-input/multi-output) time-varying channels in the sense of MMSE (minimum mean-squared-error), where the observation noise can be non-stationary. We show that all ZF (zero-forcing) receivers can be parameterized in an affine form which eliminates completely the ISI (inter-symbol-interference), and optimal channel equalizers can be designed through minimization of the MSE (mean-squarederror) between the detected signals and the transmitted signals, among all ZF receivers. We demonstrate that the optimal channel equalizer is a modified Kalman filter, and show that under the AWGN (additive white Gaussian noise) assumption, the proposed optimal channel equalizer minimizes the BER (bit error rate) among all possible ZF receivers. Our results are applicable to optimal channel equalization for DWMT (discrete wavelet multitone), multirate transmultiplexers, OFDM (orthogonal frequency division multiplexing), and DS (direct sequence) CDMA (code division multiple access) wireless data communication systems. A design algorithm for optimal channel equalization is developed, and several simulation examples are worked out to illustrate the proposed design algorithm.

Keywords: Channel equalization, Kalman filtering, Time-varying systems.

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Authors: Siyu Wang, Anthony Ward

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Emotional intelligence (EI) is a well-established personal characteristic. It has been viewed as a critical factor which can influence an individual's academic achievement, ability to work and potential to succeed. When working in a group, EI is fundamentally connected to the group members' interaction and ability to work as a team. The ability of a group member to intelligently perceive and understand own emotions (Intrapersonal EI), to intelligently perceive and understand other members' emotions (Interpersonal EI), and to intelligently perceive and understand emotions between different groups (Cross-boundary EI) can be considered as Group emotional intelligence (Group EI). In this research, a more representative Group EI measurement approach, which incorporates the information of the composition of a group and an individual’s role in that group, is proposed. To demonstrate the claim of being more representative Group EI measurement approach, this study adopts a multi-method research design, involving a combination of both qualitative and quantitative techniques to establish a metric of Group EI. From the results, it can be concluded that by introducing the weight coefficient of each group member on group work into the measurement of Group EI, Group EI will be more representative and more capable of understanding what happens during teamwork than previous approaches.

Keywords: Emotional intelligence, EI, Group EI, multi-method research, teamwork.

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Authors: S. M. Thahab, H. Abu Hassan, Z. Hassan

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The InAlGaN alloy has only recently began receiving serious attention into its growth and application. High quality InGaN films have led to the development of light emitting diodes (LEDs) and blue laser diodes (LDs). The quaternary InAlGaN however, represents a more versatile material since the bandgap and lattice constant can be independently varied. We report an ultraviolet (UV) quaternary InAlGaN multi-quantum wells (MQWs) LD study by using the simulation program of Integrated System Engineering (ISE TCAD). Advanced physical models of semiconductor properties were used in order to obtain an optimized structure. The device performance which is affected by piezoelectric and thermal effects was studied via drift-diffusion model for carrier transport, optical gain and loss. The optical performance of the UV LD with different numbers of quantum wells was numerically investigated. The main peak of the emission wavelength for double quantum wells (DQWs) was shifted from 358 to 355.8 nm when the forward current was increased. Preliminary simulated results indicated that better output performance and lower threshold current could be obtained when the quantum number is four, with output power of 130 mW and threshold current of 140 mA.

Keywords: Nitride semiconductors, InAlGaN quaternary, UVLD, numerical simulation.

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Authors: M. Ghalambaz, A.R. Noghrehabadi, M.A. Behrang, E. Assareh, A. Ghanbarzadeh, N.Hedayat

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This study presents a hybrid neural network and Gravitational Search Algorithm (HNGSA) method to solve well known Wessinger's equation. To aim this purpose, gravitational search algorithm (GSA) technique is applied to train a multi-layer perceptron neural network, which is used as approximation solution of the Wessinger's equation. A trial solution of the differential equation is written as sum of two parts. The first part satisfies the initial/ boundary conditions and does not contain any adjustable parameters and the second part which is constructed so as not to affect the initial/boundary conditions. The second part involves adjustable parameters (the weights and biases) for a multi-layer perceptron neural network. In order to demonstrate the presented method, the obtained results of the proposed method are compared with some known numerical methods. The given results show that presented method can introduce a closer form to the analytic solution than other numerical methods. Present method can be easily extended to solve a wide range of problems.

Keywords: Neural Networks, Gravitational Search Algorithm (GSR), Wessinger's Equation.

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Authors: Shoujia Fang, Guoqing Ding, Xin Chen

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The quality of press-fit assembly is closely related to reliability and safety of product. The paper proposed a keypoint detection method based on convolutional neural network to improve the accuracy of keypoint detection in press-fit curve. It would provide an auxiliary basis for judging quality of press-fit assembly. The press-fit curve is a curve of press-fit force and displacement. Both force data and distance data are time-series data. Therefore, one-dimensional convolutional neural network is used to process the press-fit curve. After the obtained press-fit data is filtered, the multi-layer one-dimensional convolutional neural network is used to perform the automatic learning of press-fit curve features, and then sent to the multi-layer perceptron to finally output keypoint of the curve. We used the data of press-fit assembly equipment in the actual production process to train CNN model, and we used different data from the same equipment to evaluate the performance of detection. Compared with the existing research result, the performance of detection was significantly improved. This method can provide a reliable basis for the judgment of press-fit quality.

Keywords: Keypoint detection, curve feature, convolutional neural network, press-fit assembly.

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Authors: N. Perko, N. Kavran, M. Bukljaš, I. Berbić

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This paper is a result of implemented research on proposed introduced methodology for nautical ports capacity planning by introducing a multi-criteria approach of defined criteria in the Adriatic Sea region. The purpose was analyzing the determinants - characteristics of infrastructure and services of nautical ports capacity allocated, especially nowadays due to COVID-19 pandemic, as crucial for successful operation of nautical ports. Giving the importance of the defined priorities for short-term and long-term planning is essential not only in terms of the development of nautical tourism, but also in terms of developing the maritime system, but unfortunately this is not always carried out. Evaluation of the use of resources should follow from a detailed analysis of all aspects of resources bearing in mind that nautical tourism used resources in a sustainable manner and generates effects in the tourism and maritime sectors. Consequently, identified multiplier effect of nautical tourism, which should be defined and quantified in detail, should be one of the major competitive products on the Croatian Adriatic and the Mediterranean. Research of nautical tourism is necessary to quantify the effects and required planning system development. In the future, the greatest threat to long-term sustainable development of nautical tourism can be its further uncontrolled or unlimited and undirected development, especially under pressure markedly higher demand than supply for new moorings in the Mediterranean. Results of this implemented research are applicable to nautical ports management and decision makers of maritime transport system development. This paper will present implemented research and obtained result - developed methodology for nautical port capacity planning - Port Capacity Planning Multi-criteria decision-making. A proposed methodological approach of multi-criteria capacity planning includes four criteria (spatial - transport, cost - infrastructure, ecological and organizational criteria, and additional services). The importance of the criteria and sub-criteria is evaluated and carried out the basis for a sensitivity analysis of the importance of the criteria and sub-criteria. Based on the analysis of the identified and quantified importance of certain criteria and sub-criteria as well as sensitivity analysis and analysis of changes of the quantified importance scientific and applicable results will be presented. These obtained results have practical applicability by management of nautical ports in the planning of increasing capacity and further development and for the adaptation of existing nautical ports. The obtained research is applicable and replicable in other seas and results are especially important and useful in this COVID-19 pandemic challenging maritime development framework.

Keywords: Adriatic Sea, capacity, infrastructures, maritime system, methodology, nautical ports, nautical tourism, service.

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Authors: Tarik Rashid, B. Q. Huang, M-T. Kechadi, B. Gleeson

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this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects the demand of energy load. So the AR-MCRN is used to learn the relationship between past, previous, and future exogenous and endogenous variables. Experimental results show that using the change in weather components and the change that occurred in past load as inputs to the AR-MCRN, rather than the basic weather parameters and past load itself as inputs to the same network, produce higher accuracy of predicted load. Experimental results also show that using exogenous and endogenous variables as inputs is better than using only the exogenous variables as inputs to the network.

Keywords: Daily peak load forecasting, neural networks, recurrent neural networks, auto regressive multi-context neural network.

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Authors: Jens Friedrich, Matthias A. Gebele, Armin Lechler, Alexander Verl

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Chatter vibrations and process instabilities are the most important factors limiting the productivity of the milling process. Chatter can leads to damage of the tool, the part or the machine tool. Therefore, the estimation and prediction of the process stability is very important. The process stability depends on the spindle speed, the depth of cut and the width of cut. In milling, the process conditions are defined in the NC-program. While the spindle speed is directly coded in the NC-program, the depth and width of cut are unknown. This paper presents a new simulation based approach for the prediction of the depth and width of cut of a milling process. The prediction is based on a material removal simulation with an analytically represented tool shape and a multi-dexel approach for the workpiece. The new calculation method allows the direct estimation of the depth and width of cut, which are the influencing parameters of the process stability, instead of the removed volume as existing approaches do. The knowledge can be used to predict the stability of new, unknown parts. Moreover with an additional vibration sensor, the stability lobe diagram of a milling process can be estimated and improved based on the estimated depth and width of cut.

Keywords: Dexel, process stability, material removal, milling.

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Authors: D. Danesh, M. J. Ryan, A. Abbasi

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Project Portfolio Management (PPM) is an essential component of an organisation’s strategic procedures, which requires attention of several factors to envisage a range of long-term outcomes to support strategic project portfolio decisions. To evaluate overall efficiency at the portfolio level, it is essential to identify the functionality of specific projects as well as to aggregate those findings in a mathematically meaningful manner that indicates the strategic significance of the associated projects at a number of levels of abstraction. PPM success is directly associated with the quality of decisions made and poor judgment increases portfolio costs. Hence, various Multi-Criteria Decision Making (MCDM) techniques have been designed and employed to support the decision-making functions. This paper reviews possible options to enhance the decision-making outcomes in organisational portfolio management processes using the Analytic Hierarchy Process (AHP) both from academic and practical perspectives and will examine the usability, certainty and quality of the technique. The results of the study will also provide insight into the technical risk associated with current decision-making model to underpin initiative tracking and strategic portfolio management.

Keywords: Analytic hierarchy process, decision support systems, multi-criteria decision-making, project portfolio management.

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Authors: C. Ardil

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Fuzzy set theory and its extensions (intuitionistic fuzzy sets, picture fuzzy sets, and neutrosophic sets) have been widely used to address imprecision and uncertainty in complex decision-making. However, they may struggle with inherent indeterminacy and inconsistency in real-world situations. This study introduces uncertainty sets as a promising alternative, offering a structured framework for incorporating both types of uncertainty into decision-making processes.This work explores the theoretical foundations and applications of uncertainty sets. A novel decision-making algorithm based on uncertainty set-based proximity measures is developed and demonstrated through a practical application: selecting the most suitable stealth combat aircraft.

The results highlight the effectiveness of uncertainty sets in ranking alternatives under uncertainty. Uncertainty sets offer several advantages, including structured uncertainty representation, robust ranking mechanisms, and enhanced decision-making capabilities due to their ability to account for ambiguity.Future research directions are also outlined, including comparative analysis with existing MCDM methods under uncertainty, sensitivity analysis to assess the robustness of rankings,and broader application to various MCDM problems with diverse complexities. By exploring these avenues, uncertainty sets can be further established as a valuable tool for navigating uncertainty in complex decision-making scenarios.

Keywords: Uncertainty set, stealth combat aircraft selection multiple criteria decision-making analysis, MCDM, uncertainty proximity analysis

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Authors: Ma. Rosario Concepcion O. Ang, Luis Caezar Ian K. Panganiban, Charmyne B. Mamador, Oliver Dan G. De Luna, Michael D. Bausas, Joselito P. Cruz

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PhilSHORE is a multi-site, multi-device and multicriteria decision support tool designed to support the development of tidal current energy in the Philippines. Its platform is based on Geographic Information Systems (GIS) which allows for the collection, storage, processing, analyses and display of geospatial data. Combining GIS tools with open source web development applications, PhilSHORE becomes a webGIS-based marine spatial planning tool. To date, PhilSHORE displays output maps and graphs of power and energy density, site suitability and site-device analysis. It enables stakeholders and the public easy access to the results of tidal current energy resource assessments and site suitability analyses. Results of the initial development show that PhilSHORE is a promising decision support tool for ORE project developments.

Keywords: GIS, Site Suitability Analysis, Tidal Current Energy Resource Assessment, WebGIS.

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Authors: Fangfang Meng, Shuang Cong

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In the closed quantum system, if the control system is strongly regular and all other eigenstates are directly coupled to the target state, the control system can be asymptotically stabilized at the target eigenstate by the Lyapunov control based on the state error. However, if the control system is not strongly regular or as long as there is one eigenstate not directly coupled to the target state, the situations will become complicated. In this paper, we propose an implicit Lyapunov control method based on the state error to solve the convergence problems for these two degenerate cases. And at the same time, we expand the target state from the eigenstate to the arbitrary pure state. Especially, the proposed method is also applicable in the control system with multi-control Hamiltonians. On this basis, the convergence of the control systems is analyzed using the LaSalle invariance principle. Furthermore, the relation between the implicit Lyapunov functions of the state distance and the state error is investigated. Finally, numerical simulations are carried out to verify the effectiveness of the proposed implicit Lyapunov control method. The comparisons of the control effect using the implicit Lyapunov control method based on the state distance with that of the state error are given.

Keywords: Implicit Lyapunov control, state error, degenerate cases, convergence.

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Authors: Zaouche Mohammed, Amini Mohammed, Foughali Khaled, Hamissi Aicha, Aktouf Mohand Arezki, Boureghda Ilyes

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In this paper, we present a piloting law based on the adaptive differentiators via high order sliding mode controller, by using an aircraft in virtual simulated environment. To deal with the design of an autopilot controller, we propose a framework based on Software in the Loop (SIL) methodology and we use Microsoft^TM Flight Simulator (FS-2004) as the environment for plane simulation. The aircraft dynamic model is nonlinear, Multi-Input Multi-Output (MIMO) and tightly coupled. The nonlinearity resides in the dynamic equations and also in the aerodynamic coefficients' variability. In our case, two (02) aircrafts are used in the flight tests, the Zlin-142 and MQ-1 Predator. For both aircrafts and in a very low altitude flight, we send the piloting control inputs to the aircraft which has stalled due to a command disconnection. Then, we present the aircraft’s dynamic behavior analysis while reestablishing the command transmission. Finally, a comparative study between the two aircraft’s dynamic behaviors is presented.

Keywords: Adaptive differentiators, Microsoft Flight Simulator, MQ-1 predator, second order sliding modes, Zlin-142.

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Authors: Maia Kukhaleishvili, Ekaterine Bulauri, Iveta Megrelishvili, Tamar Shamatava, Tamar Chipashvili

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Plant viruses can cause loss of yield and quality in a lot of important crops. Symptoms of pathogens are variable depending on the cultivars and virus strain. Selection of resistant potato varieties would reduce the risk of virus transmission and significant economic impact. Other way to avoid reduced harvest yields is regular potato seed production sampling and testing for viral infection. The aim of this study was to determine the occurrence and distribution of viral diseases according potato cultivars for further selection of virus-free material in Georgia. During the summer 2015- 2016, 5 potato cultivars (Sante, Laura, Jelly, Red Sonia, Anushka) at 5 different farms located in Akhalkalaki were tested for 6 different potato viruses: Potato virus A (PVA), Potato virus M (PVM), Potato virus S (PVS), Potato virus X (PVX), Potato virus Y (PVY) and potato leaf roll virus (PLRV). A serological method, Double Antibody Sandwich-Enzyme linked Immunosorbent Assay (DASELISA) was used at the laboratory to analyze the results. The result showed that PVY (21.4%) and PLRV (19.7%) virus presence in collected samples was relatively high compared to others. Researched potato cultivars except Jelly and Laura were infected by PVY with different concentrations. PLRV was found only in three potato cultivars (Sante, Jelly, Red Sonia) and PVM virus (3.12%) was characterized with low prevalence. PVX, PVA and PVS virus infection was not reported. It would be noted that 7.9% of samples were containing PVY/PLRV mix infection. Based on the results it can be concluded that PVY and PLRV infections are dominant in all research cultivars. Therefore significant yield losses are expected. Systematic, long-term control of potato viral infection, especially seed-potatoes, must be regarded as the most important factor to increase seed productivity.

Keywords: Diseases, infection, potato, virus.

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Authors: R. B. Ibrahim, M. S. Argungu, I. M. Mungadi

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It is obvious in this present time, internet has become an indispensable part of human life since its inception. The Internet has provided diverse opportunities to make life so easy for human beings, through the adoption of various channels. Among these channels are email, internet banking, video conferencing, and the like. Email is one of the easiest means of communication hugely accepted among individuals and organizations globally. But over decades the security integrity of this platform has been challenged with malicious activities like Phishing. Email phishing is designed by phishers to fool the recipient into handing over sensitive personal information such as passwords, credit card numbers, account credentials, social security numbers, etc. This activity has caused a lot of financial damage to email users globally which has resulted in bankruptcy, sudden death of victims, and other health-related sicknesses. Although many methods have been proposed to detect email phishing, in this research, the results of multiple machine-learning methods for predicting email phishing have been compared with the use of filter-wrapper feature selection. It is worth noting that all three models performed substantially but one outperformed the other. The dataset used for these models is obtained from Kaggle online data repository, while three classifiers: decision tree, Naïve Bayes, and Logistic regression are ensemble (Bagging) respectively. Results from the study show that the Decision Tree (CART) bagging ensemble recorded the highest accuracy of 98.13% using PEF (Phishing Essential Features). This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, hybrid, filter-wrapper, phishing.

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Authors: Amèdédjihundé H. J. Hounnou, Frédéric Dubas, François-Xavier Fifatin, Didier Chamagne, Antoine Vianou

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This paper presents the techno-economic evaluation of run-of-river small-hydropower plants. In this regard, a multi-objective optimization procedure is proposed for the optimal sizing of the hydropower plants, and NSGAII is employed as the optimization algorithm. Annual generated energy and investment cost are considered as the objective functions, and number of generator units (n) and nominal turbine flow rate (Q_T) constitute the decision variables. Site of Yeripao in Benin is considered as the case study. We have categorized the river of this site using its environmental characteristics: gross head, and first quartile, median, third quartile and mean of flow. Effects of each decision variable on the objective functions are analysed. The results gave Pareto Front which represents the trade-offs between annual energy generation and the investment cost of hydropower plants, as well as the recommended optimal solutions. We noted that with the increase of the annual energy generation, the investment cost rises. Thus, maximizing energy generation is contradictory with minimizing the investment cost. Moreover, we have noted that the solutions of Pareto Front are grouped according to the number of generator units (n). The results also illustrate that the costs per kWh are grouped according to the n and rise with the increase of the nominal turbine flow rate. The lowest investment costs per kWh are obtained for n equal to one and are between 0.065 and 0.180 €/kWh. Following the values of n (equal to 1, 2, 3 or 4), the investment cost and investment cost per kWh increase almost linearly with increasing the nominal turbine flowrate while annual generated. Energy increases logarithmically with increasing of the nominal turbine flowrate. This study made for the Yeripao river can be applied to other rivers with their own characteristics.

Keywords: Hydropower plant, investment cost, multi-objective optimization, number of generator units.

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Authors: J. R. Wang, H. T. Lin, Y. S. Tseng, W. Y. Li, H. C. Chen, S. W. Chen, C. Shih

Abstract:

TRACE is developed by U.S. NRC for the nuclear power plants (NPPs) safety analysis. We focus on the establishment and application of TRACE/FRAPTRAN/SNAP models for Chinshan NPP (BWR/4) spent fuel pool in this research. The geometry is 12.17 m × 7.87 m × 11.61 m for the spent fuel pool. In this study, there are three TRACE/SNAP models: one-channel, two-channel, and multi-channel TRACE/SNAP model. Additionally, the cooling system failure of the spent fuel pool was simulated and analyzed by using the above models. According to the analysis results, the peak cladding temperature response was more accurate in the multi-channel TRACE/SNAP model. The results depicted that the uncovered of the fuels occurred at 2.7 day after the cooling system failed. In order to estimate the detailed fuel rods performance, FRAPTRAN code was used in this research. According to the results of FRAPTRAN, the highest cladding temperature located on the node 21 of the fuel rod (the highest node at node 23) and the cladding burst roughly after 3.7 day.

Keywords: TRACE, FRAPTRAN, SNAP, spent fuel pool.

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Authors: A. Mansour Khaki, A. E. Forouhid, S. Hemmati, M. Rahnamay-Naeini

Abstract:

In this article we research on the drivers’ behavior at intersections. Some significant behaviors are chosen and designed a questionnaire which was about 2 pages. In this questionnaire, samples were being asked to answer by checking the box. The answers have been from always to never. This questionnaire related to our selection’s behaviors. Finally it has been resulted that most of aggressive behaviors were being common in them. Also it has been suggested some solutions for each of them.

Keywords: Driver, behavior, intersection, study.

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Authors: Farhan Beg, Raymond Moberly

Abstract:

The Indian subcontinent is facing a massive challenge with regards to energy security in its member countries; to provide reliable electricity to facilitate development across various sectors of the economy and consequently achieve the developmental targets. The instability of the current precarious situation is observable in the frequent system failures and blackouts.

The deployment of interconnected electricity ‘Supergrid’ designed to carry huge quanta of power across the Indian sub-continent is proposed in this paper. Not only enabling energy security in the subcontinent it will also provide a platform for Renewable Energy Sources (RES) integration. This paper assesses the need and conditions for a Supergrid deployment and consequently proposes a meshed topology based on Voltage Source High Voltage Direct Current (VSC- HVDC) converters for the Supergrid modeling. Various control schemes for the control of voltage and power are utilized for the regulation of the network parameters. A 3 terminal Multi Terminal Direct Current (MTDC) network is used for the simulations.

Keywords: Super grid, Wind and Solar energy, High Voltage Direct Current, Electricity management, Load Flow Analysis.

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Authors: M. Miladi, T. Ezzedine, R. Bouallegue

Abstract:

In the current decade, wireless sensor networks are emerging as a peculiar multi-disciplinary research area. By this way, energy efficiency is one of the fundamental research themes in the design of Medium Access Control (MAC) protocols for wireless sensor networks. Thus, in order to optimize the energy consumption in these networks, a variety of MAC protocols are available in the literature. These schemes were commonly evaluated under simple network density and a few results are published on their robustness in realistic network-s size. We, in this paper, provide an analytical study aiming to highlight the energy waste sources in wireless sensor networks. Then, we experiment three energy efficient hybrid CSMA/CA based MAC protocols optimized for wireless sensor networks: Sensor-MAC (SMAC), Time-out MAC (TMAC) and Traffic aware Energy Efficient MAC (TEEM). We investigate these protocols with different network densities in order to discuss the end-to-end performances of these schemes (i.e. in terms of energy efficiency, delay and throughput). Through Network Simulator (NS- 2) implementations, we explore the behaviors of these protocols with respect to the network density. In fact, this study may help the multihops sensor networks designers to design or select the MAC layer which matches better their applications aims.

Keywords: Energy efficiency, medium access control, network density, wireless sensor networks.

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Authors: S. Raja Ratna, R. Ravi

Abstract:

Securing the confidential data transferred via wireless network remains a challenging problem. It is paramount to ensure that data are accessible only by the legitimate users rather than by the attackers. One of the most serious threats to organization is jamming, which disrupts the communication between any two pairs of nodes. Therefore, designing an attack-defending scheme without any packet loss in data transmission is an important challenge. In this paper, Dependence based Malicious Route Defending DMRD Scheme has been proposed in multi path routing environment to prevent jamming attack. The key idea is to defend the malicious route to ensure perspicuous transmission. This scheme develops a two layered architecture and it operates in two different steps. In the first step, possible routes are captured and their agent dependence values are marked using triple agents. In the second step, the dependence values are compared by performing comparator filtering to detect malicious route as well as to identify a reliable route for secured data transmission. By simulation studies, it is observed that the proposed scheme significantly identifies malicious route by attaining lower delay time and route discovery time; it also achieves higher throughput.

Keywords: Attacker, Dependence, Jamming, Malicious.

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