Search results for: Hybrid real coded GA (HRCGA)

Authors: Feras Al-Obeidat, Nabil Belacel, Juan A. Carretero, Prabhat Mahanti,

Abstract:

In this paper, a new learning algorithm based on a hybrid metaheuristic integrating Differential Evolution (DE) and Reduced Variable Neighborhood Search (RVNS) is introduced to train the classification method PROAFTN. To apply PROAFTN, values of several parameters need to be determined prior to classification. These parameters include boundaries of intervals and relative weights for each attribute. Based on these requirements, the hybrid approach, named DEPRO-RVNS, is presented in this study. In some cases, the major problem when applying DE to some classification problems was the premature convergence of some individuals to local optima. To eliminate this shortcoming and to improve the exploration and exploitation capabilities of DE, such individuals were set to iteratively re-explored using RVNS. Based on the generated results on both training and testing data, it is shown that the performance of PROAFTN is significantly improved. Furthermore, the experimental study shows that DEPRO-RVNS outperforms well-known machine learning classifiers in a variety of problems.

Keywords: Knowledge Discovery, Differential Evolution, Reduced Variable Neighborhood Search, Multiple criteria classification, PROAFTN, Supervised Learning.

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Authors: José M. Merigó, Pilar López-Jurado, M.Carmen Gracia, Montserrat Casanovas

Abstract:

We present a method for the selection of students in interdisciplinary studies based on the hybrid averaging operator. We assume that the available information given in the problem is uncertain so it is necessary to use interval numbers. Therefore, we suggest a new type of hybrid aggregation called uncertain induced generalized hybrid averaging (UIGHA) operator. It is an aggregation operator that considers the weighted average (WA) and the ordered weighted averaging (OWA) operator in the same formulation. Therefore, we are able to consider the degree of optimism of the decision maker and grades of importance in the same approach. By using interval numbers, we are able to represent the information considering the best and worst possible results so the decision maker gets a more complete view of the decision problem. We develop an illustrative example of the proposed scheme in the selection of students in interdisciplinary studies. We see that with the use of the UIGHA operator we get a more complete representation of the selection problem. Then, the decision maker is able to consider a wide range of alternatives depending on his interests. We also show other potential applications that could be used by using the UIGHA operator in educational problems about selection of different types of resources such as students, professors, etc.

Keywords: Decision making, Selection of students, Uncertainty, Aggregation operators.

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Authors: J. Arneric, E. Jurun, L. Kordic

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This paper deals with econometric analysis of real retail trade turnover. It is a part of an extensive scientific research about modern trends in Croatian national economy. At the end of the period of transition economy, Croatia confronts with challenges and problems of high consumption society. In such environment as crucial economic variables: real retail trade turnover, average monthly real wages and household loans are chosen for consequence analysis. For the purpose of complete procedure of multiple econometric analysis data base adjustment has been provided. Namely, it has been necessary to deflate original national statistics data of retail trade turnover using consumer price indices, as well as provide process of seasonally adjustment of its contemporary behavior. In model establishment it has been necessary to involve the overcoming procedure for the autocorrelation and colinearity problems. Moreover, for case of time-series shift a specific appropriate econometric instrument has been applied. It would be emphasize that the whole methodology procedure is based on the real Croatian national economy time-series.

Keywords: Consumption society, multiple econometric model, real retail trade turnover, second order autocorrelation.

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Authors: F. Z. Eddoug, J. Benhra, R. Benabbou

Abstract:

Excellence and Success are the ultimate goal for any project and in order to achieve it, every project manager looks for the convenient tools and methods. This work proposes a framework that seeks an efficient management of general project through a lean and agile approach. In order to get this objective, the article was divided in two stages, the first one was emphasized on exploring and analyzing the existing project management models and then in the second one the desired framework was created, beginning by focusing on seven existing models and then proposing for each phase of the framework the convenient lean and agile tools.

Keywords: Agility, hybrid project management, lean, scrum.

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Authors: Syed Manzoor Qasim, Shuja Abbasi, Saleh Alshebeili, Bandar Almashary, Ateeq Ahmad Khan

Abstract:

Higher-order Statistics (HOS), also known as cumulants, cross moments and their frequency domain counterparts, known as poly spectra have emerged as a powerful signal processing tool for the synthesis and analysis of signals and systems. Algorithms used for the computation of cross moments are computationally intensive and require high computational speed for real-time applications. For efficiency and high speed, it is often advantageous to realize computation intensive algorithms in hardware. A promising solution that combines high flexibility together with the speed of a traditional hardware is Field Programmable Gate Array (FPGA). In this paper, we present FPGA-based parallel architecture for the computation of third-order cross moments. The proposed design is coded in Very High Speed Integrated Circuit (VHSIC) Hardware Description Language (VHDL) and functionally verified by implementing it on Xilinx Spartan-3 XC3S2000FG900-4 FPGA. Implementation results are presented and it shows that the proposed design can operate at a maximum frequency of 86.618 MHz.

Keywords: Cross moments, Cumulants, FPGA, Hardware Implementation.

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Authors: Gaohuizi Guo, Ning Zhang

Abstract:

Firefly algorithm (FA) and Sine Cosine algorithm (SCA) are two very popular and advanced metaheuristic algorithms. However, these algorithms applied to multi-objective optimization problems have some shortcomings, respectively, such as premature convergence and limited exploration capability. Combining the privileges of FA and SCA while avoiding their deficiencies may improve the accuracy and efficiency of the algorithm. This paper proposes a hybridization of FA and SCA algorithms, named multi-objective firefly-sine cosine algorithm (MFA-SCA), to develop a more efficient meta-heuristic algorithm than FA and SCA.

Keywords: Firefly algorithm, hybrid algorithm, multi-objective optimization, Sine Cosine algorithm.

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Authors: Gayadhar Panda, Sidhartha Panda, C. Ardil

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The main objective of Automatic Generation Control (AGC) is to balance the total system generation against system load losses so that the desired frequency and power interchange with neighboring systems is maintained. Any mismatch between generation and demand causes the system frequency to deviate from its nominal value. Thus high frequency deviation may lead to system collapse. This necessitates a very fast and accurate controller to maintain the nominal system frequency. This paper deals with a novel approach of artificial intelligence (AI) technique called Hybrid Neuro-Fuzzy (HNF) approach for an (AGC). The advantage of this controller is that it can handle the non-linearities at the same time it is faster than other conventional controllers. The effectiveness of the proposed controller in increasing the damping of local and inter area modes of oscillation is demonstrated in a two area interconnected power system. The result shows that intelligent controller is having improved dynamic response and at the same time faster than conventional controller.

Keywords: Automatic Generation Control (AGC), Dynamic Model, Two-area Power System, Fuzzy Logic Controller, Neural Network, Hybrid Neuro-Fuzzy(HNF).

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Authors: V. M. Levshakov, N. A. Steshenkova, N. A. Nosyrev

Abstract:

Application of hulls processing technologies, based on high-concentrated energy sources (laser and plasma technologies), allow improve shipbuilding production. It is typical for high-speed vessels construction using steel and aluminum alloys with high precision hulls required. Report describes high-performance technologies for plasma welding (using direct current of reversed polarity), laser, and hybrid laser-arc welding of hulls structures developed by JSC “SSTC”

Keywords: Flat sections, hybrid laser-arc welding, plasma welding, plasmatron.

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Authors: M. Veeresham

Abstract:

The microstructure, texture, phase stability, and tensile properties of annealed Ta_0.5Nb_0.5Hf_0.5ZrTi_1.5 alloy have been investigated in the present research. The alloy was severely hybrid-rolled up to 93.5% thickness reduction, subsequently rolled samples subjected to an annealing treatment at 800 °C and 1000 °C temperatures for 1 h. Consequently, the rolled condition and both annealed temperatures have a body-centered cubic (BCC) structure. Furthermore, quantitative texture measurements (orientation distribution function (ODF) analysis) and microstructural examinations (analytical electron backscatter diffraction (EBSD) maps) permitted to establish a good relationship between annealing texture and microstructure and universal testing machine (UTM) utilized for obtaining the mechanical properties. Impressive room temperature tensile properties combination with the tensile strength (1380 MPa) and (24.7%) elongation is achieved for the 800 °C heat-treated condition. The evolution of the coarse microstructure featured in the case of 1000 °C annealed temperature ascribed to the influence of high thermal energy.

Keywords: Refractory high entropy alloys, hybrid-rolling, recrystallization, microstructure, tensile properties.

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Authors: C. Pacheco, A. Cipriano

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A new concept of response system is proposed for filling the gap that exists in reducing vulnerability during immediate response to natural disasters. Real Time Early Response Systems (RTERSs) incorporate real time information as feedback data for closing control loop and for generating real time situation assessment. A review of the state of the art on works that fit the concept of RTERS is presented, and it is found that they are mainly focused on manmade disasters. At the same time, in response phase of natural disaster management many works are involved in creating early warning systems, but just few efforts have been put on deciding what to do once an alarm is activated. In this context a RTERS arises as a useful tool for supporting people in their decision making process during natural disasters after an event is detected, and also as an innovative context for applying well-known automation technologies and automatic control concepts and tools.

Keywords: Disaster management, emergency response system, natural disasters, real time.

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Authors: Ventura Assuncao

Abstract:

In automotive systems almost all steps concerning the calibration of several control systems, e.g., low idle governor or boost pressure governor, are made with the vehicle because the timeto- production and cost requirements on the projects do not allow for the vehicle analysis necessary to build reliable models. Here is presented a procedure using parametric and NN (neural network) models that enables the generation of vehicle system models based on normal ECU engine control unit) vehicle measurements. These models are locally valid and permit pre and follow-up calibrations so that, only the final calibrations have to be done with the vehicle.

Keywords: Automotive systems, neuro-hybrid models, demodulator, nonlinear systems, identification, and neural networks.

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Authors: Lu Wei, Yunhao Zhu, Ping Deng, Wentao Yu

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Past literature on business incubators distinguished incubators based on their mission statements. However, more and more mission statements become a slogan rather than a reality. It is therefore more appropriate to identify business incubators based on their real activities, rather than the missions they declared. With a sample of technology business incubators (TBIs) in China, we try to investigate business incubators’ real activities by examining the incubation efficiency along the following five dimensions, i.e., survival of new ventures, technology transfer, local economic growth, job creation, and profit generation. Furthermore, we identified six types of business incubators. The results indicate that generally Chinese TBIs have a greater preference for acquiring profits over other dimensions. 

Keywords: Business incubators, mission statements, real activities, incubation efficiency, technology business incubators, China.

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Authors: L. C. Moreira, M. Kauffman

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This paper outlines the results of an experimental research on deploying an emerging augmented reality (AR) system for real-time task assistance (or work instructions) of highly customised and high-risk manual operations. The focus is on human operators’ training effectiveness and performance and the aim is to test if such technologies can support enhancing the knowledge retention levels and accuracy of task execution to improve health and safety (H&S). An AR enhanced assembly method is proposed and experimentally tested using a real industrial process as case study for electric vehicles’ (EV) battery module assembly. The experimental results revealed that the proposed method improved the training practices and performance through increases in the knowledge retention levels from 40% to 84%, and accuracy of task execution from 20% to 71%, when compared to the traditional paper-based method. The results of this research validate and demonstrate how emerging technologies are advancing the choice for manual, hybrid or fully automated processes by promoting the XR-assisted processes, and the connected worker (a vision for Industry 4 and 5.0), and supporting manufacturing become more resilient in times of constant market changes.

Keywords: Augmented reality, extended reality, connected worker, XR-assisted operator, manual assembly 4.0, industry 5.0, smart training, battery assembly.

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Authors: Madhukar Nagare, Pankaj Dutta

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Inventory decisional environment of short life-cycle products is full of uncertainties arising from randomness and fuzziness of input parameters like customer demand requiring modeling under hybrid uncertainty. Prior inventory models incorporating fuzzy demand have unfortunately ignored stochastic variation of demand. This paper determines an unambiguous optimal order quantity from a set of n fuzzy observations in a newsvendor inventory setting in presence of fuzzy random variable demand capturing both fuzzy perception and randomness of customer demand. The stress of this paper is in providing solution procedure that attains optimality in two steps with demand information availability in linguistic phrases leading to fuzziness along with stochastic variation. The first step of solution procedure identifies and prefers one best fuzzy opinion out of all expert opinions and the second step determines optimal order quantity from the selected event that maximizes profit. The model and solution procedure is illustrated with a numerical example.

Keywords: Fuzzy expected value, Fuzzy random demand, Hybrid uncertainty, Optimal order quantity, Single-period inventory

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Authors: S. Alotaibi, S. Omer, Y. Su

Abstract:

The conventional Internal Combustion Engine (ICE) based vehicles are a threat to the environment as they account for a large proportion of the overall greenhouse gas (GHG) emissions in the world. Hence, it is required to replace these vehicles with more environment-friendly vehicles. Electric Vehicles (EVs) are promising technologies which offer both human comfort “noise, pollution” as well as reduced (or no) emissions of GHGs. In this paper, different types of EVs are reviewed and their advantages and disadvantages are identified. It is found that in terms of fuel economy, Plug-in Hybrid EVs (PHEVs) have the best fuel economy, followed by Hybrid EVs (HEVs) and ICE vehicles. Since Battery EVs (BEVs) do not use any fuel, their fuel economy is estimated as price per kilometer. Similarly, in terms of GHG emissions, BEVs are the most environmentally friendly since they do not result in any emissions while HEVs and PHEVs produce less emissions compared to the conventional ICE based vehicles. Fuel Cell EVs (FCEVs) are also zero-emission vehicles, but they have large costs associated with them. Finally, if the electricity is provided by using the renewable energy technologies through grid connection, then BEVs could be considered as zero emission vehicles.

Keywords: Electric vehicle, fuel cell electric vehicle, hybrid electric vehicle, internal combustion engine.

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Authors: Nidal F. Shilbayeh, Belal AbuHaija, Zainab N. Al-Qudsy

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In this paper, a hybrid blind digital watermarking system using Discrete Wavelet Transform (DWT) and Contourlet Transform (CT) has been implemented and tested. The implemented combined digital watermarking system has been tested against five common types of image attacks. The performance evaluation shows improved results in terms of imperceptibility, robustness, and high tolerance against these attacks; accordingly, the system is very effective and applicable.

Keywords: DWT, contourlet transform, digital image watermarking, copyright protection, geometric attack.

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Authors: H. Rezzouk, M. Hatti, H. Rahmani, S. Atoui

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This paper discusses the design and analysis of a hybrid PV-Fuel cell energy system destined to power a DC load. The system is composed of a photovoltaic array, a fuel cell, an electrolyzer and a hydrogen tank. HOMER software is used in this study to calculate the optimum capacities of the power system components that their combination allows an efficient use of solar resource to cover the hourly load needs. The optimal system sizing allows establishing the right balance between the daily electrical energy produced by the power system and the daily electrical energy consumed by the DC load using a 28 KW PV array, a 7.5 KW fuel cell, a 40KW electrolyzer and a 270 Kg hydrogen tank. The variation of powers involved into the DC bus of the hybrid PV-fuel cell system has been computed and analyzed for each hour over one year: the output powers of the PV array and the fuel cell, the input power of the elctrolyzer system and the DC primary load. Equally, the annual variation of stored hydrogen produced by the electrolyzer has been assessed. The PV array contributes in the power system with 82% whereas the fuel cell produces 18%. 38% of the total energy consumption belongs to the DC primary load while the rest goes to the electrolyzer.

Keywords: Electrolyzer, Hydrogen, Hydrogen Fueled Cell, Photovoltaic.

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Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

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In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: Real-Time Spatial Big Data, Quality Of Service, Vertical partitioning, Horizontal partitioning, Matching algorithm, Hamming distance, Stream query.

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Authors: Benjamin Gorry, Andrew Ireland, Peter King

Abstract:

Verification of real-time software systems can be expensive in terms of time and resources. Testing is the main method of proving correctness but has been shown to be a long and time consuming process. Everyday engineers are usually unwilling to adopt formal approaches to correctness because of the overhead associated with developing their knowledge of such techniques. Performance modelling techniques allow systems to be evaluated with respect to timing constraints. This paper describes PARTES, a framework which guides the extraction of performance models from programs written in an annotated subset of C.

Keywords: Performance Modelling, Real-time, SensitivityAnalysis.

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Authors: S. Hu, J. Mortensen, Bernard F. Buxton

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A real-time tracking system was built to track performers on an interactive stage. Using an ordinary, up to date, desktop workstation, the performers- silhouette was segmented from the background and parameterized by calculating the normalized central image moments. In the stage system, the silhouette moments were then sent to a parallel workstation, which used them to generate corresponding 3D virtual geometry and projected the generated graphic back onto the stage.

Keywords: Image moment, interactive stage, real-time, silhouette.

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Authors: B.Bahmani Firouzi, T. Niknam, M. Nayeripour

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Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the kmeans algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.

Keywords: Data clustering, Hybrid evolutionary optimization algorithm, K-means algorithm, Simulated Annealing (SA), Particle Swarm Optimization (PSO).

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Authors: George Yungchih Wang

Abstract:

Real options theory suggests that managerial flexibility embedded within irreversible investments can account for a significant value in project valuation. Although the argument has become the dominant focus of capital investment theory over decades, yet recent survey literature in capital budgeting indicates that corporate practitioners still do not explicitly apply real options in investment decisions. In this paper, we explore how real options decision criteria can be transformed into equivalent capital budgeting criteria under the consideration of uncertainty, assuming that underlying stochastic process follows a geometric Brownian motion (GBM), a mixed diffusion-jump (MX), or a mean-reverting process (MR). These equivalent valuation techniques can be readily decomposed into conventional investment rules and “option impacts", the latter of which describe the impacts on optimal investment rules with the option value considered. Based on numerical analysis and Monte Carlo simulation, three major findings are derived. First, it is shown that real options could be successfully integrated into the mindset of conventional capital budgeting. Second, the inclusion of option impacts tends to delay investment. It is indicated that the delay effect is the most significant under a GBM process and the least significant under a MR process. Third, it is optimal to adopt the new capital budgeting criteria in investment decision-making and adopting a suboptimal investment rule without considering real options could lead to a substantial loss in value.

Keywords: real options, capital budgeting, geometric Brownianmotion, mixed diffusion-jump, mean-reverting process

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Authors: R. Srinivasa Rao

Abstract:

Individually Network reconfiguration or Capacitor control perform well in minimizing power loss and improving voltage profile of the distribution system. But for heavy reactive power loads network reconfiguration and for heavy active power loads capacitor placement can not effectively reduce power loss and enhance voltage profiles in the system. In this paper, an hybrid approach that combine network reconfiguration and capacitor placement using Harmony Search Algorithm (HSA) is proposed to minimize power loss reduction and improve voltage profile. The proposed approach is tested on standard IEEE 33 and 16 bus systems. Computational results show that the proposed hybrid approach can minimize losses more efficiently than Network reconfiguration or Capacitor control. The results of proposed method are also compared with results obtained by Simulated Annealing (SA). The proposed method has outperformed in terms of the quality of solution compared to SA.

Keywords: Capacitor Control, Network Reconfiguration, HarmonySearch Algorithm, Loss Reduction, Voltage Profile.

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Authors: Yong-Gyu Lee, Gilwon Yoon

Abstract:

Image processing for capsule endoscopy requires large memory and it takes hours for diagnosis since operation time is normally more than 8 hours. A real-time analysis algorithm of capsule images can be clinically very useful. It can differentiate abnormal tissue from health structure and provide with correlation information among the images. Bleeding is our interest in this regard and we propose a method of detecting frames with potential bleeding in real-time. Our detection algorithm is based on statistical analysis and the shapes of bleeding spots. We tested our algorithm with 30 cases of capsule endoscopy in the digestive track. Results were excellent where a sensitivity of 99% and a specificity of 97% were achieved in detecting the image frames with bleeding spots.

Keywords: bleeding, capsule endoscopy, image processing, real time analysis

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Authors: Ammar Elyas babiker, M.Nordin B. Zakaria, Hassan Yosif, Samir B. Ibrahim

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Variable channel conditions in underwater networks, and variable distances between sensors due to water current, leads to variable bit error rate (BER). This variability in BER has great effects on energy efficiency of error correction techniques used. In this paper an efficient energy adaptive hybrid error correction technique (AHECT) is proposed. AHECT adaptively changes error technique from pure retransmission (ARQ) in a low BER case to a hybrid technique with variable encoding rates (ARQ & FEC) in a high BER cases. An adaptation algorithm depends on a precalculated packet acceptance rate (PAR) look-up table, current BER, packet size and error correction technique used is proposed. Based on this adaptation algorithm a periodically 3-bit feedback is added to the acknowledgment packet to state which error correction technique is suitable for the current channel conditions and distance. Comparative studies were done between this technique and other techniques, and the results show that AHECT is more energy efficient and has high probability of success than all those techniques.

Keywords: Underwater communication, wireless sensornetworks, error correction technique, energy efficiency

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Authors: Supitcha Rinprasertmeechai, Sumaeth Chavadej, Pramoch Rangsunvigit, Santi Kulprathipanja

Abstract:

This study was to investigate the performance of hybrid solvents blended between primary, secondary, or tertiary amines and piperazine (PZ) for CO2 removal from flue gas in terms of CO2 absorption capacity and regeneration efficiency at 90 oC. Alkanolamines used in this work were monoethanolamine (MEA), diethanolamine (DEA), and triethanolamine (TEA). The CO2 absorption was experimentally examined under atmospheric pressure and room temperature. The results show that MEA blend with PZ provided the maximum CO2 absorption capacity of 0.50 mol CO2/mol amine while TEA provided the minimum CO2 absorption capacity of 0.30 mol CO2/mol amine. TEA was easier to regenerate for both first cycle and second cycle with less loss of absorption capacity. The regeneration efficiency of TEA was 95.09 and 92.89 %, for the first and second generation cycles, respectively.

Keywords: CO2 absorption capacity, regeneration efficiency, CO2 removal, flue gas

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Authors: Alawode Kehinde O., Jubril Abimbola M. Komolafe Olusola A.

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This paper solves the environmental/ economic dispatch power system problem using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and its hybrid with a Convergence Accelerator Operator (CAO), called the NSGA-II/CAO. These multiobjective evolutionary algorithms were applied to the standard IEEE 30-bus six-generator test system. Several optimization runs were carried out on different cases of problem complexity. Different quality measure which compare the performance of the two solution techniques were considered. The results demonstrated that the inclusion of the CAO in the original NSGA-II improves its convergence while preserving the diversity properties of the solution set.

Keywords: optimal power flow, multiobjective power dispatch, evolutionary algorithm

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Authors: M. Almeshal, M. O. Tokhi, K. M. Goher

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A novel design of two-wheeled robotic vehicle with moving payload is presented in this paper. A mathematical model describing the vehicle dynamics is derived and simulated in Matlab Simulink environment. Two control strategies were developed to stabilise the vehicle in the upright position. A robust Proportional- Integral-Derivative (PID) control strategy has been implemented and initially tested to measure the system performance, while the second control strategy is to use a hybrid fuzzy logic controller (FLC). The results are given on a comparative basis for the system performance in terms of disturbance rejection, control algorithms robustness as well as the control effort in terms of input torque.

Keywords: double inverted pendulum, modelling, robust control, simulation,

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Authors: Juan Manuel Real-Espinosa

Abstract:

This paper addresses the first step to evaluate language learning apps: what theoretical framework to adopt when designing the app evaluation framework. The answer is not just one, since there are several options that could be proposed. However, the question to be clarified is to what extent the learning design of apps is based on a specific learning approach, or on the contrary, on a fusion of elements from several theoretical proposals and paradigms, such as m-learning, Mobile Assisted Language Learning and a number of theories about language acquisition. The present study suggests that the reality is closer to the second assumption. This implies that the theoretical framework against which the learning design of the apps should be evaluated, must also be a hybrid theoretical framework, which integrates evaluation criteria from the different theories involved in language learning through mobile applications.

Keywords: Action-oriented approach, apps evaluation, mobile-assisted language learning, post-method pedagogy.

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Authors: K. Vijayalakshmi, S. Radhakrishnan

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In this paper we have proposed a novel dynamic least cost multicast routing protocol using hybrid genetic algorithm for IP networks. Our protocol finds the multicast tree with minimum cost subject to delay, degree, and bandwidth constraints. The proposed protocol has the following features: i. Heuristic local search function has been devised and embedded with normal genetic operation to increase the speed and to get the optimized tree, ii. It is efficient to handle the dynamic situation arises due to either change in the multicast group membership or node / link failure, iii. Two different crossover and mutation probabilities have been used for maintaining the diversity of solution and quick convergence. The simulation results have shown that our proposed protocol generates dynamic multicast tree with lower cost. Results have also shown that the proposed algorithm has better convergence rate, better dynamic request success rate and less execution time than other existing algorithms. Effects of degree and delay constraints have also been analyzed for the multicast tree interns of search success rate.

Keywords: Dynamic Group membership change, Hybrid Genetic Algorithm, Link / node failure, QoS Parameters.

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