Search results for: adaptive learning rate.

Authors: Zsolt Dugár, Péter Barkóczy, Gábor Béres, Dávid Kis, Attila Bata, Tamás Dugár, Zoltán Weltsch

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This study is about the structural transformations of aluminium examining with the Dynamic Mechanical Thermal Analyzer (DMTA). It is a faster and simpler measuring method to make consequence about the metal’s structural transformations. The device measures the changing of the mechanical characteristics depending on the heating rate, and concludes certain transformations. This measuring method fast and shows clean-cut results comparing the conventional ways. Applying polymer measuring devices for metal investigations is not widespread method. One of the adaptable ways is shown in this study. The article compares the results of the small specimen test and the DMTA method, considering the temperature and the forming dependence of recrystallization temperature.

Keywords: DMTA, recrystallization, cold forming, rotation.

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Authors: Tin Hninn Hninn Maung

Abstract:

This paper introduces a hand gesture recognition system to recognize real time gesture in unstrained environments. Efforts should be made to adapt computers to our natural means of communication: Speech and body language. A simple and fast algorithm using orientation histograms will be developed. It will recognize a subset of MAL static hand gestures. A pattern recognition system will be using a transforrn that converts an image into a feature vector, which will be compared with the feature vectors of a training set of gestures. The final system will be Perceptron implementation in MATLAB. This paper includes experiments of 33 hand postures and discusses the results. Experiments shows that the system can achieve a 90% recognition average rate and is suitable for real time applications.

Keywords: Hand gesture recognition, Orientation Histogram, Myanmar Alphabet Language, Perceptronnetwork, MATLAB.

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Authors: V. Spaeth, A. Djerbi-Tegguer

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The recycling of concrete, bricks and masonry rubble as concrete aggregates is an important way to contribute to a sustainable material flow. However, there are still various uncertainties limiting the widespread use of Recycled Concrete Aggregates (RCA). The fluctuations in the composition of grade recycled aggregates and their influence on the properties of fresh and hardened concrete are of particular concern regarding the use of RCA. Most of problems occurring while using recycled concrete aggregates as aggregates are due to higher porosity and hence higher water absorption, lower mechanical strengths, residual impurities on the surface of the RCA forming weaker bond between cement paste and aggregate. So, the reuse of RCA is still limited. Efficient polymer based treatment is proposed in order to reuse RCA easier. The silicon-based polymer treatments of RCA were carried out and were compared. This kind of treatment can improve the properties of RCA such as the rate of water absorption on treated RCA is significantly reduced.

Keywords: Recycled concrete aggregates, water absorption, silicon-based agent and polymer.

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Authors: Reza Mollapourasl, Majid Haghi

Abstract:

In this study, we develop local meshfree methods known as radial basis function-generated finite difference (RBF-FD) method and Hermite finite difference (RBF-HFD) method to design stencil weights and spatial discretization for Helmholtz equation. The convergence and stability of schemes are investigated numerically in three dimensions with irregular shaped domain. These localized meshless methods incorporate the advantages of the RBF method, finite difference and Hermite finite difference methods to handle the ill-conditioning issue that often destroys the convergence rate of global RBF methods. Moreover, numerical illustrations show that the proposed localized RBF type methods are efficient and applicable for problems with complex geometries. The convergence and accuracy of both schemes are compared by solving a test problem.

Keywords: Radial basis functions, Hermite finite difference, Helmholtz equation, stability.

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Authors: Muhammad Azzam Ismail, Fahanim Abdul Rashid, Deo Prasad

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Green home rating has emerged as an important agenda to practice the principles of sustainability. In Malaysia, the establishment of the 'Green Building Index ' Residential New Construction- (GBI-RNC) has brought this agenda closer to the stakeholders of the local green building industry. GBI-RNC focuses on the evaluation of the environmental impacts posed by houses rather than assessing the Triple-Bottom-Line (TBL) of Sustainability which also include socio-economic factors. Therefore, as part of a wider study, a survey was conducted to gather the backgrounds of green building stakeholders in Malaysia and their responses to a number of exploratory questions regarding the setting up of a framework to rate green homes against the TBL. This paper reports the findings from Section A and B from this survey and discusses them accordingly with a conclusion that forms part of the basis for a new generation green home rating framework specifically for use in Malaysia.

Keywords: Green home rating, Malaysia, stakeholder surveyanalysis

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Authors: Naiqin Feng, Fang Wang, Yuhui Qiu

Abstract:

A new approach to promote the generalization ability of neural networks is presented. It is based on the point of view of fuzzy theory. This approach is implemented through shrinking or magnifying the input vector, thereby reducing the difference between training set and testing set. It is called “shrinking-magnifying approach" (SMA). At the same time, a new algorithm; α-algorithm is presented to find out the appropriate shrinking-magnifying-factor (SMF) α and obtain better generalization ability of neural networks. Quite a few simulation experiments serve to study the effect of SMA and α-algorithm. The experiment results are discussed in detail, and the function principle of SMA is analyzed in theory. The results of experiments and analyses show that the new approach is not only simpler and easier, but also is very effective to many neural networks and many classification problems. In our experiments, the proportions promoting the generalization ability of neural networks have even reached 90%.

Keywords: Fuzzy theory, generalization, misclassification rate, neural network.

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Authors: Hwan-Jun Choi, Sung-Bok Choi, Hyoung-Kyu Song

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Recently, among the MIMO-OFDM detection techniques, a lot of papers suggested V-BLAST scheme which can achieve high data rate. Therefore, the signal detection of MIMO-OFDM system is important issue. In this paper, efficient iterative V-BLAST detection technique is proposed in wireless communication system. The proposed scheme adjusts the number of candidate symbol and iterative scheme based on channel state. According to the simulation result, the proposed scheme has better BER performance than conventional schemes and similar BER performance of the QRD-M with iterative scheme. Moreover complexity of proposed scheme has 50.6% less than complexity of QRD-M detection with iterative scheme. Therefore the proposed detection scheme can be efficiently used in wireless communication.

Keywords: MIMO-OFDM, V-BLAST, QR-decomposition, QRD-M, DFE, Iterative scheme, Channel condition.

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Authors: Sherif K. El Dyasti, Esam A. Hagras, Adel E. El-Hennawy

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This paper addresses the performance of antenna array beamforming on Chip-Interleaved Code Division Multiple Access (CI_CDMA) system based on Minimum Mean Square Error (MMSE) detector in aeronautical mobile radio channel. Multipath fading, Doppler shifts caused by the speed of the aircraft, and Multiple Access Interference (MAI) are the most important reasons that affect and reduce the performance of aeronautical system. In this paper we suggested the CI-CDMA with antenna array to combat this fading and improve the bit error rate (BER) performance. We further evaluate the performance of the proposed system in the four standard scenarios in aeronautical mobile radio channel.

Keywords: Aeronautical Channel, CI-CDMA, Beamforming.

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Authors: Ali Jafari, Hatam Godini, Saed Hamed Mirhousaini

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This paper presents an overview of current municipal solid waste management in Khoram Abad city. According to data collected by the local authorities, the waste generation rate is estimated to be 800 g/cap.d with density of 243 kg/m3. Solid waste is stored in different types of containers at the source of generation in different areas of the city. Local Authority is responsible for waste collection, transportation. Municipality is responsible for waste collection, using private sector contracts. At present, both mechanical and manual methods are used to collect residential waste. Manual methods of collection are the most commonly used for waste collection in most parts of the city. Land filling is the main disposal method in this city. But it has some obvious problem and deficiencies The current state of solid waste management has been improved slightly in the last decade. By more actions can reduce the human and environmental risks.

Keywords: Disposal, Landfill, management, solid waste.

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Authors: M. Karamifard, M. Kazeminejad, A. Maghsoodloo

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Electromagnetic flow meter by measuring the varying of magnetic flux, which is related to the velocity of conductive flow, can measure the rate of fluids very carefully and precisely. Electromagnetic flow meter operation is based on famous Faraday's second Law. In these equipments, the constant magnetostatic field is produced by electromagnet (winding around the tube) outside of pipe and inducting voltage that is due to conductive liquid flow is measured by electrodes located on two end side of the pipe wall. In this research, we consider to 2-dimensional mathematical model that can be solved by numerical finite difference (FD) solution approach to calculate induction potential between electrodes. The fundamental concept to design the electromagnetic flow meter, exciting winding and simulations are come out by using MATLAB and PDE-Tool software. In the last stage, simulations results will be shown for improvement and accuracy of technical provision.

Keywords: Electromagnetic Flow Meter, Induction Voltage, Finite Difference

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Authors: Heroe Wijanto, Sugihartono, Suhartono Tjondronegoro, Kuspriyanto

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The use of High Order Statistics (HOS) analysis is expected to provide so many candidates of features that can be selected for pattern recognition. More candidates of the feature can be extracted using simple manipulation through a specific mathematical function prior to the HOS analysis. Feature extraction method using HOS analysis combined with Difference to the Nth-Power manipulation has been examined in application for Automatic Modulation Recognition (AMR) to perform scheme recognition of three digital modulation signal, i.e. QPSK-16QAM-64QAM in the AWGN transmission channel. The simulation results is reported when the analysis of HOS up to order-12 and the manipulation of Difference to the Nth-Power up to N = 4. The obtained accuracy rate of AMR using the method of Simple Decision obtained 90% in SNR > 10 dB in its classifier, while using the method of Voted Decision is 96% in SNR > 2 dB.

Keywords: modulation, automatic modulation recognition, feature analysis, feature manipulation.

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Authors: Kyoung Hoon Kim

Abstract:

ORC (Organic Rankine Cycle) has potential of reducing consumption of fossil fuels and has many favorable characteristics to exploit low-temperature heat sources. In this work thermodynamic performance of ORC with regeneration is comparatively assessed for various working fluids. Special attention is paid to the effects of system parameters such as the turbine inlet pressure on the characteristics of the system such as net work production, heat input, volumetric flow rate per 1 MW of net work and quality of the working fluid at turbine exit as well as thermal efficiency. Results show that for a given source the thermal efficiency generally increases with increasing of the turbine inlet pressure however has optimal condition for working fluids of low critical pressure such as iso-pentane or n-pentane.

Keywords: low-grade energy source, organic Rankine cycle(ORC), regeneration, Patel-Teja equation.

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Authors: Hilmi Yazici, Mehmet Akcay, Mustafa Golcu, Mehmet F. Koseoglu, Yakup Sekmen

Abstract:

Energy consumption rate during the cooling process of industrial glass tempering process is considerably high. In this experimental study the effect of dimensionless jet to jet distance (S/D) and jet to plate distance (H/D) on the cooling time have been investigated. In the experiments 4 mm thick glass samples have been used. Cooling unit consists of 16 mutually placed seamless aluminum nozzles of 8 mm in diameter and 80 mm in length. Nozzles were in staggered arrangement. Experiments were conducted with circular jets for H/D values between 1 and 10, and for S/D values between 2 and 10. During the experiments Reynolds number has been kept constant at 30000. Experimental results showed that the longest cooling time with 87 seconds has been observed in the experiments for S/D=10 and H/D=10 values, while the shortest cooling time with 42.5 seconds has been measured in the experiments for S/D=2 and H/D=4 values.

Keywords: Glass tempering, cooling, Reynolds number, nozzle

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Authors: Subrata Das, Sisir Kumar Guha

Abstract:

The objective of the present paper is to theoretically investigate the steady-state performance characteristics of journal bearing of finite width, operating with micropolar lubricant in a turbulent regime. In this analysis, the turbulent shear stress coefficients are used based on the Constantinescu’s turbulent model suggested by Taylor and Dowson with the assumption of parallel and inertia-less flow. The numerical solution of the modified Reynolds equation has yielded the distribution of film pressure which determines the static performance characteristics in terms of load capacity, attitude angle, end flow rate and frictional parameter at various values of eccentricity ratio, non-dimensional characteristics length, coupling number and Reynolds number.

Keywords: Hydrodynamic lubrication, steady-state, micropolar lubricant, turbulent.

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Authors: B. Malekynia

Abstract:

The anomalous generation of plasma blocks by interaction of petawatt-picosecond laser pulses permits side-on ignition of uncompressed solid fusion fuel following an improved application of the hydrodynamic Chu-model for deuterium-tritium. The new possibility of side-on laser ignition depends on accelerated ions and produced ions beams of high energy particles by the nonlinear ponderomotive force of the laser pulse in the plasma block, a re-evaluation of the early hydrodynamic analysis for ignition of inertial fusion by including inhibition factor, collective effect of stopping power of alpha particles and the energy loss rate reabsorption to plasma by the protons of plasma blocks being reduced by about a factor 40.

Keywords: Block ignition, Charged particles, Reabsorption, Skin layer ponderomotive acceleration.

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Authors: Chia-Ling Chang, Chung-Sheng Liao

Abstract:

The present study focuses on the discussion over the parameter of Artificial Neural Network (ANN). Sensitivity analysis is applied to assess the effect of the parameters of ANN on the prediction of turbidity of raw water in the water treatment plant. The result shows that transfer function of hidden layer is a critical parameter of ANN. When the transfer function changes, the reliability of prediction of water turbidity is greatly different. Moreover, the estimated water turbidity is less sensitive to training times and learning velocity than the number of neurons in the hidden layer. Therefore, it is important to select an appropriate transfer function and suitable number of neurons in the hidden layer in the process of parameter training and validation.

Keywords: Artificial Neural Network (ANN), sensitivity analysis, turbidity.

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Authors: Hrudaya Ku. Tripathy, B. K. Tripathy, Pradip K. Das

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Knowledge Discovery in Databases (KDD) has evolved into an important and active area of research because of theoretical challenges and practical applications associated with the problem of discovering (or extracting) interesting and previously unknown knowledge from very large real-world databases. Rough Set Theory (RST) is a mathematical formalism for representing uncertainty that can be considered an extension of the classical set theory. It has been used in many different research areas, including those related to inductive machine learning and reduction of knowledge in knowledge-based systems. One important concept related to RST is that of a rough relation. In this paper we presented the current status of research on applying rough set theory to KDD, which will be helpful for handle the characteristics of real-world databases. The main aim is to show how rough set and rough set analysis can be effectively used to extract knowledge from large databases.

Keywords: Data mining, Data tables, Knowledge discovery in database (KDD), Rough sets.

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Authors: Hirofumi Taki, Takuya Sakamoto, Makoto Yamakawa, Tsuyoshi Shiina, Toru Sato

Abstract:

For the improvement of the ability in detecting small calcifications using Ultrasonography (US) we propose a novel indicator of calcifications in an ultrasound B-mode image without decrease in frame rate. Since the waveform of an ultrasound pulse changes at a calcification position, the decorrelation of adjacent scan lines occurs behind a calcification. Therefore, we employ the decorrelation of adjacent scan lines as an indicator of a calcification. The proposed indicator depicted wires 0.05 mm in diameter at 2 cm depth with a sensitivity of 86.7% and a specificity of 100%, which were hardly detected in ultrasound B-mode images. This study shows the potential of the proposed indicator to approximate the detectable calcification size using an US device to that of an X-ray imager, implying the possibility that an US device will become a convenient, safe, and principal clinical tool for the screening of breast cancer.

Keywords: Ultrasonography, Calcification, Decorrelation, Forward scattered wave

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Authors: Noor Suhana Sulaiman, Rohani Abu Bakar, Norrozila Sulaiman

Abstract:

Intrusion Detection System is significant in network security. It detects and identifies intrusion behavior or intrusion attempts in a computer system by monitoring and analyzing the network packets in real time. In the recent year, intelligent algorithms applied in the intrusion detection system (IDS) have been an increasing concern with the rapid growth of the network security. IDS data deals with a huge amount of data which contains irrelevant and redundant features causing slow training and testing process, higher resource consumption as well as poor detection rate. Since the amount of audit data that an IDS needs to examine is very large even for a small network, classification by hand is impossible. Hence, the primary objective of this review is to review the techniques prior to classification process suit to IDS data.

Keywords: Intrusion Detection System, security, soft computing, classification.

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Authors: Josip Visković, Ana Rimac Smiljanić, Ines Ivić

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Housing loans play an important role in CEE countries’ economies. This fact is based on their share in total loans to households and their importance for economic activity and growth in CEE countries. Therefore, it is important to find out key determinants of housing loans demand in these countries. The aim of this study is to research and analyze the determinants of the demand for housing loans in Croatia. In this regard, the effect of economic activity, loan terms and real estate prices were analyzed. Also, the aim of this study is to find out what motivates people to take housing loans. Therefore, primarily empirical study was conducted among the Croatian residents. The results show that demand for housing loans is positively affected by economic growth, higher personal income and flexible loan terms, while it is negatively affected by interest rate rise.

Keywords: CEE countries, Croatia, demand determinants, housing loans.

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Authors: Amir M. Alani, Morteza Aboutalebi, Martin J. King

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Experimental study on the influence of fibre content on crack behaviour and propagation in synthetic-fibre reinforced beams has been reported in this paper. The tensile behaviour of metallic fibre concrete is evaluated in terms of residual flexural tensile strength values determined from the load-crack mouth opening displacement curve or load-deflection curve obtained by applying a centre-point load on a simply supported notched prism. The results achieved demonstrate that an increase in fibre content has an almost negligible effect on compressive and tensile splitting properties, causes a marginal increment in flexural tensile strength and increasesthe Re3 value.

Keywords: Fibre-Reinforced Concrete, Crack, Flexural Test, Ductility, Fibre Content, Experimental Study.

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. Medical dataset is a vital ingredient used in predicting patient’s health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. WEKA software was used for the implementation of the algorithms. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. From the results obtained, DTA performed better than ANN. The Root Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: Artificial neural network, classification, decision tree, diabetes mellitus.

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Authors: Tahseen Ahmed Jilani, Syed Muhammad Aqil Burney, C. Ardil

Abstract:

In the last 15 years, a number of methods have been proposed for forecasting based on fuzzy time series. Most of the fuzzy time series methods are presented for forecasting of enrollments at the University of Alabama. However, the forecasting accuracy rates of the existing methods are not good enough. In this paper, we compared our proposed new method of fuzzy time series forecasting with existing methods. Our method is based on frequency density based partitioning of the historical enrollment data. The proposed method belongs to the kth order and time-variant methods. The proposed method can get the best forecasting accuracy rate for forecasting enrollments than the existing methods.

Keywords: Fuzzy logical groups, fuzzified enrollments, fuzzysets, fuzzy time series.

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Authors: Marco Intelvi, Apolinar Picado, Joaquín Martínez

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In this work, simulation algorithms for contact drying of agitated particulate materials under vacuum and at atmospheric pressure were developed. The implementation of algorithms gives a predictive estimation of drying rate curves and bulk bed temperature during contact drying. The calculations are based on the penetration model to describe the drying process, where all process parameters such as heat and mass transfer coefficients, effective bed properties, gas and liquid phase properties are estimated with proper correlations. Simulation results were compared with experimental data from the literature. In both cases, simulation results were in good agreement with experimental data. Few deviations were identified and the limitations of the predictive capabilities of the models are discussed. The programs give a good insight of the drying behaviour of the analysed powders.

Keywords: Agitated bed, Atmospheric pressure, Penetrationmodel, Vacuum

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Authors: R. Alias, A. Kasa, M. R. Taha

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The effect of particle size on shear strength of granular materials are investigated using direct shear tests. Small direct shear test (60 mm by 60 mm by 24 mm deep) were conducted for particles passing the sieves with opening size of 2.36 mm. Meanwhile, particles passing the standard 20 mm sieves were tested using large direct shear test (300 mm by 300 mm by 200 mm deep). The large direct shear tests and the small direct shear tests carried out using the same shearing rate of 0.09 mm/min and similar normal stresses of 100, 200 and 300 kPa. The results show that the peak and residual shear strength increases as particle size increases.

Keywords: Particle size, shear strength, granular material, direct shear test.

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Authors: Haniza N., Md Khambari, M. N, Shahrin S., Adib M.Monzer Habbal, Suhaidi Hassan

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Wireless ad hoc nodes are freely and dynamically self-organize in communicating with others. Each node can act as host or router. However it actually depends on the capability of nodes in terms of its current power level, signal strength, number of hops, routing protocol, interference and others. In this research, a study was conducted to observe the effect of hops count over different network topologies that contribute to TCP Congestion Control performance degradation. To achieve this objective, a simulation using NS-2 with different topologies have been evaluated. The comparative analysis has been discussed based on standard observation metrics: throughput, delay and packet loss ratio. As a result, there is a relationship between types of topology and hops counts towards the performance of ad hoc network. In future, the extension study will be carried out to investigate the effect of different error rate and background traffic over same topologies.

Keywords: NS-2, network topology, network performance, multi-hops

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Authors: Nina Robson, Kenneth John Faller II, Vishalkumar Ahir, Arthur Ricardo Deps Miguel Ferreira, John Buchanan, Amarnath Banerjee

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This paper describes the development of a virtual-reality system ARWED, which will be used in physical rehabilitation of patients with reduced upper extremity mobility to increase limb Active Range of Motion (AROM). The ARWED system performs a symmetric reflection and real-time mapping of the patient’s healthy limb on to their most affected limb, tapping into the mirror neuron system and facilitating the initial learning phase. Using the ARWED, future experiments will test the extension of the action-observation priming effect linked to the mirror-neuron system on healthy subjects and then stroke patients.

Keywords: Physical rehabilitation, mirror neuron, virtual reality, stroke therapy.

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Authors: Ahsan Bin Tufail, Ali Abidi, Adil Masood Siddiqui, Muhammad Shahzad Younis

Abstract:

An early and accurate detection of Alzheimer's disease (AD) is an important stage in the treatment of individuals suffering from AD. We present an approach based on the use of structural magnetic resonance imaging (sMRI) phase images to distinguish between normal controls (NC), mild cognitive impairment (MCI) and AD patients with clinical dementia rating (CDR) of 1. Independent component analysis (ICA) technique is used for extracting useful features which form the inputs to the support vector machines (SVM), K nearest neighbour (kNN) and multilayer artificial neural network (ANN) classifiers to discriminate between the three classes. The obtained results are encouraging in terms of classification accuracy and effectively ascertain the usefulness of phase images for the classification of different stages of Alzheimer-s disease.

Keywords: Biomedical image processing, classification algorithms, feature extraction, statistical learning.

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Authors: Anas Majeed, A. A. Zaidan, B. B. Zaidan, Laiha Mat Kiah

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WIMAX relay station mesh network has been approved by IEEE 802.16j as a standard to provide a highly data rate transmission, the RS was implemented to extend the coverage zone of the BS, for instance the MSs previously were out of the coverage of the BS they become in the coverage of the RS, therefore these MSs can have Admission control from the BS through the RS. This paper describe a problem in the mesh network Relay station, for instance the problem of how to serve the mobile stations (MSs) which are out of the Relay station coverage. This paper also proposed a solution for mobile stations out of the coverage of the WIMAX Relay stations mesh Network. Therefore Ad-hoc network defined as a solution by using its admission control schema and apply it on the mobiles inside and outside the Relay station coverage.

Keywords: WIMAX, relay station, mesh network, ad-hoc, WiFi, generic algorithm.

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Authors: Slimane Ouhmad, Abdellah Halimi

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In this work, neural networks methods MLP type were applied to a database from an array of six sensors for the detection of three toxic gases. The choice of the number of hidden layers and the weight values are influential on the convergence of the learning algorithm. We proposed, in this article, a mathematical formula to determine the optimal number of hidden layers and good weight values based on the method of back propagation of errors. The results of this modeling have improved discrimination of these gases and optimized the computation time. The model presented here has proven to be an effective application for the fast identification of toxic gases.

Keywords: Back-propagation, Computing time, Fast identification, MLP neural network, Number of neurons in the hidden layer.

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