Search results for: Artificial neuronal networks

Authors: Muhammad Aqil, Ichiro Kita, Akira Yano, Nishiyama Soichi

Abstract:

This paper presents an alternate approach that uses artificial neural network to simulate the flood level dynamics in a river basin. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach and evolving graphical feature and can be adopted for any similar situation to predict the flood level. The main data processing includes the gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood level data, to train/test the model using various inputs and to visualize results. The program code consists of a set of files, which can as well be modified to match other purposes. This program may also serve as a tool for real-time flood monitoring and process control. The running results indicate that the decision support system applied to the flood level seems to have reached encouraging results for the river basin under examination. The comparison of the model predictions with the observed data was satisfactory, where the model is able to forecast the flood level up to 5 hours in advance with reasonable prediction accuracy. Finally, this program may also serve as a tool for real-time flood monitoring and process control.

Keywords: Decision Support System, Neural Network, Flood Level

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Authors: M. A. M. El-Bendary, H. Kazimian, A. E. Abo-El-azm, N. A. El-Fishawy, F. El-Samie, F. Shawki

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This paper studies a vital issue in wireless communications, which is the transmission of images over Wireless Personal Area Networks (WPANs) through the Bluetooth network. It presents a simple method to improve the efficiency of error control code of old Bluetooth versions over mobile WPANs through Interleaved Error Control Code (IECC) technique. The encoded packets are interleaved by simple block interleaver. Also, the paper presents a chaotic interleaving scheme as a tool against bursts of errors which depends on the chaotic Baker map. Also, the paper proposes using the chaotic interleaver instead of traditional block interleaver with Forward Error Control (FEC) scheme. A comparison study between the proposed and standard techniques for image transmission over a correlated fading channel is presented. Simulation results reveal the superiority of the proposed chaotic interleaving scheme to other schemes. Also, the superiority of FEC with proposed chaotic interleaver to the conventional interleavers with enhancing the security level with chaotic interleaving packetby- packet basis.

Keywords: Mobile Bluetooth terminals, WPANs, Jackes' model, Interleaving technique, chaotic interleaver

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Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

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Feature selection has been used in many fields such as classification, data mining and object recognition and proven to be effective for removing irrelevant and redundant features from the original dataset. In this paper, a new design of distributed intrusion detection system using a combination feature selection model based on bees and decision tree. Bees algorithm is used as the search strategy to find the optimal subset of features, whereas decision tree is used as a judgment for the selected features. Both the produced features and the generated rules are used by Decision Making Mobile Agent to decide whether there is an attack or not in the networks. Decision Making Mobile Agent will migrate through the networks, moving from node to another, if it found that there is an attack on one of the nodes, it then alerts the user through User Interface Agent or takes some action through Action Mobile Agent. The KDD Cup 99 dataset is used to test the effectiveness of the proposed system. The results show that even if only four features are used, the proposed system gives a better performance when it is compared with the obtained results using all 41 features.

Keywords: Distributed intrusion detection system, mobile agent, feature selection, Bees Algorithm, decision tree.

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Authors: O. S. Ebrahim, M. A. Badr, A. S. Elgendy, K. O. Shawky, P. K. Jain

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This paper demonstrates an improved Loss Model Control (LMC) for a 3-phase induction motor (IM) driving pump load. Compared with other power loss reduction algorithms for IM, the presented one has the advantages of fast and smooth flux adaptation, high accuracy, and versatile implementation. The performance of LMC depends mainly on the accuracy of modeling the motor drive and losses. A loss-model for IM drive that considers the surplus power loss caused by inverter voltage harmonics using closed-form equations and also includes the magnetic saturation has been developed. Further, an Artificial Neural Network (ANN) controller is synthesized and trained offline to determine the optimal flux level that achieves maximum drive efficiency. The drive’s voltage and speed control loops are connecting via the stator frequency to avoid the possibility of excessive magnetization. Besides, the resistance change due to temperature is considered by a first-order thermal model. The obtained thermal information enhances motor protection and control. These together have the potential of making the proposed algorithm reliable. Simulation and experimental studies are performed on 5.5 kW test motor using the proposed control method. The test results are provided and compared with the fixed flux operation to validate the effectiveness.

Keywords: Artificial neural network, ANN, efficiency optimization, induction motor, IM, Pulse Width Modulated, PWM, harmonic losses.

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Authors: Manoj Kumar, A.K. Verma, A. Srividya

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Time varying network induced delays in networked control systems (NCS) are known for degrading control system-s quality of performance (QoP) and causing stability problems. In literature, a control method employing modeling of communication delays as probability distribution, proves to be a better method. This paper focuses on modeling of network induced delays as probability distribution. CAN and MIL-STD-1553B are extensively used to carry periodic control and monitoring data in networked control systems. In literature, methods to estimate only the worst-case delays for these networks are available. In this paper probabilistic network delay model for CAN and MIL-STD-1553B networks are given. A systematic method to estimate values to model parameters from network parameters is given. A method to predict network delay in next cycle based on the present network delay is presented. Effect of active network redundancy and redundancy at node level on network delay and system response-time is also analyzed.

Keywords: NCS (networked control system), delay analysis, response-time distribution, worst-case delay, CAN, MIL-STD-1553B, redundancy

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Authors: Tripatjot S. Panag, J. S. Dhillon

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The lifetime of a wireless sensor network can be effectively increased by using scheduling operations. Once the sensors are randomly deployed, the task at hand is to find the largest number of disjoint sets of sensors such that every sensor set provides complete coverage of the target area. At any instant, only one of these disjoint sets is switched on, while all other are switched off. This paper proposes a heuristic search method to find the maximum number of disjoint sets that completely cover the region. A population of randomly initialized members is made to explore the solution space. A set of heuristics has been applied to guide the members to a possible solution in their neighborhood. The heuristics escalate the convergence of the algorithm. The best solution explored by the population is recorded and is continuously updated. The proposed algorithm has been tested for applications which require sensing of multiple target points, referred to as point coverage applications. Results show that the proposed algorithm outclasses the existing algorithms. It always finds the optimum solution, and that too by making fewer number of fitness function evaluations than the existing approaches.

Keywords: Coverage, disjoint sets, heuristic, lifetime, scheduling, wireless sensor networks, WSN.

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Authors: Javier Barbaran, Manuel Dıaz, Inaki Esteve, Bartolome Rubio

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Wireless Sensor Networks (WSNs) have attracted the attention of many researchers. This has resulted in their rapid integration in very different areas such as precision agriculture,environmental monitoring, object and event detection and military surveillance. Due to the current WSN characteristics this technology is specifically useful in industrial areas where security, reliability and autonomy are basic, such as nuclear power plants, chemical plants, and others. In this paper we present a system based on WSNs to monitor environmental conditions around and inside a nuclear power plant, specifically, radiation levels. Sensor nodes, equipped with radiation sensors, are deployed in fixed positions throughout the plant. In addition, plant staff are also equipped with mobile devices with higher capabilities than sensors such as for example PDAs able to monitor radiation levels and other conditions around them. The system enables communication between PDAs, which form a Mobile Ad-hoc Wireless Network (MANET), and allows workers to monitor remote conditions in the plant. It is particularly useful during stoppage periods for inspection or in the event of an accident to prevent risk situations.

Keywords: MANETs, Mobile computing, Radiation monitoring, Wireless Sensor Networks.

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Authors: Abdallah Al Sabbagh

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Next Generation Wireless Network (NGWN) is expected to be a heterogeneous network which integrates all different Radio Access Technologies (RATs) through a common platform. A major challenge is how to allocate users to the most suitable RAT for them. An optimized solution can lead to maximize the efficient use of radio resources, achieve better performance for service providers and provide Quality of Service (QoS) with low costs to users. Currently, Radio Resource Management (RRM) is implemented efficiently for the RAT that it was developed. However, it is not suitable for a heterogeneous network. Common RRM (CRRM) was proposed to manage radio resource utilization in the heterogeneous network. This paper presents a user level Markov model for a three co-located RAT networks. The load-balancing based and service based CRRM algorithms have been studied using the presented Markov model. A comparison for the performance of load-balancing based and service based CRRM algorithms is studied in terms of traffic distribution, new call blocking probability, vertical handover (VHO) call dropping probability and throughput.

Keywords: Heterogeneous Wireless Network, Markov chain model, load-balancing based and service based algorithm, CRRM algorithms, Beyond 3G network.

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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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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: Structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm.

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Authors: N. Muthukumaran, R. Ravi

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The Quad Tree Decomposition based performance analysis of compressed image data communication for lossy and lossless through wireless sensor network is presented. Images have considerably higher storage requirement than text. While transmitting a multimedia content there is chance of the packets being dropped due to noise and interference. At the receiver end the packets that carry valuable information might be damaged or lost due to noise, interference and congestion. In order to avoid the valuable information from being dropped various retransmission schemes have been proposed. In this proposed scheme QTD is used. QTD is an image segmentation method that divides the image into homogeneous areas. In this proposed scheme involves analysis of parameters such as compression ratio, peak signal to noise ratio, mean square error, bits per pixel in compressed image and analysis of difficulties during data packet communication in Wireless Sensor Networks. By considering the above, this paper is to use the QTD to improve the compression ratio as well as visual quality and the algorithm in MATLAB 7.1 and NS2 Simulator software tool.

Keywords: Image compression, Compression Ratio, Quad tree decomposition, Wireless sensor networks, NS2 simulator.

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Authors: Andhe Dharani, P. S. Satyanarayana, Andhe Pallavi

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Considering payload, reliability, security and operational lifetime as major constraints in transmission of images we put forward in this paper a steganographic technique implemented at the physical layer. We suggest transmission of Halftoned images (payload constraint) in wireless sensor networks to reduce the amount of transmitted data. For low power and interference limited applications Turbo codes provide suitable reliability. Ensuring security is one of the highest priorities in many sensor networks. The Turbo Code structure apart from providing forward error correction can be utilized to provide for encryption. We first consider the Halftoned image and then the method of embedding a block of data (called secret) in this Halftoned image during the turbo encoding process is presented. The small modifications required at the turbo decoder end to extract the embedded data are presented next. The implementation complexity and the degradation of the BER (bit error rate) in the Turbo based stego system are analyzed. Using some of the entropy based crypt analytic techniques we show that the strength of our Turbo based stego system approaches that found in the OTPs (one time pad).

Keywords: Halftoning, Turbo codes, security, operationallifetime, Turbo based stego system.

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Authors: F. F. Howard, I. Yakubu, C. B. Boye, J. S. Y. Kuma

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Natural and human activities, such as mining operations, expose the natural soil to adverse environmental conditions, leading to contamination of soil, groundwater, and surface water, which has negative effects on humans, flora, and fauna. Bare or partly exposed soil is most liable to fluvial erosion. This paper enumerates various methods used to identify, map, and model fluvial erosion in a mining environment. Classical, Artificial Intelligence (AI), and GIS methods have been reviewed. One of the many classical methods used to estimate river erosion is the Revised Universal Soil Loss Equation (RUSLE) model. The RUSLE model is easy to use. Its reliance on empirical relationships that may not always be applicable to specific circumstances or locations is a flaw. Other classical models for estimating fluvial erosion are the Soil and Water Assessment Tool (SWAT) and the Universal Soil Loss Equation (USLE). These models offer a more complete understanding of the underlying physical processes and encompass a wider range of situations. Although more difficult to utilise, they depend on the availability and dependability of input data for correctness. AI can help deal with multivariate and complex difficulties and predict soil loss with higher accuracy than traditional methods, and also be used to build unique models for identifying degraded areas. AI techniques have become popular as an alternative predictor for degraded environments. However, this research proposed a hybrid of classical, AI, and GIS methods for efficient and effective modelling of fluvial erosion.

Keywords: Fluvial erosion, classical methods, Artificial Intelligence, Geographic Information System.

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Authors: M. Geetha Priya, K. Baskaran, S. Srinivasan

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Digital systems are said to be constructed using basic logic gates. These gates are the NOR, NAND, AND, OR, EXOR & EXNOR gates. This paper presents a robust three transistors (3T) based NAND and NOR gates with precise output logic levels, yet maintaining equivalent performance than the existing logic structures. This new set of 3T logic gates are based on CMOS inverter and Pass Transistor Logic (PTL). The new universal logic gates are characterized by better speed and lower power dissipation which can be straightforwardly fabricated as memory ICs for high performance computer networks. The simulation tests were performed using standard BPTM 22nm process technology using SYNOPSYS HSPICE. The 3T NAND gate is evaluated using C17 benchmark circuit and 3T NOR is gate evaluated using a D-Latch. According to HSPICE simulation in 22 nm CMOS BPTM process technology under given conditions and at room temperature, the proposed 3T gates shows an improvement of 88% less power consumption on an average over conventional CMOS logic gates. The devices designed with 3T gates will make longer battery life by ensuring extremely low power consumption.

Keywords: Low power, CMOS, pass-transistor, flash memory, logic gates.

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Authors: T. N. Janakiraman, J. Janet Lourds Rani

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In practice, wireless networks has the property that the signal strength attenuates with respect to the distance from the base station, it could be better if the nodes at two hop away are considered for better quality of service. In this paper, we propose a procedure to identify delay preserving substructures for a given wireless ad-hoc network using a new graph operation G 2 – E (G) = G* (Edge difference of square graph of a given graph and the original graph). This operation helps to analyze some induced substructures, which preserve delay in communication among them. This operation G* on a given graph will induce a graph, in which 1- hop neighbors of any node are at 2-hop distance in the original network. In this paper, we also identify some delay preserving substructures in G*, which are (i) set of all nodes, which are mutually at 2-hop distance in G that will form a clique in G*, (ii) set of nodes which forms an odd cycle C2k+1 in G, will form an odd cycle in G* and the set of nodes which form a even cycle C2k in G that will form two disjoint companion cycles ( of same parity odd/even) of length k in G*, (iii) every path of length 2k+1 or 2k in G will induce two disjoint paths of length k in G*, and (iv) set of nodes in G*, which induces a maximal connected sub graph with radius 1 (which identifies a substructure with radius equal 2 and diameter at most 4 in G). The above delay preserving sub structures will behave as good clusters in the original network.

Keywords: Clique, cycles, delay preserving substructures, maximal connected sub graph.

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Authors: Somenath Mukherjee, Rajdeep Ray, Raj Kumar Samanta, Mofazzal H. Khondekar, Gautam Sanyal

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In next generation wireless networks (i.e., 4G and beyond), one of the main objectives is to ensure highest level of customer satisfaction in terms of data transfer speed, decrease in cost and delay, non-rejection and no drop of calls, availability of ‘always-on’ connectivity and services, continuity of connected services, hastle-free roaming in addition to the convenience of use of network services from anywhere and anytime. To take care of these requirements effectively, internet service providers (ISPs) and network planners have to go for major capacity enhancement of network resources and at the same time these resources are to be used effectively and efficiently to reduce cost and to increase revenue. In this work, the effective bandwidth available in a Mobile Switching Center (MSC) of a wireless network providing multi-class multimedia services is analyzed. Bandwidth requirement of the users for a customized Quality of Service (QoS) is estimated. The findings of the QoS estimation are applied for the capacity planning and admission control of the multi-class traffic flows coming into the MSC.

Keywords: Next generation wireless network, mobile switching center, multi-class traffic, quality of service, admission control, effective bandwidth.

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Authors: Tan Soo Fun, Leau Yu Beng, Rozaini Roslan, Habeeb Saleh Habeeb

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The increasing development of wireless networks and the widespread popularity of handheld devices such as Personal Digital Assistants (PDAs), mobile phones and wireless tablets represents an incredible opportunity to enable mobile devices as a universal payment method, involving daily financial transactions. Unfortunately, some issues hampering the widespread acceptance of mobile payment such as accountability properties, privacy protection, limitation of wireless network and mobile device. Recently, many public-key cryptography based mobile payment protocol have been proposed. However, limited capabilities of mobile devices and wireless networks make these protocols are unsuitable for mobile network. Moreover, these protocols were designed to preserve traditional flow of payment data, which is vulnerable to attack and increase the user-s risk. In this paper, we propose a private mobile payment protocol which based on client centric model and by employing symmetric key operations. The proposed mobile payment protocol not only minimizes the computational operations and communication passes between the engaging parties, but also achieves a completely privacy protection for the payer. The future work will concentrate on improving the verification solution to support mobile user authentication and authorization for mobile payment transactions.

Keywords: Mobile Network Operator, Mobile payment protocol, Privacy, Symmetric key.

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Authors: F. Rahnamay Roodposhti, M. Falah Shams, H. Kordlouie

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The aim of the article is extending and developing econometrics and network structure based methods which are able to distinguish price manipulation in Tehran stock exchange. The principal goal of the present study is to offer model for approximating price manipulation in Tehran stock exchange. In order to do so by applying separation method a sample consisting of 397 companies accepted at Tehran stock exchange were selected and information related to their price and volume of trades during years 2001 until 2009 were collected and then through performing runs test, skewness test and duration correlative test the selected companies were divided into 2 sets of manipulated and non manipulated companies. In the next stage by investigating cumulative return process and volume of trades in manipulated companies, the date of starting price manipulation was specified and in this way the logit model, artificial neural network, multiple discriminant analysis and by using information related to size of company, clarity of information, ratio of P/E and liquidity of stock one year prior price manipulation; a model for forecasting price manipulation of stocks of companies present in Tehran stock exchange were designed. At the end the power of forecasting models were studied by using data of test set. Whereas the power of forecasting logit model for test set was 92.1%, for artificial neural network was 94.1% and multi audit analysis model was 90.2%; therefore all of the 3 aforesaid models has high power to forecast price manipulation and there is no considerable difference among forecasting power of these 3 models.

Keywords: Price Manipulation, Liquidity, Size of Company, Floating Stock, Information Clarity

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Authors: Arash Taheri, Meysam Mohammadi-Amin, Seyed Hossein Moosavy

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Medical applications are among the most impactful areas of microrobotics. The ultimate goal of medical microrobots is to reach currently inaccessible areas of the human body and carry out a host of complex operations such as minimally invasive surgery (MIS), highly localized drug delivery, and screening for diseases at their very early stages. Miniature, safe and efficient propulsion systems hold the key to maturing this technology but they pose significant challenges. A new type of propulsion developed recently, uses multi-flagella architecture inspired by the motility mechanism of prokaryotic microorganisms. There is a lack of efficient methods for designing this type of propulsion system. The goal of this paper is to overcome the lack and this way, a numerical strategy is proposed to design multi-flagella propulsion systems. The strategy is based on the implementation of the regularized stokeslet and rotlet theory, RFT theory and new approach of “local corrected velocity". The effects of shape parameters and angular velocities of each flagellum on overall flow field and on the robot net forces and moments are considered. Then a multi-layer perceptron artificial neural network is designed and employed to adjust the angular velocities of the motors for propulsion control. The proposed method applied successfully on a sample configuration and useful demonstrative results is obtained.

Keywords: Artificial Neural Network, Biomimetic Microrobots, Flagellar Propulsion, Swimming Robots.

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Authors: Awatef Chniguir, Tarek Farah, Zouhair Ben Jemaa, Safya Belguith

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Optimal routing allows minimizing energy consumption in wireless sensor networks (WSN). Clustering has proven its effectiveness in organizing WSN by reducing channel contention and packet collision and enhancing network throughput under heavy load. Therefore, nowadays, with the emergence of the Internet of Things, heterogeneity is essential. Stable election protocol (SEP) that has increased the network stability period and lifetime is the first clustering protocol for heterogeneous WSN. SEP and its descendants, namely SEP, Threshold Sensitive SEP (TSEP), Enhanced TSEP (ETSSEP) and Current Energy Allotted TSEP (CEATSEP), were studied. These algorithms’ performance was evaluated based on different metrics, especially first node death (FND), to compare their stability. Simulations were conducted on the MATLAB tool considering two scenarios: The first one demonstrates the fraction variation of advanced nodes by setting the number of total nodes. The second considers the interpretation of the number of nodes while keeping the number of advanced nodes permanent. CEATSEP outperforms its antecedents by increasing stability and, at the same time, keeping a low throughput. It also operates very well in a large-scale network. Consequently, CEATSEP has a useful lifespan and energy efficiency compared to the other routing protocol for heterogeneous WSN.

Keywords: Clustering, heterogeneous, stability, scalability, throughput, IoT, WSN.

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Authors: Poramet Saeng-On

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This research aims to develop ways of lodging business management of Bang Khonthi community in Samut Songkram province that are appropriate with the cultural context of the Bang Khonthi community. Eight lodging business owners were interviewed. It was found that lodging business that are family business must be done with passion, correct understanding of self, culture, nature, Thai way of life, thorough, professional development, environmentally concerned, building partnerships with various networks both community level, and public sector and business cohorts. Public relations should be done through media both traditional and modern outlets, such as websites and social networks to provide customers convenience, security, happiness, knowledge, love and value when travel to Bang Khonthi. This will also help them achieve sustainability in business, in line with the 10 Home Stay Standard Thailand. Suggestions for operators are as follows: Operators need to improve their public relations work. They need to use technology in public relations such as the internet. Management standards must be improved. Souvenir and local products shops should be arranged in the compound. Product pricing must be set accordingly. They need to join hands to help each other. Quality of the business operation should be raised to meet the standards. Educational measures to reduce the impact caused by tourism on the community such as efforts to reduce energy consumption.

Keywords: Homestay, lodging business, management, standard.

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Authors: Olusola Olalekan Elekofehinti, Isaac Gbadura Adanlawo, Joao Batista Teixeira Rocha

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The potential neuroprotective effect of Phyllantus nuriri against Fe2+ and sodium nitroprusside (SNP) induced oxidative stress in mitochondria of rats brain was evaluated. Cellular viability was assessed by MTT reduction, reactive oxygen species (ROS) generation was measured using the probe 2,7-dichlorofluoresce indiacetate (DCFH-DA). Glutathione content was measured using dithionitrobenzoic acid (DTNB). Fe2+ (10μM) and SNP (5μM) significantly decreased mitochondrial activity, assessed by MTT reduction assay, in a dose-dependent manner, this occurred in parallel with increased glutathione oxidation, ROS production and lipid peroxidation end-products (thiobarbituric acid reactive substances, TBARS). The co-incubation with methanolic extract of Phyllantus nuriri (10-200 μg/ml) reduced the disruption of mitochondrial activity, gluthathione oxidation, ROS production as well as the increase in TBARS levels caused by both Fe2+ and SNP in a dose dependent manner. HPLC analysis of the extract revealed the presence of gallic acid (20.540.01), caffeic acid (7.930.02), rutin (25.310.05), quercetin (31.280.03) and kaemferol (14.360.01). This result suggests that these phytochemicals account for the protective actions of P. niruri against Fe2+ and SNP -induced oxidative stress. Our results show that P. nuriri consist important bioactive molecules in the search for an improved therapy against the deleterious effects of Fe2+, an intrinsic producer of reactive oxygen species (ROS), that leads to neuronal oxidative stress and neurodegeneration.

Keywords: Phyllantus niruri, mitochondria, antioxidant, oxidative stress, synaptosome.

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Authors: Anupama Pande, Ashok Kumar Thakur, Swapnoneel Roy

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A complex valued neural network is a neural network which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in signal processing. In Neural networks, generalized mean neuron model (GMN) is often discussed and studied. The GMN includes a new aggregation function based on the concept of generalized mean of all the inputs to the neuron. This paper aims to present exhaustive results of using Generalized Mean Neuron model in a complex-valued neural network model that uses the back-propagation algorithm (called -Complex-BP-) for learning. Our experiments results demonstrate the effectiveness of a Generalized Mean Neuron Model in a complex plane for signal processing over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error required on a Generalized Mean neural network model. Some inherent properties of this complex back propagation algorithm are also studied and discussed.

Keywords: Complex valued neural network, Generalized Meanneuron model, Signal processing.

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Authors: J. Barbarán, M. Díaz, I. Esteve, D. Garrido, L. Llopis, B. Rubio

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Wireless Sensor and Actor Networks (WSANs) constitute an emerging and pervasive technology that is attracting increasing interest in the research community for a wide range of applications. WSANs have two important requirements: coordination interactions and real-time communication to perform correct and timely actions. This paper introduces a methodology to facilitate the task of the application programmer focusing on the coordination and real-time requirements of WSANs. The methodology proposed in this model uses a real-time component model, UM-RTCOM, which will help us to achieve the design and implementation of applications in WSAN by using the component oriented paradigm. This will help us to develop software components which offer some very interesting features, such as reusability and adaptability which are very suitable for WSANs as they are very dynamic environments with rapidly changing conditions. In addition, a high-level coordination model based on tuple channels (TC-WSAN) is integrated into the methodology by providing a component-based specification of this model in UM-RTCOM; this will allow us to satisfy both sensor-actor and actor-actor coordination requirements in WSANs. Finally, we present in this paper the design and implementation of an application which will help us to show how the methodology can be easily used in order to achieve the development of WSANs applications.

Keywords: Sensor networks, real time and embedded systems.

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Authors: S. Areerachakul, N. Ployong, S. Na Songkla

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This research’s objective is to select the model with most accurate value by using Neural Network Technique as a way to filter potential students who enroll in IT course by Electronic learning at Suan Suanadha Rajabhat University. It is designed to help students selecting the appropriate courses by themselves. The result showed that the most accurate model was 100 Folds Cross-validation which had 73.58% points of accuracy.

Keywords: Artificial neural network, classification, students.

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

Abstract:

Electrical energy demands have increased due to population growth and the variety of new electrical load technologies. This increase demand has nearly doubled during peak hours. Consequently, that necessitates the construction of new power plant infrastructures, which is a costly approach due to the expense of construction building, future preservation like maintenance, and environmental impact. As an alternative approach, most electrical utilities increase the price of electrical usage during peak hours, encouraging consumers to use less electricity during peak periods under Time-Of-Use programs, which may not be universally suitable for all consumers. Furthermore, in some areas, the excessive demand and the lack of supply cause an electrical outage, posing considerable stress and challenges to electrical utilities and consumers. However, control systems, artificial intelligence (AI), and renewable energy (RE), when effectively integrated, provide new solutions to mitigate excessive demand during peak hours. This paper presents a power model that reduces the reliance on the power grid during peak hours by utilizing a hybrid solar system connected to a residential house with a power management controller, that prioritizes the power drives between Photovoltaic (PV) production, battery backup, and the utility electrical grid. As a result, dependence on utility grid was from 3% to 18% during peak hours, improving energy stability safely and efficiently for electrical utilities, consumers, and communities, providing a viable alternative to conventional approaches such as Time-Of-Use programs.

Keywords: Artificial intelligence, AI, control system, photovoltaic, PV, renewable energy.

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Authors: Jihad S. Daba, J. P. Dubois, Yvette Antar

Abstract:

With the exponential growth of cellular users, a new generation of cellular networks is needed to enhance the required peak data rates. The co-channel interference between neighboring base stations inhibits peak data rate increase. To overcome this interference, multi-cell cooperation known as coordinated multipoint transmission is proposed. Such a solution makes use of multiple-input-multiple-output (MIMO) systems under two different structures: Micro- and macro-diversity. In this paper, we study the capacity and bit error rate in cellular networks using MIMO technology. We analyse both micro- and macro-diversity schemes and develop a hybrid model that switches between macro- and micro-diversity in the case of hard handoff based on a cut-off range of signal-to-noise ratio values. We conclude that our hybrid switched micro-macro MIMO system outperforms classical MIMO systems at the cost of increased hardware and software complexity.

Keywords: Cooperative multipoint transmission, ergodic capacity, hard handoff, macro-diversity, micro-diversity, multiple-input-multiple-output systems, MIMO, orthogonal frequency division multiplexing, OFDM.

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Authors: Prakash G L, Chaitra K Meti, Poojitha K, Divya R.K.

Abstract:

Wireless Sensor Network is Multi hop Self-configuring Wireless Network consisting of sensor nodes. The deployment of wireless sensor networks in many application areas, e.g., aggregation services, requires self-organization of the network nodes into clusters. Efficient way to enhance the lifetime of the system is to partition the network into distinct clusters with a high energy node as cluster head. The different methods of node clustering techniques have appeared in the literature, and roughly fall into two families; those based on the construction of a dominating set and those which are based solely on energy considerations. Energy optimized cluster formation for a set of randomly scattered wireless sensors is presented. Sensors within a cluster are expected to be communicating with cluster head only. The energy constraint and limited computing resources of the sensor nodes present the major challenges in gathering the data. In this paper we propose a framework to study how partially correlated data affect the performance of clustering algorithms. The total energy consumption and network lifetime can be analyzed by combining random geometry techniques and rate distortion theory. We also present the relation between compression distortion and data correlation.

Keywords: Clusters, multi hop, random geometry, rate distortion.

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Authors: A. M. Pashayev, D. D. Askerov, C. Ardil, R. A. Sadiqov, P. S. Abdullayev

Abstract:

Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.

Keywords: aviation gas turbine engine, technical condition, fuzzy logic, neural networks, fuzzy statistics

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Authors: Mohd Fairuz Iskandar Othman, Nazrulazhar Bahaman, Zulkiflee Muslim, Faizal Abdollah

Abstract:

This paper discusses a curriculum approach that will give emphasis on practical portions of teaching network security subjects in information and communication technology courses. As we are well aware, the need to use a practice and application oriented approach in education is paramount. Research on active learning and cooperative groups have shown that students grasps more and have more tendency towards obtaining and realizing soft skills like leadership, communication and team work as opposed to the more traditional theory and exam based teaching and learning. While this teaching and learning paradigm is relatively new in Malaysia, it has been practiced widely in the West. This paper examines a certain approach whereby students learning wireless security are divided into and work in small and manageable groups where there will be 2 teams which consist of black hat and white hat teams. The former will try to find and expose vulnerabilities in a wireless network while the latter will try their best to prevent such attacks on their wireless networks using hardware, software, design and enforcement of security policy and etc. This paper will try to show that the approach taken plus the use of relevant and up to date software and hardware and with suitable environment setting will hopefully expose students to a more fruitful outcome in terms of understanding of concepts, theories and their motivation to learn.

Keywords: Curriculum approach, wireless networks, wirelesssecurity.

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