Search results for: Heat Exchange Network and Techno-Economic Analysis.

Authors: H. Gorine, M. Ramadan Elmezughi

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In this paper, we investigate security issues and challenges facing researchers in wireless sensor networks and countermeasures to resolve them. The broadcast nature of wireless communication makes Wireless Sensor Networks prone to various attacks. Due to resources limitation constraint in terms of limited energy, computation power and memory, security in wireless sensor networks creates different challenges than wired network security. We will discuss several attempts at addressing the issues of security in wireless sensor networks in an attempt to encourage more research into this area.

Keywords: Malicious nodes, network security, soft encryption, threats, wireless sensor networks.

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Authors: Jian-Jun Shu

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A cold, thin film of liquid impinging on an isothermal hot, horizontal surface has been investigated. An approximate solution for the velocity and temperature distributions in the flow along the horizontal surface is developed, which exploits the hydrodynamic similarity solution for thin film flow. The approximate solution may provide a valuable basis for assessing flow and heat transfer in more complex settings.

Keywords: Flux, free impinging jet, solid-surface, uniform wall temperature.

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Authors: S. M. Anowarul Haque, Md. Asiful Islam

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Electrical load forecasting is considered to be one of the most indispensable parts of a modern-day electrical power system. To ensure a reliable and efficient supply of electric energy, special emphasis should have been put on the predictive feature of electricity supply. Artificial Neural Network-based approaches have emerged to be a significant area of interest for electric load forecasting research. This paper proposed an Artificial Neural Network model based on the particle swarm optimization algorithm for improved electric load forecasting for Mymensingh, Bangladesh. The forecasting model is developed and simulated on the MATLAB environment with a large number of training datasets. The model is trained based on eight input parameters including historical load and weather data. The predicted load data are then compared with an available dataset for validation. The proposed neural network model is proved to be more reliable in terms of day-wise load forecasting for Mymensingh, Bangladesh.

Keywords: Load forecasting, artificial neural network, particle swarm optimization.

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Authors: Farshid Fathinia, Mohammad Parsazadeh, Amirhossein Heshmati

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Turbulent forced convection flow in a 2-dimensional channel over periodic grooves is numerically investigated. Finite volume method is used to study the effect of turbulence model. The range of Reynolds number varied from 10000 to 30000 for the ribheight to channel-height ratio (B/H) of 2. The downstream wall is heated by a uniform heat flux while the upstream wall is insulated. The investigation is analyzed with different types of nanoparticles such as SiO2, Al2O3, and ZnO, with water as a base fluid are used. The volume fraction is varied from 1% to 4% and the nanoparticle diameter is utilized between 20nm to 50nm. The results revealed 114% heat transfer enhancement compared to the water in a grooved channel by using SiO2 nanoparticle with volume fraction and nanoparticle diameter of 4% and 20nm respectively.

Keywords: Forced convection, Periodic grooves, Nanofluids, Turbulent model, Heat transfer.

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Authors: István Patkó, Hosam Bayoumi Hamuda, András Medve, András Szeder

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In order to efficiently solve the problems created by the deepening energy crisis affecting Europe and the world, governments cannot neglect the opportunities of using the energy produced by sun collectors. In many of the EU countries there are sun collectors producing heat energy, e.g. in 2011 in the area of EU27 (countries which belong to European Union) + Switzerland altogether 37519126 m2 were operated, which are capable of producing 26.3 GWh heat energy. The energy produced by these sun collectors is utilized at the place of production. In the near future governments will have to focus more on spreading and using sun collectors. Among the complex problems of operating sun collectors, this article deals with determining the optimal tilt angle, directions of sun collectors. We evaluate the contamination of glass surface of sun collector to the produced energy. Our theoretically results are confirmed by laboratory measurements. The purpose of our work is to help users and engineers in determination of optimal operation parameters of sun collectors.

Keywords: Heat energy, tilt angle, direction of sun collector, contamination of surface.

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

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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: Manivannan A, Velmurugan M

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Solar air heater is a type of heat exchanger which transforms solar radiation into heat energy. The thermal performance of conventional solar air heater has been found to be poor because of the low convective heat transfer coefficient from the absorber plate to the air. It is attributed to the formation of a very thin boundary layer at the absorber plate surface commonly known as viscous sub-layer. Thermal efficiency of solar air heater can be improved by providing the artificial roughness on absorber plate is the most efficient technique. In this paper an attempt is made to provide artificial roughness by incorporating inclined multiple V-ribs in the underside of the absorber plate. 60˚V – ribs are arranged inclined to the direction of air flow. Performance of collector estimated theoretically and experimentally. Results of the investigation reveal that thermal efficiency of collector with multiple V-ribs increased by 14%.

Keywords: Artificial roughness, inclined multiple V-ribs, performance, Solar air collector.

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Authors: L. Marcos Domínguez, Nils Rage, Ongun B. Kazanci, Bjarne W. Olesen

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Thermally Activated Building Systems (TABS) have proven to be an energy-efficient solution to provide buildings with an optimal indoor thermal environment. This solution uses the structure of the building to store heat, reduce the peak loads, and decrease the primary energy demand. TABS require the heated or cooled surfaces to be as exposed as possible to the indoor space, but exposing the bare concrete surfaces has a diminishing effect on the acoustic qualities of the spaces in a building. Acoustic solutions capable of providing optimal acoustic comfort and allowing the heat exchange between the TABS and the room are desirable. In this study, the effects of free-hanging units on the cooling performance of TABS and the occupants’ thermal comfort was measured in a full-scale TABS laboratory. Investigations demonstrate that the use of free-hanging sound absorbers are compatible with the performance of TABS and the occupant’s thermal comfort, but an appropriate acoustic design is needed to find the most suitable solution for each case. The results show a reduction of 11% of the cooling performance of the TABS when 43% of the ceiling area is covered with free-hanging horizontal sound absorbers, of 23% for 60% ceiling coverage ratio and of 36% for 80% coverage. Measurements in actual buildings showed an increase of the room operative temperature of 0.3 K when 50% of the ceiling surface is covered with horizontal panels and of 0.8 to 1 K for a 70% coverage ratio. According to numerical simulations using a new TRNSYS Type, the use of comfort ventilation has a considerable influence on the thermal conditions in the room; if the ventilation is removed, then the operative temperature increases by 1.8 K for a 60%-covered ceiling.

Keywords: Acoustic comfort, concrete core activation, full-scale measurements, thermally activated building systems, TRNSYS.

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Authors: Insung Jung, lockjo Koo, Gi-Nam Wang

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The objective of this paper is to design a model of human vital sign prediction for decreasing prediction error by using two states mapping based time series neural network BP (back-propagation) model. Normally, lot of industries has been applying the neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has a residual error between real value and prediction output. Therefore, we designed two states of neural network model for compensation of residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We found that most of simulations cases were satisfied by the two states mapping based time series prediction model compared to normal BP. In particular, small sample size of times series were more accurate than the standard MLP model. We expect that this algorithm can be available to sudden death prevention and monitoring AGENT system in a ubiquitous homecare environment.

Keywords: Neural network, U-healthcare, prediction, timeseries, computer aided prediction.

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Authors: Peter Krupa, Svetozár Malinarič

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Transient plane source method has been used to measure the thermal diffusivity and thermal conductivity of a compact isostatic electroceramics at room temperature. The samples were fired at temperatures from 100 up to 1320 degrees Celsius in steps of 50. Bulk density and specific heat capacity were also measured with their corresponding standard uncertainties. The results were compared with further thermal analysis (dilatometry and thermogravimetry). Structural processes during firing were discussed.

Keywords: TPS method, thermal conductivity, thermal diffusivity, thermal analysis, electroceramics, firing.

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Authors: Abdullah I. Alkraiji, Thomas W. Jackson, Ian R. Murray

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The proliferation of health data standards today is somewhat overlapping and conflicting, resulting in market confusion and leading to increasing proprietary interests. The government role and support in standardization for health data are thought to be crucial in order to establish credible standards for the next decade, to maximize interoperability across the health sector, and to decrease the risks associated with the implementation of non-standard systems. The normative literature missed out the exploration of the different steps required to be undertaken by the government towards the development of national health data standards. Based on the lessons learned from a qualitative study investigating the different issues to the adoption of health data standards in the major tertiary hospitals in Saudi Arabia and the opinions and feedback from different experts in the areas of data exchange and standards and medical informatics in Saudi Arabia and UK, a list of steps required towards the development of national health data standards was constructed. Main steps are the existence of: a national formal reference for health data standards, an agreed national strategic direction for medical data exchange, a national medical information management plan and a national accreditation body, and more important is the change management at the national and organizational level. The outcome of this study can be used by academics and practitioners to develop the planning of health data standards, and in particular those in developing countries.

Keywords: Interoperability, Case Study, Health Data Standards, Medical Data Exchange, Saudi Arabia.

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Authors: Ravichandra R., Srithar Rajoo, Tan Lit Wen

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In recent years Li-Ion batteries getting more attention among the Electrical Vehicles (EV) and Hybrid Electrical Vehicles (HEV) energy storage. Li-Ion has shown extended power density and light weight compared to other batteries readily available in the market. One of the major drawbacks in Li-Ion batteries is their sensitivity to the temperature. If the working temperature is beyond the limit, that could affect seriously on the durability and performance of Li-Ion battery. Thus Battery Thermal Management (BTM) is the most essential in adapting Li-Ion battery to the EVs and HEVs.

Keywords: Li-Ion battery, HEV/EV, battery thermal management, heat generation rate.

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Authors: Yi Yu, Lin Ma, Yong Sun, Yuantong Gu

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This paper presents a novel method for remaining useful life prediction using the Elliptical Basis Function (EBF) network and a Markov chain. The EBF structure is trained by a modified Expectation-Maximization (EM) algorithm in order to take into account the missing covariate set. No explicit extrapolation is needed for internal covariates while a Markov chain is constructed to represent the evolution of external covariates in the study. The estimated external and the unknown internal covariates constitute an incomplete covariate set which are then used and analyzed by the EBF network to provide survival information of the asset. It is shown in the case study that the method slightly underestimates the remaining useful life of an asset which is a desirable result for early maintenance decision and resource planning.

Keywords: Elliptical Basis Function Network, Markov Chain, Missing Covariates, Remaining Useful Life

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Authors: Ashok Kumar, Narottam Chand, Vinod Kumar

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Due to the limited energy resources, energy efficient operation of sensor node is a key issue in wireless sensor networks. Clustering is an effective method to prolong the lifetime of energy constrained wireless sensor network. However, clustering in wireless sensor network faces several challenges such as selection of an optimal group of sensor nodes as cluster, optimum selection of cluster head, energy balanced optimal strategy for rotating the role of cluster head in a cluster, maintaining intra and inter cluster connectivity and optimal data routing in the network. In this paper, we propose a protocol supporting an energy efficient clustering, cluster head selection/rotation and data routing method to prolong the lifetime of sensor network. Simulation results demonstrate that the proposed protocol prolongs network lifetime due to the use of efficient clustering, cluster head selection/rotation and data routing.

Keywords: Wireless sensor networks, clustering, energy efficient, localization.

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Authors: Karamitsos Ioannis, Orfanidis Konstantinos

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In this paper an analysis of blackouts in electric power transmission systems is implemented using a model and studied in simple networks with a regular topology. The proposed model describes load demand and network improvements evolving on a slow timescale as well as the fast dynamics of cascading overloads and outages.

Keywords: Blackout, Generator, Load, Power Load.

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

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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: Thomas V. Prevenslik

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Ovshinsky initiated scientific research in the field of amorphous and disordered materials that continues to this day. The Ovshinsky Effect where the resistance of thin GST films is significantly reduced upon the application of low voltage is of fundamental importance in phase-change - random access memory (PC-RAM) devices.GST stands for GdSbTe chalcogenide type glasses.However, the Ovshinsky Effect is not without controversy. Ovshinsky thought the resistance of GST films is reduced by the redistribution of charge carriers; whereas, others at that time including many PC-RAM researchers today argue that the GST resistance changes because the GST amorphous state is transformed to the crystalline state by melting, the heat supplied by external heaters. In this controversy, quantum mechanics (QM) asserts the heat capacity of GST films vanishes, and therefore melting cannot occur as the heat supplied cannot be conserved by an increase in GST film temperature.By precluding melting, QM re-opens the controversy between the melting and charge carrier mechanisms. Supporting analysis is presented to show that instead of increasing GST film temperature, conservation proceeds by the QED induced creation of photons within the GST film, the QED photons confined by TIR. QED stands for quantum electrodynamics and TIR for total internal reflection. The TIR confinement of QED photons is enhanced by the fact the absorbedheat energy absorbed in the GST film is concentrated in the TIR mode because of their high surface to volume ratio. The QED photons having Planck energy beyond the ultraviolet produce excitons by the photoelectric effect, the electrons and holes of which reduce the GST film resistance.

Keywords: Ovshinsky, phase change memory, PC-RAM, chalcogenide, quantummechanics, quantum electrodynamics.

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Authors: W. Schellong

Abstract:

Industry accounts for one-third of global final energy demand. Crossover technologies (e.g. motors, pumps, process heat, and air conditioning) play an important role in improving energy efficiency. These technologies are used in many applications independent of the production branch. Especially electrical power is used by drives, pumps, compressors, and lightning. The paper demonstrates the algorithm of the energy analysis by some selected case studies for typical industrial processes. The energy analysis represents an essential part of energy management systems (EMS). Generally, process control system (PCS) can support EMS. They provide information about the production process, and they organize the maintenance actions. Combining these tools into an integrated process allows the development of an energy critical equipment strategy. Thus, asset and energy management can use the same common data to improve the energy efficiency.

Keywords: Crossover technologies, data management, energy analysis, energy efficiency, process control.

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Authors: Hadeel S. Haj Aliwi, Saleh A. Alomari, Putra Sumari

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Nowadays, Multimedia Communication has been developed and improved rapidly in order to enable users to communicate between each other over the Internet. In general, the multimedia communication consists of audio and video communication. However, this paper focuses on audio streams. The audio translation between protocols is a very critical issue due to solving the communication problems between any two protocols, as well as it enables people around the world to talk with each other at anywhere and anytime even they use different protocols. In this paper, a proposed method for an audio translation module between two protocols has been presented. These two protocols are InterAsterisk eXchange Protocol (IAX) and Real Time Switching Control Protocol (RSW), which they are widely used to provide two ways audio transfer feature. The result of this work is to introduce possibility of interworking together.

Keywords: Multimedia, VoIP, Interworking, InterAsterisk eXchange Protocol (IAX), Real Time Switching Control Criteria (REW)

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Authors: K. Jayakumar, S. Thangavel

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In this paper proposed the effective fault detection of industrial drives by using Biorthogonal Posterior Vibration Signal-Data Probabilistic Wavelet Neural Network (BPPVS-WNN) system. This system was focused to reducing the current flow and to identify faults with lesser execution time with harmonic values obtained through fifth derivative. Initially, the construction of Biorthogonal vibration signal-data based wavelet transform in BPPVS-WNN system localizes the time and frequency domain. The Biorthogonal wavelet approximates the broken bearing using double scaling and factor, identifies the transient disturbance due to fault on induction motor through approximate coefficients and detailed coefficient. Posterior Probabilistic Neural Network detects the final level of faults using the detailed coefficient till fifth derivative and the results obtained through it at a faster rate at constant frequency signal on the industrial drive. Experiment through the Simulink tool detects the healthy and unhealthy motor on measuring parametric factors such as fault detection rate based on time, current flow rate, and execution time.

Keywords: Biorthogonal Wavelet Transform, Posterior Probabilistic Neural Network, Induction Motor.

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Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta

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Cosmic showers, during the transit through space, produce sub - products as a result of interactions with the intergalactic or interstellar medium which after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of High Energy Particle Showers involve a plethora of theoretical and experimental works with a host of constraints resulting in inaccuracies in measurements. Therefore, there exist a necessity to develop a readily available system based on soft-computational approaches which can be used for EAS analysis. This is due to the fact that soft computational tools such as Artificial Neural Network (ANN)s can be trained as classifiers to adapt and learn the surrounding variations. But single classifiers fail to reach optimality of decision making in many situations for which Multiple Classifier System (MCS) are preferred to enhance the ability of the system to make decisions adjusting to finer variations. This work describes the formation of an MCS using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN) with data inputs from correlation mapping Self Organizing Map (SOM) blocks and the output optimized by another SOM. The results show that the setup can be adopted for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

Keywords: EAS, Shower, Core, ANN, Location.

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Authors: Zeynep İltüzer Samur, Gül Tekin Temur

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Due to the increasing and varying risks that economic units face with, derivative instruments gain substantial importance, and trading volumes of derivatives have reached very significant level. Parallel with these high trading volumes, researchers have developed many different models. Some are parametric, some are nonparametric. In this study, the aim is to analyse the success of artificial neural network in pricing of options with S&P 100 index options data. Generally, the previous studies cover the data of European type call options. This study includes not only European call option but also American call and put options and European put options. Three data sets are used to perform three different ANN models. One only includes data that are directly observed from the economic environment, i.e. strike price, spot price, interest rate, maturity, type of the contract. The others include an extra input that is not an observable data but a parameter, i.e. volatility. With these detail data, the performance of ANN in put/call dimension, American/European dimension, moneyness dimension is analyzed and whether the contribution of the volatility in neural network analysis make improvement in prediction performance or not is examined. The most striking results revealed by the study is that ANN shows better performance when pricing call options compared to put options; and the use of volatility parameter as an input does not improve the performance.

Keywords: Option Pricing, Neural Network, S&P 100 Index, American/European options

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Authors: Pei-Ju Chao, Tsair-Fwu Lee, Wei-Luen Huang, Long-Chang Chen, Te-Jen Su, Wen-Ping Chen

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The main goal in this paper is to quantify the quality of different techniques for radiation treatment plans, a back-propagation artificial neural network (ANN) combined with biomedicine theory was used to model thirteen dosimetric parameters and to calculate two dosimetric indices. The correlations between dosimetric indices and quality of life were extracted as the features and used in the ANN model to make decisions in the clinic. The simulation results show that a trained multilayer back-propagation neural network model can help a doctor accept or reject a plan efficiently. In addition, the models are flexible and whenever a new treatment technique enters the market, the feature variables simply need to be imported and the model re-trained for it to be ready for use.

Keywords: neural network, dosimetric index, radiation treatment, tumor

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Authors: Bahareh Gholamzadeh, Hooman Nabovati

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Wireless sensor networks have been used in wide areas of application and become an attractive area for researchers in recent years. Because of the limited energy storage capability of sensor nodes, Energy consumption is one of the most challenging aspects of these networks and different strategies and protocols deals with this area. This paper presents general methods for designing low power wireless sensor network. Different sources of energy consumptions in these networks are discussed here and techniques for alleviating the consumption of energy are presented.

Keywords: Energy consumption, MAC protocol, Routing protocol, Sensor node, Topology control, Wireless sensor network.

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Authors: M. T. Z. Butt, T. Ahmad, N. A. Siddiqui

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Commercially SA 516 Grade 70 is frequently used for the manufacturing of pressure vessels, boilers and storage tanks etc. in fabrication industry. Heat input is the major parameter during welding that may bring significant changes in the microstructure as well as the mechanical properties. Different welding technique has different heat input rate per unit surface area. Materials with large thickness are dealt with different combination of welding techniques to achieve required mechanical properties. In the present research two schemes: Scheme 1: SMAW (Shielded Metal Arc Welding) & GTAW (Gas Tungsten Arc Welding) and Scheme 2: SMAW & SAW (Submerged Arc Welding) of hybrid welding techniques have been studied. The purpose of these schemes was to study hybrid welding effect on the microstructure and mechanical properties of the weldment, heat affected zone and base metal area. It is significant to note that the thickness of base plate was 12 mm, also welding conditions and parameters were set according to ASME Section IX. It was observed that two different hybrid welding techniques performed on two different plates demonstrated that the mechanical properties of both schemes are more or less similar. It means that the heat input, welding techniques and varying welding operating conditions & temperatures did not make any detrimental effect on the mechanical properties. Hence, the hybrid welding techniques mentioned in the present study are favorable to implicate for the industry using the plate thickness around 12 mm thick.

Keywords: Grade 70, GTAW, hybrid welding, SAW, SMAW.

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Authors: J. K. Shrestha, A. Benta, R. B. Lopes, N. Lopes

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This work provides a practical method for the development of rural road networks in rural areas of developing countries. The proposed methodology enables to determine obligatory points in the rural road network maximizing the number of settlements that have access to basic services within a given maximum distance. The proposed methodology is simple and practical, hence, highly applicable to real-world scenarios, as demonstrated in the definition of the road network for the rural areas of Nepal.

Keywords: Minimum spanning tree, nodal points, rural road network.

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion detection system (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw dataset for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle component analysis (PCA), Linear Discriminant Analysis (LDA) and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. This optimal feature subset is used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle component analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP).

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Authors: Nicole Pearcy, Jonathan J. Crofts, Nadia Chuzhanova

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In this paper, we employ a directed hypergraph model to investigate the extent to which environmental variability influences the set of available biochemical reactions within a living cell. Such an approach avoids the limitations of the usual complex network formalism by allowing for the multilateral relationships (i.e. connections involving more than two nodes) that naturally occur within many biological processes. More specifically, we extend the concept of network reciprocity to complex hyper-networks, thus enabling us to characterise a network in terms of the existence of mutual hyper-connections, which may be considered a proxy for metabolic network complexity. To demonstrate these ideas, we study 115 metabolic hyper-networks of bacteria, each of which can be classified into one of 6 increasingly varied habitats. In particular, we found that reciprocity increases significantly with increased environmental variability, supporting the view that organism adaptability leads to increased complexities in the resultant biochemical networks.

Keywords: Complexity, hypergraphs, reciprocity, metabolism.

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Authors: Sofien Chtourou, Mohamed Chtourou, Omar Hammami

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Embedded systems need to respect stringent real time constraints. Various hardware components included in such systems such as cache memories exhibit variability and therefore affect execution time. Indeed, a cache memory access from an embedded microprocessor might result in a cache hit where the data is available or a cache miss and the data need to be fetched with an additional delay from an external memory. It is therefore highly desirable to predict future memory accesses during execution in order to appropriately prefetch data without incurring delays. In this paper, we evaluate the potential of several artificial neural networks for the prediction of instruction memory addresses. Neural network have the potential to tackle the nonlinear behavior observed in memory accesses during program execution and their demonstrated numerous hardware implementation emphasize this choice over traditional forecasting techniques for their inclusion in embedded systems. However, embedded applications execute millions of instructions and therefore millions of addresses to be predicted. This very challenging problem of neural network based prediction of large time series is approached in this paper by evaluating various neural network architectures based on the recurrent neural network paradigm with pre-processing based on the Self Organizing Map (SOM) classification technique.

Keywords: Address, data set, memory, prediction, recurrentneural network.

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Authors: M. Dinakaran, P. Balasubramanie

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With the demand of mobility by users, wireless technologies have become the hotspot developing arena. Internet Engineering Task Force (IETF) working group has developed Mobile IP to support node mobility. The concept of node mobility indicates that in spite of the movement of the node, it is still connected to the internet and all the data transactions are preserved. It provides location-independent access to Internet. After the incorporation of host mobility, network mobility has undergone intense research. There are several intricacies faced in the real world implementation of network mobility significantly the problem of nested networks and their consequences. This article is concerned regarding a problem of nested network called pinball route problem and proposes a solution to eliminate the above problem. The proposed mechanism is implemented using NS2 simulation tool and it is found that the proposed mechanism efficiently reduces the overload caused by the pinball route problem.

Keywords: Mobile IP, Pinball routing problem, NEMO

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