Search results for: network index.

Authors: Dong Wook Lee, Seung Hyun Kim

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Geological structure formed by volcanic activities shows polymorphic characteristics due to repeated cooling and hardening of lava. The Jeju region is showing polymorphic characteristics in which clinker layers are irregularly distributed along with vesicular basalt due to volcanic activities. Accordingly, resident damages and environmental disputes occur frequently in the Jeju region due to blasting. The purpose of this study is to develop a blast vibration equation considering the polymorphic characteristics of basaltic ground in Jeju. The blast vibration equation consists of a functional formula of the blasting vibration constant K that changes according to ground characteristics, and attenuation index n. The case study results in Jeju showed that if there are clinker layers, attenuation index n showed a distribution of -1.32~-1.81, whereas if there are no clinker layers, n was -2.79. Moreover, if there are no clinker layers, the frequency of blast vibration showed a high frequency band from 30Hz to 100Hz, while in rocks with clinker layers it showed a low frequency band from 10Hz to 20Hz.

Keywords: Blast vibration equation, basaltic ground, clinker layer, blasting vibration constant, attenuation index.

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Authors: B.Tavakoly Sany, A. Salleh, A.H .Sulaiman, A. Mehdinia, GH. Monazami

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One year (November 2009-October 2010) sediment monitoring was used to evaluate pollution status, concentration and distribution of heavy metals (As, Cu, Cd, Cr, Hg, Ni, Pb and Zn) in West Port of Malaysia. Sediment sample were collected from nine stations every four months. Geo-accumulation factor and Pollution Load Index (PLI) were estimated to better understand the pollution level in study area. The heavy metal concentration (Mg/g dry weight) were ranged from 20.2 to 162 for As, 7.4 to 27.6 for Cu, 0.244 to 3.53 for Cd, 11.5 to 61.5 for Cr, 0.11 to 0.409 for Hg, 7.2 to 22.2 for Ni, 22.3 to 80 for Pb and 23 to 98.3 for Zn. In general, concentration some metals (As,Cd, Hg and Pb) was higher than background values that are considered as serious concern for aquatic life and the human health.

Keywords: Heavy metals, Sediment Quality, geo-accumulationindex, Pollution Load Index

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Authors: L. Abdelmalek, M. Zerikat, M. Rahli

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In this paper, we present a comparative study of the genetic algorithms and Hessian-s methods for optimal research of the active powers in an electric network of power. The objective function which is the performance index of production of electrical energy is minimized by satisfying the constraints of the equality type and inequality type initially by the Hessian-s methods and in the second time by the genetic Algorithms. The results found by the application of AG for the minimization of the electric production costs of power are very encouraging. The algorithms seem to be an effective technique to solve a great number of problems and which are in constant evolution. Nevertheless it should be specified that the traditional binary representation used for the genetic algorithms creates problems of optimization of management of the large-sized networks with high numerical precision.

Keywords: Genetic algorithm, Flow of optimum loadimpedances, Hessians method, Optimal distribution.

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Authors: Saulius Minkevicius, Genadijus Kulvietis

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The modern queueing theory is one of the powerful tools for a quantitative and qualitative analysis of communication systems, computer networks, transportation systems, and many other technical systems. The paper is designated to the analysis of queueing systems, arising in the networks theory and communications theory (called open queueing network). The authors of this research in the sphere of queueing theory present the theorem about the law of the iterated logarithm (LIL) for the queue length of a customers in open queueing network and its application to the mathematical model of the open message switching system.

Keywords: Models of information systems, open message switching system, open queueing network, queue length of a customers, heavy traffic, a law of the iterated logarithm.

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Authors: Maryam Hsaini, Mostafa Nouri-Baygi

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A critical problem in wireless sensor networks is limited battery and memory of nodes. Therefore, each node in the network could maintain only a subset of its neighbors to communicate with. This will increase the battery usage in the network because each packet should take more hops to reach its destination. In order to tackle these problems, spanner graphs are defined. Since each node has a small degree in a spanner graph and the distance in the graph is not much greater than its actual geographical distance, spanner graphs are suitable candidates to be used for the topology of a wireless sensor network. In this paper, we study Yao graphs and their behavior for a randomly selected set of points. We generate several random point sets and compare the properties of their Yao graphs with the complete graph. Based on our data sets, we obtain several charts demonstrating how Yao graphs behave for a set of randomly chosen point set. As the results show, the stretch factor of a Yao graph follows a normal distribution. Furthermore, the stretch factor is in average far less than the worst case stretch factor proved for Yao graphs in previous results. Furthermore, we use Yao graph for a realistic point set and study its stretch factor in real world.

Keywords: Wireless sensor network, spanner graph, Yao Graph.

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Authors: H.Mohammadi Majd, M.Jalali Azizpour, M. Goodarzi

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In this paper back-propagation artificial neural network (BPANN) with Levenberg–Marquardt algorithm is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.

Keywords: BPANN, deep drawing, prediction, limiting drawingratio (LDR), Levenberg–Marquardt algorithm

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Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: Intrusion prevention, network security, optimal policy, Q-learning.

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Authors: Haoyu Ma, Bin Hu, Mike Jackson, Jingzhi Yan, Wen Zhao

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In this paper we propose a new classification method for automatic sleep scoring using an artificial neural network based decision tree. It attempts to treat sleep scoring progress as a series of two-class problems and solves them with a decision tree made up of a group of neural network classifiers, each of which uses a special feature set and is aimed at only one specific sleep stage in order to maximize the classification effect. A single electroencephalogram (EEG) signal is used for our analysis rather than depending on multiple biological signals, which makes greatly simplifies the data acquisition process. Experimental results demonstrate that the average epoch by epoch agreement between the visual and the proposed method in separating 30s wakefulness+S1, REM, S2 and SWS epochs was 88.83%. This study shows that the proposed method performed well in all the four stages, and can effectively limit error propagation at the same time. It could, therefore, be an efficient method for automatic sleep scoring. Additionally, since it requires only a small volume of data it could be suited to pervasive applications.

Keywords: Sleep, Sleep stage, Automatic sleep scoring, Electroencephalography, Decision tree, Artificial neural network

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Authors: Naren Bag, S. Bhattacharyya, Partha P. Gopmandal

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In this study, we have analyzed the transport of analytes under a two dimensional steady incompressible flow of power-law fluids through rectangular nanochannel. A mathematical model based on the Cauchy momentum-Nernst-Planck-Poisson equations is considered to study the combined effect of mixed electroosmotic (EO) and pressure driven (PD) flow. The coupled governing equations are solved numerically by finite volume method. We have studied extensively the effect of key parameters, e.g., flow behavior index, concentration of the electrolyte, surface potential, imposed pressure gradient and imposed electric field strength on the net average flow across the channel. In addition to study the effect of mixed EOF and PD on the analyte distribution across the channel, we consider a nonlinear model based on general convective-diffusion-electromigration equation. We have also presented the retention factor for various values of electrolyte concentration and flow behavior index.

Keywords: Electric double layer, finite volume method, flow behavior index, mixed electroosmotic/pressure driven flow, Non-Newtonian power-law fluids, numerical simulation.

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Authors: Supachai Tangwongsan, Labhidhorn Pangphuthipong

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This research work proposes a model of network security systems aiming to prevent production system in a data center from being attacked by intrusions. Conceptually, we introduce a decoy system as a part of the security system for luring intrusions, and apply network intrusion detection (NIDS), coupled with the decoy system to perform intrusion prevention. When NIDS detects an activity of intrusions, it will signal a redirection module to redirect all malicious traffics to attack the decoy system instead, and hence the production system is protected and safe. However, in a normal situation, traffic will be simply forwarded to the production system as usual. Furthermore, we assess the performance of the model with various bandwidths, packet sizes and inter-attack intervals (attacking frequencies).

Keywords: Intrusion detection, Decoy, Snort, Intrusion prevention.

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Authors: Julien Romieux, Fabio Verdicchio

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Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.

Keywords: Cooperative signal processing, power management, signal representation, signal approximation, wireless sensor networks.

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Authors: Gunasekaran Raja, Ramkumar Jayaraman

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In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.

Keywords: Cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing.

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Authors: G. Mokryani, M. R. Haghifam, J. Esmaeilpoor

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Happening of Ferroresonance phenomenon is one of the reasons of consuming and ruining transformers, so recognition of Ferroresonance phenomenon has a special importance. A novel method for classification of Ferroresonance presented in this paper. Using this method Ferroresonance can be discriminate from other transients such as capacitor switching, load switching, transformer switching. Wavelet transform is used for decomposition of signals and Competitive Neural Network used for classification. Ferroresonance data and other transients was obtained by simulation using EMTP program. Using Daubechies wavelet transform signals has been decomposed till six levels. The energy of six detailed signals that obtained by wavelet transform are used for training and trailing Competitive Neural Network. Results show that the proposed procedure is efficient in identifying Ferroresonance from other events.

Keywords: Competitive Neural Network, Ferroresonance, EMTP program, Wavelet transform.

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Authors: Kamel Allaw, Jocelyne Adjizian Gerard, Makram Chehayeb, Nada Badaro Saliba

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In developing countries, such as Lebanon, the demographic data are hardly available due to the absence of the mechanization of population system. The aim of this study is to evaluate, using only remote sensing data, the correlations between the number of population and the characteristics of roads network (length of primary roads, length of secondary roads, total length of roads, density and percentage of roads and the number of intersections). In order to find the influence of the different factors on the demographic data, we studied the degree of correlation between each factor and the number of population. The results of this study have shown a strong correlation between the number of population and the density of roads and the number of intersections.

Keywords: Population, road network, statistical correlations, remote sensing.

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Authors: M. Wu, S. M. Feroz, A. Hagihara, L. Xue, Z. L. Huang

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In order to compare vertical stratification, floristic composition, and woody species diversity of subtropical evergreen broadleaf forests between the Ryukyu Archipelago, Japan, and South China, tree censuses in a 400 m2 plot in Ishigaki Island and a 1225 m2 plot in Dinghushan Nature Reserve were performed. Both of the subtropical forests consisted of five vertical strata. The floristic composition of the Ishigaki forest was quite different from that of the Dinghushan forest in terms of similarity on a species level (Kuno-s similarity index r0 = 0.05). The values of Shannon-s index H' and Pielou-s index J ' tended to increase from the bottom stratum upward in both forests, except H' for the top stratum in the Ishigaki forest and the upper two strata in the Dinghushan forest. The woody species diversity in the Dinghushan forest (H'= 3.01 bit) was much lower than that in the Ishigaki forest (H'= 4.36 bit).

Keywords: Floristic similarity, subtropical evergreen broadleaf forest, vertical stratification, woody species diversity.

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Authors: Nidal F. Shilbayeh, Sameh T. Khuffash, Mohammad H. Allymoun, Reem Al-Saidi

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There is a real threat on the VIPs personal pages on the Social Network Sites (SNS). The real threats to these pages is violation of privacy and theft of identity through creating fake pages that exploit their names and pictures to attract the victims and spread of lies. In this paper, we propose a new secure architecture that improves the trusting and finds an effective solution to reduce fake pages and possibility of recognizing VIP pages on SNS. The proposed architecture works as a third party that is added to Facebook to provide the trust service to personal pages for VIPs. Through this mechanism, it works to ensure the real identity of the applicant through the electronic authentication of personal information by storing this information within content of their website. As a result, the significance of the proposed architecture is that it secures and provides trust to the VIPs personal pages. Furthermore, it can help to discover fake page, protect the privacy, reduce crimes of personality-theft, and increase the sense of trust and satisfaction by friends and admirers in interacting with SNS.

Keywords: Social Network Sites, Online Social Network, Privacy, Trust, Security and Authentication.

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Authors: Manoj Kumar Dutta

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Wavelength Division Multiplexing (WDM) technology is the most promising technology for the proper utilization of huge raw bandwidth provided by an optical fiber. One of the key problems in implementing the all-optical WDM network is the packet contention. This problem can be solved by several different techniques. In time domain approach the packet contention can be reduced by incorporating Fiber Delay Lines (FDLs) as optical buffer in the switch architecture. Different types of buffering architectures are reported in literatures. In the present paper a comparative performance analysis of three most popular FDL architectures are presented in order to obtain the best contention resolution performance. The analysis is further extended to consider the effect of different fiber non-linearities on the network performance.

Keywords: WDM network, contention resolution, optical buffering, non-linearity, throughput.

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Authors: Mustafa M. Donma, Orkide Donma

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Anthropometric measurements are essential for obesity studies. Waist circumference (WC) is the most frequently used measure and along with hip circumference (HC), it is used in most equations derived for the evaluation of obese individuals. Morbid obesity (MO) is the most severe clinical form of obesity and such individuals may also exhibit some clinical findings leading to metabolic syndrome (MetS). Then, it becomes a requirement to discriminate MO children with MetS (MOMetS+) from MO children without MetS (MOMetS-). Almost all obesity indices can differentiate obese (OB) children from children with normal body mass index (N-BMI). However, not all of them are capable of making this distinction. The aim of this study was to find out the clinical availability of (waist circumference + hip circumference)/2 ((WC+HC)/2) for the differential diagnosis of MOMetS+ and MOMetS- and to compare the possible preponderance of it over some other anthropometric or fat-based obesity indices. 45 MOMetS+ and 45 MOMetS- children were included in the study. Participants have submitted informed consent forms. The study protocol was approved by the Non-interventional Clinical Studies Ethics Committee of Tekirdag Namik Kemal University. Anthropometric measurements were performed. BMI, waist-to-hip circumference (WHR), (WC+HC)/2, trunk-to-leg fat ratio (TLFR), trunk-to-appendicular fat ratio (TAFR), trunk fat+leg fat/2 ((trunk+leg fat)/2), diagnostic obesity notation model assessment index-2 (D2I) and fat mass index (FMI) were calculated for both groups. Study data were analyzed statistically and 0.05 for p value was accepted as the statistical significance degree. Statistically higher BMI, WC, (WC+HC)/2, (trunk+leg fat)/2 values were found in MOMetS+ children than MOMetS- children. No statistically significant difference was detected for WHR, TLFR, TAFR, D2I and FMI between two groups. The lack of difference between the groups in terms of FMI and D2I pointed out the fact that the recently developed fat-based index; (trunk+leg fat)/2 gives much more valuable information during the evaluation of MOMetS+ and MOMetS- children. Upon evaluation of the correlations, (WC+HC)/2 was strongly correlated with D2I and FMI in both MOMetS+ and MOMetS- groups. Neither D2I nor FMI was correlated with W/H. Strong correlations were calculated between (WC+HC)/2 and (trunk+leg fat)/2 in both MOMetS- (r = 0.961; p < 0.001) and MOMetS+ (r = 0.936; p < 0.001) groups. Partial correlations between (WC+HC)/2 and (trunk+leg fat)/2 after controlling the effect of basal metabolic rate were r = 0.726; p < 0.001 in MOMetS- group and r = 0.932; p < 0.001 in MOMetS+ group. The correlation in the latter group was higher than the first group. In conclusion, recently developed anthropometric obesity index (WC+HC)/2 and fat-based obesity index (trunk+leg fat)/2 were of preponderance over the previously introduced classical obesity indices such as WHR, D2I and FMI during the differential diagnosis of MOMetS+ and MOMetS- children.

Keywords: Hip circumference, metabolic syndrome, morbid obesity, waist circumference.

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Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

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Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.

Keywords: IDS, DDoS, MLP, KDD.

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Authors: A. Muthuramalingam, S. Himavathi, E. Srinivasan

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.Hardware realization of a Neural Network (NN), to a large extent depends on the efficient implementation of a single neuron. FPGA-based reconfigurable computing architectures are suitable for hardware implementation of neural networks. FPGA realization of ANNs with a large number of neurons is still a challenging task. This paper discusses the issues involved in implementation of a multi-input neuron with linear/nonlinear excitation functions using FPGA. Implementation method with resource/speed tradeoff is proposed to handle signed decimal numbers. The VHDL coding developed is tested using Xilinx XC V50hq240 Chip. To improve the speed of operation a lookup table method is used. The problems involved in using a lookup table (LUT) for a nonlinear function is discussed. The percentage saving in resource and the improvement in speed with an LUT for a neuron is reported. An attempt is also made to derive a generalized formula for a multi-input neuron that facilitates to estimate approximately the total resource requirement and speed achievable for a given multilayer neural network. This facilitates the designer to choose the FPGA capacity for a given application. Using the proposed method of implementation a neural network based application, namely, a Space vector modulator for a vector-controlled drive is presented

Keywords: FPGA implementation, multi-input neuron, neural network, nn based space vector modulator.

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Authors: S.B. Tavakoly Sany, A. Salleh, A.H. Sulaiman, G.H. Monazami

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The coastal sediments of West Port of Malaysia was monitored from Nov. 2009 to Oct. 2010 to assess spatial distribution of heavy metals As, Cu, Cd, Cr, Hg, Ni, Zn and Pb. Sediment samples were collected from 10 stations in dry and rainy season in West Port. The range concentrations measured (Mg/g dry weight ) were from 23.4 to 98.3 for Zn, 22.3 to 80 for Pb, 7.4 to 27.6 Cu, 0.244 to 3.53 for Cd, 7.2 to 22.2 for Ni, 20.2 to 162 for As, 0.11 to 0.409 for Hg and 11.5 to 61.5 for Cr. The geochemical indexes used in this study were Geoaccumulation (Igeo), Contamination Factor (CF) and Pollution Load Index (PLI); these indexes were used to evaluate the levels of sediment contaminations. The results of these indexes show that, the status of West Port sediment quality are moderately polluted by heavy metals except in arsenic which shows the high level of pollution.

Keywords: Heavy metals, Sediment Quality, West Port.

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Authors: Hidehiko Okada, Takayuki Akiba

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It is well-known as Fitts’ law that the time for a user to point a target on a GUI screen can be modeled as a linear function of “index of difficulty (ID).” In this paper, the authors investigate whether the traditional ID formulation is appropriate independently of device screen sizes. Result of our experiment reveals that the ID formulation may not consistently capture actual difficulty: users’ pointing performances are not consistent among pointing target variations of which index of difficulty are consistent. The term A/W may not be appropriate because the term causes the observed inconsistency. Based on this finding, the authors then evaluate the applicability of possible models other than Fitts’ one. Multiple regression models are found to be able to appropriately represent the effects of target design variations. The authors next make an attempt to improve the definition of ID in Fitts’ model. Our idea is to raise the size or the distance values depending on the screen size. The modified model is found to fit well to the users’ pointing data, which supports the idea. 

Keywords: Fitts’ law, pointing device, small screen, touch user interface, usability.

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Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

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In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: Data Estimation, link data, machine learning, road network.

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Authors: Dewan Md. Farid, Nguyen Huu Hoa, Jerome Darmont, Nouria Harbi, Mohammad Zahidur Rahman

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In this paper, we present a new learning algorithm for anomaly based network intrusion detection using improved self adaptive naïve Bayesian tree (NBTree), which induces a hybrid of decision tree and naïve Bayesian classifier. The proposed approach scales up the balance detections for different attack types and keeps the false positives at acceptable level in intrusion detection. In complex and dynamic large intrusion detection dataset, the detection accuracy of naïve Bayesian classifier does not scale up as well as decision tree. It has been successfully tested in other problem domains that naïve Bayesian tree improves the classification rates in large dataset. In naïve Bayesian tree nodes contain and split as regular decision-trees, but the leaves contain naïve Bayesian classifiers. The experimental results on KDD99 benchmark network intrusion detection dataset demonstrate that this new approach scales up the detection rates for different attack types and reduces false positives in network intrusion detection.

Keywords: Detection rates, false positives, network intrusiondetection, naïve Bayesian tree.

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Authors: A. Krishna Veni, R.Geetha

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Wireless Sensor Networks (WSNs) are suitable for many scenarios in the real world. The retrieval of data is made efficient by the data aggregation techniques. Many techniques for the data aggregation are offered and most of the existing schemes are not energy efficient and secure. However, the existing techniques use the traditional clustering approach where there is a delay during the packet transmission since there is no proper scheduling. The presented system uses the Velocity Energy-efficient and Link-aware Cluster-Tree (VELCT) scheme in which there is a Data Collection Tree (DCT) which improves the lifetime of the network. The VELCT scheme and the construction of DCT reduce the delay and traffic. The network lifetime can be increased by avoiding the frequent change in cluster topology. Secure and Efficient Transmission of Aggregated data (SETA) improves the security of the data transmission via the trust value of the nodes prior the aggregation of data. Since SETA considers the data only from the trustworthy nodes for aggregation, it is more secure in transmitting the data thereby improving the accuracy of aggregated data.

Keywords: Aggregation, lifetime, network security, wireless sensor network.

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Authors: Rahma Al Maawali, Hameed Sulaiman

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Air pollution both from point and non-point sources is difficult to control once released in to the atmosphere. There is no engineering method known available to ameliorate the dispersed pollutants. The only suitable approach is the ecological method of constructing green belts in and around the pollution sources. Air pollution in Muscat, Oman is a serious concern due to ever increasing vehicles on roads. Identifying the air pollution tolerance levels of species is important for implementing pollution control strategies in the urban areas of Muscat. Hence, in the present study, Air Pollution Tolerance Index (APTI) for ten avenue tree species was evaluated by analyzing four bio-chemical parameters, plus their Anticipated Performance Index (API) in field conditions. Based on the two indices, Ficus benghalensis was the most suitable one with the highest performance score. Conocarpus erectuse, Phoenix dactylifera, and Pithcellobium dulce were found to be good performers and are recommended for extensive planting. Azadirachta indica which is preferred for its dense canopy is qualified in the moderate category. The rest of the tree species expressed lower API score of less than 51, hence cannot be considered as suitable species for pollution mitigation plantation projects.

Keywords: Air pollution tolerance index, avenue tree species, bio-chemical parameters, Muscat.

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Authors: H. Kazemi Karegar, S. Jalilzadeh, V. Nabaei, A. Shabani

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In this paper, the problem of finding the optimal topological configuration of a deregulated distribution network is considered. The new features of this paper are proposing a multiobjective function and its application on deregulated distribution networks for finding the optimal configuration. The multi-objective function will be defined for minimizing total Energy Supply Costs (ESC) and energy losses subject to load flow constraints. The optimal configuration will be obtained by using Binary Genetic Algorithm (BGA).The proposed method has been tested to analyze a sample and a practical distribution networks.

Keywords: Binary Genetic Algorithm, Deregulated Distribution Network, Minimizing Cost, Reconfiguration.

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Authors: A. Shebani, C. Pislaru

Abstract:

The wear measuring and wear modelling are fundamental issues in the industrial field, mainly correlated to the economy and safety. Therefore, there is a need to study the wear measurements and wear estimation. Pin-on-disc test is the most common test which is used to study the wear behaviour. In this paper, the pin-on-disc (AEROTECH UNIDEX 11) is used for the investigation of the effects of normal load and hardness of material on the wear under dry and sliding conditions. In the pin-on-disc rig, two specimens were used; one, a pin is made of steel with a tip, positioned perpendicular to the disc, where the disc is made of aluminium. The pin wear and disc wear were measured by using the following instruments: The Talysurf instrument, a digital microscope, and the alicona instrument. The Talysurf profilometer was used to measure the pin/disc wear scar depth, digital microscope was used to measure the diameter and width of wear scar, and the alicona was used to measure the pin wear and disc wear. After that, the Archard model, American Society for Testing and Materials model (ASTM), and neural network model were used for pin/disc wear modelling. Simulation results were implemented by using the Matlab program. This paper focuses on how the alicona can be used for wear measurements and how the neural network can be used for wear estimation.

Keywords: Wear measuring, Wear modelling, Neural Network, Alicona.

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Authors: Marinela Istrate, Ionel Muntele, Alexandru Bănică

Abstract:

The authors propose the identification, analysis and prognosis of the quantitative and qualitative evolution of the elderly population in the functional urban areas. The present paper takes into account the analysis of some representative indicators (the weight of the elderly population, ageing index, dynamic index of economic ageing of productive population etc.) and the elaboration of an integrated indicator that would help differentiate the population ageing forms in the 48 functional urban areas that were defined based on demographic and social-economic criteria for all large and medium cities in Romania.

Keywords: Ageing, demographic transition, functional urban areas, spatial resilience.

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Authors: Sun Mei, Nagata Katsuya, Onoda Hiroshi

Abstract:

With the resource exhaustion, bad affections of human activities and the awakening of the human rights, the corporate social responsibility became popular corporate strategy achieving sustainable development of both corporation and society. The issue of Guideline of Chinese Corporate Social Responsibility Report promotes greatly corporation to take social responsibility. This paper built the index system according to this guideline and takes the textile industry as an example, uses the analytical hierarchy process to identify the weightings of different responsibilities of corporation to guide the corporate social responsibility performance assessment.

Keywords: Sustainable development, analytical hierarchyprocess, index system, corporate social responsibility

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