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Characterization of Atmospheric Turbulence Measured on Terrestrial Link
Peng Liu, Kazuhiko Wakamori and Mitsuji Matsumoto

Free-space optical communication (FSO) can provide very high speed communication services. But it is deeply influenced by the atmospheric turbulence on terrestrial links. Research on atmospheric turbulence is important for FSO design. The refractive-index structure constant is used to measure atmospheric turbulence. We measure the employing FSO through a 1km  atmospheric turbulence link. In this paper, the experimental data of atmospheric turbulence is analyzed. The theory of atmospheric turbulence is reviewed, and the relation of the with the FSO receiving power considering aperture averaging is derived. From the experimental data, we found that the atmospheric turbulence changed with time and weather conditions. The results seen in from the experiment data are very important for design optimization of free space optics system performance in actual operational environments.

Keywords: Free space optics (FSO), Characterization of atmospheric turbulence, Atmospheric turbulence, Scintillation, Refractive-index structure constant

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Conserving Energy in Real Time Parallel Disk Systems
Mais Nijim

In this paper, we propose an adaptive energy conservation algorithm (DCAPS) with guaranteed performance levels for parallel disk systems under varying workload conditions. The novel framework uses data partitioning to achieve highest degree of data parallelism, estimates the expected response times for parallel disk systems, and uses adaptive voltage scaling to determine the optimal value of the power supply levels for each disk while guaranteeing the a-priori performance levels, i.e., the desired response times, for disk requests. The experimental results have illustrated that the proposed DCAPS algorithm significantly reduces the energy consumption level of parallel disk systems in dynamic environments over traditional disk systems without the DCAPS strategy.

Keywords: Data partitioning, Dynamic voltage scaling, Parallel disk systems, Response time

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Personality Dimensions and Temperaments of Engineering Professors and Students – A Survey
Arif Raza, Zaka-ul-Mustafa and Luiz Fernando Capretz

This research work aims to study personality profiles and temperaments of Pakistani software engineering professors and students. In this survey we have collected personality profiles of 18 professors and 92 software engineering students. According to the Myers-Briggs Type Indicator (MBTI) instrument, the most prominent personality type among professors as well as among students is a combination of Introversion, Sensing, Thinking, and Judging (ISTJ). The study shows ITs (Introverts and Thinking) and IJs (Introverts and Judging) are the leading temperaments among the professors. About the students’ data, the results of the study indicate SJs (Sensing and Judging) and ISs (Introverts and Sensing) as the dominant temperaments.

Keywords: Human Factors in Software Design, Process metrics, Software Engineering Process, Statistical methods

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From Mainframe to Cloud Computing: A Study of Programming Paradigms with the Evolution of Client-Server Architecture
Dost Muhammad Khan and Nawaz Mohamudally

The rapid growth of distributed computing architectures creates new approaches and opportunities for the software engineers to develop new programming and structured information processing within an organization. New computing architectures provide the technologies that enable organizations to reengineer their business processes and the dominant of these new architectures for information processing is client-server architectures. The client-server systems have evolved in conjunction with advances in desk-top computing, new storage technologies, improved network communications, and enhanced database  technology. New development in client-server is allowing developing on-line business systems with all the possible implementations that was dream of a few years ago. The wide spread of networks, and in particular, of networks connected to each other, as the Internet, has imposed new needs that required new paradigms and new technologies. There are several network technologies available which support user-level communication between processing a shared-memory. The client-server architectures are commonly used in distributed environment due to optimization, modularly, no wastage of resources, reliability, availability and provides graphical user interface aid. This paper presents a study of the programming paradigms with the evolution of client-server architecture from mainframe to cloud computing.

Keywords: Agent-Oriented Programming, Object-Oriented Programming, Lightweight Programming

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An Energy Efficient Cooperative Clustering Protocol for Heterogeneous Wireless Sensor Networks
Md. Abdullah-al Mamun, Naoshi Nakaya, Yuji koi and Yukari Hagihara

Topology control in a sensor network balances load on sensor nodes, and increases network scalability and lifetime. Clustering sensor nodes is an effective topology control approach. In this paper, we developed a low complexity cooperative diversity clustering protocol for heterogeneous wireless sensor networks. Our proposed approach does not make any assumptions about the presence of infrastructure or about node capabilities, other than the availability of multiple power levels in sensor nodes termed as node heterogeneity. This heterogeneity may result from initial setting or uneven power draining during network operation. In contrast to these approaches, we propose a heterogeneous-aware cooperative clustered (HACC) scheme for wireless sensor networks based on weighted election probabilities of each node to become a cluster head according to its residual energy. We then propose a simple modification in the clustering algorithm to exploit virtual MIMO based cooperative transmission. In place of selecting a single cluster head at network layer, we offered multiple cluster heads in each cluster to obtain a full diversity gain over long distance communication without sacrificing transmission data rate. Thus we established virtual MIMO based cooperative transmission in ad-hoc sensor networks. We treated the cooperative cluster head selection method as a Facility Location Problem (FLP) to gain better energy utilization. Analysis and simulation results show that cooperative HACC can save a huge amount of energy over the existing clustering protocols, and increase the network lifetime in terms of both 50% node to die and first node to die. Moreover, this proposal can achieve higher order diversity gain with improved spectral efficiency when the distance to Base Station is over a given threshold.

Keywords: Wireless Sensor Network (WSN), topology control, Base Station (BS), Cluster Head (CH), Cooperative Cluster Head (CCH), Facility Location Problem (FLP)

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SSMR: A scalable Multipath Routing Protocol for Mobile Ad Hoc Networks
MohammadHasan Farzin, Sam Jabbehdari and Alireza Bagheri

Mobile Ad Hoc networks (MANET) are networks which are formed by mobile nodes and do not rely on any predefined and fixed infrastructure. Due to high mobility of this kind of network, network connectivity graph changes continuously, and consequently some paths fail. Such path failure has a significant effect on quality of service. One method to increase reliability is to use multiple support paths so that in case any path fails, other paths can be used. One of such protocols is SMR, which increases reliability by creating several disjoint link between the source node and the destination node. However, since this protocol is based on the source routing protocol DSR, as the size of the network increases, its efficiency decreases. In this paper, a mechanism is proposed to reduce overhead and maintain efficiency of this protocol when the size of the network increases.

Keywords: Reactive Routing, Multipath, SMR

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Attitude of the economic agent towards risk. Means of measurement
Colomeischi T.

This paper emphasizes an analysis concerning attitude towards risk of the economic agents in uncertainty conditions. The paper begins with a general presentation of various approaches over concepts of certainty, uncertainty and risk. Later on, an analysis about the economic agent’s attitude towards risk is carried out, thus defining the aversion, neutrality and predilection towards risk of the individuals by means of the utility functions. The main characteristics that measure attitude towards risk of the economic agents are explained in the third paragraph: the certainty equivalent, the risk premium (prize), the coefficient of absolute risk aversion, the coefficient of relative risk aversion and the Arrow-Pratt risk premium.

Keywords: uncertainty, risk, utility function, lottery, risk aversion

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Modeling of Two-dimensional Warranty Policy using Artificial Neural Network (ANN) Approach
Hairudin A. Majid, Jun C. Ang and Azurah A. Samah

Modeling of two-dimensional warranty policy is an important but difficult task due to the uncertainty and instability of data collection. Moreover, conventional numerical methods of modeling a two-dimensional warranty policy involves complex distribution function and cost analysis. Therefore, this paper attempts to present an Artificial Intelligence (AI) technique, which is the Artificial Neural Network (ANN) approach in order to improve the flexibility and effectiveness of the conventional method. The proposed ANN is trained with historical data using multi-layer perceptron (MLP), feed forward back-propagation (BP) learning algorithm. The Logarithmic (logsig) and Hyperbolic Tangent (tansig) sigmoid functions are chosen as transfer function. Four popular training functions are adopted to obtain the best BP algorithm, that are, Levenberg-Marquardt (trainlm), Gradient Descent (traingd), Gradient Descent with momentum (traingdm), and Gradient descent with momentum and adaptive learning (traingdx) back propagation algorithm. This ANN model demonstrated a good statistical performance with the mean square error (MSE) values in this four training function, especially traingd. Finally, the adopted sensitivity analysis has revealed that the proposed model had successfully implemented.

Keywords: Artificial Intelligence, Artificial Neural Network, Two-dimensional Warranty

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Implementation and Evaluation of a Software Prototype for Real-Time Steganography in VoIP Call
Abdulaleem Z. Al-Othmani, Azizah A. Manaf and Akram M. Zeki

Steganography is an effective way of hiding secret data, by this means of protecting the data from unauthorized or unwanted viewing. In fact, along with encryption, steganography is one of the fundamental ways by which data can be kept confidential. One of the new and promising communication medium that can be used as a host for steganography is Voice over Internet Protocol. VoIP is a form of communication that allows people to make phone calls over an internet connection instead of typical analogue telephone lines. VoIP characteristics, such as, real-time transmission, bi-directional nature and vast amount of data make it very appropriate medium to hide secret data. This article concerns available steganographic techniques that can be used for creating covert channels for VoIP streams. Based on that, the proposed prototype is configured to apply some of these techniques in lab environment. The main contribution of this study is designing, implementing and testing a prototype of real time VoIP steganography.

Keywords: Signal processing, VoIP, Steganography, real-time communication, LSB

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Nonlinear Robust Regressions Based on ?-Regression Quantile, Least Median of Squares and Least Trimmed Squares Using Genetic Algorithms
Antoni Wibowo and Mohamad Ishak Desa

Kernel principal component regression (KPCR) can be effectively used for nonlinear system by mapping an original input space into a higher-dimensional feature space. However, KPCR can be inappropriate to be used when our data contain outliers. Under this circumstance, we propose several nonlinear robust techniques using the hybridization of KPCA, ?-regression quantile, Least Median of Squares (LMS), Least Trimmed Squares (LTS), and genetic algorithms for handling the effects of outliers on regression models. KPCA is performed to construct nonlinearity while ?-regression quantile, LMS and LTS are used to perform robustness of regressions. The genetic algorithms are used to estimate the regression coefficients of ?-regression quantile, LMS and LTS methods. The performances of the proposed methods are compared to KPCR and give better results than KPCR.

Keywords: Kernel principal component analysis, robust, nonlinear robust regression, ?-regression quantile, LTS, LMS, genetic algorithms

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Pedesterian and Vehicle Tracking with Adaptive Background Subtraction and Adaptive Object Matching By Using Simple Object Features
Özlem Morkaya and Serdar Koruko?lu

This study focuses on systems that are tracking and classifying humans and vehicles in the case of occlusion with the use of adaptive background subtraction and adaptive object matching. Our system uses adaptive background subtraction to tackle with once moving then stopped objects, added to background; and once stable then moving objects, considered as foreground. Noise components in frames result of background subtraction are cleared via morphological operations. Adaptive object matching uses one-to-one or one- to-many matching options consecutively in the case of normal or occlusion states. Addition to this, adaptive matching provides a clear solution for the problem of object matching before and after occlusion. Nearest neighboring and size ratio features are basically used as matching criteria. Finally, tracked objects are classified as pedestrian or vehicle with regard to their object features.

Keywords: Image Processing and Computer Vision, Motion, Scene Analysis, Segmentation, Tracking

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An Integration of K-means and Decision Tree (ID3) towards a more Efficient Data Mining Algorithm
Dost Muhammad Khan and Nawaz Mohamudally

K-means clustering data mining algorithm is commonly used to find clusters in huge datasets, due to its simplicity of implementation and fast execution. After applying K-means clustering algorithm on a dataset, it is difficult for one to interpret and extract the required results from these clusters, unless an appropriate data mining tool or algorithm is used. Decision tree (ID3) is the best choice, used for the interpretation of the clusters of K-means algorithm because it is a user friendly, faster to generate and simpler to explain “understandable” decision rules, compared to the other commonly used data mining algorithms. In this research paper, we integrate K-means clustering algorithm with Decision tree (ID3) algorithm to come up with a more efficient data mining algorithm using intelligent agent, called Learning Intelligent Agent (LIAgent), which is capable to perform classification, clustering and interpretation tasks on the datasets.

Keywords: LIAgent, Data Mining Algorithms, Dataset, Clusters, Partitioned Clustered Dataset, Visualization

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Improvement the NoC Performance and Fault tolerant by Dividing bandwidth In Mesh and Fat-Tree topologies
Reza Kourdy and Mohammad Reza Nouri Rad

We propose a dividing routing algorithm which can increase fault-Tolerant and Communication load that is suitable for multimedia applications in network on chip. We compare the performance of Fat-Tree, 2d-Mesh architectures in the sense of on chip network design methodology. Dividing bandwidth in source or all switches was in order to provide additional bandwidth for application that needs more bandwidth than one link supported bandwidth. We also compare the effect of link delay in convergence of two portion divided traffics, in source switch in Mesh and Fat Tree topologies. We also carry out the high level simulation of on chip network using NS-2 to verify the analytical analysis.

Keywords: Dividing Bandwidth, Communication Load, Fault-Tolerance, Network-on-Chip, Traffics Convergence

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A Method for Routing Packets Across Multiple Paths for increase communication load in 2D and 3D Network on Chip Architectures
Mohammad Reza Nouri Rad and Reza Kourdy

Combination of Multi-path routing with equal hop count can increase Communication load of the cores in network on chip. We used an Arbiter that forwarding data packet to destination node in round-robin Manner, so that we can use the more than one link bandwidth to increasing the communication load of the cores. The equal hop count for each portion of flows caused to we have no packet reordering in destination node. We compare the performance of two and three dimensional Mesh and Torus architectures using Multi-path routing in the sense of on chip network design methodology. The simulations of each of the architectures are done with IP and Multi-path routing, two-dimensional and three-dimensional topologies. We also carry out the high level simulation of on chip network using NS2 to verify the analytical analysis.

Keywords: Network-on-Chip, increase communication load, Bandwidth utilization, 2D and 3D Mesh and torus, Multipath Routing

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A Survey on Decision based Software Architecture Design approaches
G. Zayaraz, C. Dhaya and V. Vijayalakshmi

Research on software architecture suggests that it is no longer perceived as interaction among components and connectors only, but rather as a set of architectural decisions. Architectural Knowledge is defined as the representation of the software architecture along with architectural decisions and their rationale, external influence and the development environment. Although the importance of architectural knowledge has been recognized for a considerable period of time, there is still no systematic process emphasizing the design decisions in the software architecture. Several decision-based architectural design techniques have been suggested, to provide real-world support to design reasoning and justification. This paper is a survey about the well-known existing architectural decision-based approaches for different architecture knowledge management strategies. The comparison framework is used to evaluate the level of support provided by the various approaches. Further the major differences and missing desired features in these methods are highlighted.

Keywords: Software architecture, Architectural Knowledge (AK), Design decision, Design rationale, Decision Constraint Graph, Bayesian Belief Network

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Channel Estimation using Least Mean Square (LMS) Algorithm for LTE-Advanced
Saqib Saleem and Qamar-ul-Islam

For IMT-Advanced’s high data rate requirement for the internet and multimedia services, 3GPP has proposed evolved version of LTE, known as LTE-Advanced. To achieve the targets for next generation mobile communications systems, the following systems enhancements are proposed in Rel-10: Carrier Aggregation, Co-ordinated Multipoint Transmission and Reception (CoMP), Relaying Capability, Advanced MIMO techniques and Heterogeneous Networks. In order to achieve high spectral efficiency and high cell edge throughput, Channel State Information (CSI) is desired to be known as the both ends of transceiver. Channel can be estimated in time-domain and frequency-domain. For multi-antenna transmission systems under high mobility conditions when channel is fast fading frequency selective, channel needs to be estimated at each instance. Under these situations, adaptive algorithms can be used to have knowledge of channel. In this paper, the behavior of Least Mean Square (LMS) algorithm is determined and the evaluation parameters used are number of channel taps and CIR samples of the channel. Monte-Carlo Simulations are carried for the performance and complexity comparison of LMS-based channel estimation for MIMO-OFDM system.

Keywords: MIMO-OFDM, LMS, CIR Samples, Channel Taps, LTE, IMT-Advanced

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A Novel Secure Smart Student Card Model Case Study: Guilan University
Sara Salehi Mahboob, Seyed Mohammad Asadinejad and Reza Ebrahimi Atani

Today, with the development of information technology, new technologies like (Radio Frequency Identification) (RFID) are be-coming popular and more useable in different tasks, using this technology has provided fastness and comfort in giring services to universities and Educational in is titues.Abilities of this stuff have resulted a card that contains Educational documents, Electronic identification card, self service cord, library card, Dormitory card. In fact we will have different required cards, of one student in one smart card. This card improves speed and reduces human resources reguirement. So it results, less errors, less price, and also comfortin giving services to university. In this paper, the efficiency of the smart card as a “case study” has been tested in Guilan University.

Keywords: E-Payment, Smart Cards, RFID, RBAC, Guilan University

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The Use of ANN for Cracks Predictions in Curvilinear Beams Based on their Natural Frequencies and Frequency Response Functions
R. A. Saeed and L. E. George

This paper presents the results of using different arrangements of feed forward neural network (ANN) for crack prediction in curvilinear beams. The prediction process is based on the feeding the vibration characteristic as input data. The adopted vibration characteristics include: Natural Frequencies (?n) and Frequency Response Functions (FRFs). The introduced ANNs were used to estimate the size of the crack and its location. The finite element method (FEM) has been applied to compute the vibration characteristics for intact and damaged beams. To avoid the establishment of large ANN arrangements the data reduction techniques were utilized to reduce the input set of computed natural frequencies (?n) and Frequency Response functions (FRFs). The analysis results revealed that the reduced arrangements of ANN can give a satisfactory prediction results; this reflects encouraging sign about the use of ANN for damage identification.

Keywords: Crack identification, Artificial Neural Network, Data reduction techniques, Vibration analysis

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Improving Data Quality in completeness using hybrid Algorithm AR-Modified kNN
A. Nourzad, S. Karbasi and A. Faraahi

Data quality is a major issue; however, it is neglected or less considered in data mining and knowledge discovery in databases(KDD). Data completeness and missing value are one of the most important factors in data quality. Many techniques and methods have so far been proposed to its better management and missing data values imputation; but the main disadvantage of such techniques are their dependence on just one technique and not combining several techniques. And this is the reason for their less accuracy on predicting and determining the missing data values. In this paper, to increase the accuracy of missing values imputation, hybrid approach of Association Rule mining technique is applied by using partial matching concept and modified k-nearest neighbor technique (AR-modified kNN). Experimental results on the real data set suggest that accuracy and performance of given hybrid imputation approach is more effective as compared to approaches which rely on just one technique.

Keywords: completeness, data mining, data quality, missing data

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Minimization of Waiting Time in Traffic Signals on Indian roads based on Wireless Sensor Network
Amnesh Goel, Sukanya Ray and Nidhi Chandra

The rapid growth of vehicles is leading to huge traffic and increasing traffic congestion, to solve this chaotic traffic congestion a wireless sensor based traffic signal solution is proposed in this paper. The primary motive of this paper is to minimize the waiting time for vehicles at traffic signal and optimization control of duration of a green traffic light timing based on the volume of the vehicles passing through that junction in a given period of time. In this paper Wireless Sensor Network (WSN) is used to make traffic signal fully adaptive to the traffic movement at a junction and thus maximize the volume of traffic flow through that signal and utilization green time effectively.

Keywords: WSN, Traffic signal, congestion, Adaptive

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Automobile Surveillance System
Ammara Zulfiqar, Asim Munir, Memoona Khanam and Malik Sikandar Hayat Khiyal

The ASS (Automobile Surveillance System) is directed to provide with a security which is hard to be counterfeited. ASS uses image processing technology to authenticate vehicles by their license plate and organization’s logo printed on sticker. The system is intended to help in the recognition of number plates of vehicles and sticker matching. This system is based on image processing techniques. The proposed system helps in the functions like detection of the number plates of the vehicles along with the sticker (attached to inner surface of windscreen), processing both of them individually and using processed data for further processes like storing, validating (Database matching) and permitting vehicle to pass or rebuff vehicle. It also helps in the reduction of space consumption, by conducting the graphic images of the vehicles which can be further stored in the database in text format reducing size of data to be stored. The system is implemented in Matlab involving Ms-Access as backend.

Keywords: Digital image processing, License plate recognition, Logo matching, Optical character Recognition (OCR), Template matching, Validation

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A Macro Mobility Scheme using Post Handover Techniques for optimization of Handover and Roaming
Debabala Swain, Siba Prasada Panigrahi and Prasanta Kumar Patra

Even though the PMIP provides mobility solutions, there are many issues of user identity, mobility context of users from a home network to the visiting network, the assignment of home address to a user terminal in a visiting network, identification of the user terminal’s mobility, and identification of MPA and HA. In this paper, we propose a new mechanism with proxy mobile IPv4, as a mobility solution in networks. In this mechanism during mobile node access authentication, MPA exchanges registration messages with the HA (Home Agent) to set up a suitable routing and tunnelling for packets from/to the MN. In this method, the authentication request of the mobile node is passed through the NAS or AP of visiting network, this is then passed to the AAA (Authentication Authorization and Accounting) server, and the authentication server checks the realm and does start authentication procedure at the time of initialling authorizing module of the mobile terminal. It also initiates the mobility extension module, where the AAA server initiates MPA of the access network, which also informs the AAA server of the home network with information on the mobility extensions and request of the mobility parameters of the user terminal. The home AAA server interacts with the HA and collects mobile node parameters, as well as sending back details as a reply request to the visiting AAA server. After the mobility context transfer, the MPA conducts a mobility registration to the HA for that particular mobile node. Later in this paper, we will provide sequence of message exchanges during a mobility session of a  user mobile node during handover.

Keywords: Handover, Roaming, Mobility Management

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Recognition of Handwritten Script
Aroosh Zahra , Memoona Khanam , Asim Munir and Malik Sikander Hayat Khiyal

In modern and scientific world, handwritten text recognition becomes very popular because it helps to solve complex problems to ease the tasks and also saves the time. This research paper presents a system which takes the scanned image of human handwriting script and preprocess it and segment the image into individual lines then to words and then to isolated characters eventually and then recognize these characters and display the output as the automated text on screen. The proposed techniques for segmentation of lines and words is horizontal and vertical projections while for character segmentation, a new approach is implemented in which segmented column vectors are find using foreground pixel sum and then by using these column vectors, segmentation for characters is done and object properties of area and boundaries is used  to make the segmentation more fine and accurate. After segmentation, pattern correlation technique is applied to recognize the characters.

Keywords: Foreground pixel sum, Horizontal projection, Object Properties, Recognition of Handwritten script, Segmentation of Handwritten script, Template Correlation Technique, Vertical Projection

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Comparison of AdHoc Routing Protocols on the Basis of Goodput and Routing Load
Rahul Malhotra, Sangeeta Monga and Gurmeet Kaur

During the last few years, continuous progresses in wireless communications have opened new research ?elds in computer networking, aimed at extending data networks connectivity to environments where wired solutions are impracticable. The research in wireless Adhoc networks, that provides a communication between different Adhoc or Temporary nodes. This paper compares the two protocols Adhoc On-Demand Distance Vector (AODV) and Destination-Sequenced Distance Vector (DSDV) both having nonuniform routing protocols that manage mobile nodes and different routing functions. Further, these protocols implemented in network simulator (NS2) that supports Mobile adhoc networks. The protocol works on MAC layer and properly transmitted the packet to the upper layer called Network Layer over 802.11 networks. In the implementation of these protocols using at both end i.e. sender side and receiver side uses TCP Reno protocol because the packet loss should be minimum. To minimize the delay and bandwidth therefore using RTS-CTS signal in the implementation so that no hidden nodes access the bandwidth. In this work, each mobile node works as a specialized router and obtained routing information when needed. It provides a loop free route while repairing links when it was broken.

Keywords: AODV, DSDV, NS2

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New Technique To Solve Nonogram Puzzle Problem With Quake Algorithm
Khalaf Khatatneh

Nonograms are logic puzzles in which squares in a grid are colored or left blank according to numbers given at the side of the grid where the cell is filled (black) or empty (white) which in that case called space. Once completed, the puzzle reveals a hidden picture. Nonograms may be black and white or colored, in which case the number clues are also colored to show the color of the squares. Nonograms can be of any size or shape ,also there is a different kind of nongram-called triddlers- in which cells are triangles. in this kind of puzzles we have three sets of clues instead only of two. and it vary in difficulty of the levels. The general Nonogram problem is NP-hard.

Keywords: N-Puzzle, shortest path problem ,Dijkstra algorithm, Automata with Multiplicities

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Correlation identification by Normalizing the Sequential Frequent Pattern set with  the Specification of Constraints and Preferences
Janga Vijay Kumar and Vanam Sravan Kumar

Sequential Frequent pattern(Frequent patterns can be extended to the correlation between items) mining is an important data mining problem with broad applications which involves identifying sequentially frequently co-occurring set of items in a given transactional Or relational databases. Although there are many in-depth studies on efficient sequential frequent pattern mining algorithms still they leads to generate large set of sequential frequent patterns which seems to be vulnerable and inappropriate or irrelevant. Hence such set can be reducible by considering the preferences and constraints associated with each pattern to be mined, further it can be extended to mine the Correlations between the sets of Items. In this paper, we propose set of constraints and preferences needs to be specified with an Item set in addition to specifying Item set parameters like support and confidence. A user can simply specify a preference of set of items and constraints associated with each item identifies whether an Item can be included in the frequent set or NOT. We need to formulate the preferences for mining.

Keywords: Data mining, sequential Frequent-pattern mining, constraints, preferences, Normalization

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