Login New user?  
01-Applied Mathematics & Information Sciences
An International Journal



A New Processing Method for Signal and Image Analysis Using Discrete Wavelet Transform

S. P. Kesavan, R. Rajeswari,
Abstract :
In this paper we develop a new method for the analysis of signal and image data using Discrete Wavelet Transform (DWT). The new method reduces the size of the computing devices and consumes less energy. Out of different transformation technique the most famous and dominant architecture is the discrete wavelet transform. The discrete wavelet transform design optimization has done on power and leakage current reduction. New adders are proposed which are based on power gating and reversible logic. It is shown that the proposed adders reduce the dynamic power by about 30%. The proposed design in 45 nm and 32 nm CMOS technology is efficient when compared to other methods.


Binomial Regressive Influence Behavior Ranking for Virtual Community Formation in Social Network

R. Gnanakumari, P. Vijayalakshmi,
Abstract :
A Social Network (SN) is a website which permits the people to shares the data about their personal or business endeavor to form the virtual community. Due to the communication between the users in the SN, a similar user’s behavior identification plays a significant issue. The existing techniques still have a challenging problem to identify similar behavior accurately. Therefore, Statistic Dice Similarity Based Probabilistic Binomial Regression and Ranking (SDS-PBRR) method introduced. Initially, the similarity value between the user’s behaviors is calculated using Statistic Dice Similarity Coefficient (SDSC). After that, Probabilistic Binomial Regression Analysis is carried out for evaluating the similarity value to classify the users as Influencing Behavior (IB) or Non- Influencing Behavior (N-IB) minimum error rate in the SN. Lastly, firefly algorithm is applied to perform a ranking process for discovering the level of IB users in the SN. The simulation results show that SDS-PBRR method increases the True Positive Rate (TPR) and minimizes the False Positive Rate (FPR) as well as execution time.


Dynamic Channel Assignment and Gateway Load Balanced Routing for Multi-Channel Wireless Mesh Networks

K. Saravanan, A. Chilambuchelvan,
Abstract :
In this paper, we propose the dynamic channel assignment and Gateway(GW) load balanced routing protocol. In this protocol, a combined cost metric is determined incorporating channel quality, switching cost and queue length. Then the GW having minimum cost metric is selected by the source node. Then channels are fairly assigned in the network by the selected GW between itself and the mesh clients. In GW load balanced routing, the GW selects a path with minimum load based on interface queue length. Congestion is detected at any intermediate router based on Exponentially Weighted Moving Average (EWMA) of the queue size. Each GW estimates the traffic load at the current interval and predicts the traffic load of the next interval using Hidden Markov Model (HMM). If congestion is detected at GW, then it informs the Access Point (AP) to change to another GW. By simulation results, we show that the proposed technique reduces the network congestion and improves efficiency.


An Integrated Approach of Statistical, Remote Sensing and GIS techniques for Evaluation of Vulnerable Cut Slopes

R. Chandrasekaran, P. S. Kumar,
Abstract :
Road networks are playing a vital role in socio-economic growth of all countries in the world. In developing countries like India, due to increasing in population leads to destabilisation of hill slopes and mass wasting movements. Stability of slopes is very important in hilly terrain for proper planning, development, and maintenance of hilly roads. The present study provides very important contributions towards mitigation processes, through slope stability and qualitative estimation of rock mass classification systems, in between Mettupalayam and Coonoor ghat sections, Nilgiri district, Tamil Nadu, India. The Coonoor ghat section (NH-67) plays a significant role in transportation which connects Nilgiri with two other states like Karnataka and Kerala. The geo-mechanical classifications of Rock Mass Rating (RMR) and Slope Mass Rating (SMR) provides information about both rock quality and discontinuity which is responsible for type and potential failure associated with each slopes. On the basis of RMR, most of the locations R-2 to R-5 and R-7 to R-8 represents Fair rock type (Class II) where as SMR exhibits unstable to stable slopes (Class II to IV). It is clearly depicts that RMR values provides better results than SMR values and more attention should be given in these unstable slope maintenance for more safe and economical manner.


An Efficient Algorithm for Mining Frequent Itemsets in Large Databases

B. Praveen Kumar, D. Paulraj,
Abstract :
Flexible Bitmap Index and Cluster based Bit Vector (FBICBV), mainly focuses to identify the eligible candidates from unfiltered huge volume of temporal data in order to find out frequent patterns among them. One of the best and efficient solutions is to use the mechanism of bitmap indexing and clustering. Initially by using bitmap index, the rich data are filtered out from the unfiltered raw dataset for effective analysis. Thus, the eligible candidate data are identified through this process. Secondly, the frequent patterns are identified using cluster based bit vector for effective decision making. Hence, scanning of raw data is completely avoided by using bitmap index. Also, it eliminates storage of redundant candidate’s data while forming cluster table. Thus, it clearly implies the improvements in optimizing the database storage for maximum performance and efficiency using FBICBV algorithm when compared to the existing algorithms


Multi-Objective Sub-Linear Frequent Mining-Based Information Prediction in Biomedical Datasets using Big Data Analytics

G. Elangovan, G. Kavya,
Abstract :
Recently, big data applications have been rapidly expanding into various industries. Healthcare is among those industries that are willing to use big data platforms, and mining as a result, some large data analytics tools have been adopted in this field. Medical imaging, which is a pillar in diagnostic healthcare, involves a high volume of data collection and processing. The most challenging issue is common in sub-graph mining process to reduce the dimensionality of data medical data set is reduced. In this paper, we propose a Multi-Objective Sub-Linear Frequent Mining (MOSLFM) to estimate the real values of outline processing in biomedical data, which is useful for computational complexity. This is repeated again to find the minimum representation of the most frequent supplemental edges to be compatible with the sub-border margin. Sub-linear and sub-graph often use the mining process candidate generation model to find the biometric data set used to reduce the process. Projecting a high efficient progressing cluster partitioning method is used to determine the frequency of identified terms in the biomedical dataset to easy the process using lower complexity.


Performance Optimization in Body Sensor Network using Self Calibration TDMA Algorithm

M.Mohammed Mustafa, V. Parthasarathy,
Abstract :
The paper focuses on the variation in performance characteristics such as the packet delivery ratio, throughput, jitter, and the delay varies when the queue length is changed. The results proved that there is no impact on the jitter when the queue length is varied. The packet delivery ratio and the throughput are increased when the queue length is increased by 10. So, the self-calibrating TDMA algorithm can be used to implement the body sensor network and queue length can be kept at 20 to be optimized for good throughput and packet delivery ratio.


Adapted Semi Carry Save Modular Montgomery Multiplier for High Performance Elliptic Curve Cryptographic Processor

S. Senthilkumar, P. S. Periasamy,
Abstract :
In this paper,we propose a new adaptable Semi Carry Save Modular Montgomery Multiplier (ACS-MMM) with Multi- Value Logic method (MVL). We improve the performance of Modified Carry Save Adder (MCSA) with maintaining very small hardware complexity. The proposed ACS-MMM multiplier design has several advantages over previous models. The existing system requires additional clock cycles and the critical path delay parameter is reduced.It is shown that one can avoid the ACS Montgomery Modular Multiplier by avoiding unnecessary carry save addition measures that offer less delay. Therefore, the required clock cycles are significantly reduced by montgomery modular process. As a result, the proposed montgomery multiplier gives much smaller Area-Time Product (ATP) than the previous montgomery multipliers.


Intuitionistic Fuzzy Filters of lattice Wajsberg algebra

S. Sathya, D. Kalamani, C. Duraisamy, K. Arun Prakash,
Abstract :
Intuitionistic fuzzy filter in Lattice Wajsberg algebra is introduced in this paper. Some of the equivalent conditions for an intuitionistic fuzzy set to be an intuitionistic fuzzy filter are established. Also, intuitionistic fuzzy lattice filter is defined and the relationships between these two filters are derived.


Energy Efficiency in WSNs Based on the SCMC Protocol

Rajkumar Krishnan, Ganesh kumar Perumal,
Abstract :
Wireless sensor networks (WSNs) are well-known media for communication over wide ranges. For these wireless networks, the Quality of Service (QoS) is considered to be an important factor, which is based on the performance of the end-to-end delay, energy efficiency, and packet delivery ratio. To provide better QoS, a well-developed routing protocol with unique properties should be implemented. In WSN, the single path routing mechanism faces multiple obstacles in providing a better communication channel because there is no option for an alternative path in the case of a path failure. This problem can be overcome by implementing a multipath routing mechanism with a well-designed protocol. This paper proposes a Single cluster with Multi-hop Communication (SCMC) protocol to achieve better QoS by means of improved bandwidth and packet delivery ratios, as well as improved end-to-end delays. SCMC is a multi-hop communication protocol with a single cluster head that balances the energy level and achieves high energy conservation with increased lifetime. A single cluster forms dynamic multipaths with multiple members for multi-hop communications. This work is implemented in Ns-2 and compared to the Equal-Cost Multi-Path routing (ECMP) and Stateless protocol for real-time communication in sensor networks (SPEED). The results show that the proposed protocol is more effective in terms of minimum delay, low energy consumption, and increased delivery ratio compared to the other two protocols.


Optimizing Throughput and TCP Receive Window with Node Connection in distributed Fuzzy computing with enhanced bandwidth for High Speed TCP in WSN

R. Vidhya, Palanisamy. C,
Abstract :
The high speed sensor cause congestion during communication process so thesendersends data,the receiver receives them but it doesnot send any acknowledgment for the data packet. The multitask process is difficult to reduce the resource utilization.The Proposed Regimentdata scheduler (RDS) algorithm used to monitor the node capacity and the history of a node character based on the information. It allocates the routing path effectively, TCP and FTP protocols are adjustable sop it is easy to access them frequently. It fixes the threshold values, the nodes after reaching the threshold value it starts to perform communication, otherwise difficult to achieve effective communication.High routine Fuzzy computing is proposed to find window size depends on the packet loss information, to determine the window size rate and uses queuing scheme to analyze the behavior of node, based on that counter value is update the high speed which is a modification to TCPs congestion control mechanism and TCP connections with largecongestion windows. A set of sampling values from sampling algorithm (𝑇𝑁 is applied for both homogeneous and heterogeneous resources. It reduces congestion or attacker rate and increase thePacket delivery rate.


A framework for getting most out of the enterprise social networking platforms for workplace learning

R. Venkatesan, S. Kuppusamy,
Abstract :
Change is the constant phenomena, and technological advancements are happening at a rapid phase in the Information Technology (IT Industry). It is highly critical to get up-to-date with the advancements in the technology area to be at the competitive edge. Ongoing learning is critical to the success of the employees who are working in these IT companies. In this fastmoving world, we do not have time to follow traditional methods of learning and skills development. Peer to peer learning is considered to be one of the best ways in acquiring new knowledge and skills. Social networking tools have become parts and parcels of our life. There are several professional social networking platforms available today. Organizations are using social networking tools in various ways. Several Organizations have implemented enterprise social networking platforms likes Yammer and Jive for enabling internal communication and collaboration. These tools can also support their workplace learning needs. This paper explores the attributes of an efficient social learning platform for employees working in IT companies.


A Hybrid CS-ABC optimization technique for Solving Unit Commitment Problem with Wind Power Uncertainty

A. Amudha, Mary P. Varghese,
Abstract :
This investigation anticipates a solution to power system’s optimal power flow (OPF)integrating wind power. The wind related costs estimation parameters are (i) estimation of wind generator output based on reserve cost arising (ii) cost for not utilizing completely offered wind power which incorporated in conventional OPF. A hybrid cuckoo search optimization technique and artificial bee colony optimization technique is employed for resolving wind power OPF model. Modified IEEE bus systems are used as test systems and it is show that the cuckoo searches and artificial bee colony executes better than conventional swarm optimization. The cost estimation is performed in MATLAB environment. The minimum operating cost is $156000000 at load demand 78MW and wind probability is 0.8269. Similarly, maximum operating cost is $ 416000000 for 20th hour at load demand 102MW and the wind probability is 1.



A. Ramathilagam, S. Maheswari,
Abstract :
This work proposes a Hybrid Bat and Differential Evolution Algorithm (HBDEA)based IaaS Cloud Partial Critical Path (IC-PCP) Replication and Improved Hyper Elliptic Curve Cryptography (HBDEAIPR with IHECC). The proposed HBDEAIPR algorithm applies a deadline constraint and variable budget for replication to achieve its goals. Proposed Enhanced IC-PCP with Replication (EIPR) algorithm is increasing the likelihood of completing the execution of a scientific workflow application within a user-defined deadline in a public Cloud environment. The proposed HBDEA algorithm determine the parameters of tasks are the early start time and latest finish time to replicate workflow tasks to mitigate effects of performance variation of resources so that soft deadlines can be met. Theproposed HBDEAIPR approach is verified by developing IHECC system which authenticates the user based on task deadlines and also using secret-key and encrypted value for genuine users authentication in CC environment. Simulation experiments with well-known scientific workflows show that the proposed HBDEAIPR approach increases the likelihood of deadlines being met and reduces the total execution time of applications as the budget available for replication increases.


Fuzzy Controller Based Grid Integration of Hybrid Solar Photovoltaic and DFIG Wind Energy System for Improve the Power Quality

K. Latha Shenoy, C. Gurudas Nayak, Rajashekar P. Mandi,
Abstract :
Nowadays the hybrid renewable energy based power generation very popular due to the availability of resources and meet the consumer demand without any disturbance. This paper, focused on grid integration of hybrid photovoltaic (PV) and double feed induction generation (DFIG) based wind energy system. The scope of this paper has developed an intelligent controller for generating maximum power from the above renewable energy sources and solve the grid integration issue as well as improve the power quality. This paper has three major parts such as design a fuzzy logic controller for maximum power point tracking of photovoltaic power system and generate maximum power at various weather conditions. Second part design a fuzzy logic controller for DFIG based wind energy conversion system and improve the system performance. Third part hybrid the above two renewable energy sources such as PV and DFIG based Wind energy system and develop a fuzzy logic controller for solving grid integration issues as well as improve the power quality. The above proposed design has been developed and simulated in the Matlab Simulink environment and analysis the system performance in various operating conditions. Finally, the proposed system simulation results are evaluated with IEEE 1547 standard for showing the effectiveness of the system.


Efficient Multi Keyword Search in Heterogeneous Environment based on Ranking Technique

L. Rahunathan, A. Tamilarasi, D. Sivabalaselvamani,
Abstract :
Data analysis in cloud environment according to the requirement is planned to implement with the appropriate process of service with flexible and reliable way. Additionally, the detailed process of accessing the data from the server is based on the searching process in a secure manner, which is based on authentication. To end with, the database stored information can be retrieved efficiently by implementing the approaches and processed according to the control access as appear in RBAC. The enhanced system development process is integrated for the efficient connection between the user and the provider. However, the technique for searching data is used for information access through searching technique. Based on Multi data searching approach the access of information by the user is allowed with the secure process through strings in the dictionary and the keyword coordinates are estimated.


Investigation Analysis for Software Fault Prediction using Error Probabilities and Integrals Methods

S. Karuppusamy, G. Singaravel,
Abstract :
In this paper, in-depth analysis of faults in the code phase is detected through integral methods that identify the error in software. The repositories of the data set are collected during the software product development life cycle model is integrated with machine learning algorithm namely Bayesian Decision theory to detect the error probabilities and predicting unbound error during the prediction of the software faults. In prior. The faults are predicted in repository for a given data set using error probability and error integral method that identifies the probability of error and correction, which is then applied with Gaussian method to find the levels of the error probability with minimum and maximum integral of acceptable faults in the repository.


A study of Intuitionistic Fuzzy Associative Filter in lattice implication algebra

J.Revathi, D.Kalamani, C. Duraisamy, K. Arun Prakash,
Abstract :
The notion of intuitionistic fuzzy associative filter in lattice implication algebra is introduced. Equivalent condition for an intuitionistic fuzzy filter to become an intuitionistic fuzzy associative filter are given. Relations among intuitionistic fuzzy associative filter, intuitionistic fuzzy fantastic filter and intuitionistic fuzzy positive implicative filters are discussed.


Network Performance using Multipath Congestion Segmentation in Mobile Ad Hoc Networks

T. C. Ezhil Selvan, P. Malathi,
Abstract :
The mobile ad hoc networks are subjected by its autonomous topology with restricted medium bandwidth and constrained energy at the nodes. Due to these features in mobile ad hoc networks the routes linking the source node and targets might become very uneven and due to which the transmissions in mobile ad hoc networks is quite intricate. For addressing these problems, we design a multi-path congestion segmentation algorithm. Here preliminarily diverse split routes are identified and the information packets are communicated along the routes which fulfill the limitation in routing such as bandwidth, delay and route constancy. In case if the routes do not fulfill the restrictions the congestion could be dispersed along the diverse split paths with the help of congestion segmentation routine. Inflence of the different parameters drived using mathematical expression and simulation graphs reveals that the designed scheme minimizes the packet dropping and delays with the enhanced output.


Automated performance monitoring and optimization method for cloud data centre

A.Poobalan, N. Uma Maheswari, K.Khaja Mohideen,
Abstract :
Data centre are the integral part of the cloud computing which makes the enterprises to invest less in their infrastructure. The multi-tenant nature of the cloud also adds value to this. Data are handled more efficiently with the advanced technologies in terms of infrastructure and network communication. With all this facilities, monitoring of the performance of the data centre is an essential task. This is also addressed by cloud computing through various methodologies. Differences in type of servers, user requests and capability of storage are the various factors that has their influence in handling of data and users. A model has been designed based on queuing theory. This model addresses the performance issue and also optimizes it. It follows a multi-tenant queue. The parameters that are considered and optimized are workload, response time, utilization of the resource, capability of serving resource at zero time, reservation of resources in advance and the number of users who are served. The tools provided by oracle such as automated workload reports and ADDT is used for performance measurement and optimization.


Sequential Pattern Mining using RadixTreeMiner algorithm and Neural Network based Classification

K. Poongodi, A.K. Sheik Manzoor,
Abstract :
Handling large amount of data arriving from internet-based applications is one of the challenging tasks. Recently, more contributions to the data mining algorithms, such as clustering and classification are made by the researchers. One of the most commonly used data mining schemes is Sequential Pattern Mining (SPM). Here, statistically significant and relevant sequential patterns are used for classification purpose, but the complexity grows for the increasing data sizes. This paper introduces a novel approach, namely RadixTreeMiner, for mining sequential patterns from the sequential database, and to classify the data efficiently based on maximal sequential patterns. The proposed RadixTreeMiner algorithm constructs the radixtree from the sequences available in the input database, and then, identifies the maximal sequences. Further, the Neural Network (NN) approach is employed in this work for the classification of database based on the maximal sequential patterns. Experimentation of the proposed RadixTreeMiner algorithm uses two standard gene sequence databases and its performance is evaluated based on the metric Classification Accuracy (CA). From the achieved results, it is evident that the proposed algorithm has better performance with values of 0.9038 and 0.8628 as classification accuracy for both the datasets.


The Influence of RPO over Employer Brand in IT Industries from Employer’s Perspective

C. Ramani Rajan, T. Vetrivel,
Abstract :
Outsourcing is a well-known terminology since two decades and yet it is an ever flourishing domain with global presence. When it comes to Recruitment Process Outsourcing (RPO), it is still in its beginning stage and yet to find a reliable place in the recruitment domain. The sole purpose of outsourcing recruitment services is it is cost effective and it also improves the organization’s efficiency by cutting down the hours spent. Besides, there is a requirement for expert advice and trust which are provided by the external recruiting agencies. Our objective is to find whether there is any effect on the Employer Brand by Recruitment Process Outsourcing. Our study involves five IT companies in Tamil Nadu and our investigation showed no effect on motivation, major effect on effective orientation in almost all the companies under study and also on the performance orientation in one third of the companies by RPO.


Secure and Efficient Deduplication Scheme based on Ownership Challenge for Mobile Cloud Environment

Sebastian Annie Joice, M. A. Maluk Mohamed,
Abstract :
Cloud Computing plays a vital job in providing storage, infrastructure, and processing services. The demand for storing data in cloud is increasing day by day due to the large number of users. To protect the data stored in the cloud, data is often stored in an encrypted form. Cloud storage includes a large amount of duplicated data under different encryption schemes by different users. Existing solutions that deals with encrypted deduplication does not support controlled access, ownership revocation and file modification requires uploading the entire file in encrypted form. In this paper, a scheme based on Incremental Proxy Re-Encryption (IPRE) scheme for deduplication with ownership challenge integrated with improved file modification operation in mobile cloud environment is proposed. The proposed scheme is compared with Proxy Re-Encryption (PRE) scheme based on turnaround time and energy consumption. During file modification operation, the proposed scheme shows remarkable improvement in results using the restricted storage and processing speed of mobile devices.


An Efficient Packet Loss Resilience Method Using Closed Form Solution for Unequal FEC Assignment

K. Sivakumar, S. Sasikumar,
Abstract :
This paper deals with an effective video transmission in communication networks by maintaining the quality parameters of the transmitted video file within the desired value. In this work, the Forward Error Correction (FEC) method is proposed to reduce the distortion in video transmission with H.264 video encoder. Initially, the packet distortion model is derived based on the error concealment property and error propagation effect in H.264 encoder. The transmission medium induces various noises which will be transmitted to the receiver. Hence, the Channel Pattern Integration (CPI) algorithm is employed to find the best channel which is free of noises, for transmitting the selected video. Then, the Hierarchical Sequence Pattern (HSP) algorithm is used to validate the errors present in the received packets. The simulation results show that the proposed FEC scheme gives the substantial increase in PSNR performance. Due to the reduced computational complexity compared to the previous scheme, the proposed CPI technique offers an increased flexibility of dynamic video transfer over packet-lossy environments.


Conceptual Cost Modelling for Sustainable Construction Project Planning— A Levenberg–Marquardt Neural Network Approach

P. S. Kumar, S. Gururaj,
Abstract :
The main objective of this paper is to develop a systematic neural network model to estimate the conceptual cost for sustainable construction projects. A wide range of influencing factors on micro and macro level has been considered. The proposed engineering approach was pragmatic to model labour and material cost incurred in different stages of construction using the artificial neural network (ANN) technique. The results indicated an acceptable convergence with reasonable generalization capabilities and the results obtained from the neural network model are more accurate and credible. This study contributes the construction professionals by providing insight into using different ANN activation and transfer functions along with a wide range of influencing factors to benchmark the project manager’s conceptual cost predicting capabilities. Moreover, the systematic engineering approach guides the project managers how a readily available practical database can help optimize several objectives. It supports two key factors of sustainable construction: the economic dimension and the social dimension.


Neuro-Fuzzy SVD Technique for Image Recognition and Safety in Construction Site

Mohammed Majid M. Al-Khalidy, Osama Yaseen M. Al-Rawi, Manaf Majid Al-Khalidy,
Abstract :
This paper presents a novel computer vision technique of intelligent recognition of safety in construction sites. The proposed technique relies on a new methodology for Neuro-Fuzzy Singular Value Decomposition (NFSVD). This methodology utilized unmanned safety worker’s wears. Where within a construction site entranced a multi-camera is used and fixed on a special frame inside the security Cabin. Before the workers allowed for entering the construction site, an automatic detecting, and an intelligent matching system has the ability to recognize the worker’s dress shapes and colors through a multi snap image. To improve the success of this methodology, the proposed technique empirically investigated, analyzed and verified to check the image frame quality, accept and reject indication, real-time complexity, diffusion, confusion and PSNR. The results performed by this technique demonstrated the robustness and reliability of this methodology for safety in the construction field.


Dual Tree Complex Wavelet Transform based Image Security using Steganography

T. Yuvaraja, R. S. Sabeenian,
Abstract :
Modern communication media requires high level of protection system for securing the multimedia data from hackers. The most important objective of this manuscript is to develop a simple and efficient methodology for protecting the information from hackers. In this paper, the level of image security is improved by integrating the steganography and cryptography techniques in order to produce the secured image. In this manuscript, Secured image is produced by applying Dual Tree Complex Wavelet Transform (DT-CWT). Further, cryptography algorithm is applied on the steganography image if the level of information entropy lies beyond the threshold value. Mean Square Error (MSE),Peak Signal to Noise Ratio (PSNR) and Mean Absolute Error (MAE) are the metrics which are used to evaluate the performance of the proposed method in this manuscript. The proposed image security methodology achieves 47.04 dB of PSNR, 165.86 of MSE and 31.66% of MAE on bone image dataset.


Group Mosquito Host Seeking Behaviour Based Self Organizing Technique for Genetic Algorithm

S. Ayshwarya Lakshmi, S. A. Sahaaya Arul Mary,
Abstract :
Genetic algorithms (GAs) are the most important evolutionary computation technique that is used to solve various complex problems that involve a large search space. To have a performance improvement over GA, the concept of Hybrid genetic algorithms that were inspired from the biological behaviour of different living beings was put to use to solve the Non-deterministic Polynomial (NP) complete problems. Hybrid GA can be derived by amalgamating with efficient nature inspired heuristic algorithms like Particle Swarm optimization (PSO), Ant Colony Optimization (ACO), firefly algorithm, cuckoo search, etc.. The grey wolf optimization algorithm has been the recently proposed bio-inspired optimization algorithm that proved as the most recent and best in solving complex problems. In this perspective, Group Mosquito Host Seeking Behaviour based Self-organizing (GMHSA) technique for genetic algorithm has been proposed. The proposed GMHSA model is embedded at the stage prior to genetic operations in order to achieve better exploration and exploitation. The well-known combinatorial optimization problem, Travelling Salesman Problem (TSP), is used as the testbed and the test instances retrieved from the standard TSP library. Various recent and best working hybrid GA models are used to justify the significances of the proposed model. The experimental results show that the proposed algorithm yields better outcome with respect to computational time and also achieve improvement in average convergence rate, irrespective of the size of the test instance, compared to other existing models.


A Partial Grained Attribute-Based Encryption for Secure Data Access in the Cloud Environment

M. P. Revathi, P. D. Sheba Kezia Malarchelvi,
Abstract :
A recent fast developing method for easy access and sharing of medical data is to maintain the patients’ information in the form of Electronic Health Record (EHRs). Nowadays, these EHRs are most frequently outsourced and stockpiled at third parties namely cloud servers. This reduces the burden on health care providers but introduces more safety problems like revealing of health data to unapproved parties due to access, by not only illegitimate users but also unauthorized access by legitimate users. Though illegitimate users can be identified by authentication mechanisms, unauthorized access by authentic users cannot be restricted by such authentication mechanisms. To guarantee the control of the users’ access, efficient access control mechanisms and access policies are required. This research paper introduces an innovative data access mechanism based on Partial grained Attribute Based Encryption (PABE) and policies to access, depending on users’ roles in cloud servers. The proposed secure data access aims at providing attribute based keys selectively only to sensitive data thereby restricting access to sensitive data alone to reduce access rights validation time.


A Lower Bound for Edge-congestion of an Embedding

R. Sundara Rajan, Indra Rajasingh, N. Parthiban, A. Arul Shantrinal, K. Jagadeesh Kumar,
Abstract :
In network theory, the problem of simulating one architecture into another architecture is converted into a graph embedding problem. In this paper, we have extended our work in [1] and give algorithms to compute optimal edge-congestion of embedding hypercubes, folded hypercubes, crossed cubes and circulant networks into hypertrees thereby proving that the edge-congestion bound obtained in [1] is sharp.


Performance Analysis of an M/M/1 Queue with close down periods, server under Maintenance Subject to Catastrophe

B.Thilaka, B.Poorani, S.Udayabaskaran,
Abstract :
Mathematical analysis of Queueing systems shows a significant part in wireless communication network such as channel control, energy saving schemes etc. Here, we consider a M/M/1 Queue with the server operating in three modes -Active mode, maintenance mode, sleep mode/close down period (with transitions from the maintenance mode to the sleep mode/close down period and active mode), subject to catastrophes. Catastrophes occur only when there are customers in the system and they wipe out the entire system resulting in the system being rendered inactive for a random period of time. Explicit expressions have been obtained for the transient probabilities and steady state probabilities of the close down period, maintenance state and system size along with the many performance measures. Influence of the different parameters on the steady state probabilities, system performance measures are studied using numerical examples.


A Generalized transformation function that transforms Multiplicative Preference Relation into Fuzzy Preference Relation in MCDM

M. Vijaya Lakshmi, B. Sridevi,
Abstract :
This paper proposes a generalized transformation function that transforms multiplicative preference relation (MPR) into fuzzy preference relation (FPR) in multi criteria decision making (MCDM). In analytic hierarchy process (AHP), reciprocal multiplicative preference relation is considered to be the preference representation and in fuzzy majority based selection, FPR acts as uniform representation element. Though, the effectiveness of AHP is to find incompatible judgments, it does not take into account the uncertainty to a number. In decision making problems (DMP) , the lack of consistency leads to get the inconsistent solutions. By exploiting this proposed transformation, it is possible to find a preference of alternatives with strongly consistent solutions in decision making processes. This work is an improvement to the existing work of Herrera et., al.,.


A Linguistic approach of IFSM with Euclidean Distance in decision making of compatible waste treatment methods

Lilly Merline W, Aleeswari.A, Nivetha Martin,
Abstract :
Decision making of suitable waste treatment method for promoting environmental sustainability is indeed a challenging task for the industrial sectors. There are various approaches and methods of decision making ranging from simple to complex, but in recent times the concept of soft sets represented as soft matrix are used in making appropriate decisions by associating several parameters. To overcome the uncertainty and impreciseness the notion of intutionistic fuzzy soft matrix is used (IFSM). In this paper, a new approach of linguistic IFSM is employed in which the membership and non-membership values are represented in terms of linguistic variables instead of numerical values. This approach presents the realistic opinion of experts and it creates a new paradigm of decision making. This paper primarily aims in introducing LAIFSM and validates the proposed approach with the real life application.


On Face Magic Labeling of Duplication of a Tree

B. Roopa, L. Shobana, R. Kalaiyarasi,
Abstract :
This paper deals with the problem of labeling the vertices, edges and faces of a plane graph. Let (a,b, c) ∈ {0,1}. A labeling of type (a,b, c) assigns labels from the set {1,2, . . . ,a|V(G)|+b|E(G)|+c|F(G)|} to the vertices, edges and faces of G in such a way that each vertex receives a labels, each edge receives b labels and each face receives c labels and each number is used exactly once without repetition as a label. The weight of the face w( f ) under a labeling is the sum of the labels of the face itself together with the labels of vertices and edges surrounding that face. A labeling of type (a,b, c) is said to be face magic, if for every positive integer k all k-sided faces have the same weight. Here we study the existence of face magic labeling of duplication and double duplication of trees.


Star Edge Coloring of Subcubic Graphs

Kavita Pradeep,
Abstract :
A proper edge coloring of a graph G is called star edge coloring if there is no bi-colored path or cycle of length four in G. The star chromatic index of G, denoted by c0 s(G), is the least number of colors needed for a star edge coloring of G. Dvoˇr´ak et. al. in 2013, proved that for a subcubic graph G, c0 s(G)  7 and conjectured that it is less than or equal to 6. In this paper, we show that if a subcubic graph G has maximum average degree less than 83 then c0 s(G) < 6.


Application of Category Graph in finding the Wiener Index of Rough Ideal based Rough Edge Cayley Graph

B.Praba, Benazir Obilia.X.A,
Abstract :
The Rough Ideal based Rough Edge Cayley Graph is defined on the Rough semiring (T;D;Ń) along with its Rough Ideal J and this graph consists of 2n􀀀m3m elements. The complexity in studying the Rough Ideal based Rough Edge Cayley Graph is made simpler by defining the category graph. Wiener index of the Rough Ideal based Rough Edge Cayley Graph is obtained through this category graph and the concepts are illustrated through examples.


Game chromatic number and game chromatic index of the Mycielski graphs of some families of graphs

Alagammai R, V Vijayalakshmi,
Abstract :
In this paper, we determine the game chromatic number and game chromatic index of the Mycielski graphs of some families of graphs.


Steiner Reciprocal Degree Distance Index

A. Babu, J. Baskar Babujee,
Abstract :
In this paper, we introduce the Steiner Reciprocal Degree Distance Index SRDDt (G) for some standard graph structures as well as some properties and bounds for it.


Computing Degree based Topological Indices for Molecular Graphs

A. Subhashini, J. Baskar Babujee,
Abstract :
In our paper, by means of drug molecular structure analysis and edge dividing technology, we investigate the degree based topological indices of several widely used chemical structures which often appear in drug molecular graphs.


Computational and Mathematical Analysis of Fuzzy Quota Harvesting Model in Fuzzy Environment using Homotopy Perturbation Method

S. Saravanakumar, B. Sridevi, A. Eswari, L. Rajendran,
Abstract :
The mathematical model of fuzzy quota harvesting in fuzzy environment under non-steady state conditions is discussed. Analytical expressions for population density for all values of harvesting constant rate and growth rate are presented by using Homotopy perturbation method. Further, the population densities are compared with simulation results and fuzzy solution in which a good agreement was noted.


A New Optimized Distributed Scheduling Service using Genetic Computing

A. Sandana Karuppan, N. Bhalaji, N. Ramaraj,
Abstract :
Cloud computing is a paradigm to perform distributed processing and open computing environment. It hides the need of high-cost dedicated expensive hardware, space and dedicated software to minimal interaction and management. Enormous growth of data or big-data generated by cloud system has been recognized. Recently cloud computing is delivering on-demand services like software, memory, data, network-bandwidth and IT related services on Internet. The reliable performance of cloud-services can be related to various key-factors like task-scheduling. Scheduling can be done in different levels like job level or infrastructure level or process level. In this research work focus mainly on task scheduling method. End-user sends the request to the main data-center for jobs to be computing, tasks are named. A task means piece of work or process that can be executed within the deadline. Tasks are divided into critical and non-critical where critical tasks are executed with in the given time period, and non-critical consider as low priority work in the cloud system. Scheduling dispatches the all user tasks provided by the users of cloud system to the cloud service provider for available resources in the cloud.


Multiscale Wavelet Transformation and Amplitude Zone Time Epoch Coding for ECG Data Extraction and Compression

S. Velmurugan, A. Mahabub Basha,
Abstract :
Tele-health monitoring plays a vital role in healthcare applications. Electrocardiogram (ECG) signals are an essential part in diagnosis and analysis of cardiac diseases. It consumes large amount of time and space during transmission and data storage. To reduce the time and space complexity, an Integrated Multiscale Gabor Wavelet Transformation and Amplitude Zone Time Epoch Coding (IMGWT–AZTEC) Mechanism is introduced. Multiscale Approximated Gabor Wavelet Transformation is used in IMGWT–AZTEC mechanism to decompose the ECG signals into many sub-bands and to extract the P, T waves and QRS complex. After extraction of signals, Amplitude Zone Time Epoch encoding and decoding Techniques are introduced for data compression and decompression. This in turn helps to improve the data extraction and data compression performance in IMGWT–AZTEC mechanism.


A CPW-Fed Hexagonal Antenna With Fractal Elements For UWB Applications

V. Dinesh, G. Murugesan,
Abstract :
We proposed a coplanar waveguide fed hexagonal antenna design for ultra wideband applications. The size of the antenna is miniaturized to 25×25×1.588 mm3 and the impedance bandwidth is improved by adding fractal elements at the edges. Parametric analysis of the fractal elements and the impedance behavior is performed to realize the radiation characteristics and bandwidth coverage as required for microwave imaging. The addition of fractal elements introduces multi-resonance at different frequency and covers a large bandwidth of 1.7 GHz–11 GHz respectively. The effect of surface currents in the ground plane reduces the antennas operating bandwidth which is reduced by introducing defective ground structure. The proposed antenna has an average gain of 2.35dB, radiation efficiency of 93% to 96%.


The Narrative of Renewable Sources of Energy in Science Fiction Films

Islam Abohela,
Abstract :
We identify how images of future cities in science fiction films make global change information more widely available to the public. However, it is noticed the persistence of presenting future cities as dystopias. This paper aims to identify how informed the images of future cities in science fiction films are by the current developments in renewable sources of energy and their integration within the city. It can be argued that science fiction films generally lack references to renewable sources of energy. The scarcity of these references to renewable sources of energy in science fiction films can be attributed to the perception of these images as a representation of a prosperous future society while, in many occasions, science fiction films depict future cities as a dystopia. This paper examines this assumption by comparing the dystopic visions of future cities to the utopic vision in science fiction films through the implementation of renewable sources of energy within the depicted future city and its buildings.



Salah A. Ali, Salah M. Omran,
Abstract :
This research was evolved to identify the role of managerial accounting information system (MAIS) in providing the necessary information needed for business process re-engineering (BPR), and suggestan integrated framework for such role. To achieve the study objective, an analytical field study was conducted. The analytical study comprises the BPR concepts, goals, motives and steps; the information needed for BPR; the extent to which the traditional, strategic and applied MAIS provide the information needed in conducting BPR; and the integrated framework for MAIS for the purpose of BPR. The field study was conducted through personal interview andquestionnaire to test the five hypotheses formulated from the theoretical study. The questionnaire was polled to managerial accountants, finance directors and production directors in a sample of companies engaged in the engineering industries and listed in the Egyptian stock market. The most important findings of this research are that; there are several factors that pushed the organizations to conduct the BPR, such as the accelerated developments in production and information technology, severe competition on both domestic and international levels andgrowth of the customer care concept. The BPR requires information in several areas which should be provided by the MAIS. The traditional managerial accounting information system (TMAIS) is not capable of fulfilling its role in the completion of BPR, and strategic managerial accounting information system (SMAIS) provides valued information about customers, competitors which help the organization to perform some of BPR. However, the BPR requires some more information which is not provided by SMAIS. The applied managerial accounting information systems (AMAIS) in the Egyptian companies do not provide the necessary information needed for BPR. There are a number of considerations that should be taken into account when the MAIS designed for the purposes of BPR. Furthermore, there is agreement between the finding of field study and the analytical study derived from the literature in this regard.


Modelling of HCHS System for Optimal E-O-L Combination Section and Disassembly in Reverse Logistics

T. Sathish, P. Periyasamy,
Abstract :
We propose a novel strategy for the multi period disassembly in reverse logistic. The proposed system combines the natural inspired cuckoo search with the artificial inspired harmony search algorithms for disassembly of end of life products. The new strategy is tested by considering a test case and its performance is compared with the conventional optimization techniques. The obtained results are validated based on the cost, disassembly time, and execution time. It is shown that, the performance is outperforms the conventional performance. Hence the proposed hybrid metaheuristics approach is suitable for real time reverse logistics management.


Non-Linear Machine Learning Techniques for Multi-Label Image Data Classification

D. Senthilkumar, A. K. Reshmy, M. G. Kavitha,
Abstract :
In this paper, we propose non-linear Machine Learning Techniques (MLT) for Multi-Label Image Classification (MLIC) problems. Multi-Label Learning requires MLT to identify the complex non-linear relationship between the features and class labels. Also, Multi-Label data degrades the performance of the classifiers and processing of this data with a large number of features is too complex while using traditional methods. Therefore, we propose two approaches namely ensemble Deep Learning Network (DLN) and Multivariate Adaptive Regression Splines (MARS) for MLIC. The experimental results show that the proposed (DLN and MARS) algorithms achieves a superior predictive performance rate of 94.77% and 81.68% respectively, compared to the existing methods.


An Analysis on Web Service Generated Data to Facilitate Service Retrieval

I. R. Praveen Joe, P. Varalakshmi,
Abstract :
In this paper, a novel layered clustering approach is proposed to cluster web services in order to facilitate web service selection process. The process of web service selection from a rapidly growing number of functionally similar services in the internet, results in an increase of service discovery cost, transforming data time between services and service searching time. Though suitable technologies for web services clustering are being developed, blending neural networks and swarm based algorithms is not prevailing. A novel two-phase clustering approach involving ART (Adaptive Resonance Theory) network for primary clustering with functional data and swarm algorithms (BOIDs, ABC and PSO) for sub-clustering with non-functional data (metadata, QoS and service generated data respectively) is proposed in this work. As a result of this layered approach, the computational overhead is greatly reduced and the search space is also abridged significantly in order to obtain optimal services.


Heterogeneous Image Transcoding using Interconversion Matrices

V. Mohan, P. Shanmuga Priya, Y. Venkataramani,
Abstract :
We propose a new scheme for heterogeneous transcoding of Image files from JPEG to JPEG 2000 format with directional filter analysis and modified SPIHT coding scheme. The optimal parameters QF out(I,D) and Z(I,D) that produce high perceived quality in terms of SSIM are selected using a prediction algorithm. Furthermore, the Heterogeneous Image Transcoding are performed using Inter-conversion Matrices which reduce the computational overheads. The resultant coefficients, using BDCT to DWT, are analyzed by Directional Filter banks (DFBs). The DWT-DFB coefficients are encoded via progressive SPIHT algorithm to meet the devices constraints. In the experimental set up, the quality of reconstructed image is measured using PSNR and SSIM. It is shown that there is an improvement of more than 4 dB in the quality of reconstruction for the same bit rate as that of mere DWT based SPIHT encoding.


Computing the Median and Range for Power Function Distributions

Fahrettin Özbey,
Abstract :
Median and range of a random sample are measures based on order statistics which are descriptive of the central tendency and dispersion of the population, respectively. In this paper, I obtained the median and range for order statistics from non-identical standard power distributions functions. Then, the median and range for identical standard power functions distributions and uniform distributions functions are given. Finally numerical results of the median and range are presented.


The Solution of Quantum Kinetic Equation with Delta Potential and its Application for Information Technology

Mukhayo Rasulova,
Abstract :
The existence of the unique solution, in terms of initial data of the hierarchy of quantum kinetic equations with delta potential and application of kinetic equation for information technology, has been proven. The proof is based on the nonrelativistic quantum mechanics and application of semigroup theory methods.



Poornima R, Mahabub Basha A,
Abstract :
MIMO is a key technology to meet high data rate requirement for next generation communication system. It can efficiently use the spectrum to increase the communication throughput. Designing a low-complex, high performance detection algorithm for the MIMO system has been a vital issue. The efficient detection of MIMO signal using Modified Memetic Algorithm (MMA) with Quadrature Amplitude Modulation (QAM) varying constellation size is proposed in this paper. The performance of the proposed work is at far with the optimum Maximum Likelihood Detector (MLD) in terms of Bit Error Rate (BER) and computational complexity. Three stages are there in proposed work. In the first stage, using partial ML detections certain bits are detected. The undetected bits in the first stage are calculated in the second stage using soft values generation method. In the last stage, the undetected bits are detected by using MMA. The soft values obtained from second stage and the partial ML bits from the first stage are combined and used as the input for the last stage. In this stage, the best individuals are obtained. MMA uses hill climbing local search technique to obtain the high quality individuals as starting point. The simulation results demonstrate that MMA based MIMO detectors outperformed the state of art detectors for different antenna configurations. Also it gives reduced complexity as compared to the existing detectors. For a 4x4, 16-QAM MIMO system, the proposed work gives BER of 10-4 for 8dB SNR with the complexity value of 51.4.


New aspects and applications of entrepreneur’s critical success elements

Saad Darwish, Horiya AlDeeb, Atheela Al Azzawi, Atheer Al Rashid,
Abstract :
We investigate how critical success elements are perceived by the entrepreneurs. Determining unknown factors for small and medium businesses from an ensemble of identical systems is a fundamental, yet experimentally demanding, task in business. Here we study the critical success elements needed to fully characterize the success in business. We show this task can be achieved using new model, which yield a practical though non-universal set of projective measurements. An application has been given and it is shown that Bahrain is stepping up efforts to make small and medium businesses a major contributor to its growth.


A Hybrid Approach to Optimize Feature Selection Process Using iBPSO- BFPA for Review Spam Detection

SP. Rajamohana, K. Umamaheswari,
Abstract :
With the increase in the customer reviews, feedbacks, suggestions posted in the web forum, blogs led to the emergence of spam. Spam detection is important for both the customer and service providers to arrive at a proper decision while purchasing as well as marketing the product. Most of the research works has been developed only for sentiment classification for the past few decades which favors the spammers to write fake reviews. Hence it is important to detect the spam reviews but the major issues in spam review detection are the high dimensionality of feature space which contains redundant, noisy and irrelevant features. To resolve this, optimization method for selecting subset of features is necessary. Hence, this paper proposes Hybridization of Improved Binary Particle Swarm Optimization (iBPSO) and Binary Flower Pollination Algorithm (BFPA) utilized with Naive Bayes and k-NN for optimization process to improve the classification performance. Experimentation result proves that hybrid iBPSO BFPA outperformed the existing approach by obtaining the maximum accuracy of 94.43% for review spam dataset when compared with existing Cuckoo Search NB(CS) and Shuffled Frog Leaping Algorithm NB (SFLA) which achieved only 81.87% and 88.23%. The experimental result proves that the proposed hybrid method increases the classification accuracy.


The impact of Arab Impact Factor (AIF) on Human Knowledge

Abd Elrazek Abd Elrazek, Abduh Elbanna, Hossam El Masry,
Abstract :
Inspiration driven activities and services are used more nowadays to raise a communication capacity for meeting such society demands. Arab impact factor (AIF) originally inspired by Arab Impact Factor Project, is highly needed to increase the attention towards Arabic journals regularly published. Important knowledge published in Arabic language can experience new products and services that improve Arab quality of life. Inspiration and innovation mainly achieved by mother tongue. Publications in Arabic language will increase the impact of Arab activity in a way may impact the human inspiration and innovation in different behaviors. Using data mining analyses can predict those Journals will be repeatedly cited in the future, other journals might not be highly cited, accordingly give advice to predictable high- cited journals and predictably not cited Journals to promote activities or change strategy respectively. AIF using data mining machine learning may predict success of every organization.


Magnetohydrodynamic Peristaltic Flow of Jeffry Nanofluid with Heat Transfer Through a Porous Medium in a Vertical Tube

Nabil T. M. El-dabe, Mohamed Y. Abou-zeid, Yasmeen M. Younis,
Abstract :
The present paper deals with the peristaltic motion of a non-Newtonian nanofluid with heat transfer through a porous medium inside a vertical tube. The system is stressed by a uniform magnetic field. The viscous dissipation, internal heat generation with radiation effects are considered. A Rung-Kutta-Merson method and a Newton iteration in a shooting and matching technique are used to find the solutions of the momentum, temperature and nanoparticles equations. The numerical formula of the axial velocity, temperature and nanoparticles are obtained as functions of the physical parameters of the problem. Numerical calculations are carried out for these formula. The effects of physical parameters of the problem on this formula are discussed numerically and illustrated graphically througth a set of figures.


Complete Tripartite Graph accepting Continuous Monotonic Decomposition theorem for evaluation routing of reaction mechanism of Piperdone Derivatives with different colour mobility of Graph labelling

V.Narayanan, J.B.VeeraMalini, G.Baskar,
Abstract :
This research paper has provided a new platform for the Graph labelling method of 3- isobutyl-2,6–bis(m-nitrophenyl)-piperidin-4-one semicarbazone. A futuristic approach for the synthesised compound has been developed in the graph theory and sequence of reaction mechanism of compound is done through Complete Tripartite Graph accepting Continuous Monotonic Decomposition concepts. In the same way we have desired functional illustration and acceptance of Graph Theory to chemistry dictionary. Thus the complex compound is enhanced in mathematical theory and to correlate the mode of arrangement of compound in graph labelling. The focus of this application is to bridge qualitative relationship and representation of research compound in graphical decomposition factors.


An Effective Approach for solving MHD Viscous Flow Due to A Shrinking Sheet

Mourad S. Semary, Hany N. Hassan,
Abstract :
In this paper, we present an effective technique combined between homotopy analysis method and traditional Pad´e approximation so-called (HAM Pad´e), the technique to obtain the analytic approximation solution of a certain type of nonlinear boundary value problem with one boundary condition at infinity. The analytic series solution obtained from the homotopy analysis method and the Pad´e diagonal approximation to handle the boundary condition at infinity. This technique apply to the boundary value problem resulting from the magnetohydrodynamic (MHD) viscous flow due to a shrinking sheet. The proposed technique success to obtain the two branches of solutions for important parameter. Comparison of the present solution is made with the existing solution and excellent agreement is noted.


Akaike Information Criterion and Fourth-Order Kernel Method for Line Transect Sampling (LTS)

Ali Algarni, Ahmad Almutlg,
Abstract :
Parametric and noparametric approaches were used to fit line transect data. Different parametric detection functions are suggested to compute the smoothing parameter of the nonparametric fourth-order kernel estimator. Among the different candidate parametric detection functions, the researcher suggests to use Akaike Information Criterion (AIC) to select the most appropriate one of them to fit line transect data. More specifically, four different parametric models are considered in this research. Where as two models were taken to satisfy the shoulder condition assumption, the other two do not. Once the appropriate model is determined, it can be used to select the smoothing parameter of the nonparametric fourth-order kernel estimator. As the researcher expected, this technique leads to improve the performances of the fourth-order kernel estimator. For a wide range of target densities, a simulation study is performed to study the properties of the proposed estimators which show the superiority of the resulting proposed fourth-order kernel estimator over the classical kernel estimator in most considered cases.


Median and Extreme Ranked Set Sampling for penalized spline estimation

Ali Algarni,
Abstract :
This paper improves and demonstrates two approaches of Ranked Set Sampling (RSS) method for penalized spline models which are Median and Extreme RSS. These improved methods increase the efficiency of the estimated parameters in the targeted model with comparing to usual RSS and Simple Random Sampling (SRS). Moreover, in practical studies, our improved methods can reduce sampling expenses dramatically. The paper approaches are illustrated using a simulation study as well as a practical example.


Control of Quantum and Classical Correlations in Werner-like States Under Dissipative Environments.

A.B. A. Mohamed.,
Abstract :
Quantum and classical correlations are studied for Werner-like state interacting with a thermal reservoir. Starting from Werner-like states, we have shown that entanglement sudden death and decay of both the quantum discord and classical correlation are accelerated by the different factors: thermal photons, cavity decay and the purity of the initial state. By these factors, the death-start points of the correlations can be controlled and the two-qubit states have no correlations that can be determined. There is no sudden death for quantum discord and classical correlation.


Visualisation of a Three-Dimensional (3D) Object’s Optimal Reality in a 3D Map on a Mobile Device

Adamu Abubakar, Akram M. Zeki, Haruna Chiroma, Sanah Abdullahi Muaz, Mueen Uddin, Nadeem Mahmood, Tutut Herawan,
Abstract :
Prior research on the subject of visualisation of three-dimensional (3D) objects by coordinate systems has proved that all objects are translated so that the eye is at the origin (eye space). The multiplication of a point in eye space leads to perspective space, and dividing perspective space leads to screen space. This paper utilised these findings and investigated the key factor(s) in the visualisation of 3D objects within 3D maps on mobile devices. The motivation of the study comes from the fact that there is a disparity between 3D objects within a 3D map on a mobile device and those on other devices; this difference might undermine the capabilities of a 3D map view on a mobile device. This concern arises while interacting with a 3D map view on a mobile device. It is unclear whether an increasing number of users will be able to identify the real world as the 3D map view on a mobile device becomes more realistic. We used regression analysis intended to rigorously explain the participants’ responses and the Decision Making Trial and Evaluation Laboratory method (DEMATEL) to select the key factor(s) that caused or were affected by 3D object views. The results of regression analyses revealed that eye space, perspective space and screen space were associated with 3D viewing of 3D objects in 3D maps on mobile devices and that eye space had the strongest impact. The results of DEMATEL using its original and revised version steps showed that the prolonged viewing of 3D objects in a 3D map on mobile devices was the most important factor for eye space and a long viewing distance was the most significant factor for perspective space, while large screen size was the most important factor for screen space. In conclusion, a 3D map view on a mobile device allows for the visualisation of a more realistic environment.


A bandwidth efficient video conferencing system for streaming gesture based video using a Pareto minimal approach to D-HOH-SI individuals

S. Swarna Parvathi, K.S.Easwarakumar, N. Devi, Raju Das,
Abstract :
Deaf, Hard-Of-Hearing and Speech-Impaired (D-HOH-SI) individuals have a specific interest in the development of affordable high-quality videoconferencing as a means of communicating with their family members and peers using sign language. Unlike Video Relay Service, which is intended to support communication between a caller using sign language and another party using spoken language, videoconferencing can directly be used either between two deaf signers or between a caller using sign language and the other using spoken language without the need of an interpreter. This paper proposes a Bandwidth Aware Gesture Based Layered (BAGBL) framework for sign language recognition based video conferencing application. Assuming a D-HOH-SI individual at the sender side, the proposed framework uses shape energy trajectory of hand sign gesture for video layering, a Multi-dimensional Multiplechoice Knapsack Problem (MMKP) based gradational hull pareto minimization heuristic called MMKP based Pareto Minimization Heuristic for Substream Scaling (MPMHSS) and a heuristic for substream scheduling which is based on Dynamic Multilevel Priority (DMP) called Modified DMP packet scheduling (MDMP) mechanism. At the receiving side, our framework includes an automatic sign language recognizer to recognize the sign language gesture and a speech synthesizer to convert the recognized words to speech. Our framework intelligently forms and selects video layers from a video sequence to maximize the video quality. Using extensive simulation and mathematical analysis we show that the proposed solution: (i) is efficient in terms of recognition rate (ii) achieves high radio resource utilization, (iii) maximizes the received video quality.


The Development of a Prototype of the Campus Guide Mobile Application

Jaegeol Yim, Jaehun Joo, Gyeyoung Lee, Kyubark Shim,
Abstract :
We have developed a so-called campus guide mobile application running on Android smart phones. Nowadays, a smart phone is equipped with many sensors - some of them are pretty accurate, a powerful processor, and large capacity secondary memory devices. Making use of these features of smart phones, we have made the campus guide a location-based service in that it determines where the user is located, which building the user is interested in, and plays the video which is related to the building. Our implementation of the application is briefly described in this paper.


A completely monotonic function involving the gamma and tri-gamma functions

Feng Qi,
Abstract :
In this paper we provide necessary and sufficient conditions on $a$ for the function $ \frac{1}{2}\ln(2\pi)-x+\bigl(x-\frac{1}{2}\bigr)\ln x-\ln\Gamma(x)+\frac1{12}{\psi(x+a)} $ and its negative to be completely monotonic on $(0,\infty)$, where $a\ge0$ is a real number, $\Gamma(x)$ is the classical gamma function, and $\psi(x)=\frac{\Gamma(x)}{\Gamma(x)}$ is the di-gamma function. As applications, some known results and new inequalities are derived.


Quantum information of two three-level trapped ions irradiated by laser beams

M. Abdel-Aty, F. N. M. Al-Showaikh,
Abstract :
Quantum information of two particles taking into account the time-dependent laser field is discussed. Considering the initial pure state of the ions, we discuss the properties of the entanglement due to the concurrence and quasi-probability distribution via Wigner function. Although, the results are presented in a general framework, we have realized controllable coupling between the qubit and field by inserting an additional factors between them.


An On-line Analytical Data Mining (OLAM) Prototype for Telecommunication Data Mining International Calls

A. Darwish and Sapna Tyagi,
Abstract :
In Nowadays, the telecommunication market is rapidly expanding and becoming highly competitive especially in international calls. The telecommunication companies have several millions of daily international call records. The huge corpus of database could be used to study the trend of customer. The main objective of this paper is to develop a model to decision system support. One of the main problems addressed in this paper is the shortage of quickly and accurate tool to process these data using data mining techniques. In this paper we designed an Online Analysis Data Mining (OLAM) prototype to help in the analysis of telecommunication data to support decision makers using Microsoft SQL server 2005 and SSAS 2005. We have also used association rules, clustering, Naďve Bayes, decision tree, and linear regression which have given us different views to the same data.


A new triangulation algorithm from 3D unorganized dense point cloud

xiaopeng wei,
Abstract :
This paper presents an algorithm for triangular mesh generation from unorganized points based on 3D Delaunay tetrahedralization and mesh-growing method. This algorithm requires the point density to meet the well-sampled condition in smooth regions and dense sampling in sections of a great curvature and two close opposite surfaces. The principle of the algorithm is as follows. It begins with 3D Delaunay tetrahedralization of all sampling points. Then extract part of triangles belonging to the surface as the seed facets according to the rough separation characteristics which based on the angle formed by the circumscribing balls of incident tetrahedrons. Finally, the algorithm grows the seed facets from front triangles to all triangles of the surface. This paper shows several experimental results which explain this approach is general and applicable to various object topologies.


Numerical Investigations of Turbulent Liquid Flows through a Centrifugal Impeller by Using Structural-Function LES

Zhuq-ing Liu, Xue-lin Tang, Fu-jun Wang, Yao-jun Li, Yu-lin Wu,
Abstract :
Based on second-order structural functions, a sub-grid eddy viscosity model is proposed for Large Eddy Simulation (LES) of turbulent flows through a centrifugal impeller in a rotating coordinate system. The current model is based on the modified Karman-Howarth equation of resolved scale turbulence of LES and allows energy transfer between resolved and unresolved scale turbulence, but the sub-grid eddy viscosity model is a function of structural functions and measures the ratio of cascade energy to the dissipation. During the simulation, the finite volume method is used to discretize the filtered governing equations, the SIMPLEC algorithm is used to solve the discretized equations and body-fitted coordinates are used to simulate turbulent flows in complex geometries. The computational results of turbulent flows in a centrifugal impeller are used to illustrate the effectiveness of the model and the predicted relative velocity distributions follow the practical rules of turbulent flows inside an impeller. The simulated pressure is in good agreement with experimental data.


Rotation-Invariant Texture Image Retrieval Based on Multiscale Geometric Analysis and WARD

Zhengli Zhu, Chunxia Zhao, Yingkun Hou,
Abstract :
In this paper, we present an effective approach for rotation-invariant texture image retrieval based on multiscale geometric analysis and weighted average relative distance(WARD). The anisotropy of nonsubsampled contourlet transform (NSCT) can help us to represent the texture in image more effectively than traditional orthogonal wavelet transforms. We achieve rotation-invariant features by combining average energy with average standard deviation of all subbands at each NSCT scale. We propose an effective similarity measure, and this measure need not calculate the statistics of the entire image database in advance, so it has much wider application situation, e.g., internet. Experimental results demonstrate that the proposed approach improves retrieval accuracy from 73.3% to 77.6% on the rotated database, compared with Dual-Tree-Complex Wavelet Transform (DT-CWT)- based approach.


Doubly Constrained Robust Constant Modulus Algorithm

Xin Song, Jinkuan Wang, Qiuming Li, Han Wang,
Abstract :
The constant modulus algorithm (CMA) has been known as blind adaptive beamforming because it requires no knowledge about the signal except that the transmitted signal waveform has a constant envelope. But in practical applications, the performance of the linearly constrained CMA is known to degrade severely in the presence of even slight signal steering vector mismatches. To account for the mismatches, a novel robust CMA algorithm based on double constraints is proposed via oblique projection of signal steering vector and worst-case performance optimization. To improve robustness, the weight vector is optimized to involve minimization of a constant modulus algorithm objective function with penalty for the worst-case signal steering vector by the Lagrange multiplier method, in which the parameters can be precisely derived at each iterative step. Moreover, the online implementation of the proposed algorithm has a low computational load. A theoretical analysis for our proposed algorithm in terms of the choice of step size, convergence perforamnce and SINR performance is presented in this paper. The proposed robust constrained CMA suffers the least distortion from the directions near the desired steering angle, provides a significantly improved robustness against the signal steering vector mismatches, yields better signal capture performance and improves the mean output array SINR as compared with the conventional constrained CMA. The numerical experiments have been carried out to demonstrate the superiority of the proposed algorithm on beampattern control and output SINR enhancement.


Global Exponential Stability for Hopfield Neural Networks with Varying Delays

Gao Yuan,
Abstract :
The main purpose of this paper is to study the global exponential stability of the equilibrium point for a class of Hopfield neural networks with varying delays. A new sufficient condition for the global exponential stability of neural networks is obtained by using M-matrix analysis. The condition is easy to check in practice. A numerical example is worked out by using the results obtained to illustrate it


The Evolution of Communication Network Architecture

Jinxin Zhang, Mangui Liang, Aqun Zhao,
Abstract :
Communication network architecture has experienced tremendous improvement from the ARPANET to IP with the number and traffic forms of users. Although IP is widely considered as the platform for future network, unfortunately, it is burdened by its her- itage of several decades. Nowadays, the bottleneck of bandwidth mainly lies in IP router not links. In this paper, we argue that one of the principal reasons for this is routing and forwarding planes are coupled together by analyzing the evolution of com- munication network architecture. Then we proposed a new network architecture to pro- vide faster forwarding speed. Simulation scenery shows this architecture is practical. Furthermore, we compared performance metrics (forwarding speed, length of address and total cost) with today’s IP network, our results indicate that forwarding speed is increased 72% of IP, the length of address is much less than IPv4 address and the total cost can be decreased 76% of the current network. Finally, we discuss several impor- tant issues of the new network architecture including address, network connection and end-to-end QoS as well as architecture extension.


Quaternion Encryption Scheme Modification Resistant to Known Plaintext- Ciphertext Attack and its Hardware-Oriented Implementation

Evgueni Doukhnitch, Alexander G. Chefranov, Ahmed Y. Mahmoud,
Abstract :
Quaternion encryption scheme (QES) is shown to be susceptible to the known plaintext-ciphertext attack (KPCA) due to not proper choice of the frame size and the procedure of secret quaternion updating. In this paper, we propose a modification of the QES (M-QES) which is resistant to the KPCA. The M-QES is based on adjusting the frame size and the quaternion update procedure. An approach for effective hardware (HW-QES) implementation of the proposed algorithm is discussed. The HW-QES uses mainly addition and shift operations. Experimental results show that the proposed M-QES and HW-QES are six-eight times more effective in the encryption quality of signals than the original QES. Additionally, M-QES is shown to be significantly more effective in the encryption quality of images than the original QES. Our results show that, the performance of the HW-QES is only 10% worse than that of QES.


Selfish Game-Theoretic Approach for Dynamic Spectrum Sharing with Software Defined Radio Networks

Desheng Li,
Abstract :
To analyze the dynamic spectrum access of Cognitive Radio Networks (CRN), this paper proposes the selfish game-theoretic model for multi-hop networking with wireless nodes, which matches well with the physical administrative structure in real-life situations. User communication session is investigated via a cross-layer optimization approach, with joint consideration of power control, scheduling, and routing. Both the channel quality and the spectrum substitutability are discussed. A utility function is built, for the secondary user to obtain the spectrum demand function. In addition, in terms of spectrum access opportunities, an equilibrium pricing scheme is presented to shows that it is close to optimal in most scenarios. The proposed Game-theoretic End-to-end Spectrum Sharing algorithm (GE2SS) highlights the trend of spectrum pricing design that it is not necessarily bad for the network users to behave selfishly. Simulation and experimental results are presented as verifications.


High Variability Resilient in Nano-Scaled Technologies for Low power 7T-SRAM Design

Shyam Akashe, Sanjay Sharma,
Abstract :
High variability in nano-scaled technologies can easily disturb the stability of a carefully designed standard 6TSRAM cell, causing access failures during a read/write operation. We propose a 7T-SRAM cell to increase the read/write stability under large variations. The proposed design uses a low overhead read/write assist circuitry to increase the noise immunity. Use of an additional transistor and a floating ground allows read disturb free operation. While the write assist circuitry provides a floating ground during a write operation that weakens cell storage by turning off the supply voltage to ground path of the cross-coupled inverter pair. This allows a high speed/low power write operation. Monte Carlo simulations indicate a 200% increase in the read stability and a boost of 124% in write stability compared to a conventional 6T-SRAM design, when subjected to random dopant fluctuations, line edge roughness, and poly-granularity variations. HSPICE simulations of a 45nm 64x32 bit SRAM array designed using standard 6T and proposed 7T SRAM cells indicate a 31% improvement in write speed, 30% decrease in write power, read power decreases by 60%, and a 44% reduction in the total average power consumption is achieved with the proposed design.


Numerical Simulations of Circular Anchor Plates under Pull-out in Sand

Khairul Anuar Kassim, Ramli Nazir,
Abstract :
This research presents the studies conducted on a type of soil anchor, a circular anchor plate, and its pullout capacity. Soil anchors are used as foundation system for the soil structures that needs to pull-out load. Experimental and numerical analysis investing the pullout test of 0.1m diameter of circular horizontal anchor plates in cohesion less soil show that maximum pullout increase with embedment ratio in sand. This paper investigated the ultimate pullout capacity of circular horizontal anchor plate in cohesion less soils subjected to pullout test in loose sand. An agreement between pullout loads from chamber box and finite element modeling using PLAXIS based on 0.4m analyzed maximum displacements for circular horizontal anchor plates to embedment ratio of 4. In the research, The Hardening Soil Model is using in PLAXIS. The numerical analysis based on PLAXIS predicted higher pullout load in loose sand due to experimental results but in final showed a good agreement with physical results.


Numerical Analysis of Buried Pipe under Wheel Loads by Three Dimensional at Finite Difference Method (FDM)

Khairul Anuar Kassim, Ramli Nazir,
Abstract :
The behavior of steel pipe during wheel load was studied in this paper by FLAC 3D. A steel pipe is buried at a shallow depth beneath a roadway. An analysis is needed to evaluate the effect of wheel loading on the road surface deflection and pipe deformation. The top of the pipe is 1.5m beneath the road surface. The pipe has an outer diameter of 4m and is 0.12m thick. The pipe excavation is 15m wide and 6m depth. The steel pipe is placed on a 0.4m thick layer of soil backfill, and then soil is compacted around the steel pipe. The wheel load is increased during failure occurs in the soil. Soil backfill behavior has been considered with Mohr-Coulomb Model in analysis. The analysis defines the failure load and the resulting soil and pipe displacement.

  Home   About us   News   Journals   Conferences Contact us Copyright naturalspublishing.com. All Rights Reserved