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    EDITORIAL BOARD


    special issue on Innovations in information Embedded and Communication Systems) (2016)

    SIMULATION OF MULTIMODAL BIOMETRICS WITH CRYPTOSYSTEM IN HOSPITAL SUITES

    By Lalithamani N. , B. Sruthi

    Abstract

    ABSTRACT Objectives: To apply Multimodal Biometrics in the authentication process in hospital suites, fusing two Biometric traits namely face and fingerprint at the feature level to improve the security. Methods/Statistical analysis: This paper deals with using face and fingerprints, which are fused at the feature level and processed further. Majorly, techniques for pre-processing include Histogram Equalization for face, and Skeletonizing and thinning for fingerprints. In the next stage, Feature Extraction techniques like PCA (Principal Component Analysis) for face and Ridge Endings and Bifurcation extractions for fingerprint are used. Then once fused at feature level, shuffling is done and the fusion vectors are encrypted. These are used for authentication in hospital suites. Findings: In general, Multimodal Biometrics offers higher security than Unimodal when implemented efficiently. This concept can be used in hospital suites, where security is prime importance and a breach of the same can endanger the lives of patients. Application/Improvements: As mentioned, this concept can be highly useful in hospital suites, where close monitoring of access to VIP suites is necessary. Since a breach of security can be very sensitive in such places, it is important to employ maximum protection for the authentic-cation process. Areas where it could be improved further can be in increasing the number of traits for tighter security, and exploring apt fusion methods for the same to improve efficiency. Also, in future different encryption algorithms can be tested and tried.

    SECURED IMAGE TRANSFORMATION USING DISORGANIZED CHART PATTERN TECHNIQUE

    By D.Saravanan

    Abstract

    ABSTRACT An Enhanced disorganized chart pattern based algorithm for image encryption to improve the security of the algorithm.. The basic idea behind the proposed algorithm is to alter the coupling direction used to update the map variables. The altered coupling direction results into a totally different set of initial conditions and map variables of three disorganized chart pattern Based on experiments will show that the enhanced algorithm with chosen coupling direction can encrypts the color digital images. The image which given as input is retrieved as same as the original image while decrypting. Here many distortions take place when the image is converted pixel by pixel, this helps in high secrecy of the encrypted image.

    DATABASE SECURITY INCURSION RECOGNITION TECHNIQUE USING NEURAL NETWORK

    By D.Saravanan

    Abstract

    ABSTRACT Database Intrusion Detection System (IDS) is an expert system looking for evidence of attacks on known vulnerabilities of the system. It holds a statistical model of the behaviour of a user on a system under surveillance. There are several techniques, protocols, and algorithms to increase the security level of database. In such works, there is a lack of time complexity analysis of the techniques. This time complexity has occurred due to the comparison process carried out at each time the user query is given i.e., comparing the profiles of online transactions and the stored authorized transactions each time when the query is received. This system time complexity also affects the system performance in terms of their precise security. It learns the habits a user working with the computer and to raise warnings when the current behaviour is not consistent with the previous learnt patterns, thus detecting whether the user is authentic or not. The system can be implemented using MATLAB. MATLAB is a numerical computing environment. It allows matrix manipulations, plotting of functions and data implementation of data. The learning process by neural network avoids the unauthorized transactions in the DBMS and reduces the time complexity the project improves the performance of the database system. The neural network implementation will show the effectiveness of the proposed IDS technique in securing the database from the intruders. The performance of the proposed technique is evaluated by utilizing different statistical performance measures.

    AN EFFICIENT RESOURCE ALLOCATION STRATEGY BASED ON IMPROVED PARTICLE SWARM OPTIMIZATION (IPSO)

    By Naresh, T1 Department Sandip

    Abstract

    ABSTRACT Resource allocation is a method that is deploy to allocate the accessible resource in a best way. It is the arrangement of activities and the resource needed by those activities while returns into consideration both the resource availability and the time. The proposed method discusses optimal resource discovery and dynamic resource allocation. The proposed method consists of two phases namely resource discovery and resource allocation. For resource discovery, the proposed method uses the Hierarchical Agglomerative Clustering Algorithm (HAC). Based on the HAC algorithm the proposed tree construction is generated. After that the resources are allocated by hybrid optimization algorithm. The proposed method use the Improved Particle Swarm Optimization and Cuckoo Search algorithm (IPSOCS).

    NEED OF AUTOMATION IN COMMON EFFLUENT TREATMENT PLANT

    By Sravanthi Animireddy, T. Chandra Shekhar Rao

    Abstract

    ABSTRACT Common effluent treatment plant (CETP) is used to treat effluents from a cluster of Small & medium scale industrial units. CETP not only helps the industries to control the pollution, but also provides cleaner environment and services to the society. Automation of CETP has many benefits in terms of savings of chemical, energy, O&M cost in addition to generate better quality of treated water. Most of the CETPs in India are operated manually due to cost involved in automation without realizing savings of these long term hidden costs. Advance innovations in technology offers compact and economic tools to automate CETPs. Automation can be implemented at least in the areas where there is a major contribution of the total annual costs. Usage of online measurement devices can also reduce the labour cost since there is no necessity of sampling and testing in laboratory for several quality parameters and to adjust the controls according to that. Treated water quality will also be improved due to the accuracy in measurements of quality parameters and timely control of operation of different equipment’s. Extent of automation which gives the economic benefits can be chosen by doing life cycle cost analysis before selecting any automation scheme. This paper illustrates the need of automation and its advantages in automation of CETPs.

    A COMPARISON OF SECRET IMAGE HIDE METHODS OF STEGANOGRAPHY AND VISUAL CRYPTOGRAPHY

    By Saad Al-mutairi

    Abstract

    ABSTRACT During the clandestine data transmission, to protect a secret data from the hackers or intruders is one of the difficult task. In this era, when technology grows, simultaneously the challenges of the technologies also increasing rapidly. In connection with that, while selecting any technology for the particular process, we are in position to check strengthen of the technology towards to the attackers or hackers. In this paper, we have been presenting a comparison statements of different secret image hide methods. To prepare this comparison, we have chosen two popular image hide methods of steganography and visual cryptography. The steganography is a secret image encode method, which will encode a secret image into non-secret cover image. On other hand, visual cryptography is an image hide method. In this method, the original secret image is split into different shares. A single share will not be described the original information. However, the original information can be retained when combining all shares together. In this proposed work, both methods are differentiated based on the different parameters of reconstruction quality, execution time, method strength and complexity.

    TRAWLER OCEAN CARE SYSTEM

    By J. Vivek1, M. Lakshmi, D. Manuel

    Abstract

    ABSTRACT Based on the recent survey border crossing of Indian fisherman are unsusceptible increased, to such an amenable problem a safe system must be designed. To overcome this situation a trawler ocean care system is proposed to aid the people who are crossing the border. This work is an association of hardware peripherals GPS, Microcontroller and buzzers. This device will be responsible for monitoring, alerting, controlling and stop engine, to provide a safe journey to the fisherman.

    CONJUNCTIVE KEYWORD SEARCH ON E-HEALTH RECORDS BASED 0N K-ANONYMIZATION TECHNIQUE

    By S. Sneha , P.Asha

    Abstract

    ABStract An electronic health care system greatly enhances the patient healthcare records which are stored in the cloud server. Searchable encryption scheme is used which enhances the search mechanism. Conjunctive keyword search helps the authorized users to access the records by giving multiple keywords, so that it becomes difficult for the attackers to guess the keyword and retrieve the records. Re-encryption scheme provides more security to the records by reencrypting the encrypted index before uploading them into cloud server. Since the patient’s healthcare records consist of sensitive information, it may be inconvenient for the patient when his records are accessed by everyone. To overcome the problem in our proposed work we introduce the concept called K-Anonymity which is used so that it gives only a partial access to the authorized users by using two methodologies suppression and generalization. This has

    A STUDY ON HYPERSPECTRAL DATA IMAGING BASED ON SPATIO SPECTRAL SCANNING

    By K. Rajakumar, S. Srinivasan

    Abstract

    ABSTRACT Hyperspectral data is one of the important breakthroughs in remote sensing. It has a capability of separating the different and describing the objects of same size in detail. It processes the image in the large- number, narrow and it can produce data with sufficient resolution. Hyperspectral images used to identify the spectral information and differentiate unique materials. It also provides the information by the means of very accurate and extraction of various information that relates to remote based information. Hyperspectral remote sensing purpose is to measure the various components of the Earth system that is acquired as images for scientific applications and research purpose. Hyperspectral remote sensing can be categorized the information into two ways: Feature space and Spectral space. The feature space method is not efficient because the data dimension is determined to describe the patterns. The spectral based is used for extracting anomalous pixel vector at endmember extraction. This will validate the both synthetic and real Hyperspectral data images. The scatter matrix that is preserved in the means of pixel by spatial domain and the projection of optimal discriminative is obtained with the help of scattering of spectro-spatial thus maximizing a modified scatter of information.

    MULTIPLE TUMOR & INFECTION DETECTION IN MRI BRAIN IMAGE USING SVM CLASSIFIER

    By Shrikant Burje1, Sourabh Rungta, Anupam Shukla

    Abstract

    ABSTRACT A support vector machine (SVM) classifier is being proposed for classification of brain tissues in magnetic resonance photos (MRI). A wavelet based totally texture features set is derived. The most useful texture capabilities are extracted from regular as well as tumor regions through the usage of spatial gray level dependence technique. The proposed technique resolves the massive trouble of category strategies. These most efficient functions are then used to categories the brain tissues into benign and malignant tumor. The overall performance of the set of rules is evaluated totally based on a sequence of brain tumor images.

    ADAPTIVE CENSUS AND INTERPOLATION BASED DISPARITY ESTIMATION USING WEIGHTED AUTOREGRESSIVE MODELS

    By Iswariya, E1 , Rajesh Kannan, R2

    Abstract

    ABSTRACT This paper deals with an adaptive general scale interpolation algorithm that is capable of arbitrary scaling factors considering the non-stationarity of natural images. The proposed AR terms are modeled by pixels with their adjacent unknown HR neighbors. A novel stereo matching algorithm is proposed that utilizes color segmentation on the reference image and a self-adapting matching score that maximizes the number of reliable correspondences. Modified Census Transform is a form of non-parametric local transform used in image processing within a square window to a bit string, thereby capturing the image structure. The centre pixel’s intensity value is replaced by the bit string composed of set of boolean comparisons such that in a square window, moving left to right. A new technique is used and found a solution for correspondence problem that makes use of non-parametric local transforms as the basis for correlation. Non-parametric transforms rely on the relative ordering of local intensity values, and not on the intensity values themselves. Correlation using such transforms can tolerate a significant number of images. This can result in improved performance near object boundaries when compared with conventional methods such as normalized correlation.

    A REVIEW OF LUMINANCE AND COLOR INVARIANTS BASED PARTIAL MEDICAL IMAGE RETRIEVAL SYSTEMS

    By Lakshmi R Nair , Kamalraj Subramaniam

    Abstract

    ABSTRACT The color of the surface is a very significant feature in classification and recognition process of the object. Additionally, the color of the object differs due to variation in illumination and condition of the surface. Research on analyzing appropriate methods for medical information retrieval is highly significant in this scenario. With the rapid growth of medical dataset in specific to the digital library is becoming a difficult issue towards search based data/image retrieval. For obtaining the best method for image retrieval, an extensive study of the previous literature is required. This paper describes an overview of estimation procedures related to RGB images’ color invariants that are prevalent currently and also provides a user interactive approach for efficient image retrieval system. Additionally,contributed towards enhancing the performance of partial image retrieval system at various illumination stages.

    PHYSIOLOGICAL ANALYSIS OF HYPERTENSION PATIENTS BY MONITORING THE BRAIN WAVES

    By R. Mohan Raheja, L. Kishore, I. Joe Louis Paul

    Abstract

    ABSTRACT The inability and the negligence in the detection of diseases is a major reason in the delay of treatment which may prove fatal. It is not possible for regular checkups in this time deprived world. Moreover, regular checkups are not feasible to everyone. The brain is the most interesting part of the human body. It controls the vital functions of the body and therefore any abnormality in the brain will reflect in the entire body and vice versa. The control of the brain is by the transmission of electric signals from and to the various parts of the body. The study and observation of these electrical signals will help us to find a lot of abnormalities which occur in the brain. Hence, this proposed work aims at overcoming the deficiency in time and money needed for the regular checkups. This is achieved by monitoring the brainwaves of the patient. The brainwave pattern of the patient is compared with the normal brainwave pattern. If an anomaly is observed in the patient’s brainwave pattern further comparisons with disease brainwave patterns are made. The disease pattern which matches with the patient’s pattern is identified as the disease. The patient is recommended for further tests on the disease. In this work, only hypertension patients are considered for the study of physiological analysis using Weka tool.

    EXPERIMENTAL EVALUATION OF APRIORI AND EQUIVALENCE CLASS CLUSTERING AND BOTTOM UP LATTICE TRAVERSAL (ECLAT) ALGORITHMS

    By M. Sinthuja1, P. Aruna, N. Puviarasan

    Abstract

    ABSTRACT Frequent pattern mining is the beginning of association rule mining. Association rule mining is the strongly scrutinized techniques in data mining. The basic algorithms of Apriori and ECLAT are the most identified algorithms for mining frequent patterns in association rule mining. This paper describes the application of these two algorithms that use many to achieve maximum efficiency with regards to turnaround time and memory capacity. Both algorithms are executed using discrete data sets and are further analyzed based on their performances. The performance analysis is based on different parameters such as support, speedup etc., with different quantities of datasets.

    FREQUENCY CONTROL OF AN ISOLATED HYBRID POWER SYSTEM USING PARTICLE SWARM OPTIMIZATION OPTIMIZED PID CONTROLLER

    By Israfil Hussain, Sudhanshu Ranjan, D.C Das , N. Sinha

    Abstract

    ABSTRACT The mitigation of frequency fluctuation using Particle Swarm Optimization (PSO) based controllers for an isolated hybrid power system is explored in this paper. The proposed system consists of solar photovoltaic (PV), electric water heater (EWH) and diesel engine generator (DEG) and battery energy storage system (BESS). The intermittent output power of PV and load variations cause frequency fluctuations with several adverse effects on the power system. This paper presents a methodology for maintaining system frequency within acceptable employing electric water heater as a controllable load. The generating units and EWH system are equipped with PSO based proportional–integral (PI)/ proportional–integral–derivative (PID) controllers. The solutions obtained through the optimization are capable of handling higher variations in the controllers’ gains without a significant decrease in the system performance. Also, a comparison is made between the PI and PID controllers to show the effectiveness of the proposed scheme. MATLAB/Simulink was used for simulation to verify the performance of the proposed system.

    A REPUTATION BASED TRUST MODEL FOR MANET USING ENHANCED AODV WITH TBR ALGORITHM

    By J.Gautam, B.Sudarsana Gayatri, V. Krithika , S. Shanmuga Priya

    Abstract

    ABStract Mobile ad hoc network (MANET) is a local which necessitate more security. The term “ad hoc” refers to self-configuring nodes that do not have a central entity to govern them. Network security plays a decisive role in MANET and the traditional way of providing impedance to the networks through firewalls and encryption software is no longer effective and sufficient. In this paper, a quantitative method based on trust evaluation for detecting malicious nodes in the Mobile ad-hoc network and endowing an optimal path for packet transmission is proposed using Trust based Routing algorithm. The intended system is a behavior anomaly based system which crafts it dynamic, robust, scalable and configurable. The proposed method is verified by running simulations with mobile nodes using the Ad-hoc on-demand distance vector (AODV) routing called as Enhanced Ad-hoc ondemand distance vector (EAODV).

    ISOLATION OF BLACKHOLE ATTACK IN MANET USING MAODV PROTOCOL WITH CA ALGORITHM

    By J. Gautam, S. Sindhuja , D. Nagavalli

    Abstract

    ABSTRACT Mobile Ad-hoc Network (MANET) is a self-organized system encompassed of mobile nodes without any infrastructure. Security is a decisive requisite in Mobile Ad-hoc Network (MANETs) when accessed to wired networks. Blackhole attack is a arduous issue to be addressed in MANET. Blackhole node falsely claims that it has the shortest path to the destination and dumps the packet that is supposed to be forwarded. In order to reduce the effects of Blackhole attack, we are modifying the AODV protocol and proposing counter attack algorithm that provides a efficient way to mitigate such attacks.

    ENERGY RESOURCE OPTIMIZATION IN WIRELESS AD-HOC NETWORK USING DYNAMIC STATES

    By J. Gautam, B. Lukshana Fathima, K.S. Sangeetha , P.M. Mohamed Muzammil

    Abstract

    ABSTRACT Wireless Ad-hoc network is the decentralized type of network and it does not rely on pre-existing infrastructure. The Energy efficiency continues to be a key factor in limiting the deploy ability of ad-hoc networks. Deploying an energy efficient system exploiting the maximum life time of the network has remained a great challenge since years. The major concern in Wireless network in recent days is Energy consumption. There are numerous algorithms proposed to overcome this issue. In this paper, we proposed a algorithm called Energy Efficiency Dynamic State (EEDS) algorithm. This algorithm is designed to increase the network lifetime by continuously monitoring the individual nodes in the network, thereby it increases the quality of service of the network.

    HIGH PERFORMANCE WIRELESS COMMUNICATION CHANNEL USING LEACH PROTOCOLS

    By Ch.Usha Kumari , M. Ramya Krishna

    Abstract

    ABSTRACT Wireless sensor networks take wide range of practical and useful applications. But there are many critical problems for efficient operations of sensor networks in real time applications. Sensor networks contain of number of nodes but with limited battery power and also wireless communications are deployed to collect useful information from the sensor node. It is very difficult for the sensor network to operate for a long period in an energy efficient manner for gathering sensed information. Energy saving is one critical issue for sensor networks since most sensors are equipped with non-rechargeable batteries that have limited lifetime. The power resource of each sensor node is limited. In this paper, we propose minimizing energy dissipation and maximizing network lifetime which is very important issue in the design of routing protocols for sensor networks. This paper we propose a new improved cluster algorithm of LEACH (Low Energy Adaptive Clustering Hierarchy) protocol which is intended to balance the energy consumption of the entire network and extend the lifetime of the network.

    A CASE STUDY ON SELECTION OF APPROPRIATE PROCUREMENT SYSTEM FOR SMALL SCALE CONSTRUCTION INDUSTRY

    By N.Ganapathy Ramasamy , Dhanya R

    Abstract

    ABSTRACT The development and practice of appropriate procurement systems helps to avoid problems related to time &cost and to attain the project specified goals. One of the characteristics of the construction industries over the last three decades or so has been the usage of various procurement methods which have investigated the criteria for their selection and performance in terms of time, cost and quality. Selecting the appropriate procurement system for construction projects is a complicated and challenging task. To assist the decision-making process, procurement selection tools and techniques have been developed. The main aim of this study is to develop a framework using Statistical Package for Social Sciences (SPSS) Software by performing Descriptive Analysis using Weighted Average Mean (WAM), Standard Deviation, Variance, Correlation and T- Test are used to compare the large scale construction industries and small scale construction industries for Construction Procurement Systems. A series of literature reviews and Questionnaire surveys were conducted to analyze the current situation of procurement system in construction industry. Traditional Procurement method is the most widely used method in the small scale and middle scale industries. Non Traditional Procurement like Design build and Engineering Procurement Construction (EPC) is being adopted by large scale industries. The framework developed in this paper gives opportunities to the small and middle scale industries to go for the Non – Traditional Procurement methods as it optimizes time and cost for the construction project by selecting the most appropriate procurement system.

    SECURED MOBILE AD-HOC NETWORK WITH MODIFIED DSR AND SNUPM ALGORITHM

    By J. Gautam, K. Vishali , P. Malathi

    Abstract

    ABSTRACT Security is a decisive requisite in Mobile Ad-Hoc Network (MANETs) when assessed to wired networks. MANETs are more suspicious to security attacks due to the need of a reliable centralized cloud and scanty resources. In MANET, we have malicious nodes that overcome the network protocols thereby diminishing the network’s performance. The development of mobile networks has implicated the need of new IDS models to deal with new security issues in these communication environments. In this paper, we proposed a Secured Network using Promiscuous Mode (SNuMP) which is a part of Intrusion Detection System where it can repair the malicious nodes and convert back them into a normal node for effective network performance.

    MITIGATION OF DENIAL OF SERVICE ATTACK USING ICMP BASED IP TRACKBACK

    By J. Gautam, M. Kasi Nivetha, S. Anitha Sri P. Madasamy

    Abstract

    ABSTRACT: Denial of Service (DoS) is a major threat in Network Communication which floods a remote host network with large amount of traffic thereby denying services to the legitimate computer requesting resources. In this paper an ICMP traceback message scheme is proposed to solve the problem of finding the true origin of packets causing DoS. The main objective is to propose a method to trace back the attacker without the involvement of reflector in order to reduce the traffic. The proposed method is a hybrid of bloom filters and iTrace. This method reduces the traffic and the number of ICMP messages. In bloom filters, edge router produces the ICMP messages and in iTrace each router generates ICMP messages.

    FRUIT FRESHNESS MONITORING SYSTEM DURING TRANSPORTATION -An RFID and WSN based Monitoring System

    By Joe Louis Paul, S. Sasirekha, S. Jesu Iswarya, R. Praveen Chandru

    Abstract

    ABSTRACT In India, 104 million tons of perishable products such as fruits and vegetables are transported annually between Indian cities, out of which 100 million tons of products are transported in non-refrigerated mode. If the quality change of these products during transportation is not monitored, may incur economic loss or damage to fruits. There are many systems currently available in the literature for monitoring the perishable fruits using Radio Frequency Identification (RFID) and sensor technologies. However, these systems lack in providing a comprehensive approach taking under consideration of energy consumption and compliance with the temperatures needed to preserve foods. To overcome this issue, there is an emerging need to use and integrate the efficient technologies such as RFID and Wireless Sensor Networks (WSNs) to monitor the ripening status of fruits for preventing the damage as well as to identify and track the exact presence of damage during transportation. In this work, the ripening status of the fruits can be determined by the amount of ethylene content (fruit ripening hormone) it produces using sensors and RFID. The uniqueness of the proposed system lies in identifying the condition of fruits in each box using RFID tag with unique identifier. This helps in tracking the fruit box depending upon its ripening status without even opening it. For achieving an efficient real-time monitoring, control and management of fruit freshness during transportation, an integration of WSN and RFID based system interfaced with Service Oriented Architecture (SOA) has been proposed in this work. This work aims to automate the fruit monitoring system by minimizing the system complexity and maintenance costs can be useful to suppliers with chain of warehouses, grocery retailers etc.

    A SIMPLE BIT LOADING ALGORITHM FOR LONG TERM EVOLUTION-ADVANCED VEHICULAR CHANNEL

    By Aniji John, Anitha P Mathew , Vinoth Babu K

    Abstract

    ABStract Increasing demand for energy efficient cellular networks has prompted considerable research on the topic green communication. Bit loading is a technique used in multicarrier communication systems like orthogonal frequency division multiplexing (OFDM) to assign bits efficiently based on the subchannel quality. In adaptive bit loading (ABL), the number of bits that can be transmitted in each subcarrier is determined by the signal to noise ratio (SNR) of the subcarrier. Margin adaptive (MA) algorithm is utilized to minimize the total transmitted energy. In this work, a simple bit loading algorithm (SBL) is proposed for a long-term evolution- advanced (LTE-A) vehicular channel to minimize the total energy required to transmit the target bits. Compared to other algorithms, SBL algorithm is less complex and convergent to the optimal solution in one iteration. The simulation results also prove that the algorithm minimizes computational complexity.

    A SIMPLE BIT LOADING ALGORITHM FOR LONG TERM EVOLUTION-ADVANCED VEHICULAR CHANNEL

    By Aniji John, Anitha P Mathew , Vinoth Babu K

    Abstract

    ABStract Increasing demand for energy efficient cellular networks has prompted considerable research on the topic green communication. Bit loading is a technique used in multicarrier communication systems like orthogonal frequency division multiplexing (OFDM) to assign bits efficiently based on the subchannel quality. In adaptive bit loading (ABL), the number of bits that can be transmitted in each subcarrier is determined by the signal to noise ratio (SNR) of the subcarrier. Margin adaptive (MA) algorithm is utilized to minimize the total transmitted energy. In this work, a simple bit loading algorithm (SBL) is proposed for a long-term evolution- advanced (LTE-A) vehicular channel to minimize the total energy required to transmit the target bits. Compared to other algorithms, SBL algorithm is less complex and convergent to the optimal solution in one iteration. The simulation results also prove that the algorithm minimizes computational complexity.

    IMPACT OF ADVANCED PLANNING TECHNIQUE IN INDIAN CONSTRUCTION INDUSTRY

    By N. Ganapathy Ramasamy1 , R. Devakandhan2 , Aravind3 , S. Ramasubramani4

    Abstract

    The aim of this research work is to study & analysis the Impact of advanced planning technique in Indian Construction industry, Construction Planning is under constant pressure to increase the quality and speed of its construction delivery processes. Construction planning plays vital role in the development of construction industry. There is still a huge discrepancy between execution and plan. Therefore, an efficient and effective planning method is intensively needed to enhance the project performance and to minimize the risk of cost overrun and delays. In Engineering and Construction, building construction schedule is prepared by visualizing 2D design documents of a building project. This process is difficult to associate mechanism in the 2D documents with their related construction activities, and then visualize the construction sequence. In advanced Planning technologies, visually representing the construction schedule along with the 3D BIM model components has the potential to aid this process by providing a common visual language for Planners. The research presented an assessment based survey to identify knowledge, features, benefits & barriers in implementation of 4D planning in construction project. Better visualization of works, reducing the conflicts between the design/execution were the key benefits in 4D planning as observed from an assessment.

    AN INTELLIGENT HYBRID APPROACH FOR BRAIN PATHOLOGY DETECTION IN MRI IMAGES

    By B.Deepa , M.G.Sumithra

    Abstract

    ABSTRACT Medical Image Processing is a complex and challenging field nowadays. Processing of MRI Images is one of the parts of this field for efficient brain pathology detection like tumor, asymptomatic unruptured aneurysms, Alzheimer's disease, vascular dementia, cerebral microbleeds in brain and multiple sclerosis (MS) in magnetic resonance (MR) images. The methodology used in this paper for brain pathology detection consists of the following steps: The first step includes pre-processing by a Wavelet Transform (WT) for removal of noises like Salt and Pepper noise, Gaussian, Speckle and Brownian noise, without affecting the image quality. The second step is to extract the features from the pre-processed image. The process of feature extraction is carried out by a Walsh- Hadamard Transform (WHT) methodology. The final step involves the detection of abnormality by segmenting the abnormal tissues using a combined methodology called Modified Fuzzy C-Means Clustering (MFCM) followed by Level Set (LS). The performance measure of proposed system is evaluated both by objective and subjective method. Feature extraction and segmentation is evaluated objectively by using confusion matrix and by measuring Accuracy, Sensitivity, Specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV), False Positive Rate (FPR) or Over Segmentation(OvS), False Negative Rate (FNR) or Under Segmentation(UnS), and Total False Rate or Incorrect Segmentation(InS). Subjective evaluation is done by taking the opinion of 35 expert radiologists that is average mean opinion score to corroborate the results of proposed method. From the obtained results it is understand that the proposed new amalgam technique is giving 95% accurate results for detecting abnormality in MRI brain images when compared to other hybrid methodology.

    POWER AWARE ENTROPIC HIDDEN MARKOV CHAIN ALGORITHM FOR CODE BASED TEST DATA COMPRESSION

    By S. Rooban , R. Manimegalai

    Abstract

    ABSTRACT Even though the scan architectures generally utilize advanced designs for testing reason, most of them remain an expensive design in test data volume and power consumption. A novel software based test data compression technique for testing System on Chip (SoC) is proposed in this paper. The proposed technique concurrently addresses the problem of reducing large test data volume and reduction of power consumption for scan testing on embedded Intellectual Property (IP) cores. In comparison to the aim of reducing only test data volume by recognizing the appearance of vector patterns and thereby eliminating don't-care bits using entropic Hidden Markov Chain (HMC) algorithm, here we address the task of decreasing power consumption. The proposed power proficient test data compression method is tested using the Verilog model of ISCAS'89 and ITC'99 benchmarks. Index Terms: Automated Test Equipment, Circuit under Test, System on Chip, Built-in self-test, low power test, Test data compression