As sensor-driven applications become progressively more integrated into our lives; issues linked to sensor privacy will become increasingly important. In wireless sensor networks, adversaries can make use of the traffic information for locating the monitored objects. Network coding has been shown to be an efficient approach to improve the wireless system performance. In a wormhole attack, the attacker can forward each packet using wormhole links and without modifies the packet transmission by routing it to an unauthorized remote node and pose a severe threat to many functions in the network, such as routing and localization. We developed a wormhole attack and are prevented by DAWN (Distributed detection Algorithm against Wormhole attack in wireless Network coding systems) algorithm using hash operation in cryptosystems. Simulation and methodical results reveal that our scheme acquires low energy consumption and less false positive rate than hotspot attack.

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Wireless Sensor Networks (WSNs) embodies sensor nodes, which are sufficiently little to deploy where legitimate base is not accessible. With an imperative of constrained battery power. Information accumulation has a noteworthy effect in vitality utilization of sensor nodes. In our proposed strategy Cluster-Based Priority Traverse method, portable sink cross in an element way bound by the static sink, which chooses the way from the prioritization routing table. Information that are sensed are not all of much significant. Sensed information are arranged into essential information, information that shows radical variety from past information and auxiliary information, information that fit in with typical sensed information pattern. Clusters in the system are organized based upon their Primary Data Count. Classification of information is performed by computing mean and standard deviation for the sensed within a group and discovering the information of extensive variety. To give high dependable navigate way to mobile sink to accumulate information from groups with high need sooner than low need cluster. Minimum Spanning Tree is developed for each group to all other clusters in the system. The performance of the network  is investigated through various simulations.

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An image-rich information network is a social media website which contains billions of images uploaded by users which are associated with information about owner, consumer, producer, annotations, and comments are forming heterogeneous image-rich information networks. In feature extraction has been  extract both global feature as visual and local feature as color for an image and the relevance feedback approach to increase retrieval accuracy and gives more personalized results for the user. In a hybrid approach which measures the similarity of images to retrieve based on the link based, content based and relevance feedback. The link similarity based on HMoK-SimRank algorithm depends upon the social network information like tags, groups and human annotation over the images. Content based similarity considers both global and local features, for measuring the similarity. In relevance feedback based approaches, a system learns from feedback provided by the user for an efficient way to retrieve the image. The Main advantage is to improve the image retrieval very effective and performance has to be improved.

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Wavelet transform has played an important role in Image processing task such as compression and restoration. Unlike most of existing denoising algorithms, using the curvelet makes it needless to hypothesize a statistical model for the noiseless image. This wavelet transform fails to represent the images, which has edges and treated them as smooth functions with discontinuity along curves. The curvelet transforms, where frame elements are indexed by scale, location and orientation parameters. This curvelet transform is designed to represent edges and other singularities along the curves which are more efficient than the traditional wavelet transform. Moreover, the curvelet transform and Gaussian filter are used for an effective image denoising system. This process will be based on the block-based noise estimation technique, in which an input image will be contaminated by the additive white Gaussian noise and filtering process to be performed by an adaptive Gaussian filter and curvelet transform. Coefficients of the Gaussian filter will be selected, as the functions of the standard deviation of the Gaussian noise will be estimated from an input noisy image. Denoising an image is carried out by processing an noisy image through Gaussian filter and using curvelet transform which gives better PSNR. The obtained PSNR values can be compared with that of many wavelet and curvelet in RGB regions. The renowned index Peak Signal to Noise Ratio (PSNR) and Root Mean Square Error (RMSE) demonstrate marked improvement of image denoising over other methods.

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Generally, The NLP (Tamil) applications are programming with different kinds of input data. Inputs classified into Text, Image, sound waves etc., Tamil Text based applications are creating under the word formation techniques. These words analysis and generation are activating in these ways, i) Untagging and Tagging and ii) Word-level and Character-level accuracies. This method is processing based on sequence labeling. These are the features for creating preprocessing stages for build the Dravidian applications.

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This paper deals with the development of a micro inverter for single phase photovoltaic applications which is suitable for conversion from low voltage DC to high voltage AC. The circuit topology is based on half-wave cycloconverter and grid connected micro inverter with a very less number of conversion stages and passive components. To interface the full bridge converter to the half-wave cycloconverter a high- frequency transformer and series-resonant tank are used. To determine the average output power of the inverter, a steady state analysis is used and to control the output power of the inverter, phase-shift power modulation is used. The operational characteristic is analyzed and multidimensional control technique is used to achieve high efficiency voltage gain, quality factor and phase shift of the inverter. The micro inverter and converter have light weight and reduced switch count. The operation of proposed micro inverter in grid-connected mode is validated using MATLAB simulation.

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Fault Diagnosis in a DC-DC converter is very important to prevent the converter from the damage. The aim of the paper is to diagnosis the fault and to prevent the converter from the damage. This Paper deals with design, modeling and simulation of open and short circuit switch fault analysis using MAT Lab Simulink. The converter used here is a Positive Output elementary Super Lift LUO Converter (POESLLC). Open Circuit and Short Circuit Switch faults are created, and cleared using a closed loop control and corresponding waveforms are studied. The Simulation results are compared with theoretical results. A simulink model is developed and it is successfully used for fault diagnosis.

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People expect more convenient ways to access the network. In this scenario, Wireless (WLAN) offers tangible benefits over traditional wired networking. Antenna a key element used to get better coverage. In this paper we are going to design a solution to replace the traditional Omni directional antenna with proposed Double Bi-quad antenna which is cost effective high gain, directivity and easy to fabricate. Current high gain antennas on the market that meet these specifications are expensive and cannot cover a larger distance. The proposed antenna consists of four equally sized squares radiating element on a printed circuit board with 50 ohm SMA connector which produces high directivity and peak gain of 12.9 dBi and works at 5.8 GHz.

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RSA algorithm is used to overcome security attack. Neural network classification is used to detect the forgery involved in digital images. Contrast Enhancement is typically used to adjust the global brightness and contrast of digital images. It is significant to detect contrast enhancement for verifying the originality and authenticity of the digital images. The main strategy relies on the blind identification of zero-height gap bins. Two data sets are taken for evaluation, namely, Dataset1 and Dataset2. Dataset1 is the unaltered image and Dataset2 is altered image from the original image. The detection of global contrast enhancement in both the images are determined. The zero-height gap bins in gray level histograms are exploited as identifying features. The probabilities of detection and false alarm determined by thresholds which are calculated as the percentage of the enhanced images correctly classified and that of the unenhanced images incorrectly classified, respectively. The receiver operating characteristic curves are generated for evaluation. The consistency between regional artifacts is checked for detecting image forgeries and locating composition boundaries.

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Ad-Hoc on Demand Networks is distributed open networks that establish communication on request with a minimal routing overhead. Data aggregation is alone par tedious due to its random scattered deployment. Mobile sinks, security threats, key sharing delay, etc. also influence seamless transmission between nodes. Currently existing works depend on the behavior of the nodes, by appropriately determining a gateway-like node to transmit its data and other information. The joint data aggregation and routing technique, initiated from the source recommends the collection path for each source and mobile sinks. It ensures minimum data loss and less communication disruption. The proposed system use HEC algorithm which provides low overhead in key distribution, encryption and decryption deduction when compared to the previous approaches. The joint aggregation integrating mobile sink navigation and secure hashing techniques, improves the performance of a network in terms of throughput, drop, security factor and encryption delay. Maritime tactical network requires high performance and security are one of the mainly used areas of MANET. Maritime tactical network are composed of mobile nodes (submarine, ship, aircraft etc.) and static nodes (shore stations), which can only couple with each other through radio electromagnetic spectrum.

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Long Term Evolution (LTE) is a technology that allows operators to achieve a very high data rate of 4G and more. Different types of modulation and multiplexing schemes are used in order to form high data rate systems. Orthogonal Frequency Division Multiplexing (OFDM) is one such modulation and multiplexing scheme which offers very high data rate. IFFT and FFT block forms the major part of OFDM transmitters and receivers respectively in the conventional OFDM system that is used currently. In order to increase the data rate further, the FFT based OFDM system is replaced by DWT based OFDM. This paper provides the comparison between the conventional OFDM and DWT based OFDM system with-in the technical limitations as applicable for LTE systems.

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Image processing became a big challenge in the multimedia usage for processing the images with low power and high efficiency. For processing images, DCT (Discrete cosine transforms) are utilized for compression because of its advantages over the energy consumption. In existing methods, they used Approximate DCT with fast algorithm and regular pipelining structure for reducing the design complexities. Because of the recursive nature in the existing design, high speed applications are becoming tedious. In our proposed system, we are using Modified Approximate DCT transforms with efficient binary adder circuits. The proposed solution possesses reduced number of gates and logic realization becomes easy for implementation.

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String transformation is an essential issue in online application. String transformation initially starts with one kind of string then onto the next structure. Every change might incorporate spelling error correction, word interpretation and word stemming process that are streamlining the string. This change is not directed adequately and precisely. Existing work makes a probabilistic way to String transformation, incorporates the utilization of log linear model, a strategy and a calculation produces the top k result by utilizing the word reference. Proposed work actualizes the weighted dissimilarity measure and Ahocorasick tree calculation for acquiring top k results in this change. In light of the guidelines, pruning is executed to produce the ideal top k results that must be positioned in web seek. Viable and ideal results demonstrate that this work enhances String transformation proficiently in diverse usage.

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Underwater sensor network consists of a number of underwater sensor nodes, autonomous underwater vehicles (AUV) that are deployed to perform collaborative monitoring and resource exploration tasks over a given area. But submarine detection and tracking referred to as anti-submarine warfare (ASW) is one of the most important application. In ASW system port-starboard (Ps) ambiguity is the most challenging issues which cause severe performance degradation. In the Bayesian approach, the dynamic state estimation is used to construct the posterior probability density function (pdf) of the state based on all available information, including the set of received measurements. Since this pdf embodies all available statistical information, it contains the complete solution to the estimation problem, and the optimal estimate of the state may be obtained from the posterior .the data from the sensors are not identically distributed as each sensor has its own location/ orientation with respect to the target, which can be time varying, this characteristics a key feature to solve the Ps ambiguity. The contribution of the proposed work in three fold by using game theory. First, Efficient target tracking with security enhancement. Second, prolong the life time of wireless sensor network by reducing the power consumption. Third, Comparison of Kth parameter in Bayesian approach versus game theory.

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QoS routing is an important research issue in wireless sensor network. Existing work exploits multipath routing and geographic opportunistic routing for QoS provisioning with both end to end reliability and delay constraints in WSNs but they are not efficient for QOS provisioning in WSNs. The proposed Improved Efficient QoS-Aware Geographic Opportunistic Routing (IEQGOR) is used to improve the energy efficient in WSNs. The quality of geographic opportunistic routing is improved by combining geographic routing with awake-asleep scheduling. The IEQGOR presents   probability-based target prediction and sleep scheduling protocol (PPSS) to improve the efficiency of proactive wake-up and enhance the energy efficiency with limited loss. IEQGOR significantly increase the QoS in WSNs. The proposed IEQGOR is compared with the EQGOR routing approach through NS-2.34 software. Simulation results demonstrate that IEQGOR improves the energy efficiency, packet delivery ratio and reduce the delay.

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A novel method for unsupervised change detection in multi-temporal satellite images using Gaussian mixture model (GMM) with spatial information is proposed. This approach is based on three steps. Firstly, the difference image between two Synthetic Aperture Radar (SAR) images of the same area taken at two different times is obtained using the standard log–ratio operator. Secondly, a preprocessing step of anisotropic diffusion is applied to the difference image. Thirdly, Gaussian Mixture Model is used for segmentation of the difference image in which the parameters are estimated using Expectation algorithm. The standard GMM considers each pixel as independent and hence the segmentation is sensitive to speckle noise present in the SAR images. To incorporate the spatial information in segmentation, anisotropic preprocessing is done and also the posterior probability computed in the M step is weighted with the mean filter. The proposed method is tested on four sets of multi-temporal images. The obtained results demonstrate the effectiveness of the method in obtaining higher change detection accuracies compared to the related methods.

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Generally, a major power system problem is dynamic economic dispatch problem (DEDP) for multiple fuel power plants. This problem is a nonlinear and non- smooth optimization problem when multi fuel effects and valve-point effects are considered. In this contribution, Improved Radial Basis Function Network (IRBFN) and Weighted Probabilistic Neural Network (WPNN) are compared and employed to forecast a one-hour ahead wind power for ensuring reliable power supply. Also Teaching Learning Based Optimization (TLBO)and biogeography based optimization is utilized to minimize the overall cost of operation of wind – thermal power system. The above algorithms are integrated with Sequential Quadratic Programming (SQP) for fine tuning the better solutions to reach the optimized minimal level. The proposed hybrid neural network model with the considered algorithms are  applied for a test bench DEDP and a practical DEDP wind power forecasted based on real time data from Wind Power Plant. The effectiveness of the approach is also validated with the comparison with the existing methodologies available in the literature.

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Network intrusion detection has been identified as one of the most challenging needs of the network security community in recent years. Intrusion detection systems (IDS) can analyze a large amount of data in a reasonable time to detect the attacks. Feature selection is necessary to reduce the time consumption and memory wastage. The dataset may be imprecise, incomplete or uncertain. Rough sets deals with vagueness and uncertainty. Rough set theory (RST) is used as a selection tool to find data dependencies and reduce the number of attributes which are redundant in a dataset. Particle swarm optimization (PSO) is known to effectively solve large-scale nonlinear optimization problems. An unsupervised hybrid feature selection based on PSO and RST for high dimensional network dataset is proposed. Feature selection algorithm namely PSO-quick reduct is applied for the different dimensions of network datasets. The simulation results for the unsupervised learning show that hybridization of PSO with rough set algorithm selects features more effectively than rough set algorithm without hybridization of PSO.

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Broadband Wireless Access (BWA) has been serving great satisfaction of its users. The WiMAX technology is ideal for the challenges related with earlier versions of wired and wireless access networks. IEEE 802.16 working group standardizes PHY layer and MAC layer only. The most challenging tasks in WIMAX networks are Hidden delay such as Handoff delay and network selection delay, and also Packet loss, Signaling overhead and Average serving rate. The two-tiered mobility management defined in WiMAX can potentially minimize handoff delay and packet loss, but it leads to another problem such as Gateway relocation. In this paper, we propose Gateway Relocation Request Control (GRRC), which combines ASNGW relocation and RC algorithm to maximize system capacity. The proposed system can reduce the average signaling overhead and signal traffic and also increases the average serving rate by solving the ASNGW relocation problem which effectively minimizes the hidden delay. In existing techniques we can’t predict the Main Station (MS) position instead it searches the Base Station(BS)which is nearer to the MS. In this paper we predict the MS position for the improvement of better hidden delay which includes Handoff Delay and Network Selection delay.

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In this work selection and combination technique is used to enhance the performance of classifiers. The main objective of the work is to select efficient classifiers, from a group of seven classifiers, based on the error rate and combining them, to determine multiple heart diseases simultaneously.  The classifiers are combined efficiently based on the decision of each classifier thus improving the classification accuracy of the signal. Heart ailments are the major health problem in the current scenario. These ailments in heart may even lead to death when not found at correct time. In recent years rate of patients with heart disease is increasing due to stress and unhygienic activities etc. This work is mainly done to develop an efficient detection system of multiple heart ailments. Three types of ECG signal, Normal, Arrhythmia and Sudden cardiac arrest signal is taken from physionet database is used as input signal.

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Mobile Ad hoc Networks (MANET) are self-organizing and self-configuring multi hop wireless networks capable of adaptive re-configuration network. The absence of infrastructure, limited bandwidth, dynamic nature and unpredictable link failure perturbs the efficient network services. Trust is an important aspect in the design and analysis of secure distribution systems. Hence, in this proposed study, trust based security is chosen as a security scheme to strengthen the cluster head. Therefore, a secured cluster head could be selected for each cluster, which guarantees the safe routing. Therefore, to strengthen the selected cluster head, a security measure, called trust mechanism is proposed.

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Over the last decades digital radio systems evolved from GSM with Time Division Multiple Access (TDMA) to UMTS with Code Division Multiple Access (CDMA) to LTE which uses Orthogonal Frequency Division Multiple Access. Goals for Long Term Evolution (LTE) development include higher data rates and lower latencies. The study related to physical layer design is the basic for any mobile system. The Long Term Evolution (LTE) standard defines a multi-mode air interface based on Orthogonal Frequency Division Multiplex (OFDM) within its downlink structure. LTE transceiver is simulated using Simulink. SIMULINK is tool that is being used. OFDM transceiver simulation is to be done that specifies the LTEsystem each of the individual block are assigned with their specific function where the data is sent and received with low bit loss. . A fast LTE signal processing may be achieved by these measures.

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MANET is a self methodized system comprised of mobile nodes without any infrastructure. MANET are at more imperil to attacks since it is dynamic in nature. To define and manage trust in a military MANET, we must cogitate the interface between the communication networks, and severe resource constraints such as computing power, energy, bandwidth, time etc and dynamics. Dynamics include changes in topology, mobility of the node, failure of the node and conditions for propagation channel. Therefore trust in MANET plays a vital role in the performance of MANET. MANET is vulnerable to several attacks. Black Hole attack is one of the attacks that advertise it for having the shortest route to destination node and then drops the entire packet that is coming from source node. In this paper, we have reviewed different solutions against Black hole attacks in Mobile Ad-Hoc networks and thoroughly compare these schemes to find out their various advantages and disadvantages based on trust evaluation and management.

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A Novel Morpho Image Codec called L Shaped Morpho Codec (LSMC) based on Lifting Wavelet Transform (LWT) is proposed. LWT is used for decomposing Medical Image into various sub-bands. Significant pixels of sub-band is been tracked by LSMC in particular order. Morphological dilation immediately applied using L shaped structuring element if significant pixel is found. Experimental results show that the proposed LSMC outperforms standard codec’s such as Set Partitioning in Hierarchical Trees (SPIHT) and Set Partitioned Embedded bloCK coder (SPECK) for Lossy and Lossless Compression for 512 x 512 and 1024 x 1024 images. The average bits per pixel (bpp) required for Lossless Compression by LSMC is less over by SPECK.

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In this paper the Darlington pair and internal circuit biasing technique is used for the enhancing the slew rate as well as gain and unity gain bandwidth. The proposed CMOS Op-Amp has been verified through Cadence Analog Design Environment with spectre simulator in the standard 45nm CMOS process. In this proposed circuit the gain stage is divided in two parts, first is modified gain stage and second one is Darlington pair stage. The effects of both the modified gain stage and Darlington stage currents are considered in this circuit and a simple analytical expression is given in terms of the load and compensation capacitors. The new scheme allows the slew rate to be increased with only a small increase in static power consumption. At the dc power dissipation of 0.76 mW, the proposed circuit achieves a slew rate of 2791V/μs, gain of 70 dB and unity gain bandwidth of 1.74 GHz.

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Wireless Sensor Network (WSNs) is a promising technology which supports large number of upcoming applications.  Wireless Sensor nodes are deployed in unreceptive environment. In this environment, sensor nodes are subjected to various attacks such as false data injection, eavesdropping, selective forwarding etc., The proposed work deals with security aspect in WSNs. Injected false data at sink level is a threat to WSNs security system. When the false data is injected at sink it creates a problem when updating the information at Base Station (BS) and also to filter the false data. False data injection leads to energy wastage in WSNs architecture. To minimize the energy wastage and to achieve better energy efficiency, to reduce the false data injection at sink node a novel method is proposed which drops the packets at node level and also in the sink level with Gang Injection Filtering Algorithm based Key Management Scheme. Spatial correlation concept is also adapted in the proposed work.  Gang attack is considered in the proposed work and the parameters such as End to end delay, Throughput, Packet delivery ratio, Energy Consumption, Enrouted probability are analyzed using  network simulator (NS2) tool.

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Nowadays Image retrieval is becomes more challenged thing in many of the fields like medical diagnosis, crime prevention, military services, architectural and engineering design, geographical information, trade- mark matching, etc. So there is the necessitates of effectively retrieving relevant images when needed. Thus, content-based image retrieval systems (CBIR) have become very popular for browsing, searching and retrieving images from a large database of digital images. So in order to improve the retrieval accuracy, this paper will focus on to use content-based image retrieval systems with k-means as the clustering algorithm and B+ tree for speeding up the retrieval process. For representing the images, we extract their feature vectors of images using Daubechies’ wavelets. Then we introduced the Zernike moments in the retrieved images with the reference image by that we find out the variations of the images. After that by comparing the images using Zernike moments and find out the forgery between the images.

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Electric power is one among the basic need in day to day life of human being. Electric power generation using conventional source of energy leads to environmental degradation and pollution. In the present work experimental comparison between power generations using solar based Brayton cycle and biomass based Brayton cycle. Brayton cycle is one which uses hot compressed air to generated power by expanding it in a turbine. In this work compressed air is varied at a flow rate of 20-50, and heating is carried out using solar scheffler reflector and biomass.

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This paper deals with the various methods for reduce the load frequency control (LFC) issues in an interconnected power system under deregulated environment. The effect of inclusion of doubly fed induction generators (DFIG) in both control area for load frequency control applications in a deregulated power system. For analyzing the load flowing application, the test system consists of a two area interconnected power system under deregulated environment having to GENCOs and two DISCOs in each area. To minimize the objective function, PID controller parameters are tuned by using Genetic Algorithm (GA). Simulations results under Matlab/Simulink environment validates that inclusion DFIG unit effectively it improve the LFC application for different contract scenarios under deregulated power system.

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Data mining plays an important role in Health care. It really helps to predict the disease based on collated data. Diagnosis in the medical field is a complicated task that should be performed with accuracy and efficiency. A diagnosis performed by a physician for a single patient may differ significantly if the same is examined by the other physicians or by the same physicians at different times to that single patient. Now a days, automated medical analysis are used to help doctors to predict diseases at a very fast pace. Gynecological disease is addressed in this study which is neglected; it may even prove disastrous if left unattended. Sum of 626 instances with 5 attributes are used as the medical dataset for this work. Weka is built in software tool for data mining. J48 (decision tree), Navie Bayes (NB), Multilayer perception (Artificial Neural Networks), ZeroR (Rule based) and Multiclass classifier (Support Vector Machines) are the five classification algorithms used.one of the difficult task in the predicting  dermatological diseases is that as there exist a large number of similar typed presentations. This paper deals with the data collected from the southern.

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Clustering and visualizing high dimensional dynamic data is a challenging problem in the data mining. Most of the existing clustering algorithms are based on the static statistical relationship among data. In the clustering process there are no predefined classes and no examples that would show what kind of desirable relations should be valid among the data. This paper gives existing work done in some papers related with dynamic clustering and incremental data clustering. Since most researchers will move and concentrate on solving the problem of using data mining dynamic databases.

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This work specifically focus on the k-nearest-neighbor (kNN) query verification on road networks and design verification schemes which support both distance verification and path verification. That  is the k resulting objects have the shortest distances to  the query point among all the objects in the database, and  the path from the query point to each k-nearest-neighbor  result is the valid shortest path on the network.  In order to verify the kNN query result on a road network, a naïve solution would be to return the whole road network and the point of interest (POI) dataset to the client to show correctness and completeness of the result.

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Cluster analysis finds its place in many applications especially in data analysis, image processing, pattern recognition, market research by grouping customers based on purchasing pattern, classifying documents on web for information discovery, outlier detection applications and act as a tool to gain insight into the distribution of data to observe characteristics of each cluster. This ensures that cluster places its identity in all domains. This paper presents the clustering validity measures which evaluates the results of clustering algorithms on data sets with the three main approaches of cluster validation techniques namely internal, external and relative criteria. Also it validates the cluster using the cluster indices namely Dunn’s index, Davies- Boludin index and Generalized Dunn Index using K-mean and Chameleon algorithm.

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In industrial control systems the liquid level is carrying its significance as the control action for level control in tanks containing different chemicals or mixtures is essential for further control linking set levels. The three tank level control techniques are well thought-out in our work. In conventional model for three tank liquid level, the control was done with predictable PID control model. The auto fine-tuning performance of PID regulator is adopted for more dependable and accurate control action which incorporate the uncertain factors also. A new evolution function including the system adjusting time, rise time, on reshoot, and system error is defined. By optimizing the PID controller and comparing the results obtained by conventional methods like Ziegler-Nichols using this techniques method the systems time delay and performance improved.

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In Visual Object Detection, traffic sign detection and reorganization is a recurring application domain. The automatic visual recognition and classification of the information contained in the panel could be very useful to assist the driver. Traffic panels instructs the driver assistance on routes by means of iconic symbols and text strings. Based on the color and shape features, the traffic sign is detected and recognized.  The various techniques has been used to extract the color and shape features of the traffic sign. This paper provide a survey of the traffic sign detection and recognition, to detail the system for driver assistance to ensure safe journey. A brief review of recent advancement techniques used by researchers has been provided for the detection and the reorganization stages.

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Orthogonal  Frequency  Division Multiplexing  (OFDM)  is  a  bandwidth  efficient signaling  scheme  for  wide  band  digital communications.  A  general  problem  found  in high  speed  communication  is  Inter-Symbol Interference  (ISI).  ISI  occurs  when  a transmission  interferes  with  itself  and  the receiver  cannot  decode  the  transmission correctly. Orthogonal frequency division multiplex (OFDM) modulation is being used more and more in telecommunication, wired and wireless.  DVB  and  DAB  already  use  this modulation  technique  and  ADSL  is  based  on  it. The advantages of this modulation are the reason for its increasing usage.  OFDM  can  be implemented  easily,  it  is  spectrally  efficient  and can  provide  high  data  rates  with  sufficient robustness to channel imperfections. Multiple-input-multiple-output and orthogonal frequency division multiplexing (MIMO-OFDM) systems provide high spectral efficiency for wireless communication system. However, they have a major drawback of high peak to-average power ratio (PAPR) which results in inefficient use of a power amplifier. . Thus, many studies have sought to develop PAPR reduction methods. The  purpose  of  this  paper  is  to  enhance  the  Bit  Error Ratio (BER) of a transmission varies when Signal to Noise Ratio (S/N Ratio) is changed on transmission channel and also we reduced the peak average power ratio. Here we discussed commanding of OFDM signal in time domain to reduce PAPR and also we discussed how ISI is reduced.

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Modeling and analysis of gripper arm system for bore well rescue operations and a humanoid model is designed to test the various parameters inside the well at various stages of time and places (humidity, temperature, pressure, oxygen, atmospheric air supply, speech ability, carbon dioxide, carbon level) and the rescue device is tested for its holding capacity.

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Wireless sensor network (WSN) defined as a group of spatially dispersed and committed sensors for sensing and recording the physical situation of the environment and arrange the collected data at a base station. WSNs measure environmental surroundings like temperature level, sound effect, pollution levels, humidity, wind speed and direction, pressure condition, etc.Sensor network is battery power operated. The major limitation of wireless sensor network is energy and network life time. To solve this problem Enhanced Quadrant based Low Energy Adaptive Clustering Hierarchy (Enhanced Q-LEACH) protocol is used. For each round routing protocol will check if energy of cluster head has fallen which is referred as threshold level than it will undertake cluster head and cluster formation operation. Otherwise same cluster head will continue its procedure by considering residual energy. This is how much of energy that goes wasted in cluster head formation action can be saved. Moreover, control overhead is also limited. Experimental results show that when compared to the existing system, in the proposed system is highly efficient in terms of network life time, energy consumption, Routing overhead and Average end to end delay.

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Input vector monitoring concurrent BIST performs two modes of operation, normal mode and test mode During test mode the test generator value is compared with higher order bits and the output is given to comparator circuit. During normal mode the inputs to the CUT are driven from the normal inputs. The modified SRAM is used to reduce the switching activity hence the dynamic power dissipation can be reduced. The output is verified by response verifier (RV) and the fault is identified using testing. The operating speed is faster since the operation is carried out as parallel process and it is suitable for all the type of IC’s.

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Image processing is one of the common research areas in recent decades, since noisy images cause harmful consequence on several applications and considerably degrade visual quality. The term denoising indicates to the method of estimating the unidentified (original) signal from available noisy data. Hyperspectral imaging has been established that it has several applications in farming, diagnostic medicine, and military surveillance. On the other hand, in these applications, the occurrence of the noise considerably reduces the classification accuracy. In order to solve these setbacks, for HSI, there is much global and local redundancy and correlation (RAC) in spatial/spectral dimensions is proposed in earlier work to eliminate noise from samples. Additionally, denoising performance can be enhanced significantly if RAC is exploited professionally in the denoising process. Nevertheless, the available RAC method denoising performance possibly will decrease when noise is strong. It turns out to be one of the important issues on dictionary learning. With the intention of surpassing these setbacks, in this paper presented a noise removal scheme to eradicate noise from image samples, at first the sensing noise in the image samples are eradicated with the help of the Singular Value Decomposition (SVD) and the Gaussian noise in the image samples are eradicated with the help of the Compression Sensing (CS) methods. SVD algorithm utilizes both the spectral and the spatial information in the images. Noise can be eliminated by sparse approximated data with SVD techniques. The denoising outcome from the proposed method is better than the other hyperspectral denoising schemes. Our results demonstrate that our denoising method can achieve competitive performance than other state-of-the-art methods.

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Radio Frequency (RF) spectrum is an expensive and limited natural resource for wireless communication systems. In recent times, Cognitive Radio (CR) has come out as one of the most competent candidates for enhancing the spectral exploitation effectiveness. Spectrum sensing is one of the most decisive elements in a CR system facilitating CR to access the licensed spectrum when it is not exploited by Primary Users (PUs). Conventional spectrum sensing approaches such as waveform based sensing algorithm, matched filter algorithm and energy detection algorithm are employed for recognizing the spectrums holes in the band. In actual fact, existing wideband spectrum sensing approaches in a distributed CR network is complicated to recognize, owing to huge implementation/computational complication and huge economic/energy costs. In order to overcome these concerns, a novel spectrum sensing method based on the ANFIS algorithm which is principally exploited to identify the borders of the subband and recognize the spectrum holes in specified input band. ANFIS is employed for effectively sensing the spectrum and considerably reducing the sensing error throughout the process spectrum sensing. The parameters such as power spectral density, bandwidth efficiency, SNR and channel capacity is used for identifying the condition of the spectrum. The experimental results shows that the sensing the spectrum using the proposed method is better than the other techniques.

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With the growth of different networking technology and multimedia technology the real time delivery of multimedia content becomes an imperative field. Most of the applications such as video conferencing need multimedia transmission techniques that send multimedia data from one end to another with enhanced efficiency in quality and minimized delay. Conventional packet fragmentation schemes shed a packet if all its fragments are not received correctly. But video data is loss tolerant and delay-sensitive. In this paper we propose a new family of delay based fragmentation algorithm which reduces the packet loss and delay thereby attain Quality of service in Multimedia applications.

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In this paper S-shaped slot antenna has been designed that can be implemented in a microwave system to detect the Congestive Heart Failure.  This antenna fed through waveguide port for a frequency 2.4GHz used for ISM band operating frequency (2.3-2.5) GHz.  An antenna is the most important element of biomedical application.  This paper is focused on the analysis of S-Shaped Slot antenna with dimensions of 60x60mm2.  Here we are designing two different structure of the antenna (i)Dual S-Shaped Slot Antenna (ii)Quad S-Shaped Slot Antenna.  By comparing both antennas, Quad S-Shaped Slot antenna has the maximum gain and minimum return loss compared to the Dual S-Shaped Slot Antenna by increasing the thickness of the substrate.  The antenna is designed on CST Microwave Studio Simulation Software with a significant Return loss, Gain, Directivity, VSWR Power and efficiency which shows a good performance.  Its total volume is only 6cm.  

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Information retrieval plays a major role in all the fields such as medicine, industry, information technology and research. In order to retrieve the medical images from healthcare section, feature based retrieval methods are used to enable automation.  In this paper, we proposed a new framework to make the retrieval system to outperform well. In this case, we have taken the advantage of feature based retrieval system along with relevance feedback mechanism in the first stage and text based query refinement at the second stage on heterogeneous datasets. In CBIR, rank order and precision values calculated in each iteration make appropriate weight adjustments among different features. As the image retrieval system is highly subject to user semantic concepts, the text based query is also adapted to enable the retrieval system to perform better.

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This work deals with the analytical method for estimating coupling between arbitrarily directed multiple finite-length lines with different line lengths and heights. Coupling or crosstalk analysis is performed by developing an expanded circuit-concept approach based on PEEC Method. An electric image method using the quasi-static terms of the accurate Green’s function is used to estimate the electromagnetic fields in an inhomogeneous medium such as a printed circuit board. The approach is applied to the analysis of parallel and nonparallel or bent micro strip models, and embedded-line models in which one line is embedded and the other is on the surface layer. To verify the proposed approach, we conducted some experiments and compared the results of our approach with the results of measurements and a commercial electromagnetic solver.

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In this review article, different structures of monopole antennas based on metamaterial concepts which have been developed for various wireless applications are presented. The antennas designed for wireless applications must be broad band, low profile, small size and have better performance. Monopole antennas embedded with Artificial magnetic conductors (AMC), Electromagnetic band gap structures (EBG), Complementary split ring resonators (CSRR), Transmission line metamaterial (TL-MTM), Simplified MTM (SMTL) are reviewed in this paper.

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Generally, any product has various features (also known as aspects). For example, a mobile phone can have more than three hundred aspects, such as battery, design, multi-touch, and 3G network. It can be argued that some aspects are more important when compared to others, and have greater impact on the eventual consumers’ decision making as well as firms’ product development strategies. Identifying these important product aspects from the consumer reviews or feedbacks will increase the usability of reviews and is beneficial to both consumers and firms. It becomes easier for consumers to make wise purchasing decision by paying attention to the important aspects and can firm also concentrate on improving the quality of these aspects and this will enhance the product reputation effectively.  However, it is tedious and time consuming for people to manually identify the important aspects of products from numerous reviews. Thus, this project proposes agent based product aspect ranking framework to identify the important aspects of products and rate them according to the consumers’ opinion about them. A false detection technique is also employed to indicate those features for which an overall positive or negative opinion cannot be determined. The potential of aspect ranking can be shown in many real-world applications like e-commerce, retail, entertainment etc.

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Peer -to-peer systems offer toughness beside failure and come forward from a oblige to understand a computing architecture which cannot be taken down by attacking any single point. Scale and massively distributed nature of its architecture are its characteristics defense. This has made it reasonable for resource consuming and, in general, concurrent communication to adapt and exploit the benefits of P2P. Such a migration needs to address a new set of P2P specific security problems. The untrusted nodes may be faulty, malicious, and act together to commit as much damage to the P2P network as possible. We go over some of the known issues found in common P2P networks. We then analyze the relevance of such issues and the applicability of existing solutions when using P2P architectures for secure communication.

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An efficient VLSI architecture implementation for barrel distortion correction in surveillance camera images is presented. The distortion correction model is based on least squares estimation method. To reduce the computing complexity, an odd-order polynomial to approximate the back-mapping expansion polynomial is used. By algebraic transformation, the approximated polynomial becomes a monomial form which can be solved by Horner’s algorithm. The proposed VLSI architecture can achieve frequency 218MHz with 1490 logic elements by using 0.18µm technology. Compared with previous techniques, the circuit reduces the hardware cost and the requirement of memory usage.

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This novel proposes a modern approach for developing inverse model of a plant which will be based on fuzzy control logic. Purely analytical method was used in developing an inversion strategy of the plant. The proposed Fuzzy Nonlinear Internal Model Control (FNIMC) representation lies in the possibility to determine exactly the model inverse which grandees offset free control performances. The inverse model is conventionally having been performed using proportional-Integral-Derivative (PID) controller. This paper concludes by comparing the conventional method with Fuzzy Nonlinear Internal Model Control (FNIMC).

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A computer network is a system whose components are autonomous computers and other devices that are connected together usually over long physical distance. Each computer has its own operating system and there is no direct cooperation between the computers in the execution of programs. A basic feature for a system is that its components are connected together by physical communication links to transmit information according to some pattern. Moreover, it is undoubted that the power of a system is highly dependent upon the connection pattern of components in the system. A connection pattern of the components is a system is called an interconnection network, or network for short, of the system.  In this paper, using the new graph class called Super Strongly Perfect (SSP), some bipartite and non bipartite based interconnection networks (Path, Helm and crown graphs) are discussed.

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Uncompressed videos fetched from video cameras generally takes huge disk space approx 18MB per second. When these uncompressed videos are required to be shared over internet it would take huge time to upload or download. To overcome these situation videos need to be compressed so that it can be digitally distributed. This process is also known as transcoding. In the event of transcoding it is essential to ensure the quality of the video is not compromised and overall size of the video is reduced. Transcoding or compression is the process of segregating the video in to digital tracks, decoding the individual tracks to eliminate the high RGB and redundant pixels. In the existing paper video compression was tested using DCT (discrete cosine transformation), However there are few know issues on DCT such as artifacts blocking. In this paper testing is performed using DWT (discrete wavelet transformation) and there by the input coding is not overlapped by another 2-D blocks. In the proposed work PSNR value is improved when compared to the existing work.

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Image fusion is the process of merging two or more images obtained from the same sensor at different times or from two or more sensors at the same instant. The objective is to obtain more information from the fused image than from the individual images. In satellite images, the lower spatial resolution multispectral images are fused with higher spatial resolution panchromatic images. The fusion should result in the transfer of spectral and spatial information without introducing any artifacts. The goal is to combine the spectral and spatial resolutions of the multispectral and the panchromatic images respectively to obtain a high-resolution multispectral image. Most of the fusion techniques that have been proposed are based on the compromise between the desired spatial enhancement and the spectral consistency. This paper provides an overview of the techniques available in the literature for the fusion of multispectral and panchromatic images. The evaluation of the fusion technique employed is also an important step in the fusion process. Various quality metrics have been used in the literature to study, compare and assess the fusion technique employed. This paper provides a brief study on such quality metrics employed in the literature.

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Design of dual band 1x2 microstrip patch antenna array for GPS receivers

S. Subhashini and S. Sadhish Prabhu

An ‘H’ shaped dual band micro-strip patch antenna array is designed, simulated and fabricated for Global Positioning system (GPS) receivers covering L1 and L5 frequencies of 1.575 GHz and 1.176 GHz respectively. Antenna parameters like return loss, VSWR, impedance matching, radiation pattern and directivity are analyzed. The designed antenna has a bandwidth of 1.3% and 2.2% for GPS L1 and L5 receivers respectively. In addition to it, the micro-strip patch antenna array is fabricated using    co-axial feed mechanism and tested. The antenna had a return loss of -27 dB and -18 dB for GPS L1 and L5 band respectively.

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Security and privacy of relational data using access control and privacy protection mechanism

Limy Sebastian and Panchami V.

Authentication and authorization are two pivotal security mechanisms generally implemented to enforce security both on data and resource levels in computer applications, especially over the internet. Once a user is authenticated, application starts a session for the user. But authentication does not mean license for anything for user. Several application resources and data sources are further secured by a Role based Access Control mechanisms. The sensitive and confidential information in many organizations is shared by the means of authorized access. But an authorized user can still compromise the privacy of persons leading to an unwanted identity disclosure. An anonymization technique is normally employed to suppress identifiable attributes yet capable of sharing information. Anyway some accuracy of data is compromised for the sake of privacy protection. In this paper a framework is developed which puts an additional aspect of accuracy constraint for multiple roles. Once the access control and data anonymization techniques are integrated they work together as a service for any application as a configurable privacy preserving role based access control framework.

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Feasibility of log-domain technique for high performance LDPC decoding concatenated with STBC

Nishandhini V. and Rajasekar B.

An approach concerned with low-density parity-check (LDPC) codes that have high performance decoding capability. With help of Alamouti STBC (space time block codes) which is concatenated with LDPC, it has been deduced that, the so constructed model has better performance than the existing in terms of Bit Error Rate (BER). A soft decision based decoding algorithm shows best performance than other decoding algorithms. Thus, for better performance Log-domain decoding of LDPC codes is implemented.

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Modeling and performance comparison of grapheme and carbon nanotube based FETs

Sreenath R, B Bala Tripura Sundari

The era of nanoelectronics has emerged to overcome the effects of limits of physics due to technology scaling. Hence there is a need to explore the use of advanced nanomaterials namely, graphene and carbon nanotube that can overcome the limitations of short channel effects that arise in conventional silicon based field effect transistors (FET).  The high carrier mobility of these materials on a substrate at room temperature and high electron velocity and thermal conductivity, are the motivation to explore the possibility to use FETs based on these materials. The focus in this work is the electronic characterization of such FET models. In this work, SPICE compactible models using closed form equations that are suitable for future circuit level simulations have been developed for single gate graphene FET (GFET), dual gate GFET (DG-GFET) and carbon nanotube field effect transistor (CNT-FET). This paper presents a modified single gate GFET model that is compatible with device length of 100nm and it is found to have better linear and saturation characteristics compared with the existing model. The modified GFET is found to have dirac point stability for lower values of drain to source voltage (V_ds<0.4V) which is suitable for voltage scaling. A ballistic, non-linear piece-wise approximation approach in CNT-FET has been applied to achieve the saturation of drain current rather than using the computationally complex self-consistent field approach. This work also presents a detailed study of variation in transconductance and transit frequency for the modified GFET model and it is established to have a higher transit frequency at 100nm than the existing model. The simulation of models and comparison of various parameters are done using MATLAB.

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Adaptive traffic control system using heuristic approach

Sharanya C. and Muthiah M. A.

Traffic which is the main backbone of a city plays an important role in social stability and development. The traffic signals in our country are standalone systems where the duration of the signal is determined by a traffic officer or a constant value of signal duration is pre-programmed. Sometimes this timing is too short in high traffic density and too long for lesser number of vehicles. These lead to economic losses and unnecessary delays. Therefore we go for Adaptive Traffic Control (ATC) systems which change the signal duration continuously based on the changing arrival pattern of the vehicles. In this paper we design an ATC using heuristic approach where the system is trained to many images with various possibilities of vehicles using Probabilistic Neural Network (PNN). Before training each image is processed using background subtraction with morphological filtering and connected component analysis to detect the number of vehicles. The real time input image from the camera is forwarded to the system which uses heuristic technique to match the current image with one of the trained images and displays the duration of the traffic signal based on the counted number of vehicles thereby regulating traffic easily without any congestion.

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Synchronous generator equipped with power system stabilizer for power oscillation damping

P. Sarmila Devi and S. Bharath

The increasing magnitude and difficulty of interconnected power systems due to competitive energy markets, economy and population development have created the need to operate the power systems close to their capacity limits. This leads sometimes to stability problems or poor dynamic behaviours like power oscillations. These oscillations can cause a reduction of the system components lifetime, expensive operations of the electrical grids and in the worst case, risks of partial system collapses. On the other hand, in the synchronous generator, the damping that the field and damper windings provide to the rotor oscillations is weakened due to excitation control system action. The reason for this is that in the rotor circuits appear additional currents induced by the voltage regulation and those currents oppose to the currents induced by the rotor speed deviations. Therefore, an additional stabilizing signal was needed and the Power System Stabilizer (PSS) was developed with this aim. The PSS is a feedback controller, part of the control system for a synchronous generator, which provides an additional signal that is added to the input summing point at the Automatic Voltage Regulator AVR. The PSS main function is to damp generator rotor oscillations. By adding the stabilizing signal the PSS is expected to produce an electric torque component that counteracts the mechanical dynamics. The produced electric torque component should be in phase with the deviations of the generator rotor speed in order to be able to damp the oscillations. The simulation of the proposed model was carried out using specialized power system analysis toolbox (PSAT).

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A comparative study of fuzzy logic controllers for BLDC motor drive

The development of high performance variable speed brushless dc motor drive is very important in all industrial applications. Generally, a high performance BLDC motor drive system must have good dynamic speed response, reference speed command tracking capability and load regulating response. Conventional controller such as PI, PID does not provide good dynamic response due to the problem of non-linearity, difficulty in the tuning of controller parameters. With the fast growing of intelligent controllers for precise motor speed control, fuzzy logic controllers are taken in this paper. This paper demonstrates a comparative study of PI, fuzzy logic, hybrid fuzzy PID controllers using MATLAB/SIMULINK environment.

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Comparison of PI and ANN controller for HVDC link

Sayara Y. Tamboli and H. T. Jadhav

This paper presents the HVDC system for power system to control the power flow between two converter stations. In this paper, rectifier side is used to control current and inverter side is used to control current as well as extinction angle. In power control system, proportional-integral (PI) controller is widely used. Here we compare its performance with conventional controller and artificial neural network controller. The MATLAB/SIMULINK shows that HVDC controller for power system.

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A study of dynamic prediction based multi-queue (DPMQ) drop policy in ferry based protocols for disconnected mobile ad hoc networks

Suganthe R C and Ramya T

Delay Tolerant Network (DTN) is an approach to address the technical issues in heterogeneous networks that may lack continuous network connectivity. The issues that are related to DTN are delivery probability, overhead, latency and drop rate. To improve message delivery probability and reduce network overhead, routing protocol and buffer management has to be selected efficiently. This scheme is used to decide which message to be transmitted when two nodes come within the transmission range and to decide which message to drop when buffer overflow occurs. This effort improves delivery probability of a message by choosing probabilistic type of routing protocol called as Prophet and a new buffer management policy called as Dynamic Prediction based Multi Queue (DPMQ) drop policy. This routing protocol forwards the message only when the encountered node has the highest probability of reaching the destination than the sending node. The DPMQ drop policy classifies the buffer into three queues such as LPQ, HPQ and DCQ based upon the delivery prediction. This buffer management policy along with Prophet Routing performs well by reducing overhead and latency while improving delivery probability for a global village scenario.

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Glitch free NAND based DCDL in phase locked loop application

S. Karpagambal and M. S. Thaen Malar

This paper presents a glitch free NAND based digitally controlled delay lines for the avoidance of glitches by using different driving circuits. In glitch free NAND based DCDL, driving circuits are used to generate the control bits which consumes considerable amount of power and delay time. Driving techniques suggested here are dual edge triggered sense amplifier based flip-flop and NIKOLIC sense amplifier based flip-flop, which comparatively have reduced power consumption and delay time. The proposed NAND based DCDL have been designed in 90nm CMOS technology and various performances of these techniques are compared by the simulation parameters like power, area and delay. In addition, the proposed DCDL is adopted in phase locked loop.

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Q-back-pressure algorithm in visual sensor networks to achieve energy efficiency through delay reduction

G. Aravind Swaminathan, D. Manimegalai and S. Kalyani

Visual Sensor Networks (VSNs) have emerged its technology in the wireless networking. Because of these advantages over other wireless networks, VSNs are undergoing rapid progress and inspiring numerous applications. Frequent congestion or routing loop is an important issue in Visual Sensor Networks. This is caused due to the node partitioning in the Visual Sensor Networks. This leads to routing problem in the Visual Sensor Network. Adaptive Routing Algorithm is the major cause of this problem. Due to these the VSNs becomes less energy efficient and   the throughput gets reduced. To overcome the above drawbacks, Q-Backpressure algorithm is implemented in VSNs. Q-Backpressure algorithm maintains a queue and thus it eliminates the self failure in the link by maintaining the deterministic route. However, to achieve energy efficiency, Autonomous Recovery Scheme (ARS) is implemented. ARS helps in recovering from path failure. The reconfiguration planning technique in ARS identifies local configuration changes for the recovery of path failure.

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Performance improvement of Indian railway signalling

Arokia Mary Caroline P.

The present way of signalling in Indian railway is through traditional land post light signals controlled from the station and the train operation is regulated by the light signals. Sometimes because of poor vision due to climatic conditions [mist and heavy rain] , sharp blind bends , up and downs and dazzling sunlight , it is difficult to run the train in a constant speed and needs to apply brakes which will lead to discomfort journey and loss of energy and time too. To enhance the performance of the train operation without any interruption due to the above cause we can provide cab signals instantly to the loco pilot. Here, I introduce a method to provide cab light signal by electromagnetic waves (EMW) with the help of traditional land post light signal power.

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Design of microstrip patch antenna and a configuration to improve gain

P. Subhashini and K. Jayanthi

Microstrip antennas are a rapidly growing area of research. The applications of microstrip antennas are limitless, because of their compact size, ease of manufacturing and light weight. A variety of approaches have been taken, including modification of experimentation with substrate parameters, the patch shape, Most notably mobile communication systems where many frequency ranges could be accommodated by a single antenna. This paper deals with the design of microstrip patch antenna and the configuration to improve the gain so that the distance for communication can be enhanced. The proposed configuration involves the Broadside patch antenna of six elements built in an array to improve the gain whereas the existing method involved four radiating elements designed in E-Shaped. The gain of Microstrip Antennas can be increased by building a broadside array. By exciting a number of microstrip antenna elements to make them radiate in the same phase at the broadside direction, the broadside gain will increase with the number of elements. In this paper a microstrip patch antenna is designed and the parameters analyzed are s-parameter and gain.

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Error free file placement in large database management system

Evan Nicholas Dawson and G. Merlin Sheeba

In growing need of large database handling and analysing becomes a greater challenge. There are technologies like parallel computing and shared memory technology to split up the processing task and execute it at much ease and convenience. However, there are situations while specific large files which are under query process and the same file cannot be updated or placed from server as there will be a conflict on read/write operation in memory system. Therefore, current technique suggest with priority assignment to handle the issue of concurrency. However, this proposes a methodology to handle up the file placement more successfully without priority assigned but on approach called conditional basis, using this technique we will be able to implement both write and read operation simultaneously without affecting presently running files and we will also be able to ensure the data packets are not lost due to waiting on queue.

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Assessment of ground water quality in Guntur district using data preprocessing approach

Kamakshaiah Kolli and R. Seshadri

In this paper we have made an attempt has to study water quality analysis in Guntur District. In Andrapradesh. In order to assess the detailed analysis of ground water quality has been carried out. Totally 31 water samples have been collected and tested for various physicochemical parameters such as pH, Temperature, Electrical Conductivity, Ammonical Nitrogen, Total Dissolved Solids, Total Hardness, Calcium, Magnesium, Chloride, Sulphate, Total Alkalinity, Fluoride, Sodium, Potassium, Total Phosphorus, Salinity, Total Nitrogen and Dissolved Oxygen. Correlations study was also carried out as it is an excellent tool for the prediction of parameter values within reasonable degree of accuracy. A systematic correlation study showed significant linear relationship among different pairs of water quality parameters. We have applied the Various Data-Mining techniques to analyze the ground water quality by taking a number of samples in various villages and cleanly synthesized the parameters on the water.

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Amputating wormhole attack in wireless sensor network using swarm intelligence

Thanga Mariappan L. and Ruba Soundar K.

In wireless sensor networks (WSNs), due to the restricted resources of the nodes, are highly vulnerable to attacks at all network layers; however, the so-called “wormhole attack” is particularly challenging because it resists self-protective measures exclusively based on cryptographic protocols, this attack that not only diminishes the network capacity but also affects the reliability of information being transmitted. No emphasis was made towards the preventing the wormhole attack. In this paper a swarm-based framework that uses the security agents and security officer nodes. Preserving the legitimate packets coming from reserved route only, thereby discarding the contaminated packets has been proposed from another network.

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ISFR: An effective framework for efficient image retrieval system based on interactive segmentation and fuzzy rules

Sabena S. and Yogesh P.

In an image retrieval system, the major challenges are image understanding and image annotation. This paper presents an Interactive Segmentation and Fuzzy Rules (ISFR) framework that includes two major components: Interactive Image Segmentation (IIS) for image understanding and Fuzzy Annotation Theory (FAT) for image annotation. IIS extracts multiple objects and background regions from the images and identifies the user context objects in the images through multiple markers. FAT is used to develop the image annotation systems. The colour, shape, and texture of objects are used to represent the visual concepts of the images. This paper extends and enriches the fuzzy based knowledge representation to map visual concepts to high level concepts. Thus the formal specifications of the visual concepts to the corresponding high level concepts are constructed. The proposed ISFR framework produces automatic annotation of segmented objects and retrieves images that best match user’s expectations. Experiments on benchmark dataset validated that the proposed ISFR framework yields better segmentation than the existing algorithms.

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A novel cohesive and service driven methodology for augmenting the vertical handover performance in heterogeneous wireless networks

A. Prithiviraj, K. Krishnamoorthy and M. Usha

Due to the mounting requirement for anytime, anywhere network services, we need to integrate diverse kinds of wireless networks. For assisting this integration, the mobile users should be allowed to freely move across networks. The chances of delay in packet transmission, jitter and out of order arrival of packets are predominant when the mobile node gets detached with its home network. This could possibly become a problem when vertical handover needs to be addressed. Proxy Mobile IPv6 (PMIPv6) is a network based mobility management protocol which facilitates the removal of overhead on the mobile node. In order to achieve seamless handover we have proposed a new algorithm which helps to overcome the challenges and issues that can occur during vertical handover. In this paper we have introduced multiple attribute decision making approach for selecting the next access network when the mobile node moves away from its home network. Media independent localized routing is the strategy for accomplishing vertical handover. The proposed algorithm greatly reduces the packet loss and other mobility oriented issues when compared with the prevailing algorithms.

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IMWT coding using lossy image compression techniques for satellite images

K. Rajakumar and T. Arivoli

The performance of the wavelets in the field of image processing is well known. It is experimental with multiplicity of different images types are compressed using a fixed wavelet filter. In this work Integer Multiwavelet Transform (IMWT) algorithm for Lossy compression has been derived for three different types of images like Standard Lena, Satellite urban and Satellite rural. The IMWT shows high performance with reconstruction of the images. This work analyses the performance of the IMWT for lossy compression of images with Magnitude Set-Variable length Integer coding. The Transform coefficients are coded using the Magnitude set coding and run length Encoding techniques. The sign information of the coefficients is coded as bit plane with zero thresholds. The Peak Signal to Noise Ratios (PSNR) and Mean Square Error (MSE) obtained for Standard images using the Proposed IMWT lossy compression scheme. The effectiveness of the lossy compression method can be evaluated by examining the Image with 8-bit Gray (256x256) pixels. The results confirm that Standard Lena, Satellite rural and urban images are better suited for proposed scheme compared to that of Existing SPIHT (Set Partitioning in Hierarchical Trees) Lossy algorithm. The Simulation was done in Mat lab. 

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Performance assessment of direct and indirect current control strategies for shunt active power filter

A. Sakthivel, P. Vijayakumar and A. Senthilkumar

This paper compares Direct Current Control Technique (DCCT) and Indirect Current Control Technique (ICCT) for the control of Shunt Active Power Filter (SAPF). A current controlled voltage source inverter is used as SAPF and three-phase diode bridge rectifier with RL load is considered as Non-Linear Load (NLL). Dynamic response analysis of both techniques of current control is compared. Based on experimental results, it is evident that ICCT becomes simpler, requires less hardware and offers better performance.

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On a possible characterization of a q-ary linear MDS code of length n

M.Mary JansiRani and K.Prabhakaran

Let be a finite field having q – elements (q=, p is a prime, m1) by a linear [n, k, d] code. We mean a subspace of the vector space if  having dimension k and minimum distance d denoting this code by C we analyse certain sub-codes of C. The inequality dn-k+1is obtained via a sub-code of dimension (k-1) in which the left- most coordinate position of each of its code words is zero. Under suitable circumstances, it is possible that dn-k+1.A q-ary linear code of length n, dimension k and having minimum distance d is said to be a mean distance separable code if d=n-k+1 writing a mean distance separable code as an MDS code, we obtain a possible characterisation of an MDS code. A equivalence relation of the set of code words of a q-ary [n, k, d] code suggests an algorithm for finding the minimum distance of an [n, k, d] code.

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Sharing data in cloud based on trust attribute based encryption (TABE)

Now a day’s everyone storing there data in cloud because we can’t depends on hard drives if they crash one can’t have backup for ever data. Famous Cloud storage applications are Drop box, Google drive, Sky drive, Box, Amazon cloud drive, Surdoc and Apple icloud. In cloud data security is provided by various security algorithms. In our research we have chosen attribute based encryption technique to encrypt the data in cloud. We have proposed new attribute based encryption techniques which is known as trust attribute based encryption. In trust attribute based encryption first we find the trust of the attribute in web site and second based on trust attribute we from the access policy to cipher text. We propose scalable revocation scheme to trust based attribute based encryption by applying proxy re-encryption and lazy re-encryption to trust based attribute based encryption to provide efficiently revoke rights to users. We compare trust based attribute based encryption with key policy attribute based encryption; cipher text policy attribute and Hierarchical attribute based encryption based on time and number of attributes. We prove that trust based attribute based encryption is efficient compare to existing techniques.

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Study of connectivity properties and network topology for neuroimaging classification by using adaptive Nero-fuzzy inference system

R. Sampath P. GayathriDevy  A. Swedah and A. Saradha

Neuro imaging techniques are used to study the structural and functional connectivity of the human brain to identify abnormalities, Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD) can be identified by quantitative measurement of brain connectivity. In this paper, Multi kernel based approach is employed. Two types of Kernels i.e., vector based kernel and graph based kernel are used to study the local and global topology properties of a network. Then Adaptive Neuro Fuzzy Inference System (ANFIS) is adopted for neuroimaging classification. This analyses two different yet complementary properties of the network.

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An efficient routing optimization using secure reverse multicast bellman ford ad hoc routing using aomdv protocol in MANET

E.Selvi M.S. and Shashidara

Route optimization is the basic requirement to improve the QOS of the ad hoc network.  Multiple qualities of service (QoS) guarantees are required in most multicast applications in mobile ad hoc networks (MANET).  In this paper introduce a novel multiple constraints QoS multicast routing optimization algorithm in MANET called SRMBAR (Secure Reverse Multicast Bellman Ford Adhoc Routing) that ensure QoS guarantee by allowing reverse multicast routing on possible multiple paths between source and destination and helps in decreasing the routing overhead through Routing Interference Communication (RIC) framework. The proposed SRMBAR can improve reliability of data transmission and optimize the maximum link utilization which achieves data integrity and then reduce the consumption of time and the transmission delay. Experimental results show that the reverse multicasting approach is efficient when compared with existing Bellman Ford Algorithm, has promising performance in multicast traffic engineering and for evaluating the route stability in dynamic mobile networks.

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Congestion management in competitive power market using TCSC

G. Sophia Jasmine and P. VijayaKumar

The Optimum Power Flow (OPF) in an interconnected power system is an imperative procedure with respect to transmission loss and other operating constraints. Deregulation of power industry leads to huge change in the process of operation and control strategy of optimum power flow. Increase in power demand leads to increase in power transaction and for satisfying those demands competition arise among the market players (GENCO’s), which create stress on the power system. Thus leading the system to get congested. In this paper, Thyristor Controlled Series Compensator (TCSC) has been used to relieve congestion using conventional NR method. Allen J. Wood six bus systems have been considered as the test bus system. Simulation results with and without TCSC, before and after compensation has been discussed to analyse the impact of TCSC on the congestion levels of the six bus test system.

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An efficient lifting scheme architecture for 2D discrete wavelet transform

V. Vaishnavi and M. Thamarai

A high-speed and reduced-area lifting architecture for 2D Discrete Wavelet Transform computation and the 2-D DWT Image Decomposition is proposed in this work. Lift scheme is one of the wavelet computation techniques. Prior DWT architectures are mostly constructed on the basic lifting scheme or the flipping structure. In order to attain a critical path with only one multiplier, at least four pipelining stages are mandatory for one lifting step, or a large temporal buffer is required. In this work, modifications are made in the lifting scheme as the Radix-8 booth multiplier is used and the intermediate values are recombined and stored to reduce the number of pipelining stages and the registers. The two-input/two-output parallel scanning architecture is adopted in the design. The detailed analysis is performed to compare the proposed architecture with the modified architecture in terms of hardware complexity computation time and Power consumption. In the proposed architecture, the number of LUTs reduced to 50%, power consumption is reduced to 89mw, and computation time delay is reduced to 36.6% when compared to the conventional Lifting Scheme.

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A soft computing approach on ship trajectory control for marine applications

T. K. Sethuramalingam and B. Nagaraj

The objective of this paper is to create a PID controller for the movement of the cargo ship containing with oil that is tuned using soft computing algorithms. Oscillation in liquids is called ‘slosh’ or ‘slop’ and is important because the movement of large quantities of liquid can strongly influence the movement of the container itself – this is usually undesirable and often dangerous. The liquid slosh system is notoriously difficult to control optimally using a PID controller because the system parameters are constantly changing. The movement of the cargo ship containing with oil is a complex nonlinear system. Due to its strong nonlinear behavior, the problem of identification and control of cargo ship filled with oil is always a challenging task. Usually the cargo ship filled with oil is controlled using linear PID control configurations. If the process is subjected to larger disturbance due to liquid slosh effect, the state cargo ship can considerably deviate from the aforementioned neighborhood and consequently deteriorates the performance of the controller. They are inherently nonlinear. In spite of the knowledge that one of the characteristic is inherent nonlinearity of the process, it is traditionally controlled using linear control design techniques. The ability of PID controllers to compensate most practical industrial processes has led to their wide acceptance in industrial applications. To aid with the development of this system was chosen at random and a PID controller was designed for it using conventional methods. A genetic algorithm was then created to evaluate the PID coefficients of the same system and the results of the two techniques were compared. A fourth order system was selected as the Ball and Hoop system.

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Authentication of leaf image using image processing technique

Vijayashree T. and A. Gopal

The aim of the work is to classify and authenticate the medicinal plant materials and herbs widely used for Indian herbal medicinal preparation. The quality and authenticity of these leaves are to be ensured for the preparation of herbal medicines. The medicinal plant leaves are thoroughly screened, analyzed and compared with the database to give the correct measures of the texture to which category the leaf belongs to. This method is adopted due to the mistaken of look-alike leaves. Using image processing technique the mistaken of look-alike leaves can be authenticated by various parameters of the leaves.

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Design and analysis of noninvasive intraocular pressure sensor

A. Vimala Juliet, S. Saranyaa and Joshua Amrith Raj C.

This paper presents a design of noninvasive capacitive pressure sensor using micro electromechanical system (MEMS) for the measurement of Intraocular pressure (IOP). The normal IOP of a human eye ranges from 12mmHg to 20mmHg. IOP is the important factor in the diagnosis of glaucoma. The corneal curvature of eye changes with the change in IOP. Thus the IOP can be measured by measuring the variation in the corneal curvature. Since it is going to be used for human eye, it has to measure the pressure of range 5-40 mmHg. The sensor consists of a poly silicon layer which gets deflected when pressure is applied. This simulation is done in COMSOL software and it gives good sensitivity and linearity in the IOP range. Here, the changes in the sensitivity according to the number of perforations has been shown. The transfer of sensed information is often achieved through a wireless interface established between transmission/reception antennas of the involved parts.

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A pervasive platform for monitoring exogenous stressors to forewarn the possible occurrence of SIDS

Siva Pujitha Mareddy and A. Vimala Juliet

The statement “SIDS is not Predictable but Preventable” emphasizes the need to adopt proactive measures for reducing the risk of Sudden Infant Death Syndrome (SIDS). One of the important strategies for effective management of SIDS risk is to provide a safe environment for infants. By nullifying the important link of external and environmental triggers referred to as exogenous stressors, the risk of SIDS can be reduced. This work presents a scheme for monitoring the exogenous stressors like prone sleeping position, exposure to cigarette smoke, exposure to ammonia gas (built up due to frequent urination in diapers), infant ambient temperature and infants body temperature which are attributed to the possible occurrence of SIDS. These parameters will be monitored through a host of sensors placed around the cradle.  We intend to encash on the increasing role of smart phones and tablets as platforms for health interventions. These smart devices are entrusted with the task of receiving, processing, displaying the values of the parameters and producing necessary alarms when required. In order to accomplish the above mentioned task, an application has been developed for the devices working on android platform using android version 4.1. All necessary communication protocols are established between the sensing system and the smart devices through this application.

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Improved power generation of micro thermoelectric generator using microfluidic heat transfer system

Jeyashree Y., Saptarshi Mukhopadhyay and A. Vimala Juliet

In this paper microfluidic properties is applied to a micro thermoelectric generation device (μTEG) and compared it with a micro thermoelectric generator where the microfluidics property is not used. By computationally applying a constant temperature difference between the hot side and cold side of the micro thermoelectric generator where the fluid parameters are considered as a laminar flow and the micro thermoelectric generator efficiency is calculated. Furthermore using the same temperature difference between the hot side and the cold side of the same dimension micro thermoelectric generator efficiency is calculated. In this paper it shows that using microfluidics properties the generated power is more. Experimental studies have done for a 50µm×50µm cross sectional area and 700K temperature distribution of a µTEG where the output power is 380 mv which 16% more than the previous.

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MEMS alcohol sensor for safety of driver in automobiles

Sintu Punnoose and J. Sam Jeba Kumar

The objective of this paper is towards designing a new MEMS (Micro Electro Mechanical Systems) based alcohol sensor to detect the presence of alcohol in a driver. Alcohol impaired driving accounts for nearly one-third (31%) of all traffic-related deaths in the United States. Vehicle-based alcohol detection systems use technologies which are bulky, space occupying, requires skin contact and is less sensitive to low concentration of alcohol and so there is need for designing a robust alcohol sensor. Thus the prime reason for choosing MEMS based alcohol sensor is to reduce the size of existing sensor, thereby providing high sensitivity, high stability, non-invasive and non-obtrusive device. Two different configuration of MEMS Alcohol sensor has being designed; first SAW (Surface Acoustic Wave) Alcohol Sensor and secondly based on surface reaction consisting of micro pillar (reacting pillars). The design and analysis of these two configurations were performed in COMSOL Multiphysics 4.4 software. The simulated results for both sensors show the concentration of alcohol in breath. Thus the MEMS alcohol sensors are designed for safety purposes in automobiles.

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Optimization of micro thermoelectric generator as a source of power for bio implantable devices

Jeyashree Y, Vimala Juliet A, C. PrantikBarua, J. SreeHarsha, and Abhilash Mallick

As the lifespan and power stability of the Implantable Biomedical Devices (IMDs) is quite limited, usage of Micro Thermoelectric Generator (μTEG) powered batteries is seen as a suitable potential solution to come over the drawbacks owing to its tiny size, light weight and recharge free attributes. A μTEG employs body energy harvesting techniques to utilize the temperature gradient within a human body and ambience to provide the electrical energy for various IMDs. In this paper, first we have comprehensively studied and discussed about the potential materials suitable for μTEG. Secondly we have investigated and optimized the material properties and design parameters, by studying various designs to obtain efficient power. A poly-SiGe based, 800x800x8000μm μTEG was made to convert the temperature gradient formed between the body heat that is 310 K and ambient temperature of 298 K and by this, the power generated was found to be 1.062×10^-6 W for a single μTEG. The performance of the μTEG and its biocompatibility to power the IMDs was evaluated and summarized. Thus, it was found that this device can be utilized to power the bio-implants.

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Energy efficient approach to protect source location privacy from global eavesdropper in sensor network

Karthiga S.

Sensor networks are used in monitoring the physical world objects. Generally protocols for sensor network provide secrecy for the content of messages, but contextual information can exposed to adversary. From contextual information, adversary can derive the locations of monitored objects and data sinks. Attacks on these components undermine network applications. Sensor nodes are limited in processing speed and energy supplies. The traditional communication techniques are very expensive to apply for hiding the communication between sensor nodes and sinks. Hence method to provide location privacy that accounts for the resource limitations of sensor nodes is needed. There are number of privacy-preserving routing techniques. Most of the techniques protect against an adversaries which are capable of eavesdropping on a limited portion of the network. Any global eavesdropper can easily eavesdrop on the entire network and defeat these schemes. The recently proposed periodic collection location privacy technique can protect against global eavesdropper. But the drawback is these techniques does not account for energy efficiency which was inevitable as sensor nodes have limited power supply. The proposed energy based routing enhance source location privacy preserving techniques periodic collection method is enhanced as energy efficient to increase the network lifetime.

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