A novel and maximum-likelihood segmentation algorithm for touching and overlapping human chromosome images

Sri Balaji V and Vidhya S

The chromosome abnormality in human is a vital issue. These abnormalities happen due to touching or overlapping chromosomes in human beings. It may cause breast cancer, improper structure or functions in body metabolism, birth defects, down syndrome, turner syndrome etc. To overcome these problems a stringent screening and diagnosing must be followed during earlier stage of pregnancy. In this paper Novel and Maximum-Likelihood segmentation algorithms were used to segment the overlapping and touching human chromosome images. Either the gray scale image was converted into color image or a color image is directly applied as the input to the Novel as well as Maximum-Likelihood segmentation algorithms. After obtaining threshold from binary, the watershed transform was applied. The output of watershed was improper. So after threshold the iterations were applied, followed by edge detection and corresponding segmentation. The Novel algorithm worked better only for touching chromosomes images but failed to work for overlapping images. Then the segmentation was followed using Maximum-Likelihood segmentation algorithm. By comparing with Novel algorithm, the Maximum-likelihood segmentation algorithm works better for both touching and overlapping chromosome images.

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Efficient growcut based image seam covering with quantization matrix estimation using anfis for JPEG error analysis

S. Vishnu Priyan and S.K. Srivatsa

The recognition of JPEG compression plays a significant part in digital forensics. Earlier, JPEG image can be compressed upto n times. However, in the JPEG compression error analysis in the JPEG images are not primarily concentrated. To solve this problem size of the JPEG image is reduced based on Growcut based seam covering technique. For the purpose of assessing the influence of image compression for JPEG image samples, Discrete Cosine Transform-Singular Value Decomposition (DCT-SVD) was computed for single and double image compression, images were quantized through quantization matrices, and quantization matrix results are assessed using Adaptive Neuro Fuzzy Inference System (ANFIS). Extensive experiments and evaluations with previous techniques reveal that the proposed DCT-SVD-ANFIS scheme can discover the double JPEG compression efficiently; it has extremely much significance in the field of digital forensics. The results of the proposed DCT-SVD-ANFIS  it is measured based on the parameters like, Peak Signal to noise Ratio (PSNR) and Mean Square Error (MSE).

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Optimization using fodpso algorithm for uhf rfid reader antenna

Madona jenifer D and Sivasundarapandian S

A new FODPSO algorithm is used to design the radio frequency identification (RFID) reader antenna for gain optimization is presented in this paper.  The problem of choosing the optimum locations and the associated parameters of readers in RFID communication systems is considered. In this paper, a novel optimization algorithm, namely the multi-community FODPSO, is proposed to solve the complicated RFID network planning problem of large-scale system. The effectiveness of using FODPSO (Fractional Order Darwinian Particle Swarm Optimization) for RFID reader antenna design will be investigated by a number of iterations required to achieve optimum solution along with the quality of solution. To validate the proposed design methodology, an antenna working at UHF radio-frequency identification (RFID) band is benchmarked.

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In most scenarios, several categories of DC-DC converter topologies have been utilized in the motor drive systems. On account of their irrespective distinctions, they all try to input the maximum quantity of power from the system with as diminutive loss of energy as possible inside the circuit itself. DC-DC converter is a kind of switching converter which fundamentally offers a certain quantity of ripple in the current, while it results in reducing the effectiveness. In general, this ripple is diminished by using a filter at the output terminals. At the same time as this is a solution, the magnitude, cost and life of the filter is completely based on the types of converter employed. Converters like buck, boost, buck-boost and cuk are derived topologies are employed in numerous applications are discussed here. This survey investigates and examines about the performance of the various converters in several applications especially in BLDC motors.

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In WSN the link failure is conquer by re-routing from the source node which is considered to be a time intense process that increases the overhead of the nodes. Also, in case of various link failures, there is probability for loss of data packets. The recital of the network during link failure has to be maintained vigorously in circumstances such as long data transfer and defend possible attacks during data transmission. Using SJFR algorithm we are going to recover the link failure.

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Vehicular ad hoc network is a wireless ad hoc network which carries some important functions such as message forwarding and route determination. In areas where there is sparse density of vehicles the network gets disconnected which affects the communication between the vehicles. In the existing system position based forwarding scheme have been used in which the data will be forwarded based on its position. Initially network will be dividing into small zones. Routing will select by the nodes which are placed in the same zone. Dynamically zones will change, because of node mobility in the network. Hence it is difficult to monitor the zone nodes periodically and Over Head will be high. In this paper multicasting technique is introduced based on trajectories. Here the information will be forwarded to group of destinations. Each node estimate the delivery delay to the access point (AP) based on trajectory. Also predict the future position of the nodes. Finally the source will determine which route has less delay and then it predicts route for data forwarding. Multiple nodes are involved in network for route selection. So easily we can select better route for data forwarding in a multicast way and hence the delay is reduced.

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The segmentation of the text from the historical degraded image documents is a very challenging task because the variations between the foreground text and background text are hard to determine. In this paper we have implemented a new segmentation algorithm to analyse and extract the words from a degraded image; the process carried here is the image contrast which is adaptively found to solve the issue. Initially the contrast map is taken from the degraded document images. The combination of local image gradient and the local image contrast is the adaptive image contrast, and then it is converted to binary level and combined with canny edge detecting algorithm to extract text edge pixels. The document text is further segmented by a local threshold that is estimated based on the intensities of detected text stroke edge pixels within a local window.

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In today’s epoch of computer science storing and computing data is a very important phase. In recent days even a petabyte and exabytes of data is not adequate for storing large number of databases which contains large data sets. Therefore organizations today use concept called Hadoop which is a software framework of big data in their application. Hadoop is designed to store and process large volume of data sets consistently. While using geographically distributed data centers there may be a chance of data loss due to network link failure and node failures. Hadoop provides high reliability and scalability features. Along with it also afford faults tolerance mechanism by which the system functions properly even after a node in the cluster fails. Faults tolerance is mainly achieved using data replication and Heartbeat messages. Heartbeat messages are like acknowledgement messages between two nodes and  Data replication is achieved by creating copies of same data sets into more than one computing nodes. In this paper we describe about the Hadoop architecture and its components and also describe how the fault tolerant mechanism is achieved using data replication and heartbeat messages.

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This project is to design and develop a robotic exosuit intended to assist over ground gait for paraplegic the person who have suffered from spinal cord injury. This robotic suit is giving wheelchair users the chance to walk. Almost fully encasing the bottom half, they hold the legs in place while they walk from place to place, controlled by a small joystick at waist height. Compared to previous soft exoskeleton suit, this device is a very powerful tool which resulting in high mechanical efficiency for steady walk and even it enables the navigation of stairs and slopes safely. This device is a bipedal exoskeleton suit with eight degrees of freedom which can give acceleration to the patient’s hip, knee and ankle. It is designed to implement different control strategies like walk forward, turn left and turn right. The interface between the user and the device can be controlled through mems sensor or joystick. It does not require crutches or a walking frame to provide stability, leaving the hands free.

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The common methodology in data embedding is that in the sender side, the data is to be hidden within the pixel values of the cover image that is producing the stego image. In the receiver side the embedded data in the stego image is retrieved by reversing the same process that is employed for embedding. The data that is to be hidden which is embedded in the AES encrypted image using Reversible Data Hiding (RDH) method. The RDH improves the data hiding process. In existing the data retrieval process the error is accrue it affect the data, in our proposed improve the data hiding and retrieval accuracy. A content owner encrypts the original image using an encryption key and reserves the room for data hiding. Then, a data-hider hides the data in reserve space of the image. If a receiver has the data-hiding key, he can extract the additional data though he does not know the image content.  AES algorithm uses two different keys for encryption and decryption. Each byte of the state is combined with a block of the round key using bitwise XOR. Then each byte is replaced with another according to a lookup table. The last three rows of the state are shifted cyclically a certain number of steps. Four bytes in each column were combined. In the receiver side the same procedures are reversed in order to obtain the secret message and the cover image. The performance of the process is measured with the help of the calculation of the Compression Ratio, PSNR and MSE. The measured performance indicates that the proposed system is capable of hiding the messages with better accuracy and the process is reversible also and hence has numerous applications.

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Quality of the product which is used in our day-to-day life is important to be analyzed. When the level of chemicals increases exceeds day by day then it may cause quality of the product to be low and causes side effects for the person. The sensitivity of the human nose varies according to the unique characteristics of persons. By using E-Nose technology, the array of sensors is placed for sensing the alcoholic content in the samples injected. E-Nose is a simple, rapid and gives accurate result. MOS gas sensors are preferred more than other gas sensing system in the sensory array, it extracts the VOC’s present in the samples. The E-Nose consisting of six MOS gas sensors was used to identify the various smell print. The main purpose of this paper is to identify the various cosmetics products which has alcoholic component with the designed prototype of E-Nose setup which is used in normal day-to-day activity and to identify the various smell print for the product.

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The Present day workstations, low-power processors, computers and super computers are using fast Static Random Access Memory (SRAMs) and will require, in the future, larger density memories with faster access time and minimum power consumption. Acknowledging the intense requirements for power, in current high performance memories of computing devices, the circuit designers have developed a number of power optimizing techniques which target several sources of energy dissipation in an SRAM. The total power dissipated in a typical SRAM architecture is the active and standby power. The access to the memory cell is performed through word line and bit line. The hetero junction concept of SRAM was simulated. The single bit line for a 16 SRAM cell was implemented in an array fashion and the power results are computed and compared with multiple individual SRAM cell structures .The results show that single bit line results in 2.5 times reduction of power. The simulation results are obtained from tanner 14.1 environments.

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Health monitoring is regarded as a crucial part in the patient management, since it provides vital data for diagnosis and treatment. The main challenges in current health monitoring devices are the lack of remote monitoring in real time and logging for future evaluation. Typical devices used for health parameter measurement provide basic information regarding health status. A proposal for dynamic monitoring is done to overcome these challenges. A system for patient monitoring using biomedical sensors and displaying it in a remote place is proposed. Constant measurement of health factors such as electrocardiogram, oxygen saturation in blood, heart rate, and surface temperature of the body is incorporated into this system. A prototype is developed to process and transmit the accumulated sensor data to the receiving unit where it is viewed through the implementation of cloud services.

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The investigation of the modeling of Proton exchange Membrane Fuel cell is generally rely on the rudiments of the chemical reaction or other chemical equations which governs the behavior of fuel cell , But in this manuscript probes about likely numerical solutions of a fuel cell. This manuscript probes about maximum attainable potential upshot yielded by fuel cell by analyzing the Voltage - Current characteristics obtained from the simulative analysis of the fuel cell modeling of fuel cell done using Matlab for diverse operating condition and maximum harvestable latent output is evaluated at that juncture.

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Web Mining is the integration of information gathered by traditional Data Mining methodologies and techniques with information gathered over the World Wide Web. The World Wide Web today provides users access to extremely large number of Web sites many of which contain information of education and commercial values. Web mining research, in its last 15 years, has on the other hand made significant progress in categorizing and extracting content from the Web. Nowadays the Web has proved to be as a rich and extraordinary data source of information, where multiple domains can be accessed and mined. Mining Web data is referred as Web Mining. Some of the objectives of mining web data include finding relevant information discovering new knowledge from web personalized, web synthesis and learning about individual users. Amongst these the most common use is finding relevant information. In this paper, we represent Web Prediction Method on Social Network Analysis. These techniques can be used for real world applications like market strategies, business intelligence and etc... Social Networks the interest of a single user represents the interest of the whole group. Ontology defines a set of representational primitives with which to model a domain of knowledge or discourse.

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This paper presents a method of reducing the losses and balancing the loads in the radial distribution network. Differential evolution strategy is used for reconfiguration of the radial distribution network. Multiple objectives such as loss reduction, voltage deviation and maximum branch current are considered. These objectives are integrated into the objective function through weighting factors and the configuration with minimum objective function is selected for each tie-switch operation. The proposed methodology is tested and validated on 33 radial bus distribution networks. Performance is assessed by using the results of the implemented algorithm with various other algorithms.

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The proposed system is a portable camera based visual assistance prototype for bind people to identify currency notes and also helps them to read printable texts from the handheld objects. To read printable texts, an efficient algorithm that combines an Optical Character Recognition (OCR) with Hierarchical optimization is used. In Pattern Recognition OCR every character is localized and separated then the resulting character image is sent to a pre-processor to reduce noise and to perform normalization. Certain characteristics will be extracted from the character for comparison. After comparison the identified characters are grouped and reconstructed to form original text strings, then the output is given to the speech engine to perform text to voice conversion. For identification of currency notes a novel recognition system is developed using SIFT (Scale Invariant Feature Transform) to improve precision and accuracy. The input image undergoes pre-processing and thereafter the distinct features are extracted and compared with the templates from the database. The resulting outcome is given through Earphone to the blind users.

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Multiport dc/dc converters are widely used in hybrid energy generation systems, microgrids and electric vehicles to provide stable power to key loads with high power density. In this project, a multiport isolated bidirectional dc–dc converter is anticipated for hybrid energy storage system in microgrids. Microgrids are connected to the nearby renewable energy generation systems as solar, wind, etc. These systems do not provide pure DC voltage for conversion into AC required by the grid. Hence a single stage DC-AC-DC conversion is required. For energy management and single stage power conversion, multiport BDC is the best choice. Also to minimize the switching losses and henceforth to improve the efficiency of the converter system, Zero Voltage Switching (ZVS) can be achieved for all switches in any direction of power flow in the whole load range with decoupled duty cycle control and phase shift.

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Self-transforming robot is a robot which transforms its shape according to the hindrance occurring in the path where the robots are being moved. Such robots have been recognized as very attractive design in exhibiting the reliable transformation according to the situations. Military and defense application needs a robot should possess arbitrary movements like human. In some scenarios transformations are made by biological inspired control strategies using Central Pattern Generators (CPG). CPG is used in the locomotion control of snake robots, quadruped robots, to humanoid robots. This paper presents a Fuzzy system for the Self-transforming robot which possess alteration in its original shape to exhibit a human-like behavior while passing over the particular location. Quadrupedal locomotion on rough terrain and un-predictable environments is still a challenge, where the proposed system will provide the good adaptability in rough terrain. It allows the modulation of locomotion by simple control signal. The necessary conditions for the stable dynamic walking on irregular terrain in common are proposed. Extensive simulations are carried out to validate the performance of the proposed Fuzzy system using LABVIEW. Arbitrary parameters such as distance, angle and orientation of the obstacles are provided as input to the fuzzy system which gives the required speed modulation on the motoric module.

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Visible Light communication (VLC) using White Light Emitting Diode (LED) is a promising technology for next generation communication for short range, high speed wireless data transmission. In this paper inexpensive transmitter and receiver of VLC system is designed and its performance is evaluated. The effect of natural and artificial ambient light noise sources is also considered. Experimental results show that the data transmission distance achieved upto 0.45m.Performance analysis is done with respect to optical power, photo sensitivity of photodiode at the receiver and the increase in distance between the transmitter and receiver.

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A Distribution Static Compensator (DSTATCOM) is a powerful tool for mitigation of the power quality problems. The power quality problem arises due to increasing number of sensitive loads. Hence, in order to maintain power quality the DSTATCOM has been installed. DSTATCOM will provide or absorb the reactive power. In distribution system reactive power is the main reason of power quality problems and system loses. This paper explains the system used to compensate the reactive power, Unbalance load condition and unbalance voltage. The effectiveness and performance of the DSTATCOM to mitigate the power quality problems are analyzed by using SPWM technique. The results are obtained through MATLAB and Simulink software.

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In this paper, the design of five port structures using power dividers and hybrid coupler was done using Advance Design Systems. Micro strip lines were used in the design procedure and the termination is done with 50 ohm resistance. This methodology yields encouraging results in impedance matching, performance improvement  and the scattering parameter simulation has been done for the design and simulation results are obtained. 

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The ancient stone inscriptions and epigraphy corroborate information from other sources; afford the dossier and habit of pharmaceutical remedies and also the hints of Ayurveda significance, which provides an insight into early Indian bureaucratic structure, legal codes, and myth practices. Hence here proposed a theme to analyze and translate the epigraphs of Bhrami, Grantha, Vattezhuthu and Devenagiri font into our 21st century Tamil fonts using segmentation technique integrated using Sobel edge detector, Otsu thresholding and Particle Swam Optimization (PSO) technique whereas the filtering techniques play a crucial role in enhancing the quality of an image. Probabilistic Neural Network (PNN) involves to identifying the noise as well as help to predict the suitable filter for the removal of a specific type of noise, along with the PNN for noise removal and accurate segmented image, there were mapping technique of ancient Grantha font to our 21st century image are wrought by Lab VIEW thus the recognized and translated output is been obtained.

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The availability of cheap computing power and instrumentation electronics accompanied by the communication revolution has engendered a complete paradigm shift in the design and implementation of electrical grids. Power grids are envisaged to be transformed into “Smart Grids” incorporating a high degree of intelligence with a view to enhance the reliability and efficiency of generation, transmission and distribution systems. Real-time monitoring of grid parameters enables more effective management of power generation. Prevention of theft by means of smart metering is another major advantage. However, the large scale use of embedded systems, computing resources and communication networks makes the grid vulnerable to cyber attacks. These vulnerabilities can result in consequences ranging from diminished quality of service to catastrophic events such as line trips, extended blackouts and downright damage or destruction of assets. This paper gives a review of the current state-of-the art in cyber security for the smart grid environment. An FPGA based engine for detection of denial-of-service attacks in packets in an Ethernet link is also proposed.

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There exists several `attributes for a data, and among them confidentiality and security is gained by the entity which is termed as Authentication. The defined entity exhibits the involvement of another entity called as identification involving two or more parties, which in turn confirms an identity. Worldwide interoperability for Microwave Access (WiMAX) and Long-Term Evolution (LTE) has been the alluring Fourth Generation (4G) wireless technology in the networking between vehicles providing explicit quality of service (QoS) and security architecture. In spite of its advantage it has some security threats such as denial of service (DOS), node capture attack, etc., which mainly occurs in Multihop wireless networks. It could be alleviated by secured and prompt authentication methods. In the VANET communication, especially in Multihop networks the forwarder node authentication is more important. So, we need to provide authentication for each and every hops. Hop by Hop message authentication is required to provide high level security in VANET. Simultaneously, the address of the data origin known by the attacker leads to node capture attack. So, to avoid this, we have to consider the source anonymity also. To provide Hop by hop authentication and the source anonymity, we are going to use the SAMA on Elliptic Curve Cryptography in VANET.

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Maximum power point tracking (MPPT) algorithm increases the solar energy efficiency of a solar PV systems.  Incremental conductance based MPPT technique is used to track maximum power point exactly with fast response. The Incremental conductance method search the exact MPP based on the feedback voltage and current but does not depend on the characteristics of PV array. The MPPT algorithm is implemented in PV based power generation systems along with two different DC-DC converters to boost up the output voltage. The working of proposed algorithm is checked by simulation using Matlab/Xilinx system generator. The performance of the algorithm with boost converter is validated and compared with SEPIC and the conclusions were drawn at the end of this paper.

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Administration recommender frameworks have been indicated as important apparatuses for giving proper proposals to clients. In the most recent decade, the measure of clients, administrations and online data has developed quickly, yielding the enormous information examination issue for administration recommender frameworks. Also the greater part of existing administration recommender frameworks, exhibit the same appraisals and rankings of administrations to distinctive clients without considering various clients' inclination, and hence neglects to meet clients' customized necessities. Consequently we approach a customized administration proposal rundown for the most suitable administrations to clients, by proposing a keyword-aware suggestion strategy and Natural Language Processing, to address the above difficulties. Particularly, keywords are utilized to demonstrate clients' inclination, and a client based Collaborative Filtering calculation is received to create proper suggestions. To enhance its versatility and productivity in vast information environment, it is actualized on Hadoop platform, a generally embraced appropriated figuring stage utilizing the MapReduce parallel transforming framework. At long last, far reaching trials are directed on certifiable information datasets, and results exhibit that personalized search technique fundamentally enhances the exactness and versatility of administration recommender frameworks over existing methodologies.

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Large-scale application programs in grid requires resources from several grid service providers (GSPs). These grid service providers form virtual organizations (VOs) by pooling their resources together to provide the required capabilities to execute the application. In this model, the VO formation in grids using concepts from the coalitional game theory and design a mechanism for VO formation. The mechanism enables the GSPs to organize into VOs, reducing the cost of execution and guaranteeing maximum profit for the GSPs. In this approach, the mechanism guarantees that the VOs are stable but GSPs not stable it will break away from the current VO and join some other VO. Thus the results show that the mechanism produces VOs that are stable yielding high cost for the participating GSPs.

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In our previous work, it was proved that the performance of bic-tcp was good under satellite network, and a new adaptive window increment based bic-tcp algorithm (bic_AWI) was proposed to show an improved data transfer in satellite network. We, implemented the idea on ns2’s implementation of bic tcp. Proposed modifications has been made on bic-tcp, and improvement in performance has been realized. Even though, the congestion avoidance mechanism of standard bic will be very much influenced by this proposed adaptive window change strategy, in update method of the bic, some of the parameters like BICTCP_B are kept as constant during finding a optimum tcp windows size. The constant value BICTCP_B has been cahnged dynamically with respect to the acceleration and deceleration of rtt, has shown a considerable improvement in performance. Based on that idea, we proposed a dynamic parameter estimation  based binary increase congestion control algorithm (bic_DPE) for data transfer in satellite network. In this method, with respect to the acceleration of deceleration of rtt the important parameter BICTCP_B will be dynamically adjusted to provide best performance. Further, we added the mechanism to minimize packet loss during terminal handover. Proposed modifications has been made on bic-tcp, and the performance of the improved protocol “bic_AWI” and “bic_DPE”  has been compared with normal bic-tcp under Iridium satellite constellation. The  performance of the algorithms has been measured using suitable metrics and theproposed bic_DPE performed better than normal bic-tcp  as well as our previous “bic_AWI” method.

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Diabetic macular edema (DME) is a complication of diabetes .It can blur or distort patients’ vision and make the blindness. It is categorized by the presence of lesions. Habituallythe presence of lesions is detected by Ophthalmologists from the dilated retinal images captured by dropping chemical solution into an eye. This process peeves the patients. So, there is a need for an autonomous method to detect the presence of lesions using image processing algorithm from the non-dilated images to help the ophthalmologists to diagnose the disease without inconvenience and irritation to the patient and thus protects patients from vision loss. In this work, Meadian filter and Contrast Limited Adaptive Histogram Equalization used in image preprocessing. Motion pattern estimation with masking process used for segmentation. To extract the feature Grey Level Co-occurrence Matrix isused.  Support vector machine used to classify the severity level for disease.The proposed algorithm has produced the sensitivity of 99.743%, specificity of 97.14% and accuracy of 97.711%.It is more helpful for ophthalmologist in the detection of DME. Since this method is automated, it detects faster and this level of accuracy in result helps the ophthalmologists to diagnose the disease very easily.

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Permanent Magnet Brushless DC Motor (PMBLDC)  is one of the best electrical drives that has increasing popularity, due to their high efficiency, reliability, good dynamic response and very low maintenance. Its predominant applications are in automotive, aerospace, household appliances, office automation and other industries. This paper proposes a new multistage interleaved buck converter fed PMBLDC drive system having very low switching losses and improved step down conversion ratio, which is suitable for the applications where the input voltage is high and the output voltage is low, where the operating duty cycle is below 50%. When compared  with the conventional interleaved buck converter where two active switches are connected in series and a coupling capacitor is connected in the power path,  where as in the proposed Multistage Interleaved Buck Converter(MIBC) fed system it can be seen that the voltage stress across all active switches is half of the input voltage before turn on or turn-off when the operating duty cycle is below 50%, the capacitive discharging and switching losses can be reduced considerably, following that the MOSFET fed inverter bridge is feeding the PMBLDC drive system. This allows the proposed multistage IBC to have higher efficiency and operate with higher switching frequency. In addition, the proposed Multistage IBC has a higher step-down conversion ratio and a smaller output current ripple compared with a conventional IBC. The multistage IBC fed PMBLDC drive system features, operation principles, relevant analysis and results are presented in this paper. The validity of this study is confirmed by the experimental results of prototype system with 40-60V Input, 12V/5A output. Further the closed loop system is controlled using Fuzzy controller to enhance the motor performance in various load conditions and the corresponding results are also presented.

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The most significant planning bustle in the electric utilities is the Generation Expansion Planning (GEP). This paper aims to incorporate Wind Power Plant (WPP) as one among the candidate option in GEP and analyse the cost incurred to incorporate WPP as one of the candidate. The total cost consists of the Initial cost, Operation and maintenance cost, Outage cost and Salvage cost. Outage Cost is calculated based on Expected Energy Not Served (EENS). In this paper, equivalent energy function method is applied to compute EENS and to compute Loss of Load Probability (LOLP) which is considered as a reliability constraint. Particle Swarm Optimization (PSO) technique has been applied. The results obtained by PSO were compared with Dynamic Programming (DP) method. Addition of WPP to instead of conventional plants is expected to increase the total cost, and it is necessary to study the impact of such increase. The resulting cost and reliability indices variations were also reported.

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Wireless cellular networks have to be designed and deployed with unavoidable constrains on the limited radio resources such as bandwidth and transmit power. The primary objective of this paper is to improve the capacity and utilization of the radio resources that are available by the service providers. This paper deals with the resource allocation problem relay-based Orthogonal Frequency Division Multiple Access (OFDMA) cellular network where relay stations (RS) perform network coding with downlink and uplink sessions of a mobile station (MS). The aim of the paper is to maximizing the weighted sum rate for both uplink and down link for all users while satisfying quality-of –services(QoS).To make the proposed system more realistic additive white Gaussian noise, and fading present in the communication channel for both uplink and down link.

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Biodiesel is explored to be used in standard diesel engines and is thus distinct from the mineral oils. Biodiesel can be used alone, or blended with diesel in any proportions. A numberof studies have shown significant increase in nitrogen oxides (NOx) emissions in biodiesel fuelled diesel engine. The increase in NOx, HC and CO emissions and solutions to this problem has been the subjects of research for considerable time.Itis difficult to control NOx emissions. In the Internal Combustion Engine, at high temperature, oxidation of nitrogen takes place and a significant amount of NOx will be formed at the end of combustion. The majority of NOx formed will however decompose at the low temperatures of exhaust.  But due to very low reaction rate at the exhaust temperature, a part of NOx formed remains in exhaust. An attempt has been made to reduce this emission using Cetane improver DEE that helps to reduce the ignition delay thereby reducing the combustion temperature. As the NOx increases linearly with the amount of blend, in this experiment, DEE is added at 0.01 to 0.05% by volume to the different blends and NOx emissions are measured with exhaust gas analyzer. From the results, it is shown that B30 blend with DEE gives the better results for reduction in NOx.

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Conservative logic is one of the best nano technologies to design digital circuits. This paper proposes testable reversible sequential circuits based on conservative logic. Any sequential circuit can be tested for classical unidirectional stuck at faults 1’s using only two test vectors. The completely testable sequential circuits design based on conservative logic gates using fault leeway model is proposed here.  The proposing fault leeway model consist of two test vectors all 0’s and 1’s. The proposing design of D latch, master slave flip-flop, DET flip-flop is done with the help of conservative logic gate (Fredkin gate). This results in reduction of testing time. With that result the proposed work takes some advantages such as reduced number of gates, reduced power consumption and reduced delay time.

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Applications of Digital Image Processing (DIP) have become common in our day to day life. Exploitation of digital image processing systems for real time applications indeed requires efficient computing techniques., the proposed algorithm mainly focuses on Very Large Scale Integration (VLSI) chip based implementation of digital image processing applications since it suits better for real time processing. The proposed method VLSI implementation for interesting applications such as identification the pest affected or not affected crops in the agriculture field. But farmers used fertilizer at certain period of time at field crops growth. These crops are purchased by the customers without any knowledge. All the fertilizers are made from chemicals. These chemicals affect the human health. To overcome all the problems mentioned above, a system is proposed with high computation speed in this research work. This will help the customers as well as farmers in the agriculture field. The equipment for this purpose should be portable, and the measurement method should be quick, capable of providing test results within a very short time. High Quality Interpolation Algorithm (HQIA), Edge Matching Algorithm, Edge detection, anisotropic weighting model and filter based compensated methods is used. The design is based on VLSI for the hardware implementation using Mathematical Laboratory Matlab and Modelsim software. Field Programmable Gate Array (FPGA) Cyclone III kit is used for the hardware implementation.

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Wireless Sensor Network become a promising technology to observe various universal parameters and conditions and help to diminish decline virtual and physical world.  This article describes an application based temperature sensing in a critical sensing environment such as military environment or furnace temperature etc. where the cut of value of a temperature value is so important. It is based on microcontroller in the transmitter side and a web enabled management of data in the receiver side. The algorithm adopted here is SEEMD which is security enabled energy efficient Middleware for WSN.

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Now-a-days leakage power is an important issue in microprocessor’s and hardware’s. In modern computer systems memory components covers 70 to 80 percent of total area of microprocessors that means memory contains more number of transistors. Generally leakage power dissipation proportional to the number of transistors. So the leakage power dissipation is more in the memories. In high performance memories systems sense amplifiers are very important part for sensing the output. In this paper we are focusing on memory leakage power reduction particularly in sense amplifiers using Fine Grain Power Gating (FGPG), Variable Body Biasing Technique (VBBT), Proposed Different Footer Dual Stack Technique (FDST) based both PMOS, one PMOS and one NMOS, both NMOS and Proposed PMOS Footer Triple Stack Technique (PFTST), PMOS Footer Four Stack technique (FFST) in Current Sense Amplifier (CSA), Charge Transfer Sense Amplifier (CTSA) and High Speed Sense Amplifier (HSSA).Variable Body Biasing Technique and PMOS Footer Triple Stack Technique are proposed techniques. We are applying these techniques in Different Sense Amplifiers. Proposed Variable body biasing leakage power dissipation in Current Sense Amplifier  1.5 times less than compare to Sleep Stack, Sleepy Keeper and 0.73 percent less than Forced Stack technique and this technique is much power efficient than other existing techniques. Second proposed Triple stack technique leakage power dissipation in Current sense amplifier is 2 to 3 times less than other techniques and total power dissipation almost 99 percent less than other existing techniques. Proposed techniques are also much efficient for other sense amplifiers.

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Highway obstacle detection is one of the most challenging task in real time for autonomous vehicle navigation system. The basic idea is to design an effective system for real time environment, which detects the presence of obstacles in the track of the vehicle. In the proposed work Raspberry Pi Camera module is employed for object detection and image acquisition. A thorough investigation is performed on a test image in order to validate the best algorithm suitable for edge detection of images. Sufficient analysis is performed to consolidate the results.

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This project presents moving object detection based on background subtraction under complex wavelet transform domain for video surveillance system. The proposed approach has some advantages of background noise insensitiveness and invariant to varying illumination or lighting conditions. It also involves background updating model based on current frame and previous background frame pixels comparisons. The object detection also helps to track detected object using connected component analysis. The simulated result shows that used methodologies for effective object detection has better accuracy and with less processing time consumption rather than existing methods.

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In this specific paper, we have suggested an algorithm for synergistic segmentation of skin ulcer images of the diseased. If a small number of user pixels are provided, then by using Grow Cut method, we can automatically segment the rest of the images. User can sharply observe the segmentation procedure and guide the algorithm whenever the segmentation becomes difficult. In particular areas, where the segmentation is done automatically, no extra effort by the user is necessitated. The segmented skin ulcer images are presented.

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This paper deals with power dissipation in digital circuits. Effect of leakage power reduction techniques are deal with digital circuit design. Analyses of these techniques are done in MICROWIND environment. Power dissipation of these techniques is calculated and compared with conventional design. The layouts are designedusingMicrowind. The simulation outputs are taken and observed. Power dissipation of the circuits are tabulated and compared.

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Cache memory is a additional and fast memory unit that has to be placed between the processing unit and the physical memory. The most recently used instructions and data, where this information are needed to be accessed again are stored in cache .The use of cache memory makes the processing to be faster. As the cache memory moves away from the CPU, the access time and the size of the cache memory storage unit increase as well. The physical memory and external disk storage devices can be accessed faster by the internal registers and cache which are located near to CPU. Cache which are accessed faster and also with less miss rate can be considered to be more power efficient. On-chip caches which are of large size are used in order to overcome cache miss are increasingly used by the modern processors. Also, with each CMOS technology generation, the leakage power consumption is said to be increasing for the past few decade. For this reason, cache power management has become a very important scenario in modern processor design. To address this challenge and also sustainable computing goals are met by several energy efficient techniques that are proposed for the cache architecture. The static and dynamic power consumption will lead to the total power consumption. The power consumption of set associative cache due to access of every cache is more when compared to the direct mapping method, this includes both the tag and the data parameter of the cache. This paper presentsa review on different cache technique and the cache optimization parameters and there are different low power techniques for low power cache.

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Music player are provided with very few search options. In this paper, two different user interfaces touch screen and audio recognition module are used to access music player. This can be used by both blind people as well as normal persons. The project is based on the MSP430 microcontroller which has low power consumption. Feedback is also provided when song selected is not present in music player. This overcomes the disadvantage of other audio players by providing search option in an easy manner.

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Fovea is one of the important features of a fundus image. Extract the different features like blood vessels, optic disk, and fovea are automatically from the retinal image is very difficult process. Fovea detection helps doctors to identify Diabetic Retinopathy (DR), Age Related Macular degeneration (AMD), Retinopathy of Pre-maturity (ROP) and some other diseases of the patients. Diabetic Retinopathy is a cause of sight loss sometimes it will reach an advanced stage and cannot be cure. However Retinal image is essential and crucial for the ophthalmologists to diagnosis the disease. In the RGB image the green channel exhibits the best contrast between the vessels and background. With the help of Adaptive Histogram Equalization, thresholding method and smoothening method, can detect the fovea region. Also the Automatic screening will help for the doctors to quickly identify the condition of patients. Here implemented a new efficient method to localize the fovea in retinal fundus image. In this proposed work aim for automatic screening of Fovea for detection of Diabetic Retinopathy. By automatically identifying the normal images, the workload and its costs will be reduced by increasing the effectiveness of the screening programs. Here collected the data base from LOTUS EYE HOSPITAL, Coimbatore. Based on that data base done this work.

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Now a day it is indeed to design and implement an adiabatic logic in Vedic multiplier. Normally the power consumption was the main thing to remember before designing and implementing. So, the main aim to concentrate on the power consumption is very important. Here the proposed adiabatic logic is efficient charge recovery adiabatic logic based design. Compare with other multiplier the Vedic multiplier consume very less power, here combining with this adiabatic logic the power consumption is dramatically reduced. The tool used here was tanner EDA to designing the Vedic multiplier using efficient charge recovery adiabatic logic.

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System On Chip is a complete integrated system because it consists of several different microprocessor subsystems together with memories and I/O interfaces. So the connections between these IP’s components are the major issue and the Network On Chip (NOC) plays an important role in connecting these IP’s. The adaptive XY routing never runs into deadlock or live lock therefore it consumes more power and it also passes the data through fault path. In the proposed, a new Network On Chip use Genetic Algorithm which is an optimization algorithm used to find the shortest path and critical path analysis by routing the router on four sides so this algorithm is free from live lock and deadlock problem thereby it consumes less power. It also finds fault part of NOC components by using fault analysis process to identify the damaged router in NOC chip architecture. The experimental results shows reduction in power with 20% and delay can be reduced with 40% on average compared to adaptive router architecture for network on chip.

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This paper explains the simulation of a high frequency (20kHz) single phase full-bridge voltage-fed Series Resonant Inverter for the Induction heater and the Pulse Density Modulation has been employed in-order to control the output power.. The open loop system and the closed loop system with PI and FLC are simulated and their results are presented. The results of FLC based system are compared with those of PI based system. This inverter system has advantages like high power density, reduced steady-state error and improved response.

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Adhoc Networks are new paradigm of wireless communication which lack specific infrastructure. Scalability and Routing are the two major challenging issues that needs to be addressed for providing better performance of the network. Due to mobility nature and dynamic topology, the conventional routing protocol should be manipulated to meet QoS requirements required for multimedia traffic.  To overcome the scalability issue, QOS parameters are kept in rigorus bound for group communication. Fuzzy Inference based System (Adaptive Neuro Fuzzy Inference) is used to optimize the QoS parameters such as delay and node speed for attaining the better performance of the network. This proposed scheme provides improvement in QoS metric such as delay, packet delivery ratio and minimizes the possibility of link failures and the overhead needed to construct the paths.

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T-Source Inverter (TSI) is proposed for Induction Heating (IH) applications to obtain higher efficiency with reduced Total Harmonic Distortion (THD). Sinusoidal Pulse Width Modulation (SPWM) technique is used to control the switches of T-source inverter. Utilization of shoot through switching operation provides voltage boost ability to the inverter. Operation of induction heating load is based on the principle of electromagnetic induction. Skin effect and eddy current is used to produce heat in working pot. The operating performance of T-Source Inverter was shown through experiment results.

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Communication is transfer of information from source to sink or sender to receiver. The signal when transferred through the noisy channel gets affected by the noise and becomes an error signal when it reaches the receiver. Decoding is the process of retrieving the correct information from the received signal. The weighted bit flipping LDPC decoding algorithm gives a good performance in retrieving information. The proposed algorithm which is modified multi bit threshold weighted bit flipping decoding (MMTWBF) algorithm of low density check code (LDPC) gives a good performance and an effective practicability in comparison with reliability rate weighted bit flipping algorithm (RRWBF) and good speed compared to multi-bit threshold rate based weighted bit flipping algorithm(MTRWBF). This algorithm flips the plurality of bits at each time, which helps in reducing the shortcomings in improved reliability rate weighted bit flipping algorithm (IRRWBF) decoding convergence speed. The simulation results reveal the improvement in simulation speed and the decoding iteration is reduced.

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Filtering techniques are used in  image and video processing applications for various technologies. Field Programmable Gate Array (FPGA) technology has become a viable target for the implementation of real time algorithms and it  is suitable for real time  video image processing applications.  Explicit type of  image filter called  the guided filter is proposed to remove the noise in video by smoothing and  sharpening of image frames and it is also used to preserve the edges . Weighted least square filter is used to remove the halo effect. Here, the systolic array architecture is proposed for modified guided filter. Systolic array architecture is an efficient data  to improve the pipeline and parallel processing. The guided filter is derived from the local linear model which  computes the filtered output by considering  the content of  the guided frame  as  the input frame. It  can also transfer the structure of filtering image to the filtering output enabling the filtering application like dehazing  and guided feathering. Application such as  Computer  vision and computer graphics includes edge-aware smoothing,  HDR compression, image matting. FPGA can be used to implement any logical function that an ASIC could perform. An efficient modified guided filter architecture is implemented on cyclone II FPGA device which offers less cost ,speed and supports the NTSC video.

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The MHD peristaltic flow of a couple stress fluid permeated with suspended particles through a porous medium in two dimensional flexible channel under long wave length and low Reynolds approximation is studied. An analytical method of solution is obtained in terms of wall slope parameter and closed form of expressions has been derived for axial velocity and transverse velocity in fluid phase and particle phase. The expression for velocity profile and pressure gradient and the volumetric flow rate in the wave frame is obtained. The graphical results obtained for velocity profile and pressure gradient. It is observe that velocity profile decreases with increase in Hartmann number M and couple stress parameter S. The pressure gradient has an opposite behavior compared with velocity profile for Hartmann number M.

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Box Jenkin’s Auto Regressive Integrated Moving Average (ARIMA) technique is one of the most sophisticated extrapolation methods for prediction and Artificial Neural Network (ANN) is a modern non linear technique used for prediction. This paper compares the performance of both these models for the net asset values of Sahara Mutual fund-Growth for a period of 6 years (from 2006 to 2012) and the Mean Absolute Error (MAE), Mean Square Error (MSE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE) and Mean Percentage Error (MPE) are used to evaluate the accuracy of the models. In all these error estimates ANN model performs much better than ARIMA model.

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Skin cancer is rapidly increasing in western parts of the world. Survival rate of skin cancer is high, if detected early. So an efficient method is necessary to detect skin lesion at the earliest. Since the cost of dermatoscope scan for screening the patient is high, there is a need for an automated system to detect skin lesions captured using a standard digital camera. The main aim of a skin cancer detection system is to reduce the percentage of error by choosing the appropriate method in each stage .In this paper, for pre-processing stage adaptive histogram equalization technique and wiener filter is used. A novel method is proposed for the segmentation and classification of skin lesions.

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Fovea is the centre most part of the macula. A healthy fovea is key for reading, watching, driving  etc... Fovea detection helps doctors to identify diseases like diabetic retinopathy (DR), age related macular degeneration (AMD) and retinopathy of pre-maturity (ROP). Diabetic retinopathy is the most common diabetic eye disease and it can eventually leads to blindness. With the help of adaptive histogram equalization, threshoulding method and smoothing method can detect the fovea region. These features are proceeded with the help of Fuzzy C-Means clustering algorithm to detect the different diabetic  retinopathy stages and the result will be compared with KNN. The accuracy of the diabetic retinopathy detection system is 98.5%.

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OFDM Orthogonal Frequency Division Multiplexing is a multicarrier modulation scheme. It is widely used in wired and wireless communication systems. Impulse noise can be mitigated by considering it as a sparse signal in time, and using recently developed algorithms for sparse signal reconstruction. We propose an algorithm that utilizes the guard band null subcarriers for the impulse noise estimation and cancellation.

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Creating an efficient and effective system is a motto of a software engineer. The companies are spending 60% of cost for producing good quality software, software metrics require to measure qualitative in terms of software performance and reliability related characteristics like dependencies, coupling and cohesion etc. This paper proposes a set of new measures to find coupling and cohesion in a developmental system using Java reflection components to assess the usability. It will predict the fault in an object oriented system. Coupling and cohesion metrics are calculated by considering a number of relationships of a class. In this paper these metrics are calculated by using structural parameters like classes, methods and attributes. The structured information embedded in the source code. Classes, methods and attributes are retrieved in a package by using Java reflection. The retrieved information helps to measure the coupling and cohesion.

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Cloud computing is well developed popular option for renting of computing and storage infrastructure services. Cloud computing is a computing resource in which tasks are assigned to a different set of connections, services and software that can be accessed over internet. This paper proposes the security methods provided in orphan home secure system. The main aim of this project is to protect sensitive data of orphans using claim carry catch method (CCC). The Orphan Home Management System is going to be secured to overcome the problems that occur in the orphan home. We proposed a secure cloud storage model that addresses security and storage issues for cloud computing environments. In this paper Security is achieved by anonymous authentication which ensures that cloud users remain anonymous while getting duly authenticated. Cloud gives more storage area to the system. The cloud computing relies on the internet. We used cryptographic and claim carry catch method to enhance security in cloud.

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Search engines history goes back to the field of Information Retrieval, that has gone through a tremendous change over the period of time.  Though search Engines have experienced many enhancements in the last few years, the query processing Techniques that the Information Retrieval (IR) Technology relies on are still based on Keywords.  It is difficult to formulate queries which are well designed for retrieval purpose. Query Expansion can solve this problem.  Query Expansion is normally aimed to form a query into one that is more responsive for Information Retrieval.  Though there are many approaches aimed at query expansion, ontology based query expansion has been found to have more advantages compared to the traditional ones.  This paper compares the performance of the Traditional query processing methodology with the Domain Independent Ontology based query expansion Methodology.

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Knee Osteoarthritis is a common joint disorder that is most prevalent in the knee joint. Knee osteoarthritis (OA) can be characterized by the gradual loss of articular cartilage (AC).  Articular Cartilage is a hard but greasy coating on the end of each bone which forms the joint. Cartilage seizes up and erodes away in OA. In this work, image processing techniques are applied on magnetic resonance images (MRI) of knee, the Adaptive histogram equalization, Contrast enhanced image process, Gaussian Filter, OstuThresholding Algorithm, Edge Detection Technique, Automatic Region Detection Method, Euclidean and connected component algorithm are adopted in this work. Quantification of cartilage thickness is carried out for normal and OA cases. The results are useful in the study of measurement of articular cartilage for OA and for therapeutic decisions.

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Among the challenges that we face in our day to day life one of most unavoidable challenge is parking the car wherever we go. As our need increases our travelling increases but due to drastic increase in usage of vehicles and increase in population we face the tough task of parking our car particularly during busiest hours of the day. During peak hours most of the reserved parking area gets full and this leaves the user to search for their parking among other parking area which creates more traffic and leaves them with no indication on availability of parking space. To overcome this problem there is definitely a need for designed parking in commercial environment. To design such parking slot we need to take into the account of reservation of parking slot with optimal parking space which depends on cost and time. Cost function should also combine with the parking cost and proximity to the destination. However here we have designed the time driven sequence method which solves the problem of parking using slot allocation method. This paper proposes an android application, which is used to implement a prototype of Smart Parking System based on Reservation (SPSR) that allows drivers to effectively find and reserve the vacant parking spaces with the help of IoT (Internet of Things) with slot allocation method and performs automatic billing process.

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An Electro Magnetic (EM) launcher can be utilized as an observational tool to accelerate low-mass specimens up to 350 m/s to study impact phenomena. A plasma armature is used to avoid the friction developed by a sliding metal armature. High current flows are applied to achieve high accelerations, resulting in high plasma temperatures. Yet to our knowledge, there are no existing design methods to control the plasma temperature so we propose a new model using gold coil and plasma gases to reduce the plasma temperature and armature friction. For this purpose, 2-D and axisymmetric plasma models are widely used as these are less complicated and fairly available. This proposed model solves the drawbacks of rail guns, these simulations are performed using ComsolMultiphysics version 4.3b software.

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The wireless sensor network (WSN) poses many challenges due to critical mobility environment such as large propagation delay and limited bandwidth capacity of communication channels. WSN often finds difficulties on the overhead produced during message passing, constant energy and node cost. The solution has expressed to address these issues, this paper proposes Fuzzy logic and Search Based Gravitational Routing Protocol (FSBGRP) for Lifetime improvement. The Search based Gravitational Algorithm (SBGA) is used for searching the paths. As SBGA finds the global optimum faster, it has higher convergence rate. An improved routing technique is proposed for lifetime improvement in WSN. To estimate the node cost using fuzzy logic, the parameters such as link quality, residual energy and system load are used. Simulation results prove that the proposed protocol performs well compared to the existing protocols.

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Mobile sink is used to collect the data and as well as to transfer the data. For delay sensitive application mobile sink can be used. This is not suitable for all kinds of network. Sensor node will be charged with some battery power. This cannot be charged again and again because it may be costly, so we have to sense the data before it loses it power. To reduce the usage of energy, hybrid moving pattern is formed so that mobile sink visits only the rendezvous points. Furthermore to reduce the delay and energy Weighted Rendezvous Planning (WRP) is used. Weight is assigned to each node, the highest weight will be given first preference and mobile sink collect the data from it. Clustering is the effective method to improve network lifetime. EECS is implemented along with WRP. EECS is used in the applications where the data is being collected periodically.

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Cognitive Radio (CR) is a emerging technology that enables optimal utilization of the of the spectrum. Reduction of delay and the maximization of the throughput should be satisfied which possess a challenge to the proposed cognitive mesh network. A collaborative routing and spectrum utilization with minimal interference with the use of on demand routing protocol finds a reliable solution of optimization. The evolved protocol is proposed to solve the spectrum sharing capabilities in the cognitive mesh networks. The existing protocol in cognitive network challenges aspects like hidden terminal, cross layer design communication in the established network.

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Cooperative communication is an active area of research, and wireless devices are evolving into multipurpose systems with data extensive applications running on them, by this such applications require strong error protection and high speed connectivity. These networks are emerging to support the varied networks for an effective communication between the end users. The overall network performance depends on the optimal choice for relay nodes. In this paper, a relinquish mechanism based on locations with repeated selection technique is proposed for efficient the relaying. Nodes are made to be grouped. This plays a significant role for the usage of location based algorithm. Simulation is done by using NS2 and Simulation results shows that this relinquishing mechanism works seamlessly enhancing the overall performance of the wireless cooperative network.

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The majority of telecommunication service providers use DWDM systems which allow expansion of existing capacity without laying additional fiber optic cables. For the successful transmission of optical signals over long distance single mode fibers and EDFA are used. The performance is degraded if single mode fiber is used because of nonlinear effects like dispersion, FWM etc. To ensure the communication quality,   reduction of these nonlinear effects becomes essential. This paper proposes a novel design technique which aims at improvement in performance of a DWDM system by the usage of hybrid amplifier and dispersion compensated fiber. Performance of the proposed system is analyzed for different fiber length of 50km, 80km and 100km. Optisystem 13.0 is the software used for the analysis of the design study. The results obtained shows that the Q- factor is very much enhanced by the proposed system while BER is very much reduced. The impact of the fiber length studied here shows that if the fiber length is increased beyond 80km the Q- factor is very much degraded and BER is increased.

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The proposed work is to implement the parallel architecture for adaptive LMS filter configuration, a concurrently processed filter is realized which adapts the time controlled block. The filter co-efficient are negotiated, which are uploaded in to the look up table. These data are further configured and retrieved from the stored buffers. Single block is realized here depends upon the timing control these blocks are called a function. This architecture reduces the area utilization and Power consumption. The proposed system is precise and easy to configure and update.

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In general, mobile nodes consume more energy than the sensor nodes due to the presence of mobility. If the path stability is not maintained properly, network partition will occur. From the analysis of the previous work, the load balancing of energy routing is not established well. It leads to network performance degradation. In this work, Efficient Energy based Load Balancing Routing Protocol (EELBP) is proposed to make a balance between load balancing and energy consumption. The main aim of the proposed work is to reduce energy consumption and provide better stability using the stability model.  The proposed scheme consists of three phases like Load balanced Routing, stability of path and energy consumption model. Multipath routing is developed to ensure better network lifetime and more energy efficiency. The multipath routing stability is calculated to ensure more network stability. Energy spent for transmission is reduced using the energy consumption model.  By simulation results the proposed algorithm EELBP achieves better performance in terms of packet delivery ratio, delay, overhead, network lifetime, energy consumption link availability than the existing method PLSS and LAER schemes.

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Localization is one of key issues in MANET. It provides information about coverage, deployment, routing, location service, target tracking and rescue. If high mobility among the Mobile nodes occurs, path failure breaks. Hence the location information cannot be predicted.  Here, we have proposed aLocalization based Optimized Energy Routing (LOER) based on cluster and energy consumption model to provide location information of nodes based on Trilateration in WSNs. Proposed approach consists of three phases. In first phase, Cluster head is chosen based on energy level. In second phase, location aided routing is chosen to alleviate computation cost and save Mobile nodes energy.  In third phase, localization method is developed to improve accuracy and reduce node degree. To locate the target and Mobile Nodes Discrete Fourier Transform and distributed algorithm was used. By simulation results, the proposed approach LOER achieves high location updated rate, improved network lifetime, less end to end delay and overhead in terms of mobility, pausetime, throughput, and number of nodes than existing protocol ALERT.

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Using an effective Predictive Current Control strategy to a single phase voltage source inverter and to analysis its performance for various parameters variations is the main objective of this paper. An improved performance of the proposed predictive current control method has been analyzed with various conditions is carried out such as steady state, transient state, non sinusoidal references, input frequency variations, sampling frequency variations, current reference amplitude variations and filter inductance variations, that offers excellent reference tracking with less current harmonic distortion for all conditions. The control algorithm and inverter model was developed in Matlab/Simulink software.

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Speed is one of the major issues for any electronic component. Speed based microprocessor system mainly depends on speed of the microprocessor and memory access time. The off-chip memory takes more time for accessing than on-chip memory. For these reasons, microprocessor system designers find cache compression is such a technique to increase the speed of a microprocessor based system, as it increases the cache capacity and off-chip bandwidth. Previous work on cache compression has made unsubstantiated assumptions about performance, power consumption and area overheads of the proposed compression algorithm and hardware. In this work we propose a lossless compression algorithm that has been designed for high performance, fast on-line data compression and particularly for cache compression. This algorithm has a number of novel features tailored for this application, including combining pairs of compressed lines into one cache line and allowing parallel compression of multiple words while using a single dictionary and without degradation in compression ratio.

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Now a day, Embedded systems has greatly improved in terms of performance and features. However the process of managing the power consumption is becoming complicated. Many techniques are proposed to address this issue. In this paper the techniques for reducing the power consumption in discussed. This paper summarizes about different   ideas   regarding the working of different power management techniques so that better techniques can be designed for more efficient and high performance embedded systems. Also this work focuses on most of the portable embedded systems that are used in the real time Applications.

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The tremendous increase in the use of fossil fuels and rapid depletion of natural resources are lead to the alternative sources of energy which is environment friendly are renewable energy. There has been a great interest in wind energy in recent years because it is a potential source for electricity generation with minimal environmental impacts and with no cost of fuel. The usually used wind electric conversion system (WECS) based on Doubly Fed Induction Generator (DFIG) uses slip rings and brushes. Due to depreciation of the slip rings and brushes of generator maintenance is a major issue. Also it will be very difficult to access them in the case of offshore wind farm. So, Brushless Doubly-Fed Induction Generator (BDFIG) was proposed to replace the traditional DFIG. This paper deals with mathematical modeling of BDFIG based Wind Electric Generator (WEG) with converter control. Modeling is done for 5kW WEG with the help of mathematical equations governing each component using MATLAB Simulink and the results are presented.

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A fingerprint authentication system for the privacy protection of the virtual identity is introduced. By extracting minutiae points from one fingerprint, orientation from other fingerprint and reference points from both the fingerprints, a new biometric authentication framework is proposed for identifying an individual. With the help of these three combined features a new virtual identity is generated. A combined biometric composed of two fingerprints is stored in the server database, and query fingerprints from both fingers are required in the verification process which reduces loss of privacy and misuse. The main intention of this paper focuses on the security and privacy of a virtual identity. In order to attain high security and privacy Liveness Detection technique is applied to distinguish legitimate and imposter user. To protect the virtual identity templates Delaunay quadrangle based fingerprint authentication system which deals with nonlinear distortion-induced local structural change. Finally the virtual identity is compressed and stored in database for further verification process. 

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Cloud computing is one of the recent emerging technologies for providing classy services by means of the Internet based on the requirements of the users. Numerous efficient scheduling algorithms are required to make a valuable use of terrific capabilities of the cloud environment. The aim of task scheduling is to schedule the tasks within the given deadline to achieve minimum makespan. The heuristics scheduling algorithm schedules the tasks on cloud by multiple iterations. The diversity revealing and improvement revealing operators are used to determine which low-level heuristic is to be used for finding enhanced solutions in task scheduling. The heuristics task scheduling should be fault tolerant to overcome the failure of tasks. The proposed Fault Tolerant Based Hyper Heuristic Algorithm (FT-HHA) provides fault tolerance in task scheduling by using task replication and task resubmission. FT-HHA schedules the tasks within the given deadline even in the occurrence of failures. The experiments were carried out in a simulated cloud computing environment by scheduling tasks in the existence of malfunction which are generated randomly. 

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Edge detection is one of the most commonly used operations in image analysis particularly in the areas of feature extraction. Edge in an image indicates the boundaries between overlapping objects. An edge represents the boundary between an object and the image background, hence if the edges are identified with high accuracy in an image then all its objects can be located and basic properties of an image can also be measured. An edge can also be defined as a set of connected pixels that forms a boundary between two disjoints regions. Edge detection is a basic method of segmenting an image into regions of discontinuity. The data which are extracted in edge detection is too large, so to achieve the high speed of image processing is a difficult task. To solve this problem, a distributed canny edge detection algorithm is proposed that results in significant reduction of memory requirements with decreased latency and increased throughput with no loss in edge detection performance as compared to the original canny algorithm. In addition, the new algorithm uses a non uniform gradient magnitude histogram to compute block-based hysteresis thresholds. The resultant block-based algorithm has significant reduction in latency and can be easily integrated with other block-based image codecs then it is made capable of supporting fast edge detection of images and videos with high resolution rate, including full-HD videos as the latency is changed as a function of the block size instead of the frame size. In addition to that, quantitative conformance evaluations and subjective tests show that the edge detection performance of the proposed algorithm is better than the original frame-based algorithm, especially for noisy images. Furthermore, FPGA-based hardware architecture of our proposed algorithm is presented in this paper and the architecture is synthesized on the Xilinx Virtex-5 FPGA. Simulation results are dispensed to illustrate the performance of the proposed distributed Canny edge detector. The FPGA simulation results displays that we can process a 512×512 image in 0.287ms at a clock rate of 100 MHz.

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Web page prediction is a technique of web usage mining used to predict the next set of web pages that a user may visit based on the knowledge of previously visited web pages. The World Wide Web (WWW) is a popular and interactive medium for publishing the information. While browsing the web, users are visiting many unwanted pages instead of targeted page. The web usage mining techniques are used to solve that problem by analyzing the web usage patterns for a web site. Clustering is a data mining technique used to identify similar access patterns. If mining is done on those patterns, recommendation accuracy will be improved rather than mining dissimilar access patterns.  The discovered patterns can be used for better web page access prediction. Here, two different clustering techniques, namely Fuzzy C-Means (FCM) clustering and FLAME clustering algorithms has been investigated to predict the webpage that will be accessed in the future based on the previous action of browsers behavior. The Performance of FLAME clustering algorithm was found to be better than that of fuzzy C-means, fuzzy K-means algorithms and fuzzy self-organizing maps (SOM). It also improves the user browsing time without compromising prediction accuracy.

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In this paper a novel method is proposed to enhance the lifetime of the nodes by introducing clusters which communicate to the main fusion center of the cognitive sensor network. Each sensor sends its spectrum sensing result to the cluster head the node which is nearer to the fusion center is selected as cluster head. The cluster heads sends its decision to the main fusion center which makes the final decision. The proposed method is tested with a simulation scenario of three clusters with a total of thirty sensing nodes and a main fusion center. The results simulated using NS-2 shows that there is a reduction in consumed energy in the proposed network model when compared with the Parallel distributed spectrum sensing network model. The percentage remaining energy in the proposed model is 86.9646 and that of Parallel distributed spectrum sensing network model is 81.4277. Since the remaining energy in the proposed model is more ultimately this would lead to the maximization of its life time. 

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Personalized web search is effective way of improving the quality search result based on the use profile. But people who want to search in internet do not want to reveal his identity or profile to the outside world. In this paper, the privacy of the user profiles is analyzed as a hierarchical data structure. The framework captures the user profiles in a hierarchical taxonomy. The framework adaptively generalizes a user profile for a query, keeping the preferences of the user privacy. Since the hierarchical taxonomy which maintain in the server will take more time to search if the number of users increases. So, a greedy algorithm in map reduce paradigm is evolved to process the hierarchical taxonomy tree structure in parallel.

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Location based system are used for discovering the point of interests (POI)s from a specific location based search on the user queries. The GPS latitude and longitude is sent as an input to the location servers which is based on the GPS coordinate with the point of interests and the current location of user can be served back to the client from the location server. This issue is characterized as tails: (i) a user needs to inquiry a database of area information, known as Points Of Interest (POI) s, and would not like to uncover his/her area to the server because of security concerns; (ii) the manager of the area information, that is, the area server, would not like to just convey its information to all clients. The area server longings to have some control over its information, since the information benefit for the location server. On the other concerns over how such possibly untrusted area servers can prompt client's private data revelation. This paper gives an exhaustive study of area based protection safeguarding, and present the different area security models and systems successful in the area anonymization based system.

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A Sensor Network (SN) is a group of sensor nodes work collaboratively to perform a common task. Sensor Networks plays a major role in the development of monitoring air, soil and water, habitat monitoring, agricultural monitoring, military surveillance, inventory tracking etc. Sensors are used in agriculture to monitor Temperature, Humidity (soil, leaf, ambient), Soil moisture, Wind (speed and direction), Pressure, Ph and Redox. In the existing system microcontroller, bridge rectifier, PAR sensor, solar power system and GPRS are used to find the canopy growth. The circle node of canopy which receives the total solar radiation for data processing to calculate a leaf area index and the Moderate Resolution Imaging Spectroradiometer (MODIS), is used to observed the data continuously, Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) is used to collect details about maps of land surface temperature, reflectance, and elevation. GPRS is used to collect the data; if it fails data collection is lost. To overcome the failure in data collection, GSM is used with LDR sensor. In proposed system, when a canopy growth reaches a defined threshold value a message will be displayed in the printed circuit boards (PCB) LCD, and a SMS will be sent to the users’ mobile phone.

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With the aim of controlling power consumption in core networks, we consider energy-aware devices able to reduce their energy requirements by adapting their performance. We propose new algorithm for scheduling the task to different pipelines to balance the energy consumption in networking. We also use MILP(Mixed Integer Linear Programming) which is an optimization problem of task assignment, data loading and data movement. The firefly algorithm (FA) is a meta heuristic algorithm, inspired by the flashing behavior of fireflies. The primary purpose for a firefly's flash is to act as a signal system to attract other fireflies. Mixed integer linear programming framework that solves the virtual topology problem under the communication delay constraint. An arbitrary optical network has been considered with different distances between the nodes and different link capacities. We are using following steps to minimize the energy consumption ,Packet Segmentation for avoiding the collision in single pipeline,  Firefly Algorithm for optimizing the identifying the pipe line , Mixed Integer Linear Programming is for joint optimization of task assignment , data loading and data routing. The purpose of our work is to minimize the energy consumption in overall network.

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Currently, online searching process increases and people searches new information in the search process. Most of the search engine gives additional supporting information. Recommender system involves in this process and implements as service.  Service recommender system gives additional information to the user but if information grows then these process become a critical one. The proposed work analyses issues occurring when service recommender system implements in large data sets. This work proposes a keyword-Aware services Recommender method, to split the services to the users and mainly focused keywords from the user preferences. Hybrid Filter algorithm generates keyword recommenders from the previous user preferences. To implement effective results in big data environment, this method is implemented using the concept of Map Reduce parallel processing on Hadoop. Experimental results are shown the effective results on real-world datasets and reduce the processing time from large datasets.

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A hybrid paradigm of artificial immune systems with fuzzy cognitive maps for Classification of learning disabled datasets

In recent years, Soft computing techniques have been researched and implemented in various domains. These methodologies which include Fuzzy Cognitive Maps (FCMs) are similar to the human reasoning approach and effectively applied in a variety of application domains. These techniques learn from experimental data and deals with the uncertain values and imprecise data. It plays a vital role in image processing, data compression, classification, clustering and decision support systems. Also there is a huge increase in emphasis of interest in studying biologically inspired systems called artificial immune systems (AIS) which are a class of computationally intelligent systems inspired by the principles and processes of the vertebrate immune system. Researchers are particularly interested in the capabilities of this system, whose complexity is comparable to that of the human brain. AIS algorithms are machine-learning algorithms that typically exploit the immune system's characteristics of learning and memory to solve complex problem. It attempts to take advantages and benefits of natural immune systems for use in tackling complex problem domains. It is a class of adaptive or learning computer algorithm inspired by function of the biological immune system, designed for and applied to difficult problems such as intrusion detection, data clustering, and classification and search problems. A new hybrid paradigm of artificial immune recognition system algorithm along with FCM (AIRS_FCM_LD) is proposed for classification of learning disabled datasets and yields a classification accuracy of 94.87%.

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Orthogonal Frequency Division Multiplexing (OFDM) is digital multi-carrier modulation technique which divides the whole channel into several orthogonal sub- channels. OFDM transmits a high data rate signal and offers high frequency efficiency, helps to increase robustness against Inter Symbol Interference (ISI) and fading caused by multi- path propagation. OFDM is chosen as air interface technique for LTE and it has high sensitivity. CA (Carrier Aggregation) is defined by 3GPP (the 3rd Generation Partnership Project) to support wide-bandwidth transmission. Carrier Frequency Offset (CFO) and Sampling Time Offset (STO) is a challenging problem in OFDM. Non continuous CA scenario’s synchronization problem is addressed and CAZAC algorithm is proposed to suppress synchronization error, STO (Sampling Time Offset) and CFO (Carrier Frequency Offset). Precoder design is used to improve BER (Bit Error Rate) performance and to minimize the MSE (Mean Square Error Value).

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