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With the advent of cloud computing, the affinity between business and technology had increased manifold, allowing users to access IT resources at their convenience through the pay-per-use scheme. With such huge demand surging day to day, the cloud environment must cater to the user requirements flawlessly and also should be rewarding to the providers of cloud service. To maintain its high level of efficiency, there are several challenges that the cloud environment should tackle. One amongst those challenges is the balancing of load. It is one of the primary features of cloud computing that focuses on avoiding the overloading of nodes where there may be idle nodes or nodes with lesser load present at the same juncture. By keeping an effective check on the load several the Quality of Service (QoS) parameters including response time, throughput, resource utilization, energy consumption, cost etc., can be improved, adding to better performance of the entire cloud environment. Even distribution of load among datacenters will contribute to optimal energy consumption and keeps a check on carbon emissions. In this paper we have presented a methodical review on literature pertaining to load balancing strategies that had been proposed in the cloud environment. We had made in-depth analyses of available load balancing techniques and had come up with their advantages, limitations along with the challenges to be addressed by researchers for developing efficient load balancing strategies in the near future. We had also suggested prospective insights about the aspects in load balancing that could be applied in the cloud environment.

Direct current microgrids are attaining attractiveness due to their simpler configuration and high-energy efficiency. Power transmission losses are also reduced since distributed energy resources (DERs) are located near the load. DERs such as solar panels and fuel cells produce the DC supply; hence, the system is more stable and reliable. DC microgrid has a higher power efficiency than AC microgrid. Energy storage systems that are easier to integrate may provide additional benefits. In this paper, the DC micro-grid consists of solar photovoltaic and fuel cell for power generation, proposes a hybrid energy storage system that includes a supercapacitor and lithium–ion battery for the better improvement of power capability in the energy storage system. The main objective of this research work has been done for the enhanced settling point and voltage stability with the help of different maximum power point tracking (MPPT) methods. Different control techniques such as fuzzy logic controller, neural network, and particle swarm optimization are used to evaluate PV and FC through DC–DC boost converters for this enhanced settling point. When the test results are perceived, it is evidently attained that the fuzzy MPPT method provides an increase in the tracking capability of maximum power point and at the same time reduces steady-state oscillations. In addition, the time to capture the maximum power point is 0.035 s. It is about nearly two times faster than neural network controllers and eighteen times faster than for PSO, and it has also been discovered that the preferred approach is faster compared to other control methods.

This paper intends a newfangled quasi imitative based originating System-Procedure for Power System State Approximation (PSSA). The fundamental initiative of the projected technique is utilization of an imitative to support the evolution System-Procedure in the search of a solution where, PSSA is Non-deterministic Polynomial hard (NP-hard) and it is very tough to search for a solution in an optimum way. Therefore, a quasi-imitative is established into evolution System-Procedure for the purpose of guesstimating the state of power system accurately. The effectiveness of the proposed approach is tested on the standard IEEE test systems (IEEE 30, IEEE 57 and IEEE 118-bus systems) and on a small scale system (3 bus system) where, the proposed method is proficient of guesstimating the state of power system with high accuracy.

PurposeThe purpose of this paper is to analyze the Luo super boost converter coupled fragmented source inversion system (LC-FSIS) and the progress of a controller structure for energy stored. The inversion system is characterized by a diode arm structure and can be easily amassed into a conversion system for high/medium- power conversion systems.Design/methodology/approachThe investigation is based on the practice of a simplified circuit established as common anode/common cathode, where all the diodes in each arm are connected to a renewable DC voltage source. In this proposed work, a novel fuzzy digital logic switching technique (FDLST) for three-phase fragmented source inversion (FSI) for enhancement in power excellence is measured to enterprise the novel fuzzy digital logic switching technique to authorize operative voltage utilization and enhanced harmonic spectrum.FindingsSequential circuit design using flip-flops is used in the analysis of fuzzy digital logic switching technique.Originality/valueThe three-phase fragmented source configuration is designed using a split DC source which is obtained from the Opto-electric source and is implemented using MOSFET. The procedure of novel FDLST reduces the Statistical Harmonic Reduction (SHR). Simulation and results are carried out to prove the dominance of designed FDLST.

Intrusion Detection and Prevention System disclosure is approach towards watching the action appearing in a pc structure and separating them for signs of probable scenes, which are infringement or moving toward perils of infringement of PC security courses of action, commendable use methodologies, or standard security practices. An interruption identification framework is customizing that robotizes the intrusion disclosure process. An interruption avoidance framework is modifying that has all of the capacities of an intrusion distinguishing proof structure and can in like manner try to stop possible scenes. IDS and IPS progressions offer an expansive number of comparable capacities, and administrators can ordinarily impede neutralizing activity incorporates into IPS things, making them fill in as IDSs. As necessities are, for brevity the term interruption recognition and anticipation frameworks are used all through whatever is left of this segment to insinuate the two IDS and IPS advancements. Any exclusion is expressly acclaimed.

There are many problems in metering and billing processes like the going of meter reader to each customer meter to manually take the meter reading, the probability of the non-existence of the customers at their homes during that time, the lack of integrity and credibility of some of the meter readers, the safety and the outback areas represent a huge drawback cannot be neglected. In other hand, the in service classical energy meter type (induction type) suffers from well-known measuring errors. The above problems result in two significant points, waste of much money due to the large number of employees (meter readers) and the weakness in electricity management which results in lack in electric power. This project provides an excellent solution to the problems mentioned above where the system has been designed based on the use of energy smart meter to read electrical energy consumed to get an accurate reading. Then the energy reading is sent to the control centre in the electricity department based on GSM/SMS technology. The system in the electricity department receives readings and makes processing operations on them and extracts the bills that must be paid by the customer. The system also sends a message to the own customer mobile phone which contains the current bill, due bill, and total bill every two months have to be paid. In addition the system has the ability to print out a hard copy of the customer bill. Finally the proposed system has the ability of automatic power outage if the customer refrains or delays for certain time in paying the bills by means of an SMS.

The application of Internet of Things (IoT) has been emerging as a new platform in wireless technologies primarily in the field of designing electric vehicles. To overcome all issues in existing vehicles and for protecting the environment, electric vehicles should be introduced by integrating an intellectual device called sensor all over the body of electric vehicle with less cost. Therefore, this article confers the need and importance of introducing electric vehicles with IoT based technology which monitors the battery life of electric vehicles. Since the electric vehicles are implemented with internet, an online monitoring system which is called Things Speak has been used for monitoring all the vehicles in a continuous manner (day-by-day). These online results will then be visualized in MATLAB after an effective boosting algorithm is integrated with objective function. The efficiency of proposed method is tested by visual analysis and performance results prove that the projected method on electric vehicle is improved when using IoT based technology. It is also observed that cost of implementation is lesser and capacity of electric vehicle is increased to about 74.3% after continuous monitoring with sensors.

In the present scenario the depletion of conventional sources causes an energy crisis. The energy crisis causes load demand with respect to electricity. The use of renewable energy sources plays a vital role in reducing the energy crisis and in reduction of CO2 emission. The use of solar energy is the major source of power in generation as this is the root cause for the development of wind, tides, etc. However, due to climatic condition the availability of PV sources varies from time to time. Hence it is essential to track the maximum source of energy by implementing different types of MPPT algorithms. However, use of MPPT algorithms has the limitation of using the same during partial shadow conditions. The issue of tracking power under partial shadow conditions can be resolved by implementing an intelligent optimization tracking algorithm which involves a computation process. Though many of nature’s inspired algorithms were present to address real world problems, Mirjalili developed the dragonfly algorithm to provide a better optimization solution to the issues faced in real-time applications. The proposed concept focuses on the implementation of the dragonfly optimization algorithm to track the maximum power from solar and involves the concept of machine learning, image processing, and data computation.

Autism Spectrum Disorder ASD specifies where lots of behavioral disabilities, such as social connections and lack of commutating, repetitions of same works, and only single areas are focused. While ASD is noticed in initial stage, some deficiencies and behavioral patterns may not be found as the indication unless they affect a person’s life in a particular way. An infrastructure to record, detect and label the behavioural patterns of children with Autism Spectrum Disorder (ASD) has been developed. Autism Spectrum Disorder (ASD) effects the entire life of a person. The major symptoms of ASD are noticed as lack of social contact and communication, same pattern recurrence, predetermined interests and works. The critical issues is ASD identified at initial stage and age. This study, the grouping technique for ASD diagnosis was utilized in children aged 4-11 years. The Linear Discriminant Analysis (LDA) and KNN algorithms are used for categorizing.

Ecological checking, earth-assets mappings, and military frameworks require expansive territory imaging to achieve perfection. Frequently, these pictures must be obtained during the night or during the severe climate. Synthetic-aperture radars (SAR) give such a capacity. Engineered aperture radar frameworks will exploit the long-run spread attributes of a radar signal and the preparation of the intricate data abilities of present-day computerized electronic gadgets to give a high-goals picture. SAR is an emerging technology that has been widely used for more than 20 years in remote sensing areas. It is quite complicate to take an image in remote sensing areas without the use of SARs. This paper provides an overall view of a SAR images using various image processing techniques. These techniques are used to provide high resolutions in SAR images and detect the accuracy of each images.

This article focuses on addressing the data aggregation faults caused by the Phasor Measuring Unit (PMU) by installing Wireless Sensor Networks (WSN) in the grid. All data that is monitored by PMU should be sent to the base station for further action. But the data that is sent from PMU does not reach the main server properly in many situations. To avoid this situation, a sensor-based technology has been introduced in the proposed method for sensing the values that are monitored by PMU. Also, the basic parameters that are necessary for determining optimal solutions like energy consumption, distance and cost have been calculated for wireless sensors, whereas, for PMU optimal placements with cost analysis have been restrained. For analyzing and improving the accuracy of the proposed method, an effective Binary Logistic Regression (BLR) algorithm has been integrated with an objective function. The sensor will report all measured PMU values to an Online Monitoring System (OMS). To examine the effectiveness of the proposed method, the examined values are visualized in MATLAB and results prove that the proposed method using BLR is more effective than existing methods in terms of all parametric values and the much improved results have been obtained at a rate of 81.2%.

In the scenario of Vehicle Tracking is the process of locating a moving object or multiple entities over time using a camera. It can be a time-consuming process due to the amount of data that is contained in video. Capture objects in video sequence of surveillance camera is nowadays a demanding application to improve tracking performance. The advanced technology makes video acquisition devices better and less costly, thereby increasing the number of applications that can effectively utilize digital video. Compared to still images, video sequences provide more information about how objects change over time. Thus, in this review, we discussed the several techniques attempted to site the available technique and various merits and demerits of it. In the present work we are detecting the moving object done by using simple background subtraction. For tracking of single moving object has been done using modified mean shift method and Kalman filter. Further result of both algorithms is compared on basis on time and accuracy.

Emerging technologies such as cloud computing and data mining deal with issues such as scalability, security and efficiency. Web mining is broadly classified under data mining, refers to the resultant data combination obtained by assembling data available in the Web and information mining techniques. In general, mining can be defined as the process of extracting significant things from huge datasets. The applications of Web mining include the evaluation of the successful completion of a particular task, assessing the applicability of specific Web sites and comprehending client conduct. The proposed work is concerned with distributed networks and is aimed at improving the efficiency of data mining and cloud computing techniques. The main goal is to find a solution for generating various itemsets in each site. A well-known algorithm in data mining is the Apriori algorithm which discards infrequent items at the cost of useful data. A major limitation of this algorithm is its slowness, owing to increased transactions. The K-means segmentation algorithm is employed for increasing the efficiency by clustering the initial itemset.

The power generated from the optoelectric source in the conversion system and the connected system should satisfy several factors such as high efficiency, less total harmonic distortion, reduced cost, less complexity, better boosting capability, etc. The boosting capability can be achieved by means of single juncture or two juncture architecture in DC–DC boost converter. Among different architecture, the Z-source riven bias inverter controls the parameter on the AC and DC sections. The steady state quantity and the time-varying parameter are regulated by controlling the intonation index. The modulation indexes are framed by digital to look at its supervision theme in grid coupled structure that has certainly not been studied so far. Hence, in this paper, the Z-source riven bias electrical converter modeling has been studied in conjunction with the decoupled space vector modulation as a control technique. The deliberate theme is studied and simulated by using a MATLAB/Simulink model to approve the analysis and simulations.

This article presents a new protection scheme for the µgrid structure is implemented on low voltage side as DC system’s protection methods are quite new when compared to the AC systems. The protection system designed in AC system faces many difficulties like frequency matching, reactive power violation, and instability. The main objective of the proposed system is to eliminate the faulty segment promptly while keeping the healthy segments functioning unaltered. In the proposed method, a unitwise controller is designed and is connected in feedback so as to maintain stability under all conditions. The unitwise controller comprises primary and secondary controllers which continually monitor all the units of DC grid comprising semiconductor bidirectional switches and snubber circuits. A primary controller is used for monitoring the complete variation in the parameters in all the units. If the observed parameter value is greater than the acceptable range, the secondary controllers receive the command so as to take the required action to eliminate the faulty segment. Both lines and ground faults are tested on all the sections separately and also simultaneously. The tested results are analyzed in all aspects and the results of the states that the designed protection scheme competent in isolating the defective segment within a short period of time. Once the defective segment is isolated, the other segments retain the stabilized voltage and current limits. The protection scheme is designed and verified using MATLAB/Simulink.

Purpose The purpose of studying the low voltage direct current (DC) microgrid, which uses computerised control system techniques, an orderly coordination control stratagem considering optimisation of a hybrid energy storage system (HESS) was projected in this paper. Design/methodology/approach The projected control stratagem was divided into three levels: topmost power dispatch level, transitional bus voltage regulation level and bottommost converter control level. Findings At the topmost power dispatch level, the cost of system stability was introduced, which is related with state of charge and discharging power of HESS. Originality/value Furthermore, the cost of system stability and HESS depreciation was compared with commercial price, and HESS switches its operating mode to discharge more at higher price or charge more at lower price to ensure the DC microgrid in economic operation. At the transitional bus voltage regulation level, DC bus gesturing is used as a control signal to achieve an autonomous decentralised operation of DC microgrid. The Matlab/Simulink simulation inveterate that the economical and autonomous decentralised operation can be achieved through the control stratagem.

Purpose According to bidirectional ability, wind application are having variable acceleration which connected large quantity of wind ability bearing system with doubly-fed induction generator (DFIG) fed by the two-stage cast converter (TSMC) system, the accentuation action for TSMC and arithmetic standard for DFIG are all deduced. The purpose of this study is for, stator accelerated action in Doubly fed induction generator and controlled by the Two Stage Cast Converter for better control. Design/methodology/approach The purpose of this study is for, stator accelerated action in Doubly fed induction generator and controlled by the Two Stage Cast Converter for better control. Findings Then, the beginning ancestor was set up to verify this system; the allotment of the filigree beginning after-effects are offered beneath no-load and the three plan states. Originality/value These after-effects apparent by the fact that the arrangement fed by TSMC-DFIG could apprehend the safe ability bearing accumulated to the filigree in the sub-synchronous, synchronisation and super-synchronous state; meanwhile generated sinusoidal describes the displacement factor.

The aim of this project is to develop a dynamic model of a converter fed Microgrid operated in Islanded DER Control Mode to regulate its voltage and frequency in the islanded mode of operation. Controllers like PI, FUZZY, FUZZY-PI to be implemented to fine which is best controller for the developed control scheme. The microgrid has two operating modes: the grid-connected mode and the islanded mode. In the grid-connected mode, the MMS is locked and the microgrid can interchange the energy with the host lattice network. In this mode, the DER systems exchange real and reactive powers with the distribution network, according to the corresponding set points; the difference between the aggregate power generated by the DER systems and the power demanded by the local loads is balanced by the upstream network.

Heart Disease is one of the primary causes of mortality and morbidity in the Globe since the 19th Century. Most of the Globalized Multi-Specialty Hospitals are not able to control and governed by emerging technologies, at the same time, the death rate escalates day by day in addition to Covid-19 is a multifaceted state. Heart disease classification involves identifying numerous health problems and sickness symptoms of ones’ individual with significant feature selection, there is misclassification probability that could be very high and priceless. There are many diverse methods were designing for heart disease prediction systems in earlier days, even though it is unsolved and rising the death rate. As observed by many research groups, PSO is an intensive computational and inspired biologically inspired algorithms like Genetic Algorithms (GA) has a proven track record to handle computationally complex problems with competence for predicting heart diseases. This research contribution through the proposed model downs the computation time and increases the accuracy. The high-level comprehensibility, predictive accuracy are good and desired through this Intelligence Hybrid Approach (IHP) to reduce Heart attacks and control the death rate.

Cognitive-Radio Network (CRN) is an enabling and promising technology to enhance the spectrum utilization and the key functionality of cognitive radio (CR) systems is spectrum sensing in order to function in an unoccupied spectral bands. To safe-guard the presence of licensed users from any interference in a spectrum, CR should be capable of detecting reigning channels even in the scenario of low signal to noise ratio (SNR). Here, in this article, various spectrum-sensing parameters such as detection probability, bit error probability (BEP), miss-detection probability, probability of false alarm are amended in the case of lower SNR by employing demand and need based genetic-algorithm(GA) by considering geographical disparities of spectrum-holes. The outcomes convey that the GA can provide a finer real-time solution for the sensing capability of a cognitive-radio network.

Voltage and frequency regulation is one of the greatest challenges for proper operation subsequent to the isolated microgrid. To validate the satisfactory electric power quality supply to customers, the proposed manuscript tries to enhance the quality of energy provided by DG (Distributed generation) units connected to the subsequent isolated grid. Microgrid and simulation-based control structure including voltage and current control feedback loops is proposed for microgrid inverters to recover voltage and frequency of the system subsequently for any fluctuations in load change. The proportional-integral (PI) controller connected to the voltage controller is an end goal to obtain smooth response in most of the consistent frameworks. The present controller creates the space vector pulse width modulation signals which are given to the three-leg inverter. The objective elements of the multiobjective optimization issue are voltage overshoot and undershoot, rise time, settling time, and integral time absolute error (ITAE). The hybrid Multiobjective Symbiotic Organism Search (MOSOS) calculation is associated for self-tuning of control parameters keeping in mind the end goal to deal with the voltage and frequency. The proposed PI controller, along with the hybrid Multiobjective Symbiotic Organism Search algorithm, provides the solution for the greatest challenge of voltage and frequency regulation in an isolated-microgrid operation.

Now a modern time many area such as company, medical, research and file require large number of image for general-purpose application to solve the complex problem. Image contain more information that require more storage space and transmission bandwidths, so the image compression is required to store only important information and reduce the different types of redundancy of image for storing and transmission in an efficient manner, because uncompressed image required more data storage capacity and transmission time. In the present work the storing space used is very less ecuase it help in reducing the processing time. For image compression, different transform technique is used. Image can be represented as a matrix of pixel values and after compression by applying different method there is no change or little change between pixel values. This present work is uses haar method and Lifting Wavelet Transform for image compression for increase the efficiency of Discrete Wavelet Transform (DWT).

This paper mainly deals with a two phase service queueing model with gated service vacation. In this gated service vacation model, only those customers who are present in the queue when the server starts a batch mode service are taken into the batch. We have derived probability generating functions of the system size and the orbit size. We have investigated the conditions under which the steady state exists. Some useful performance measures are also obtained. The service to further arrivals is deferred until the server completes the second phase individual service to the batch. Based on the numerical calculations and graphical representations it reveals the fact that this type of modelling helps in analyzing certain situations in which customers require service in two stages of which the first stage of service is essentially of gated type.

Magnetic Levitation is a process in which an object is suspended with the support of the magnetic field. Despite being an unstable system, Magnetic Levitation Systems (MAGLEV) have profound applications in various fields of engineering. MAGLEV systems are sensitive, unstable, and nonlinear and uncertainties always pose a challenge in Controller Design. As a solution, adaptive controllers came into existence with adaptation mechanisms to cover the system uncertainties. In this study, a simple, novel, and an effective approach to the Enhanced Adaptive Control scheme is proposed for the ball position control and tracking of an unstable Magnetic Levitation System. The proposed Enhanced Model Reference Adaptive Scheme (EMRAC) follows the same phenomenon of the Model Reference Adaptive Scheme (MRAC) with a slight difference in its control strategy. The proposed scheme consists of Proportional-Integral-Velocity plus Feed Forward as the control structure and a modified version of the standard tuning rule is used as the adaptation mechanism. The control scheme is applied to a standard benchmark Magnetic Levitation System and the tracking performance of the scheme is tested by applying square and multi-sine pattern trajectories to the Magnetic Levitation System. The performance of the developed Enhanced MRAC performance is compared with that of the Proportional Integral Velocity with Feedforward Control (PIV+FF) scheme and the proposed control scheme is proven to be more suitable. The performance of the proposed scheme is also analyzed with Power Spectral Density and Root Mean Square Error to evaluate the ball position tracking control. It is inferred from the experimental results that Enhanced MRAC accommodates the changes and makes the system more reliable with good tracking ability.

In the current era of technological advancement, the access to the internet has predominantly increased due to plethoric hand held devices. All day---day activities which require time and energy are being been done effortlessly in the blink of an eye. This extreme sophistication rendered to the mobile Wi-Fi users prorogues them to do all pecuniary transaction through mobile phones. A Wi-Fi hotspot which connects such hand held devices has become a temporary repository of sensitive information, thereby giving an opportunity for hackers to accrue monetary gain. Therefore information security policies addressing Wi-Fi hotspots (Wi-Fi phishing attack) has become the need of the hour. The possible ways to attack the security of Wi-Fi hotspots and counter-attack mechanisms has been addressed in this paper. In this paper a live Wi-Fi Phishing attack has been demonstrated and a novel approach based on association rule mining to circumvent the same has been discussed in this paper.

A main focus in microgrids is the power quality issue. The used renewable sources fluctuate and this fluctuation has to be suppressed by designing a control variable to nullify the circulating current caused by voltage fluctuations and deviations. The switching losses across power electronic switches, harmonics, and circulating current are the issues that we discuss in this article. The proposed intelligent controller is an interface between a voltage-sourced converter and a utility grid that affords default switching patterns with less switching loss, less current harmonic content, and overcurrent protection, and is capable of handling the nonlinearities and uncertainties in the grid system. The interfaced controller needs to be synchronized to a utility grid to ensure that the grid&ndash, lattice network can be fine-tuned in order to inject/absorb the prominent complex reactive energy to/from the utility grid so as to maintain the variable power factor at unity, which, in turn, will improve the system&rsquo, s overall efficiency for all connected nonlinear loads. The intelligent controller for stabilizing a smart grid is developed by implementing a fuzzy-built advance control configuration to achieve a faster dynamic response and a more suitable direct current link performance. The innovation in this study is the design of fuzzy-based space vector pulse width modulation controller that exploits the hysteresis current control and current compensation in a grid-connected voltage source converter. By using the proposed scheme, a current compensation strategy is proposed along with an advanced modulation controller to utilize the DC link voltage of a voltage source converter. To demonstrate the effectiveness of the proposed control scheme, offline digital time-domain simulations were carried out in MATLAB/Simulink, and the simulated results were verified using the experimental setup to prove the effectiveness, authenticity, and accuracy of the proposed method.

Energy security (ES) has great impact on power grids. Therefore it is important to have power security service (PSS). The PSS should be designed to handle interference and interruption attack in the grid. The interference and interruption attack in the grid is handled by incursion-detection system (IDS). The IDS is the most obtainable strategy to sense and classify different security issues and abnormal issues that occur in power grids. Therefore the IDS have to be up to date with the latest issues that happened in the entire grid. The proposed concept illustrate the collection of data with reference to intrude-attacks in power-grid and to test and evaluate different machine-learning strategy to illustrate the different attacks and issues that happen in power system grid. The research work is illustrated with a modified J48 decision tree algorithm.

The Microgrid (MG) paradigm is developing as a striking solution for the designs of future grids. In islanded micro grid, the variances in the system cause MG flimsiness. A portion of the controllers used to handle such issue are powerless against stack aggravation and results in an impressive voltage vacillation, or frequency variety, of the micro grid. Subsequently in this examination work we propose a novel fell controller system with the incorporation of EANFIS-PID controller and SVPWM controller. The EANFIS-PID controller is responsible for the erratic irregularities of voltage and frequency though the SVPWM controller is in charge of current vacillations that are the higher request harmonics. The proposed fell controller in this manner produces a balanced out micro grid with higher system effectiveness. Likewise a novel Hybrid Artificial Bee Colony-Particle Swarm Optimization (HAPSO) based Selective Harmonic Elimination (SHE) conspire is utilized in SVPWM controller for wiping out the harmonics produced by the VSC inverter. The proposed system is confirmed through MATLAB/SIMULINK stage and from the reproduction comes about it has been demonstrated that this outcomes in a more responsive control activity contrasted with the conventional controllers.

A broadcasting delay is an important problem for the application of the critical event monitoring in wireless sensor networks. To prolong the network lifetime some of the sleep scheduling methods are always employed in WSNs it results in a significant broadcasting delay. A novel sleep scheduling method to be proposed it is based on the level-by-level offset schedule to achieve a low broadcasting delay in wireless sensor networks (WSNs). There are two phases to set the alarm broadcasting first one is, if a node detects a critical event, it create an alarm message and quickly transmits it to a center node along a pre-determined path with a node-by-node offset way. Then the center node broadcasts the alarm message to the other nodes along another predetermined path without collision. To eliminate the collision in broadcasting, a colored connected dominant set (CCDS) in the WSN via the IMC algorithm is established. An on demand distance vector routing protocol is established in one of the traffic direction for alarm transmission. The proposed system is used in military and forest fire application. Keywords - Wireless Sensor Network (WSN), critical event monitoring, sleep scheduling, broadcasting delay.

In this paper, a watershed transformation technique is used with gradient magnitude with morphological open image and two important features is used as foreground and background to identify the tumor. First the Magnetic Resonance imaging (MRI) Scan of tumor is given as an input and it undergoes into watershed technique which is a topological boundary dividing into two adjacent brain cells. With the gradient magnitude for segmentation technique the rate of inclination or declination of a tumor will be identified. To identify the foreground of the tumor, open the image morphological, thus it acquires clear idea about how the particular tumor will be closer to normal cells. With the background marker, the invisible tumor will be identified using threshold value. In the segmentation output finally, the intensity, size, shape of the tumor in the brain is displayed and can be analysis.

The electrocardiogram (ECG) is the graphical signal representation of overall functioning of the heart. The graph for electrocardiogram shows voltage versus time produced by a method of non-invasive medical procedure. Analyzing the process of ECG plays a lively role in the research of processing of biomedical signals. Cardiac arrhythmia is also known as cardiac dysrhythmia or irregular heartbeats. At present scenario, it's a big challenge to detect the arrhythmia. In this article a method of analysis of ECG signal using fractal features and its properties.ECG signals has its fractal patterns. Hence the fractal dimension of the ECG is calculated in a feature extraction phase. The estimation of fractal dimension in the feature extraction phase is used to discriminate between the normal and abnormal heart. If the heart is in abnormal condition then ECG characteristics point such as P and T waves of abnormal wave is detected. Detecting P and T waves in the abnormal signal is crucial for diagnosing and it is to detect heart rate variability and some cardiac diseases related to it. The obtained results of this paper confirm mostly preferable of the proposed method for examining P and T waves of the abnormal ECG signal based on graphical user interface.

With the rapid development of web applications, and with the comfort provided by these web applications, internet users utilize this benefits to a great extent that they make almost all their day to day activities such as news paper reading, shopping, electricity bill payment, ticket booking and entertainment with the help of the internet. This phenomenon forces the users of the internet to get connected with the internet for a prolonged time and hence it increases the chances of the users to get caught in the web of phishing - an attack crafted by hackers to steal sensitive information by tempting the users with lucrative offers initially and then redirecting them to a fraudulent website(which the user may not suspect) where they can deceive the user by asking them to submit their credentials(usually users submit their credentials without knowing that these are fake offers created with a sole intention of stealing sensitive information). In spite of the alert and awareness given by the web community in this regard, more and more phishing artist succeed in their attack. Also these phishing artist develop novel attacks such as tab nabbing, website impersonation etc that attracts more and more internet user to be caught in the web of phishing. However many tools and methodologies have been developed to prevent phishing and to alert users orally and visually. But still the success rates of the phishing attack remains high and also the approaches related to phishing detection suffers high false positive and false negative ratio. In this paper various tools and methodologies used to prevent phishing has been analyzed and an efficient mechanism has been proposed to prevent phishing.

Target Tracking as it moves through a sensor network has become an increasingly important application in Wireless Sensor Networks. This paper examines some of the target tracking techniques in use today. An analysis of each technique is presented along with it advantages, problems and possible improvements. There are seven main categories explored in this paper. The survey promotes overview of recent research literature along with their performance comparison and evaluation.

the never-ending growth of Web services and Web-based information systems, the volumes of click stream and user data collected by Web-based organizations in their daily operations has reached enormous proportions. Analyzing such huge data can help to evaluate the effectiveness of promotional campaigns, optimize the functionality of Web-based applications, and provide more personalized content to visitors. In the previous work, we had proposed a method, Grey Relational Pattern Analysis using Markov chains, which involves to discovering the meaningful patterns and relationships from a large collection of data, often stored in Web and applications server access logs, proxy logs etc. Herein, we propose a novel approach to analyse the navigational behavior of User using GRPA with Variable-Length Markov Chains. A VLMC is a model extension that allows variable length history to be captured. GRPA with Variable- Length Markov Chains, which reflects on sequential information in Web usage data effectively and efficiently, and it can be extended to allow integration with a Web user navigation behavior prediction model for better Web Usage mining Applications.