The present work has focused on residual fatty substances available in ground nut oil cake and attempt has been made to blend the extracts of oil cake with diesel at different proportions namely 5%, 10%, 15%, 20% and 25% by weight added to known volume of diesel without any engine modification. This new fuel is investigated in the diesel engine and its performance and emission characteristics are determined. The physical and fuel properties are determined as per ASTM standards and found to be within the limits prescribed for biodiesel. The quality of all blends is evaluated using gas chromatography and found to have esters of fatty acids similar to groundnut oil. It has been observed that the presence of wax, triglycerides, free fatty acids and molecular oxygen in the fatty substances help in improving the combustion causing reduction in HC, CO and smoke density. However it is observed that there is a marginal increase in NOx emission. With regards to brake thermal efficiency, 15% oil cake extract diesel blend gives better efficiency than neat diesel and other blends.

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In recent years, industry has begun to demand higher power equipment, which now reaches the megawatt level. Controlled ac drives in the megawatt range are usually connected to the medium-voltage network. Today it is hard to connect a single power semiconductor switch directly to medium voltage grids. For these reasons a new family of multilevel inverters has emerged as the solution for working with higher voltage levels. They can generate output voltages with extremely low distortion and lower dv/dt, they draw input current with very low distortion, they generate smaller common mode voltage and they can operate with a lower switching frequency. Because of these features worldwide research and development of multilevel inverters is occurring. In this report the simulation results and its comparison of diode clamped 3 levels and 5 level inverter has been shown.

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As Mobile Ad hoc Networks (MANETs) gains popularity, the need for suitable ad hoc MAC and routing protocols will continue to grow. Cross-layer design is an emerging proposal to support flexible layer approaches in MANETs. Various algorithms were proposed to improve the packet delivery ratio and fairness among flows for multi-hop ad hoc networks through cross-layer interaction between MAC and the routing layer. The routing information about bandwidth, channel capacity, received power and distance to reach its destination could be exploited by the MAC layer in order to give priority to the packets that are closer and appropriate to their destination. In this work I am going to exploit bandwidth information by the MAC layer in order to find out the best route for multimedia data. Normally shortest route is computed in network layer routing, whereas my problem here is to find out adequate "bandwidth" route required by multimedia traffic instead of finding a shortest route. Then, with the help of performance metrics like packet delivery ratio, average end-to-end delay and normalized routing load, it will be shown that cross-layering between MAC and routing layer performs much better than using routing layer and MAC layer separately. I am going to use NS2 for the implementation of the said problem.

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The Seismic interpretation is one of the latest techniques to extract data and getting information on the geometry and physical properties of earth surface. The most important task in reservoir characterization is porosity interpretation which defines property of reservoir. This paper presents a work flow to determine porosity with the help of intelligent Caianiello neural network. Acoustic impedance-porosity relationship is given for the learning process of intelligent Caianiello neural network

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A Joystick is an input device that can be used in a variety of applications, starting from gaming to vehicle operation. The joystick sends out electric current or voltage signal depending on the position of the plastic stick. The signal generated by the joystick actuates a system based on its intensity. However, usually, the feedback on the operation of the system will not be sent back to the joystick. Hence, the operator misses the haptic component of the system and is likely to lead to asynchrony in the operation of the system. In this study, a system will be developed to create synchronous operation between the vehicle navigation systems and the vehicle operator. The joystick will be used to maneuver a car effortlessly, however with virtual operating environment.

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Basically nonnegative matrix factorization (NMF) is performing on the original data for data transformation (dimensionality reduction) which is followed by the SVM classification. Using multiplicative update rules, there is a classification using SVM on two classes data which employ two sets of class one belongs to maximum margin classification constraints imposed into NMF and second is belongs to maximum margin classification constraints imposed into discriminant NMF. This paper aims to multiclass classification using two approaches multiclass SVM classifier and combining two class classifier. The previous framework two class which have also a very high accuracy of classification on various database. But this paper leads keeping the classification accuracy high with doing multiclass classification which employ maximum margin between the multiple classes of data.

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Wireless sensor network will be increasingly deployed in several application for accurate monitoring. In Wireless sensor network, energy conservation is one of the main problems, since wireless sensor network is used in much application such as military appliance and home monitoring etc. We need to reduce energy used by sensor node to increase the network lifetime and decrease communication cost. Due to high density of node, the nearby node will detect data while sensing an event. In order to save energy Data fusion and aggregation technique is used. In this case redundant data is aggregated at intermediate node ant it will send to the sink node. Security plays a fundamental role in Wireless sensor network. We propose a Novel Data Routing for In-network Aggregation using DRINA Algorithm and implement privacy preserving technique to achieve confidentiality and authentication. Drina algorithm is cluster-based approach compared with two existing algorithm LEACH, SPT and INFRA. Drina provides the best aggregation rate compared to existing algorithm.

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To improve the accuracy of learning result, in practice multiple parties may collaborate through conducting joint Back propagation neural network learning on the union of their respective data sets. During this process no party wants to disclose her/his private data to others. Existing schemes supporting this kind of collaborative learning are either limited in the way of data partition or just consider two parties. There lacks a solution that allows two or more parties, each with an arbitrarily partitioned data set, to collaboratively conduct the learning. This paper solves this open problem by utilizing the power of cloud computing. In our proposed scheme, each party encrypts his/her private data locally and uploads the cipher texts into the cloud. The cloud then executes most of the operations pertaining to the learning algorithms over cipher texts without knowing the original private data. By securely offloading the expensive operations to the cloud, we keep the computation and communication costs on each party minimal and independent to the number of participants. To support flexible operations over cipher texts, we adopt and tailor the BGN doubly holomorphic encryption algorithm for the multi-party setting. Numerical analysis and experiments on commodity cloud show that our scheme is secure, efficient and accurate.

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The sophistication of the web browsing depends on the likelihood of user reaching the intended web page at the earliest. Patterns of usage have to be tracked in order to conclude the user’s intent. These usage patterns are analyzed with respect to URL’s identified from user segmentation which is obtained from finding similar behavioral patterns. The technique employed here to achieve this phenomenon is the formation of user communities using pattern mining technique. Agglomerative clustering methods are used to typically discover the strongly linked communities. But these methods prove to be inefficient when implementing in large networks with several thousand nodes. Hence the method of triad formation, with graph mining can be applied to resolve new combination of edges which are not connected and establish links between them thereby increasing the identification of active users. The methodology is to form links between URL’s that are most frequently used. The prerequisite for this is to detect communities based on the user’s interests and increasing connectivity. The ultimate aim is to help the network providers serve their customers based on the user interest. The genetic programming method of churn prediction is applied to identify the possible customers who may leave the network with the help of which steps to retain the existing customers in a network can be made

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Multimedia educational resources play a vital role for distance e-learning experiences. It is necessary to explore, share, reuse and link these educational resources. With the help of linked data technology, video annotation and browser platform with two online tools namely Annomation and Sugar tube are used. These mentioned tools will generate further videos and educational resources from the Linked Open Data cloud and the web. The Annomation technique is limited to search of related videos which are listed based on a general or random keyword weightage. In order to enhance the methodology, the application is extended to provide a more accurate search results by listing the links based purely on the keyword value which is maintained in the database by an expert using the Prioritized Context Aware Technique. Thereby, when a search is made based on the keyword, the highest prioritized link as per the expert’s knowledge will be provided. This approach improves the functionality of the e-learning since the search is more optimized and specific.

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Electrical Discharge Machining is a technological process with a large industrial implementation. Its use is particularly intense when very complex shapes on hard and brittle material with high geometrical and dimensional accuracy are required. Material Removal Rate, Tool Wear Rate and Surface Finish are most important parameters, which decide machining performance. Present study attempts to find out electrodes performance in electric discharge machine (EDM). In this work, the effect of different electrodes performance with different input with their different levels in EDM on machining characteristics of cold work tool steel has been studied. Three parameters are electrode Materials, Peak current and pulse on time. The process performance is measured in terms of Material Removal Rate (MRR). The result outcome will identify the important parameters and their effect on MRR in the presence of dielectric fluid in EDM

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Jet ejectors are the simplest devices among all compressors and vacuum pumps. They do not contain any moving parts, lubricants or seals; therefore, they are highly reliable devices with low capital and maintenance costs and also energy saving device. Furthermore, most jet ejectors use steam or compressed air as the motive fluid, which are easily found in chemical plants. Due to their simplicity and high reliability, they are widely used in chemical industrial processes; however, jet ejectors have a low efficiency. The major consideration of this study is to optimize jet ejector efficiency at each operating condition. Consequently, the motive stream consumption and operating cost is minimized. Many factors affect jet ejector performance, including the fluid molecular weight, feed temperature, mixing tube length, nozzle position, throat dimension, motive velocity, Reynolds number, pressure ratio, and specific heat ratio. This paper reviews the various research on jet ejector with different application.

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The paper covers a reading device for blind or visually impaired persons for recognizing and reading text passages. It comprises an image capturing unit being configured to capture an image of an environment of a blind or visually impaired person and an image processing unit being configured to process the image data such that text is recognized and extracted from the image. The text is then converted into an audio message which can thus guide the blind in their daily lives.

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We know that multiple data mining methods have been developed for finding useful patterns in contents like PDF files, text files. Current paper addresses the problem of making text mining results more effective to humanities scholars, journalists, intelligence analysts, and other researchers. To use effective and bring to up to date discovered patterns is still an open research task, especially in the domain of text mining. Text mining is the finding of very interesting knowledge (or features) in the text documents. It is a very difficult to find exact knowledge (or features) in text documents to help users what they actually want. This paper represent efficient mining algorithm to find particular patterns.

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Cloud computing is known as digital service delivery over the Internet by several applica¬tions which are carried out by computer systems in distributed datacenters. It supplies a high performance computing based on protocols which allow shared computation and storage over long distances. Managing the allocation of cloud virtual machines at physical resources is a key requirement for the success of clouds. It aims at spreading the workloads among the processing resources in an optimal fashion to reduce the total execution time of jobs and then, to improve the effectiveness of the whole cloud computing services. A new Bee Swarm optimization algorithm called Bees Life Algorithm (BLA) is applied to efficiently schedule computation jobs among processing resources onto the cloud datacenters. The algorithm mimics the food foraging behavior of swarms of honey bees. The algorithm performs a kind of neighborhood search combined with random search and optimization problems.

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Wireless sensor networks have a wide range of potential applications, including security and surveillance, control, actuation and maintenance of complex systems and fine-grain monitoring of indoor and outdoor environments. Sensor nodes have limited transmission power and limited resources. Once they are deployed, they are remotely managed. There are many security attacks possible on sensor network like Jamming. Sinkhole, Selective Forwarding, Wormhole, Sybil attack etc. Among all the attacks, wormhole is very dangerous attack because the attacker does not require any cryptographic break to launch the attack. The attacker tunnels the packet from one area to another area, and disturbs the whole routing process. Traditional security algorithm cannot work on sensor network because of their limited resources. So new cryptographic measures are needed to protect the sensor nodes. Our proposed method can easily identify real and fake neighbours.

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Reducing energy consumption has been an important design issue for large-scale streaming media storage systems. Existing energy conservation techniques are inadequate to achieve high energy efficiency for streaming media computing environments due to media is streamed from the hard disk drive. To address this problem, we propose in this paper a new energy-efficient method stream media from flash memory. Streaming media from flash memory significantly reduces power utilization because of two reasons. First, a set of hard disks in media server side consumes more power compared to flash memory. Second, heat dissipation on the media server side. Therefore Streaming media from the flash memory is conducive to saving more energy for the long media data. This approach is achieved using the kernel and device driver concepts on the Linux operating system. Our experimental results show that it can save up to 28.13%-29.33% energy consumption. Energy efficiency of streaming media storage systems can be improved by 3.3~6.0 times.

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Now-a-days the data has become bigger because of E-commerce and Social Networking sites. So, there is a need to handle such big data and it has to be analyzed in such a way that it can produce some useful information which can be used in some kind of decision making. MapReduce framework has emerged as one of the most widely used parallel computing platforms for processing data on terabyte and petabyte scales. Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce function that merges all intermediate values associated with the same intermediate key. Today Map Reduce has been used daily at companies such as Yahoo!, Google, Amazon, and Facebook, and adopted more recently by several universities, it allows for easy parallelization of data intensive computations over many machines. There are many algorithms for retrieving the information using MapReduce like Sorting, Searching, TF-IDF, BFS, and Page-Rank etc Hadoop is a distributed file system where files can be saved with replication. It provides high fault tolerance and reliability. Moreover, it provides an implementation of MapReduce programming model. Hadoop can work directly with any distributed file system which can be mounted by the underlying OS. Hadoop-MapReduce can handle huge amount of data. Scalability is a matter of concern for a long time. Same is true for semantic web data. We can store huge amount of semantic web data in Hadoop clusters built mostly by cheap commodity class hardware and still can answer queries fast enough. The aim of this survey is improving the performance of parallel query processing using MapReduce.

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In their early years electric power systems did not reach far from the generating station. Since then power systems have been inter-connected to cover first regions and later nations. Today they extend over entire continents and contain a huge number of components that together serve to supply electric energy to the customers. The aim is to maintain the voltage and the frequency at their nominal values. To improve reliability both design and operation of power systems involve safety margins to the cost of some profit. Much effort today is spent on control and supervision that can reduce these margins, which also has environmental aspects. "Environmental and economic aspects make it difficult to build new power lines and to reinforce existing ones. The continued growth in demand for electric power must therefore to a great extent be met by increased loading of available lines. A consequence is that power system damping is reduced, leading to a risk of poorly damped power oscillations between the generators. This thesis proposes the use of controlled active loads to increase damping of such electro-mechanical oscillations. The focus is on structural aspects of controller power system damping by fact device Statcom ."

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The studied system here is a variable speed wind generation system based on Doubly Fed Induction Generator (DFIG). The stator of the generator is directly connected to the grid while the rotor is connected through a back-to-back converter which is dimensioned to stand only a fraction of the generator rated power. In order to improve the operation capacity of wind turbine under critical situation, the intensive study of both machine side converter control and grid side converter control is necessary. The system uses two back-to-back converters in the rotor circuit. The basic concept behind the total system (DFIG with back to- back converters) is that the machine-side converter controls the active and reactive power by controlling the d-q components of rotor current (i.e. idr and iqr), while the grid-side converter controls the dc-link voltage and ensures the operation at unity power factor by making the reactive power drawn by the system from the utility grid to zero.

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Conventionally Wireless-controlled Robots use RF circuits, which have limited working range, limited frequency range and limited control. Use of a mobile phone for robotic control can overcome these limitations. It provides the advantage of robust control, working range as large as the area of the service provider, no interference with other controllers. Although the appearance and capabilities of robot vary vastly, all robots share feature of a mechanical, movable structure under some form of control. The control of Robot involves three distinct phases: perception, processing and action. Generally, the preceptors are sensors mounted on the robot, processing is done by the on-board microcontroller or processor, and the task is performed using motors or with some other actuators. In this project the robot is connected to gsm modem which is controlled by user mobile phone. With the help of AT commands we can move our robot in desired direction as per our requirement.

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This paper deals with Energy meters are replacing conventional energy meters (electro Postpaid mechanical energy meters) throughout the world power systems. They have outperformed the electromechanical meters in terms of functionality and performance. The manufacturing investment, the measurement accuracy and quality, and fault tolerant billing are each unquestionably superior to the traditional electromechanical meter design. The electronic energy meter have built in microcontroller based technology that makes it accurate, more reliable, tamperproof and with future enhancing prospect the most preferable over electromechanical meter. Electromechanical meters have been the standard for metering electricity since billing began. Today’s electricity companies are demanding more information from meters in the residential sector, where metering has typically been limited to kilowatt-hours. New features such as multi-tariff billing, reactive energy measurement and power quality monitoring are desirable to improve generation, distribution, customer service and billing. Postpaid energy meters are mainly uses to restrict the energy theft, especially in urban & rural areas. 8051 microcontroller & Energy Metering IC ADE7751 along with other circuit are used in this project.

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Multilevel inverters are mainly devised for high power applications, due to higher voltage operating capability, lower dv/dts and more sinusoidal outputs. The Diode Clamped, Flying Capacitor and the Cascaded H-bridge inverter, are the most suitable topologies. The Cascaded H-Bridge, also known as multi-module converter, has been particularly used in very high power applications, due to its modularity and attractive input current harmonics cancellation. Multilevel converters are mainly controlled with sinusoidal PWM technique and it includes two types of multiple carrier arrangements: Level Shifted (LSCPWM) and Phase Shifted (PSCPWM). In this paper comparison between these two modulation techniques is carried out.

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In this Paper, we present a new neural network based method for optical character recognition as well as handwritten character recognition. Experimental results show that our proposed method achieves 98 percent accuracy in optical character recognition. In this thesis, we present an overview of existing handwritten character recognition techniques. All these algorithms are described more or less on their own. Handwritten character recognition is a very popular and computationally expensive task. We also explain the fundamentals of handwritten character recognition . We describe today's approaches for handwritten character recognition. From the broad variety of efficient techniques that have been developed we will compare the most important ones. We will systematize the techniques and analyze their performance based on both their run time performance and theoretical considerations. Their strengths and weaknesses are also investigated. It turns out that the behavior of the algorithms is much more similar as to be expected.

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In order to search education related information/resources there is only one traditional method, that is exploring things through search engine and navigating the resultant URL’s even though this method actually leads to waste of time and energy, still this method is used widely. Now-a-days people all over the world show keen interest in using social network sites; the term “social networking” does not exclusively belong to digital technology on the Web. On the contrary, social networks had been studied from the beginning of 20th century with the aim to comprehend how the members of a certain community interact and which mechanism can determine the interaction itself but today every social networking service platform helps to build social networks or social relationship among people who share common interests, activities, backgrounds, or real-life connections. There are many social networks like Facebook, Twitter, LinkedIn etc., but they have limited service scope in terms of educational resources and information as there is no such existing system like Educational Social Network so far which can provide a single platform to Colleges/Universities to have its own hub for regular educational updates and intercommunication also to have exclusive classrooms with online lectures.

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