Augmented Reality is a new computer technology that combines virtual computer generated 3D graphics with realistic environments in natural visual perception. Augmented reality is a technology which allows 2D and 3D computer graphics to be accurately aligned or registered with scenes of the real-world in real-time. The occlusions usually cause a disappearance of the 3D model. Such behavior has substantial negative impact on the application usability. In this article we present a hybrid marker detection approach. With this approach, markers are detected using the well-known SURF method. This method is able to recognize complex natural objects and deal with partial occlusions. Further, we overcome the problem of distinguishing similar markers by using the Golay error correction code patterns. The described approach represents a robust method that is able to identify even significantly occluded Markers, differentiate similar markers, and it works in a constant time regardless of the amount of used markers.

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We know that automotive engine parts are made of different material, to make a part of automobile like "piston" we must chosen the material which is most suitable for manufacturing this parts, so we have to consider about structural condition of piston and physical and chemical property of material. This is the main part of the engine. Its purpose is to transfer force from expanding gas in the cylinder to the crank shaft via connecting rod. In this study structural analysis of the piston has been carried out on the two different materials.A three dimensional Finite Element Model is built in the CAE software CREO2.0 parametric and the analysis is to be done in ANSYS-15.0. Material used Al alloy 2014A and 6106T6.The main objective is to investigate and analyze the stress distribution and deformation of the piston at the real engine condition during combustion process. The material used Aluminium alloy.

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This paper presents a structured approach to RCM and DOFR, and discusses the various steps in the approach for critical components in a dairy plant as a continuous. The homogenizer, Air heating system, drying chamber and vibrofludiser are most critical equipments in drying unit of milk powder plant in dairy industry. The proper combination of RCM and DOFR method provides a framework for utilizing operating experience in a more systematic way. The requirements for reliability parameters and data are therefore highlighted. The effort is made to fill gap between existing maintenance and new plan, together with some future challenges. After the application of RCM and DOFR process to critical components of the milk powder drying unit, there is a considerable improvement of 12-15% in uptime. Moreover, there is also considerable savings on setup loss, equipment failure time etc. Finally at the end the paper suggestions for maintenance of homogenizer, air heater, drying chamber and vibrofludiser are indicated to ensure trouble free operation and maximum service life, which may ultimately improve uptime and productivity.

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This paper focuses on designing a robust and flexible registration method for wide-area augmented reality applications using scene recognition and natural features tracking techniques. Instead of building a global map of the wide-area scene, we propose to partition the whole scene into several sub-maps according to the user’s preference or the requirements of the augmented reality (AR) applications. Random classification trees are used to learn and recognize the reconstructed scenes because they naturally handle multi-class problems, while being both robust and fast. The result is a system that can deal with large scale scene that previous methods cannot cope with. We also propose a hybrid natural features tracking strategy combining both wide and narrow baseline techniques. While providing seamless registration, our system can recover from registration failures and switch between different sub-maps automatically. Experimental results demonstrate the validity of the proposed method for wide-area augmented reality applications.

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The Dissolved Gas Analysis has been widely used by utilities throughout the world as the primarily diagnostic tool for transformer maintenance. The gas generated in mineral oil of power transformer can be monitored by all conventional methods, online DGA system and by application of various Artificial Intelligence practices. This sequential hybrid system ANN and FIS can be a good solution for reliable results for predicting faults because one should not depend on a single technology when dealing with real–life applications. This paper compares the conventional system of DGA and various analysis techniques by application of Artificial Intelligence.

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To improve and optimize the responses of a Laser Beam machining process, the various input machining control parameters are to be set at an optimal value. As such one has to adopt experimental methods, which are cumbersome, time consuming, costly and at times not feasible. During such situations, optimization technique like Taguchi can be used as it provides a cost effective method for solution of such complex problems. Unlike traditional optimization techniques, Taguchi is robust and performs well in optimization problems. Considering these advantages of Taguchi, optimization of Co2 Laser beam machining process is done using this technique. In this research work, the desired responses are kerf width and surface roughness and Perpendicularity of cut are calculated. The process control parameters considered are Gas pressure, Cutting Speed, pulse frequency and power.

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Tall buildings and hazardous utilities require regular inspection and maintenance to comply with the ordinance, and to ensure the integrity and safety. The traditional manual inspection and maintenance on tall building normally requires the installation of expensive scaffoldings or gondolas in which human operators need to work in mid-air and life threatening environment. The prospect of climbing robots is popular because they can take the place of humans to carry out hazardous and maintenance job such as cleaning glass surfaces of skyscrapers, fire rescue, and inspection of pipes and wall, cleaning & inspection of high rise buildings, evaluation and diagnosis of a storage tank in nuclear power plants & petrochemical plants, maintenance of ship, aircraft wing inspection with the consideration of operational efficiency, safety and human health. These types of climbing robots are classified in to different groups based on their locomotion and adhesion mechanism. Due to the ability to relieve human beings from these hazardous works, more & more people are interested in developing various service climbing robots in recent years.

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With the enhancement in technology e banking like credit Card, Debit Card, Mobile Banking and Internet Banking is the popular medium to transfer the money from one account to another. E Banking is gaining popularity day by day, which increases the online transaction with the increase in online shopping, online bill payment like electricity, Insurance Premium and other charges, online recharges and online reservation of railways, bus etc., cases of fraud associated with it are also increasing and it puts a great burden on the economy, affecting both customers and financial bodies. It not only costs money, but also a great amount of time to restore the harm done. The purpose is to prevent the customer from online transaction by proposing unique and hybrid approach containing Data Mining and Artificial Intelligence based techniques and in order to prevent from fraudulent transactions, PIN, One Time Password mechanisms are used to prevent from online transactions.

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In this paper, we are presenting an overview of existing frequent item set mining algorithms. Nowadays frequent item set mining is a very popular and computationally expensive task. We have also explained the fundamentals of frequent item set mining. We have described today’s approaches for frequent item set mining. From the broad variety of frequent item set mining algorithms that have been developed we will compare the most important ones. We will compare the algorithms and analyze their performance based on both their run time performance.

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The text summarization is the need of the hour. As the information is rapidly growing on the internet. The problem is that when you search for any information the internet provides more information than the required. So there is a need to summarize the result. Also there is a need to maintain the quality of information in the summary. In this paper, we will elaborate the concept of the multi document summarization. We have also given a classification of the text classification. The literature review of the modern multi document summarization technique is also given. The working, the merits and the demerits of each text summarization technique will be discussed.

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Computer vision field is becoming the area for the research these days. Technological improvement made the computers and imaging hardware to find their applications in the field of computer vision. Hence they found applications in the military for targeting, surveillance and biometric etc. Originally, business used video surveillance as both a deterrent to thieves and evidence to help police to apprehend criminals. Objective of our work is to ‘Provide foolproof’ security in the restricted zones like bank, jewelry shops etc. There are many traditional technologies which provide security to restricted zones but these traditional technologies do not take quick action and are not foolproof. To give strong security solutions for restricted zones, this will have smart camera connected to the cell phone by which one can take quick action without wasting time. In our project approaches used for face recognition and face detection are SMQT algorithm, split up Snow classifier and PCA for efficient face recognition.

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This article deal with conceptual design the flow path and optimization the efficiency power and losses. In this paper concentrate on high pressure axial compressor and further discuss about the different type of flow path design and also investigate the effect on performance parameter and design parameters. Design parameters of gas turbine plant are used from available references. Investigation is done using Axstream software. The flow path design is most important for designer because some characteristic effect by flow path. This article carried out three type of flow path like that constant hub diameter, constant mean diameter and constant tip diameter further, investigate the different of performance parameter and design parameter of all the flow path.

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Limited energy is a serious issue in sensor networks. Therefore, there is a need to optimize the network architecture for the applications in order to minimize resources consumption. This paper compares the strategies of cluster-head selection in K-means algorithm in wireless sensor network when applied as a routing algorithm. The single-objective cluster-head selection takes account of only inter cluster distance of nodes and cluster head while multi-objective strategy considers cluster head position in cluster and distance between base station and cluster head besides inter cluster distance. The later strategy fails to provide equal distribution of energy among nodes and the results confirm our hypothesis proving single objective function as a better strategy.

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Feature selection is a term commonly used in data mining to describe the tools and techniques available for reducing inputs to a manageable size for processing and analysis. Feature selection implies not only cardinality reduction, which means imposing an arbitrary or predefined cutoff on the number of attributes that can be considered when building a model, but also the choice of attributes, meaning that either the analyst or the modeling tool actively selects or discards attributes based on their usefulness for analysis. Feature selection involves identifying a subset of the most useful features that produces compatible results as the original entire set of features. A feature selection algorithm may be evaluated from both the efficiency and effectiveness points of view. While the efficiency concerns the time required to find a subset of features, the effectiveness is related to the quality of the subset of features. The proposed algorithm works in two steps. In the first step, features are divided into clusters by using graph-theoretic clustering methods. In the second step, the most representative feature that is strongly related to target classes is selected from each cluster to form a subset of features. Features in different clusters are relatively independent; the clustering-based strategy of this algorithm has a high probability of producing a subset of useful and independent features. To ensure the efficiency of this algorithm, we adopt the efficient minimum-spanning tree clustering method. Features in different clusters are relatively independent; the clustering-based strategy of this algorithm has a high probability of producing a subset of useful and independent features. The efficiency and the effectiveness of the algorithm can be evaluated by the runtime efficiency, classification accuracy and the subset of features selected. Extensive experiments are performed on this algorithm by comparing it with known classifiers like tree-based C4.5. The results on the high dimensional image and microarray data, demonstrate that the algorithm not only produces smaller subsets of features but also improves the performance of the C4.5 classifier.

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Query clustering is a concept of grouping the related searches based on a predefined set of rules which end up with a most appropriate grouping of the queries. In our day to day life we use search engines like google to search the information, but we end up with the searches which provide an inappropriate results. As the search engine are meant to be user friendly, the overhead of grouping of the queries should be the task of the search engines rather than, distracting the user experience by ending up with unrelated searches for their query. Clustering is the process of organizing the objects in a group which have some common similarities. Query clustering is an unambiguous process which groups the data item sets in a predefined way, where in a query header is given to each of the cluster which determines in which cluster each query should fall in.

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Internet traffic classification is an important tool for network management. It allows operators to better predict future traffic matrices and demands, security personnel to detect anomalous behavior, and researchers to develop more realistic traffic models. We present here a traffic classifier that can achieve a high accuracy across a range of application types without any source or destination host-address or port information. We use a Semi-Supervised method for classification of network traffic. The proposed method classifies network traffic using flow statistics that allows classifiers to be designed from training data consisting of only a few labeled and many unlabeled flows. The approach consists of two steps, clustering and classification. Clustering partitions the training data set into clusters. After making clusters, classification is performed in which labeled data are used for assigning class labels to the clusters. The results showed that the proposed method outperforms to existing method. During more specific comparison we use KDD (Knowledge Discovery in Databases) data set and tested our proposed and existing algorithm, we show the proposed algorithm is better than existing algorithm. The results are represented in Receiver operating characteristics (ROC) graphs.ROC graphs are a very useful tool for visualizing and evaluating classifiers.

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In today’s age, where product witness major changes in shape and size within short time, it becomes necessary for an organization to set control over its manufacturing processes so as to make efficient use of its resources to produce optimum output. While introducing new parts or products in an organization, it becomes essential to bring on all functional departments in that organization to a platform which is product data oriented. Manufacturing Execution System (MES) helps to bring on all functional departments within extended organization to that platform, through real time data collection. It signifies functioning of each department with the help of key performance indicators (KPIs). Manufacturing Execution System through Lean manufacuring approach is focused on creating a perfect process of value creation in product development and operations; along with the supporting processes within organizations.

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The strange part of Indian education system is that on the one hand we have college like IIT's, IIM's and many high-quality schools too which are well-recognized for their quality education, Research and highly intelligent faculties but on the other hand we have colleges which are not even nearby IIT's or IIM's. In the year 2011-2012 Indian Government has provided Rs in thousands crore to Ministry of Human Resources development (MHRD) for uplifting the education system in India. even though similar budgets have been allotted by the government earlier in many years to improve the education system but in spite of that one fourth population of the India is still uneducated and in this figure educated means number of peoples who have passed their school, if we check for higher education level then this percent again going to reduced. Reasons we find that there is no centralized system for the government to check the educational institutes. If we talk about technical education of India we found lack distribution of resources like teaching tools, Infrastructures, software’s, teaching stuffs etc. As Cloud Computing technology is the most capable technology that provide solution to all the mentioned deficiency, thus we recommend that with the help of this technology we can overcome these deficiencies and reach our goal of hundred percent literacy rates. And also complete the aim to provide quality education to each and every citizen of India. Cloud computing has the potential to provide computation and storage resources as services. Both the public as well as the private institutions can use the cloud computing to deliver better services with limited resources. Around 45 million people will be in the age group of 18 to 20 years by 2020 in India. To make available quality education for them will be challenging task. So this paper is an analytical study on role of cloud computing in Technical education.

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Learning through the use of web technology or web based learning has become an important media in the education revolution of the 21st century. The Internet particularly, has become an important tool for learners to acquire information and knowledge that encompasses various elements such as text, graphic, numeric, and animation for their learning process. Learners soon learn that the links in the Internet can lead them to various web pages that can lead them to more information that have a link with one another or to other information that has no link at all with the previous information. The visually impaired learners who actually represent a substantial proportion of the world’s population living in certain parts of the world have no access at all to this tool nor can it be easily taught to them as they are not able to see the links. So in this project a Local Search engine module is implemented where the user can search for keywords and get the corresponding information about searched keyword. This project hopes to highlight the GANAKA DHRISTI system to enable the visually impaired learners experience the world of the Internet, which comprises of five modules: Automatic Speech Recognition (ASR), Text-to-Speech (TTS), Local Search engine, Braille-to -Text module.

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Many applications require finding the nearest objects closest to a specified location that contains a keywords. Nearest neighbor queries that aims to find objects both a spatial predicate and predicate on their associated texts. For example a nearest neighbor query search restaurant that is the closest among many restaurants within a particular area, whose menu contain required food keyword with respect to query. The problems of the nearest neighbor search on spatial data and keyword search on text data have been studied separately. Existing solution to queries is based on IR2-Tree (Information Retrieval R-Tree), but it has a few deficiencies that it requires more time to process the query and fails to give real time answers. To overcome these problems, we present an efficient access method to answer spatial keyword queries. we introduce an indexing structure called spatial inverted index that extends the inverted index.

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Transformer is an important electrical device in the power system which is used to step up and step down the voltage & Transfer electrical power according the need of customer. Oil filled Transformers get the insulation and heat transfer properties form the oil. But ironically the same oil causes one of the major defects of the transformer i.e. moisture. The transformer there is always mechanical, thermal or electrical stress generated during its operational period , it causes fault in transformer, the source of fault may lie in design, manufacturing, material used, handling & site , as this is the major pain area for all transformer industries , we introduced a latest quality tool to resolve this repetitive problem with target to reduce it at 0.01 DPU level ,In this paper we used six sigma methodology & approach, this is statistical tool which is based on past data, process parameter , results and analysis of the problem .

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Wireless networks are gaining attractiveness day by day, as users want wireless connectivity irrespective of their geographic location. A wireless ad-hoc network is a temporary network set up by wireless mobile nodes moving random in places that have no infrastructure. For communication in mobiles nodes routing protocols are used like Reactive routing protocol i.e. Ad-Hoc on Demand Distance Vector (AODV), Proactive routing protocol i.e. Optimized Link State Routing (OLSR) and Hybrid routing protocol i.e. Temporary Ordered Routing Algorithm (TORA). However due to security vulnerabilities of the routing protocols, MANETS are vulnerable to malicious nodes. There is an increasing threat of malicious nodes attacks on the Mobile Ad-hoc Networks (MANET). Black hole attack is one of the security threat in which the traffic is redirected to such a node that actually does not exist in the network.

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Cloud Computing has been proposed as the next-generation architecture of IT Enterprise. It moves the application software and databases to the integrated large data centers, where the management of the data and services may not be fully trustworthy. This unique paradigm brings about many new security challenges, which have not been well understood. This work studies the problem of ensuring the integrity of data storage in Cloud Computing. In particular, we consider the task of allowing a third party auditor (TPA), on behalf of the cloud client, to verify the integrity of the dynamic data stored in the cloud. The introduction of TPA eliminates the involvement of the client through the auditing of whether his data stored in the cloud is indeed intact, which can be important in achieving economies of scale for Cloud Computing. The support for data dynamics via the most general forms of data operation, such as block modification, insertion and deletion, is also a significant step toward practicality, since services in Cloud Computing are not limited to archive or backup data only. While prior works on ensuring remote data integrity often lacks the support of either public auditability or dynamic data operations, this paper achieves both. We first identify the difficulties and potential security problems of direct extensions with fully dynamic data updates from prior works and then show how to construct an elegant verification scheme for the seamless integration of these two salient features in our protocol design. In particular, to achieve efficient data dynamics, we improve the existing proof of storage models by manipulating the classic Merkle Hash Tree construction for block tag authentication. To support efficient handling of multiple auditing tasks, we further explore the technique of bilinear aggregate signature to extend our main result into a multi-user setting, where TPA can perform multiple auditing tasks simultaneously. Extensive security and performance analysis show that the proposed schemes are highly efficient and provably secure.

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The proposed research work implemented and fine-tuned meta-heuristic based search algorithms namely PSO algorithm for automatic test case generation using path testing criterion. The three parameters namely size of population (NIND), inertia weight (W), social learning rate (C1), and cognitive learning rate (C2) have been chosen for setting PSO algorithm for test data generation. For input generation, symbolic execution method has been used in which first, target path is selected from Control Flow Graph (CFG) of Software under Test (SUT) and then inputs are generated using search algorithms which can evaluate composite predicate corresponding to the target path true. We have experimented on two real world programs showing the applicability of these techniques in genuine testing environment. The algorithm is implemented using MATLAB programming environment. The performance of the algorithms is measured using average test cases generated per path (ATCPP) and average percentage coverage (APC) metrics.

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Wireless Sensor Network (WSN) consists of low cost and small sized motes known as sensor nodes. The use of sensor nodes depends upon the need of an application. Various challenges of WSN affect the performance of the network. Limited energy and power are the main issues in WSNs due to this different routing protocol are designed to improve the energy efficiency of the whole network. Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the best energy efficient protocol falls under the category of hierarchical routing protocol. This works on the concept of cluster formation. Different algorithms are used for cluster setup. This paper explains the working of LEACH in detail with some advantages and disadvantages. Also highlights some improvement over LEACH and analyze the Particle Swarm Optimization (PSO) algorithm for cluster setup.

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