iosr-JCE   International Conference on RECENT TRENDS IN ENGINEERING AND MANAGEMENT

Abstract: Users can remotely store their data in the cloud storage and can use the applications and services from a collective pool of configurable computing resources, without the trouble of local data storage and protection. Additionally, users should be able to just use the cloud storage as if it is local, without worrying about the need to authenticate its integrity. Hence, enabling public auditability for cloud storage is of critical importance so that users can resort to a Third Party Auditor (TPA) to prove the reliability of outsourced data and be burden free. To strongly initiate a valuable TPA, the auditing process should bring in no new vulnerabilities toward user data confidentiality, and bring in no other online trouble to user. In this paper, we propose a protected cloud storage system supporting privacy-preserving public auditing for active data. To allow the TPA to carry out audits for multiple users simultaneously and also prove the accuracy of remotely stored data efficiently. The audit outcome would also be useful for the cloud service providers to progress the cloud service platform. Extensive protection and performance analysis show the proposed schemes are provably protected and highly efficient. The test accomplished on Amazon EC2 instance further demonstrates the fast performance of the design.
Keywords - Data Storage, privacy-preserving, public auditability, cloud computing, batch verification

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[8] Q. Wang, C. Wang, K. Ren, W. Lou, and J. Li, Enabling Public Auditability and Data Dynamics for Storage Security in Cloud Computing, IEEE Trans. Parallel and Distributed Systems, 22(5), 2011, 847-859.
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Abstract: Building high Quality cloud applications becomes an immediately required research problem in cloud computing technology. Non-functional performance of cloud services is normally described by Quality-of-Service (QoS). To acquire QoS values, real-world usage of services candidates are generally required. At this time, there is no framework that can allow users to estimate cloud services and rank them based on their QoS values. This paper intends to framework and a mechanism that measures the quality and ranks cloud services for the users. Cloud Rank framework by taking the advantage of past service usage experiences of other users. So it can avoid the time consuming and expensive real life service invocation. This tactic determines the QoS ranking directly using the two personalized QoS ranking prediction approach i.e., CloudRank1 and CloudRank2. These algorithms make sure that the active services are accurately ranked. The interior purpose is ranking prediction of client side QoS properties, which likely have different values for dissimilar users of the similar cloud service. It estimates each and every one the applicant services at the user-side and rank the services based on the observed QoS values.
Keywords - Cloud Services, Cloud rank Framework, Quality-of-Service, Ranking Prediction, And Personalized Framework.

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Abstract: Automated analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience, and related disciplines. Promising approaches have been reported, including automatic methods for facial and vocal affect recognition. Facial activities are characterized by three levels. First, in the bottom level, facial feature points around each facial component, i.e., eyebrow, mouth, capture the detailed face shape information. Second, in the middle level, facial action units, represent the contraction of a specific set of facial muscles, i.e., lid tightener,eyebrow raiser, etc.Finally,in the top level, six prototypical facial expressions represent facial muscle movement. A unified probabilistic framework based on the dynamic Bayesian network to simultaneously and coherently represent the facial evolvement in different levels, their interactions and their observations. Advanced machine learning methods are introduced to learn the model based on both training data and subjective prior knowledge.
Keywords:- Bayesiannetwork,expression recognition, facial action unit recognition, facial feature tracking, simultaneous tracking and recognition

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Abstract: The current image retrieval systems are successful in retrieving images, using keyword based approaches. However, they are incapable to retrieve the images which are context sensitive and annotated inappropriately. Content-Based Image Retrieval (CBIR) aims at developing techniques that support effective searching and browsing of large image repositories, based on automatically derived image features. The current CBIR systems suffer from the semantic gap. Though a user feedback is suggested as a remedy to this problem, it often leads to distraction in the search. To overcome these disadvantages, novel interactive keyword based image retrieval and integrating text with image content are proposed to enhance the retrieval accuracy. Also GOOGLE search engine is used as a back end to search and retrieved images with their link. The robustness of the result obtained by the proposed method is shown by various performance analyses like different web browsers, different internet service providers and etc.
Keywords:- Context sensitive, Annotation, Content-Based Image Retrieval, Google search engine

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Abstract: Motivated by the needs of semantic search and retrieval of multimedia contents, operating directly on the video based annotations can be thought as a reasonable way for meeting these needs as video is a common standard providing a wide multimedia content description schema. Raw data and low-level features alone are not satisfactory to fulfil the user's requirements; that means, a deeper understanding of the content at the semantic level is necessary. A semantic content extraction system that allows the user to query and regain objects, events, and concepts that are extracted automatically is proposed. In automatic extraction process, starts with object and define class for each process in video data. A new ontology based fuzzy video data semantic model uses spatial/temporal relation in event and concept definition is declared. Objects extracted from consecutive representative frames are processed to extract temporal relations. In addition to that, additional rule to lower spatial relation computation cost and to be able to define some difficult situations more successfully is used. Event extraction process uses objects, spatial relations between objects and temporal relations between events. Similarly, objects and events are used in concept extraction process
Keywords:- Content-based retrieval, fuzziness, ontology, Semantic content extraction, video content modeling.

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Abstract: Grid computing is an important and developing computing initiative that involves the collection of network connected computers to form a distributed system for coordinated problem solving and resource sharing. This paper presents a state-of-the-art review of grid computing
. Keywords:- Computing, Distributed System, Grid Computing, Resource Sharing, Review.

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Abstract:An extensive helplessness of wireless networks in exacting the Mobile Ad-Hoc Network (MANET) is their vulnerability to node compromise and physical capture attacks. Detecting replication attacks is a nontrivial problem in MANETs due to the challenges resulted from node mobility, cloned and compromised node collusion, and the outsized number and extensive of the replicas. It has two replication detection schemes Time Domain Detection (TDD) and Space Domain Detection (SDD). The theoretical analysis indicates that TDD and SDD provide high detection accuracy and excellent resilience against smart and colluding replicas. It has no restriction on the number and distribution of replicas, and incurs low communication and computation overhead. According to theoretical analysis, for validating the path to occur any interference before transmitting the data from source to destination the RIP Protocol, TDD and SDD are the only approaches that support mobile networks that places no restrictions on the number and distribution of the cloned frauds and on whether the replicas collude or not.
Keywords:-TDD (Time Domain Detection), SDD (Space Domain Detection), RIP (Routing Information Protocol), MANET.

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Abstract: In this paper proposes new strategies for object tracking initialization using automatic moving object detection based background subtraction. The new strategies are integrated into the real-time object tracking system. The proposed background model updating technique and adaptive thresholding are used to produce a foreground object mask for object tracking initialization. Traditional background subtraction technique detects moving objects by subtracting the background model from the current image. Compare to various common moving object detection technique, background subtraction segments foreground objects more accurately and detects foreground objects even if they are non moving. However, one drawback of traditional background subtraction is that it is vulnerable environmental changes, for instance, gradual or fast illumination changes. The reason of this disadvantage is that it assumes a static background, and therefore a background model update is needed for dynamic backgrounds. The most important challenges are how to update the background model, and how to find out the threshold for classification of foreground and background pixels. The proposed technique is to determine automatically and dynamically depending on the intensities of the pixels within the current frame and a technique to update the background model with learning rate depending on the variations of the pixels within the background model and also the previous frame. This paper additionally represented a shape tracking technique to track the moving multiple objects in surveillance video.
Keywords:- moving object detection, background model, shape tracking.

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Abstract: Delay Tolerant Networks (DTNs), also called as intermittently connected mobile networks, are wireless networks in which a fully connected path from source to destination is unlikely to exist. However, effective forwarding based on a limited knowledge of contact behavior of nodes is challenging. When large files need to be transferred from source to destination make all the packets available at the source and transfer the file as small packets. We study the packets arrival at source and analysis their performance. We consider the linear blocks and rateless linear coding to generate redundancy and also for energy constraint .We scheduling the large file into small packets and delivering through multipath to destination, for this we use optimal user centric allocation and scheduling the packets in the receiver side.
Keywords:- Delay tolerant networks,network coding, rate less codes,.

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