For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
I am Tapas Kumar Palei. I am studying B.Tech CSE in Ajay Binay Institute Of Technology. Grid computing is my seminar presentation topic. I try to gather everything about the grid computing in this seminar presentation.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
I am Tapas Kumar Palei. I am studying B.Tech CSE in Ajay Binay Institute Of Technology. Grid computing is my seminar presentation topic. I try to gather everything about the grid computing in this seminar presentation.
RECENT PHD RESEARCH TOPIC IDEAS FOR COMPUTER SCIENCE ENGINEERING 2020 Exclusi...Tutors India
Artificial intelligence (AI) based data mining and pattern recognition method for knowledge extraction & decision-making process over the cloud environment. Design and implementation of autonomic resource provisioning and a scheduling method to satisfy the user QoS requirement in a cloud platform. The implementation of privacy-aware efficient resource scheduling and load balancing approach for big data storage system. Location-based image retrieval system using deep neural network and image Features Information Fusion technique. To detect network intrusion/attacks over the cloud data using soft computing and optimization technique.
Towards Deep Programmable Slicing. IEEE Netsoft'19 Distinguished Expert Panel Theme: Barriers and Frontiers of Softwarization for the Network of 2030, Paris, 2019. https://netsoft2019.ieee-netsoft.org/program/distinguished-expert-panel/
The XLcloud project strives to establish the demonstration of a High Performance Cloud Computing (HPCC) platform based on OpenStack that is designed to run a representative set of compute intensive workloads. Two Use Cases will be demonstrated during this presentation. First, the interventional radiology use case of the XLCloud project has the goal to show that the XLCLoud platform can be used to leverage an application requiring both interaction and high performance computing. This simulator, developed by CEA and Esprimed, allows medical staff to prepare or replay an intervention in a 3D interactive environment (manipulation of the radiological system, position of people and their protections) while having the benefit of precise estimation of the dose they are exposed to through a 3D monte carlo simulation optimized in order to provide results in interactive time. The second use case will be based on cloud gaming and 3D visualization. XLcloud is a three-year long collaborative project funded by the French FSN (Fonds national pour la Société Numérique) programme.
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Several applications, such as smart cities, smart homes and smart hospitals adopt Internet of Things (IoT) networks to collect data from IoT devices. The incredible growing speed of the number of IoT devices congests the networks and the large amount of data, which are streamed to data centers for further analysis, overload the data centers. In this paper, we implement a fog computing platform that leverages end devices, edge networks, and data centers to serve the IoT applications. In this paper, we focus on implementing a fog computing platform, which dynamically pushes programs to the devices. The programs pushed to the devices pre-process the data before transmitting them over the Internet, which reduces the network traffic and the load of data centers. We survey the existing platforms and virtualization technologies, and leverage them to implement the fog computing platform. Moreover, we formulate a deployment problem of the programs. We propose an efficient heuristic deployment algorithm to solve the problem. We also implement an optimal algorithm for comparisons. We conduct experiments with a real testbed to evaluate our algorithms and fog computing platform. The proposed algorithm shows near-optimal performance, which only deviates from optimal algorithm by at most 2% in terms of satisfied requests. Moreover, the proposed algorithm runs in real-time, and is scalable. More precisely, it computes 1000 requests with 500 devices in <; 2 seconds. Last, the implemented fog computing platform results in real-time deployment speed: it deploys 20 requests <; 10 seconds.
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See the video at: https://www.youtube.com/watch?v=4hKvgIi-HZY
RECENT PHD RESEARCH TOPIC IDEAS FOR COMPUTER SCIENCE ENGINEERING 2020 Exclusi...Tutors India
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Towards Deep Programmable Slicing. IEEE Netsoft'19 Distinguished Expert Panel Theme: Barriers and Frontiers of Softwarization for the Network of 2030, Paris, 2019. https://netsoft2019.ieee-netsoft.org/program/distinguished-expert-panel/
The XLcloud project strives to establish the demonstration of a High Performance Cloud Computing (HPCC) platform based on OpenStack that is designed to run a representative set of compute intensive workloads. Two Use Cases will be demonstrated during this presentation. First, the interventional radiology use case of the XLCloud project has the goal to show that the XLCLoud platform can be used to leverage an application requiring both interaction and high performance computing. This simulator, developed by CEA and Esprimed, allows medical staff to prepare or replay an intervention in a 3D interactive environment (manipulation of the radiological system, position of people and their protections) while having the benefit of precise estimation of the dose they are exposed to through a 3D monte carlo simulation optimized in order to provide results in interactive time. The second use case will be based on cloud gaming and 3D visualization. XLcloud is a three-year long collaborative project funded by the French FSN (Fonds national pour la Société Numérique) programme.
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Spatial related traffic sign inspection for inventory purposes using mobile l...ieeepondy
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Ijeee 16-19-digital media hidden data extractingKumar Goud
Abstract— Magnetic Resonance Imaging (MRI) brain tumor image classification is a difficult task due to the variance and complexity of tumors. This paper presents an efficient techniques for the classification of the magnetic resonance brain images. In this work we are taking MR images as input; MRI which is directed into internal cavity of brain and gives the complete image of the brain. The proposed technique consists of two stages.In the first stage, discrete wavelet transform is used for dimensionality reduction and feature extraction.In the second stage, classification is performed using the probabilistic neural network. The classifier have been used to classify real MR images as benign (non-cancerous) and Malignant (cancerous). Probabilistic neural network (PNN) with image and data processing technique is employed to implement an automated brain tumor classification. The use of artificial intelligent technique has shown great potential in this field.
Index Terms— Brain tumors, Feature extraction,Classification, MRI, Probabilistic neural network, Dimensionality reduction, Discrete wavelet transform.
A deep intelligence framework for online video processingieeepondy
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Comparative Study on Watermarking & Image Encryption for Secure CommunicationIJTET Journal
Over the past decades, research in security has concentrated on the development of algorithms and protocols for authentication, encryption and integrity of data. Despite tremendous advances, several security problems still afflict system’s. In this android app watermarking and encryption is being applied on images and data. Because of the human visual system’s low sensitivity to small changes and the high flexibility of digital media, anyone can easily make small changes in digital data with low perceptibility. Here watermarking and encryption are being performed in wavelet domain. Here in watermarking, the coefficients of watermarks are being embedded with the coefficients of the original image. Encryption is being done in wavelet domain so that the probability of an intruder trying to access the contents is very much minimized. Thus, this model provides a high level of security.
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider.
For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
CONCLUSION
This proposal of monitoring data access patterns by profiling user behavior to determine if and when a malicious insider illegitimately accesses someone’s documents in a Cloud service. Decoy documents stored in the Cloud alongside the user’s real data also serve as sensors to detect illegitimate access. Once unauthorized data access or exposure is suspected, and later verified, with challenge questions for instance, this inundate the malicious insider with bogus information in order to dilute the user’s real data. Such preventive attacks that rely on disinformation technology could provide unprecedented levels of security in the Cloud and in social networks.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Video steganography based on DCT psychovisual and object motionjournalBEEI
Steganography is a technique of concealing the message in multimedia data. Multimedia data, such as videos are often compressed to reduce the storage for limited bandwidth. The video provides additional hidden-space in the object motion of image sequences. This research proposes a video steganography scheme based on object motion and DCT-psychovisual for concealing the message. The proposed hiding technique embeds a secret message along the object motion of the video frames. Motion analysis is used to determine the embedding regions. The proposed scheme selects six DCT coefficients in the middle frequency using DCT-psychovisual effects of hiding messages. A message is embedded by modifying middle DCT coefficients using the proposed algorithm. The middle frequencies have a large hiding capacity and it relatively does not give significant effect to the video reconstruction. The performance of the proposed video steganography is evaluated in terms of video quality and robustness against MPEG compression. The experimental results produce minimum distortion of the video quality. Our scheme produces a robust of hiding messages against MPEG-4 compression with average NC value of 0.94. The proposed video steganography achieves less perceptual distortion to human eyes and it's resistant against reducing video storage.
Study on Secure Cryptographic Techniques in Cloudijtsrd
Cloud Computing is turning into an increasing number of popular day by day. If the safety parameters are taken care properly many organizations and authorities corporations will flow into cloud technology.one usage of cloud computing is statistics storage. Cloud affords considerable capability of garage for cloud users. It is more reliable and flexible to users to shop and retrieve their facts at whenever and everywhere. It is an increasingly more growing technology. Mariam Fatima | M Ganeshan | Saif Ulla Shariff "Study on Secure Cryptographic Techniques in Cloud" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42363.pdf Paper URL: https://www.ijtsrd.comcomputer-science/computer-network/42363/study-on-secure-cryptographic-techniques-in-cloud/mariam-fatima
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DOTNET Project Domain list 2015
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4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
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3. Embedded project
4. Robotics project
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3. B.Tech IT
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IJLBPS provides an inclusive environment for researchers to share original research, reviews, case studies, and technical notes across a broad spectrum of life sciences, biotechnology, and pharmaceutical sciences.
The journal publishes original works with practical significance and academic value. All papers submitted to IJMRR are subject to a double-blind Authors are invited to submit theoretical or empirical papers in all aspects of management, including strategy, human resources, marketing, operations, technology, information systems, finance and accounting, business economics, public sector management. peer review process. IJMRR is an international forum for research that advances the theory and practice of management.
Authors are invited to submit theoretical or empirical papers in all aspects of management, including strategy, human resources, marketing, operations, technology, information systems, finance and accounting, business economics, and public sector management. The journal publishes original works with practical significance and academic value.
A variety of solutions have been proposed to mitigate the reduction in mobility due to VI.
A variety of solutions have been proposed to mitigate the reduction in mobility due to VI.
Enhanced Dynamic Leakage Detection and Piracy Prevention in Content Delivery ...Editor IJMTER
Due to the increasing popularity of video services application in recent days, it is
undesirable to prevent the content leakage on the trusted video delivery and piracy prevention has
been indeed, become critical. In order to preserve content leakage and prevent piracy,
conventional system addressed the issue by proposing the method based on the observation of
streamed traffic throughout the network .Also piracy has hindered the use of open peer to peer
networks for commercial content delivery. Hence the basic idea is to propose an enhanced
dynamic content leakage detection scheme that is robust to the variation of the video lengths. It
enhances the detection performances even in the environment subjected to variation in length of
videos. To detect pirates, identity-based signature and time stamped token have been generated. It
helps to solve piracy without affecting P2P clients so that colluder cannot download the secured
videos. The advantage lies mainly in advanced content availability, low cost and copyright
agreements in protecting the secured videos.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
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D pcode privacy preserving frequent visual patterns publication on cloud
1. DPcode: Privacy-Preserving Frequent Visual Patterns Publication on Cloud
Abstract:
Nowadays, cloud has become a promising multimedia data processing and
sharing platform. Many institutes and companies plan to outsource and share
their large-scale video and image datasets oncloud for scientific research and
public interest. Among various video applications, the discovery of frequent visual
patterns over graphical data is an exploratory and important technique. However,
the privacy concerns over the leakage of sensitive information contained in the
videos/images impedes the further implementation. Although the frequent visual
patterns mining (FVPM) algorithm aggregates summary over individual frames
and seems not to pose privacy threat, the private information contained in
individual frames still may be leaked from the statistical result. In this paper, we
study the problem of privacy-preserving publishing of graphical data FVPM
on cloud. We propose the first differentially private frequent visual patterns
mining algorithm for graphical data, named DPcode. We propose a novel
mechanism that integrates the privacy-preserving visual word conversion with the
differentially private mechanism under the noise allocation strategy of the sparse
vector technique. The optimized algorithms properly allocate the privacy budgets
among different phases in FPM algorithm over images and reduce the
corresponding data distortion. Extensive experiments are conducted based on
datasets commonly used in visual mining algorithms. The results show that our
approach achieves high utility while satisfying a practical privacy requirement.
