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Multimedia understanding could be a quickrising analysis. Advances in multimedia system understanding area unit connected on to advances in signal knowledge base analysis space. there`s tremendous potential for effective use of multimedia system content through intelligent process, pc vision, pattern recognition, multimedia system databases, and sensible sensors. In reality, each content and context info area unit made sources of knowledge for mining, and therefore the full power of mining and process algorithms is completed solely with the utilization of a mixture of the 2. As digital libraries of pictures area unit speedily growing in size, content primarily based image retrieval has been spotlighted in many fields. During this paper we tend to make a case for content and context primarily based multimedia system retrieval, state of art techniques supported multimedia system retrieval. Then as a case study we tend to implement content primarily based image retrieval exploitation color feature.

Information retrieval, Multimedia databases, Content and context links, State of art techniques, Content-based image retrieval

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[2] Guo-Jun Qi, Charu Aggarwal, Qi Tian, Heng Ji, and Thomas S. Huang, ―Exploring Context and Content Links in Social Media: A Latent Space Method ‖ IEEE Transactions on Pattern analysis and machine intelligence, vol. 34, no. 5, May 2012
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N. Aarthi, "Multimedia Information Retrieval Using Content and Context Indexing", International Journal of Computer Sciences and Engineering, Vol.07, Issue.04, pp.107-111, 2019.

Multiple watermarks is to convey multiple sets of information designed to suit differing objectives and is used to increase robustness and security with many different methods in which the embedded information is not easily lost. DWT-SVD based successive and segmented watermarking technique is proposed using Artificial Bee Colony Algorithm (ABC). The understanding between the transparency and robustness is considered as an optimization problem and is removed by applying the ABC algorithm. This algorithm is used to obtain the highest possible robustness without losing the transparency. The successive and segmented of multiple watermarking techniques makes the watermarks much more robust to more attacks. The optimization on successive and segmented watermarking achieves more imperceptibility and robustness.

Successive and Segmented watermarking, Security, Artificial Bee Colony algorithm, Discrete Wavelet Transform, Singular value decomposition

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C. Ananth, M. Karthikeyan, "Successive and Segmented Watermarking Techniques Based on DWT-SVD and Artificial Bee Colony Algorithm", International Journal of Computer Sciences and Engineering, Vol.07, Issue.04, pp.112-118, 2019.

Wireless Ad-hoc Networks encompass variety of nodes that communicate with one another over a wireless channel that have numerous forms of networks, device networks, ad-hoc networks, and so on. The most drawback in these channels is expounded to security as a result of the secure communication, a very important side of any networking setting, is associate particularly vital challenge in spontaneous networks. A reliable system for such message exchanges is considered to be a particular strength for such organizations. Information security is a more general concern for officers of the armed forces and armed forces personnel is in constant pursuit of better procedures to ensure data protection and integrity. Privacy is needed in Ad-hoc networks. A secured on demand position based private routing algorithm is proposed for communication and which provides a security in Mobile Ad-hoc Network. This proposed is used for security to prevent message hacking information from internal & external attackers.

Wireless Network, Ad-hoc Network, secure message transmission, secure message communication

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M.P. Virgin Mary , "Emergency Data Transmission for Disaster Planning in MANETs", International Journal of Computer Sciences and Engineering, Vol.07, Issue.04, pp.119-125, 2019.

Bitcoin is so far is been the most versatile form of the cryptocurrency we came across in recent times, and the one which is widely accepted as well. Its values are varying like anything as we can see the frequent variation in the market value. We can say that this variation is dependent on various factors which a simple linear form of an equation or the method may fail to predict. In such a condition, it is very important that we apply a more efficient way of prediction. Several methods were employed having mathematical models which didn’t give out the expected results. Deep learning methods are widely known to solve such conditions, due to which the Recurrent Neural Networks come into the picture with its ability to learn the problem with the previous literature data. It can analyze the previous value and variations in the bitcoin pricing and using it as its base of knowledge, it can make the predictions more accurate. Even more by restructuring the activation function inside the Recurrent Neural Networks, its prediction accuracy can be further improved.

Activation Function, Bitcoin, Deep Learning,Prediction, Recurrent Neural Networks

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V. Adarsh, A. Martin, "A Study on Deep Learning Techniques to Improve Bitcoin Price Prediction", International Journal of Computer Sciences and Engineering, Vol.07, Issue.04, pp.126-129, 2019.

Image restoration is the operation of taking a corrupted/noisy image and estimating the clean original image. Corruption may come in many forms such as motion blur, noise and camera misfocus. Deconvolution is an example of image restoration method. The deconvolution tries to invert the blurring of an image that is modeled by the convolution g = f*h+n. Blind deconvolution tries to do this without knowledge of the point spread function h that blurred the image. In this paper, different methods for image restoration viz. Deterministic Filter, Bayesian Estimation and iterative distribution reweighting (IDR) are discussed in detail.

Bayesian estimation, blind image deconvolution, Maximum A Posteriori (MAP) estimation, L1-Regularization, Iterative Distribution Reweighting (IDR).

[1] Chao Wang, Lifeng Sun, Peng Cui, Zhang, Yang, “Analyzing Image Deblurring Through Three Paradigms”, IEEE Transactions on Image Processing, Vol 21 No.1,2012
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[6] Anat Levin,Yair Weiss,Fredo Durand & William T.Freeman , “Understanding Blind Deconvolution Algorithms”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 33 No.1,2011
[7] Leah Bar,Nir Sochen and Nahum Kiryati, “Semi Blind Restoration via Mumford-Shah Regularization”, IEEE Transactions on Image Processing, Vol 15 No.2,2006
[8] Jian Feng Cai,Hui Ji,Zuowei Shen, “Framelet Based Blind Motion Deblurring from a single image”, IEEE Transactions on Image Processing, Vol 21 No.1,2011
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[10] Laura B. Montefusco and Damiana Lazzaro, “An Iterative L1-Based Image Restoration Algorithm With an Adaptive Parameter Estimation”, IEEE Transactions on Image Processing, Vol 21 No.4,2012
[11] Wangmeng Zuo and Zhouchen Lin ,”A Generalized Accelerated Proximal Gradient Approach for Total-Variation-Based Image Restoration”, IEEE Transactions on Image Processing, Vol 20 No.10,2011

S. Santhi, "A Study on Image Restoration and Deconvolution Techniques", International Journal of Computer Sciences and Engineering, Vol.07, Issue.04, pp.130-133, 2019.

Super-resolution (SR) is a technique to enhance the resolution of an image without changing the camera resolution, through using software algorithms. In this context, this paper proposes a fully automatic SR algorithm, using a recent nonparametric Bayesian inference method based on numerical integration, known in the statistical literature as integrated nested Laplace approximation (INLA). By applying such inference method to the SR problem, this paper shows that all the equations needed to implement this technique can be written in closed form. Moreover, the results of several simulations show that the proposed algorithm performs better than other SR algorithms recently proposed.

Bayesian inference, Closed form, Integrated Nested Laplace Approximation (INLA), Nonparametric, Super-resolution (SR)

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M. Hemalatha, "Image Resolution Enhancement Using Bayesian Inla Approximation", International Journal of Computer Sciences and Engineering, Vol.07, Issue.04, pp.134-136, 2019.

A vast amount of text data is recorded in the forms of repair verbatim in railway maintenance sectors. Efficient text mining of such maintenance data plays an important role in detecting anomalies and improving fault diagnosis efficiency. However, unstructured verbatim, high-dimensional data, and imbalanced fault class distribution pose challenges for feature selections and fault diagnosis. We propose a bilevel feature extraction-based text mining that integrates features extracted at both syntax and semantic levels with the aim to improve the fault classification performance. We first perform an improved χ2 statistics-based feature selection at the syntax level to overcome the learning difficulty caused by an imbalanced data set. Then, we perform a prior latent Dirichlet allocation-based feature selection at the semantic level to reduce the data set into a low-dimensional topic space. Finally, we fuse fault features derived from both syntax and semantic levels via serial fusion. The proposed method uses fault features at different levels and enhances the precision of fault diagnosis for all fault classes, particularly minority ones. Its performance has been validated by using a railway maintenance data set collected from 2008 to 2014 by a railway corporation. It out performs traditional approaches.

Bilevel, Feature Selection, Feature Extraction, Railway, Text Mining

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D.Keerthanaa, C. Premila Rosy, "Bilevel Feature Extraction-Based Text Mining for Fault Diagnosis of Railway Systems", International Journal of Computer Sciences and Engineering, Vol.07, Issue.04, pp.137-139, 2019.

Informal communication has turned out to be a standout amongst the most mainstream specialized instruments to have advanced over the past decade, making it a ground-breaking new data sharing asset in the public eye. To date understanding the capability of Long range informal communication Sites (Social Networking Sites SNSs) past their relaxation utilizes has been extremely confined in various regions. This paper centers around the utilization of SNSs in a learning domain and the effect this could have on scholastic practices. While without a doubt, because of the exceptionally easygoing nature of person to person communication, there are not kidding worries over how it could be incorporated in a learning situation; the potential positive results are numerous and shifted. As a specialized device, its viability is now showing in the millions who use these systems to impart once a day. So it is possible that instructors ought to have the capacity to make a learnscape - a situation for formal and casual learning - that holds fast to instructive rules, yet additionally outfits the social emotionally supportive network of these on-line networks. This paper looks at the dangers included in the production of this new learning nature, and investigates the difficulties looked by both innovation specialists also, educators in conveying a genuinely inventive and successful new way to deal with instruction.

Web Platform, Social Learnig, Rich User Experiences

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S. Chitra, "Long Range Interpersonal Communication in Education", International Journal of Computer Sciences and Engineering, Vol.07, Issue.04, pp.140-150, 2019.

Internet of Things is a new pattern which provides a set of new services for the next form of technological development. IOT in the sense, it is a “universal global neural network” in the cloud which connects various things. The form of communication that is either human-device, or human-human but the Internet of Things (IoT) promises a great future for the internet where the type of communication is machine-machine (M2M). This paper aims to provide a future vision , IoT Architecture , Applications and its Challenges.

Vision, Challenges, Applications, Architecture

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V. Vinothini, C. Muthukumaran, "Key Exchange Technique in Cryptography Using Diffie-Hellman Algorithm", International Journal of Computer Sciences and Engineering, Vol.07, Issue.04, pp.151-152, 2019.

Cloud computing emerges as one of the hottest topic in field of information technology. Cloud computing is based on several other computing research areas such as HPC, virtualization, utility computing and grid computing. This topic discusses the grid and cloud computing in basics techniques. Typically, a grid works on various tasks within a network, but it is also capable of working on specialized applications. It is designed to solve problems that are too big for a supercomputer while maintaining the flexibility to process numerous smaller problems. Cloud computing is the delivery of computing services services–servers, storage, databases, networking, software, analytics, intelligence and more-over the Internet(“the cloud”) to offer faster innovation, flexible resources and economies of scale.

Bandwidth, Software as a Service, Wide area Network, deployment, Middleware

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S. Razool Begum, S. Suganya, "Comparison of Cloud Computing and Grid Computing: A Review", International Journal of Computer Sciences and Engineering, Vol.07, Issue.04, pp.153-156, 2019.