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Heart is the major organ comparing to other organs in the human body. It pumps the blood and supplies to all organs of the whole body. It is a significant work to predict the heart disease. Accurate and on time diagnosis of heart disease is important for heart failure prevention and treatment. Detecting heart disease is one of the major issue. Heart disease diagnosis is a very complex task which requires much experience and knowledge. Since heart is the most important part of human body, one should have healthy heart for their lifetime. Heart disease is a prevailing disease nowadays. The cost of diagnosis itself is very large and due to this many people who are not financially affordable step back from early diagnosis. Hospitals and clinic have a huge amount of patient data over years, and these data can be used for analysis of risk factors of many disease. Artificial neural network has emerged as an important tool for classification, they helps for efficient classification of given data. In this SMART HEART CONSULTING SYSTEM, we are proposing a prediction system for heart disease using artificial neural network. The proposed system is using 13 attributes and 80 datasets. Here in the system the user gives results of various clinical tests and the system provides the chances for heart disease.

ANN, Backpropagation algorithm, ECG

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Disease Prediction using Machine learning and data analytics approach”International journal
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Raechel Baby, Nisha Elsa Varghese, Anju S James, Athulya Chandran, Anna Liya Mathew, "Smart Heart Consulting System," International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.679-683, 2019.

The mobile ad hoc networks (MANETs) encompassed of a dynamic topology and open wireless medium may lead to MANET affected by several security liabilities. MANET could be set of restricted vary wireless nodes that perform in a cooperative manner thereby increasing the overall range of the network. The performance of ad hoc networks depends on the supportive and trust environment of the distributed nodes. To enhance security in ad hoc networks, it is important to evaluate the trustworthiness of alternative nodes without centralized authorities. In this paper, a study was made based on the trust models such as direct Trust, Indirect Trust and Analytic Network Process (ANP). These trust models are incorporated to reflect the trust relationship`s complexity and uncertainty. Based on the trust factors, the selection of the trusted nodes is obtained by using methods like direct Trust, Indirect Trust, and Analytic Network Process. ANP is used for making trust decisions which replace the traditional methods like direct Trust and Indirect Trust methods. Hence from the study, we analyzed that the selected nodes obtained by using the ANP decision theorem eliminate the malicious nodes and helps to protect the network from any internal attacks.

MANET, Trusted Node, Direct Trust, Indirect Trust, Analytic Network Process

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[17] Lubdha M. Bendale, Roshani. L. Jain, Gayatri D. Patil, "Study of Various Routing Protocols in Mobile Ad-Hoc Networks", International Journal of Scientific Research in Network Security and Communication, Vol.06, Issue.01, pp.1-5, 2018.
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G. Viswanathan, M. Jayakumar, "Finding Trusted Node in Mobile Ad-Hoc Network," International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.684-689, 2019.

In recent years cloud computing has achieved great development as it provides economic and convenient services. Cloud data services are an interesting and the latest way for storing enterprise data as more companies and users are uploading their data to cloud. The problem of data privacy and security needs to be addressed efficiently to fully utilize the power of cloud data services. Data security is a crucial aspect in cloud data storage and transmission. The use of data hiding methods for the security in data transmission and data storage would be very effective in securing cloud data. In this paper, we present a survey of data encryption methods, steganography methods and hybrid methods, that have been extensively applied in this context. However, majority of these methods suffer the overloads involved with encryption techniques and also have heavy computational time. A new method that specifically addresses security of cloud without the usage of encryption process is essential for reducing the overheads of encryption techniques, thereby improving the overall performance. At this juncture, data hiding techniques are considered to be more suitable and potential substitute over the encryption-based cloud data storage security techniques existing in the literature. We propose to build such data hiding techniques as future work.

Data Hiding, Cloud data security, Encryption Techniques, Data aggregation

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[15] Suneetha, D., and R. Kiran Kumar. "A Novel Algorithm for Enhancing the Data Storage Security in Cloud through Steganography". Advances in Computational Sciences and Technology,Vol. 10: 2737-2744, 2017
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A Mallareddy, R Sridevi, Ch G V N Prasad, "A Survey of Data Hiding methods for data security in Cloud," International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.690-694, 2019.

Extractive Single Document Summarization (SDS) is the task of summarizing a single document via extracting importance sentences verbatim and arranging them in a cohesive manner. It is different from Multi-Document Summarization (MDS) where multiple source documents are processed to generate a single summary. This paper proposes a two-stage mechanism to perform single document summarization via multi-document summarization technique. The approach involves the use of popular extractive summarization algorithms to generate summaries which are then further processed as multi-document summarization instance. The MDS approach used is based on word graph based sentence fusion followed by concept-based Integer Linear Programming (ILP) method for maximizing the coverage in sentence selection. The proposed system outperforms each of the single document summarizers by at least 2.6 percent point ROUGE scores, thereby indicating that performing single document summarization via multi-document summarization is a promising venue for further research in summarization.

Text Summarization, Single Document Summarization (SDS), Multi-Document Summarization (MDS), Extractive Summarization, Integer Linear Programming (ILP)

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Sandhya Singh, Kevin Patel, Krishnanjan Bhattacharjee, Hemant Darbari, Seema Verma, "Towards Better Single Document Summarization using Multi-Document Summarization Approach," International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.695-703, 2019.

Envisioning a new imaginative idea together is a popular human need. Imagining together as a team can often lead to breakthrough ideas, but the collaboration effort can also be challenging, especially when the team members are separated by time & space. What if there is a AI that can assist the team to collaboratively envision new ideas?. Is it possible to develop a working model of such an AI? The contribution of this paper is to develop such an intelligence. This paper proposes a formula to design such a creative & collaborative intelligence by employing a form of distributed machine learning approach called Federated Learning along with Generative Adversarial Network (GAN) fusion. This paper demonstrates this novel deep learning architectural paradigm by developing a practical working prototype. The outputs of the prototype of this novel AI paradigm in showcased in this paper. This collaborative creative AI presents a new paradigm in AI, one that lets a team of two or more to come together to imagine and envision ideas that is mutual liked by all team members as well one that synergies well with each other’s likes. This was possible by a completely new way to combine federated learning with an interesting new way to combine multiple GAN together. In short, this paper contributes a novel type of AI paradigm, called Federated AI Imagination one that lets geographically distributed teams to collaboratively imagine new possibilities.

Artificial Intelligence, Distributed Machine Leaning, Generative Deep Learning, Generative Adversarial Networks, Federated learning, Creative AI, AI based Collaboration, AI planning

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[6] Hard at el., “Federated learning for mobile keyboard prediction”, arXiv:1811.03604 , 2018.
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Rajagopal. A, Nirmala. V, "Federated AI lets a team imagine together: Federated Learning of GANs," International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.704-709, 2019.

The usages of internet and increasing volume of internet users force us to think about the current cyber security and its infrastructure. There are a number of different kinds of attack deployed using the internet among the phishing is one of the most serious attack conditions. In this condition an innocent user can lose their financial status or social credibility. The phishing attacker still the users private, sensitive and confidential information, additionally usages these data to harm the target person. Therefore it is a serious criminal offence. In this context a number of techniques are developed for resolving the issues of phishing attacks, but most of them are not much effective due to changing strategies of the phishing attackers. The phishing attacks are mostly deployed using the malicious and forged URLs. Thus the pattern recognition of these URLs can help us to resolve the phishing attacks. In this presented work a data mining based phishing URL classification technique is proposed for design and implementation. The proposed technique usages the phish tank database for obtaining the knowledge about the phishing URL properties and then using these properties the data mining system prepare the rules for identifying the target phishing URLs. In this context the ARM algorithm is employed. The Arm algorithm first prepares the association rules using the apriori algorithm. After generation of association rules the confidence based score are used to label each rule to a score values. Finally on the basis of score threshold the unfruitful rules are pruned. The remaining rules are used for classification task. The proposed technique is implemented and their performance is measured, according to the gained performance the proposed technique is accurate and efficient as compared to the traditional apriori algorithm based classification technique.

phishing attack, malicious URL classification, association rule mining, rule based classification, ARM algorithm, outlier removal

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Rahul Patel, Anand Rajavat, "Phishing URL Classification Using ARM Based Association Rules," International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.710-717, 2019.

The text presented in videos contains important information for content analysis, indexing, and retrieval of videos. The key technique for extracting this information is to find, verify, and recognize video text in various languages and fonts against complex backgrounds. In this paper, we propose a novel method that transferred deep convolutional neural networks for detecting and recognizing video text. We partition the candidate text regions into candidate text lines by projection analysis using two alternative methods. We develop a novel fuzzy c-means clustering-based separation algorithm to obtain a clean text layer from complex backgrounds so that the text is correctly recognized by commercial optical character recognition software. The proposed method is robust and has good performance on video text detection and recognition, which was evaluated on three publicly available test data sets and on the high-resolution test data set we constructed.

Video Text Detection, Recognition, Transferred convolutional neural network, Fuzzy c-means Clustering.

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Namrata Choudhary, Kirti Jain, "Video Text Detection and Recognition Based on a Transferred Deep Convolutional Neural Network," International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.718-723, 2019.

This paper attempts to analyze the current use of social networks and their promising advantages for electronic governance in governmental organizations. Discuss potential problems, especially issues related to the security and privacy of people, Employees, infrastructure and data that prevent the successful implementation of social networks for electronic governance. Examine India`s governance framework project to integrate social media into the organizational structure and examine those issued guidelines for the platform to be used, authorization to participate on behalf of the government organization, scope and extent of said commitment, etc. Compare these guidelines with similar patterns from other nations in terms of access, account management, acceptable use, employee conduct, content, security, legal issues and citizen behavior list its merits, demerits and scope for future improvements.

e-Governance; Social Media; Social Media Policy; Social Media Framework

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M. I. Sandhi, D. Hiran, N. I. Modi, "Use of Social Media in e-Governance: A Study Towards Special Reference to India," International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.724-733, 2019.

From data extraction to movie recommendation, spam filtrating to bank fraud detection and object detection to self-driving cars these are all being possible due to the term Deep Learning. This term is being a buzz word in the tech industry. Deep Learning is based on Machine Learning and Artificial Intelligent models, which helps in building the model more efficiently and access the data accurately. The buzz word is always seeming to be in news, many types of research and inventions are going on. People are not aware of the term Deep Learning. This technique takes decisions so preciously to make our day to day life so easy and efficient. In this research paper, we will elaborate the term Deep Learning, what it is, what is going on at the backend, how it works, what are its potential, how it helping the people’s life to industry world and what is the application of it.

Deep Learning, Neural Network, A.I, Machine Learning, chatbot, LSTM, CNN, RNN

[1] J K Gupta and S Agarwal ― An Epitome of Chatbot: A Review Paper Vol.-7, Issue-1, Jan 2019
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[4] Greg Surma ―Leveraging Convolutional Neural Networks (CNNs) and Google Colab’s Free GPU Nov 19, 2018
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Jeetu Kumar Gupta, Sohit Agarwal, "Automated Query handling system based on Deep Learning Technique," International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.734-738, 2019.

in this paper, watermark is to hide information in cover image. This paper represents a reliable digital image watermarking. It provides high imperceptibility and robustness for copyright protection. In this proposed method, combination of Discrete Wavelet Transform, Singular Value Decomposition, and Discrete Cosine Transform are used for robust watermarking. A multi-channel image watermarking technique is used in this work. It means multiple watermarks are embedded. In this method, initially first level of three watermark images are embedded in the second RGB watermark image and then this second level RGB image watermark is embedded in the RGB cover image to obtain the watermarked image. This process increases the robustness of watermark. An embedded watermark is retrieved by using reverse process of embedding. The second level of watermark is retrieved and then first levels of watermarks are retrieved. Experimental results show that, as compared to existing method, it shows that proposed multi-channel watermarking method is highly robust against attacks. The experiment result having high Peak Signal to Noise Ratio after different types of attacks. Bit Error Rate and normalized Cross-Correlation shows fidelity of retrieved watermark is very good.

Embedding process, extraction process, Peak signal to noise ratio, normalized cross correlation and Bit Error Rate.

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[2]. Nazir A. Loani, Nasir N. Hurrah, Shabir A. Parah, Jong Weon Lee, Javid A. Sheikh and G. Mohiuddun Bhat “Secure and Robust Digital Image Watermarking Using Coefficient Differencing and Chaotic Encryption” IEEE access, vol. 6, pp.19876-19897, 2018.
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Foram R. Suratwala, S. G. Kejgir, "A Robust Multi-Channel Digital Image Watermarking Technique with SVD, DWT, DCT," International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.739-751, 2019.