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Happiness travels quickly in comparison to sadness or disgust, but proliferation of anger and fear surpasses them all. This defines the bottom-line of information virality on social media. Pertinent psychological studies convey that human emotions may be ‘activated’ or ‘deactivated’ to drive people to take action. Based on this, we propose the use of cognitive behavioural features to assess the virality of information in tweets by finding a dominant emotion of same type across tweets as an indicator of viral spread. Fluctuations in emotions convey uncertainty and may reduce the frequency and intensity of discussion of a trending topic. The proposed virality prediction framework detects the emotion quotient (EQ), a measure of emotional intensity associated with five emotions, namely, fear, disgust, sadness, anger, and happiness for the exposed information in tweets to predict its outburst, i.e., virality, pertaining to social and political issues. The hybrid (lexicon + supervised learning) approach using parts-of-speech (adjectives, adverbs, verbs, emoticons) is proffered to transform the tweet into an emotional vector representative of the sentimental value for a trending topic. This emotional quantifier is then used as an empirical evidence to determine the likelihood of information going viral based on the strength of emotion in tweets and its no. of re-tweets. Preliminary results clearly demonstrate the effectiveness of the approach which affirms information virality.

Viral, Twitter, Emotion

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A. Kumar, S.R. Sangwan, "Information Virality Prediction using Emotion Quotient of Tweets," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.642-651, 2018.

The invention of Internet has made the day-to-day life easy and less complicated. The proposed system is called Interactive clothes that make use of QR code and IoT. A QR code is embedded within the clothes that consist of a unique Id. A mobile application is developed that scans the QR code present in the cloth and gets linked to a database stored in a cloud database. It provides a digital environment for both the manufacturers and the end users. From manufacturing perspective, the system has the ability to identify fake brands, keep track of the loyal customers, and minimize the resources waste and keeping track of the goods using a single relational database system. For end users, the benefits are huge. The mobile application(Personal Stylist) provides a simple user interface where users could get suggestions regarding their clothes with other outfits, dressing according to the season and deciding whether the color suits their skin tone or not.

Cloud database, IoT, Mobile application, QRcode, Relational database system

[1] Xiao-song Hu, Li-ling Jiang , Rui Cheng , Tie-jun Wang , Qing Li, “A probabilistic clothes recommender based on cloth features”, School of Economic Information Engineering, Southwestern University of Finance and Economics, Chengdu 611130, China, August 2014.
[2] Poorva Parkhi, Snehal Thakur, Sonakshi Chauhan, “RFID based parking management system”, Department of Computer Engineering, Sinhgad Academy of Engineering, Pune, India, February 2014.
[3] Jia Ning Luo, Ming-Hour Yang , Ming Chein Yang, “An anonymous car rental system based on NFC”.
[4] Weibing Chen, Gaobo Yang, and Ganglin Zhang, “A Simple and Efficient Image Pre-processing for QR Decoder” Dept.of Electrics Communication Engineering, Changsha University, Changsha Hunan.
[5] Teuta Cata, Payal S. Patel and Toru Sakaguchi “QR Code: A New Opportunity for Effective Mobile Marketing” Northern Kentucky University, Highland Heights, KY 41099, USA.
[6] Lefayet, Sultan, Lipol “Quick Response in the Textile Industries” International Journal of Scientific and Research Publications, Volume 5.
[7] Deepthi, Pradyumna G.R “Comparison of MD5 and Blowfish Algorithm” NMAM Institute of Technology, Nitte, Udupi, Karnataka, India.

Prasad Mutkule, Malakappa Ankoshe, "A Survey on Interactive Clothing Based on IoT using QR code and Mobile Application," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.652-654, 2018.

In recent era, websites are the ultimate media for getting information, advertisement of organizations, shopping, entertainment, education, as well as social contacts. But a website must possess a high quality to provide success to organizers as well as to satisfy the users. The academicians proposed a lot of website evaluation models which has been designed by taking a variety of approaches and methods. To evaluate the website, one needs knowledge about the diversity in website evaluation approaches and methods to be followed. This paper highlights the ethics involved in the application of prominent website evaluation methods by conducting an in-depth study of reputed research papers from large databases such as IEEE, Springer, ACM and Taylor & Francis publications. Website methods have been classified on the basis of actors involved in the evaluation. Analysis of the usage of these methods in previous website evaluation studies has been accomplished which concludes that the majority of evaluation studies relied upon user based evaluation methods. It is recommended that there should be more orientation towards the automated evaluation methods as it is free from human biasing and can be exercised when the website just completed the design phase to predict the quality of the website. Due to summarization of major website evaluation methods, the paper has massive value for academicians as well as industry readership in the discipline of website evaluation.

Website evaluation, Evaluation methods, Website quality, Website assessment

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S. Kaur, S.K. Gupta, "Analyzing the usage of website evaluation methods – an actor based approach," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.655-669, 2018.

Cloud is the Internet based computing that provides resources on-demand. This has become an attractive solution to data owners as the can outsource data and computing. There is potential risk in terms of security and privacy of the outsourced data as the cloud servers are treated untrusted. In this context, there are two security mechanisms that are widely used. They are known as cryptography and steganography. The cryptography converts data into some format that cannot be comprehended by humans while the steganography hides the presence of a message (may be encrypted one) in an image or any digital media. If both are used independently they have their own limitations. When both are combined, it forms a realizable mechanism with both security and secrecy. Thus, the Crypto-steganography is the approach that overcomes the limitations of individual mechanisms as it proves to be difficult to adversaries to launch attacks. In this paper an LSB substitution method and quadruple efficient image encryption method are used to secure sensitive messages when they are outsourced to public cloud. We built a prototype application to show the utility of the proposed hybrid method. The results revealed that the proposed is capable of increasing security to the data outsourced to public cloud.

Cloud computing, cryptography, steganography, crypto-steganography

[1] M.Y. Wu, M.C. Yu, J.S. Leu, and S.K. Chen, "Improving security and privacy of images on cloud storage by histogram shifting and secret sharing," Proceedings of the 83th IEEE Vehicular Technology Conference, Nanjing China, pp. 1-5, May 2016.
[2] H. Reza, and M. Sonawane, "Enhancing mobile cloud computing security using steganography," Journal of Information Security, Vol. 7, No. 4, pp. 245-259, July 2016.
[3] J. Stone, "Reddit Fappening ban triggers outraged response from nude photo distributor," International Business Times, September 2014. (http://www.ibtimes.com/reddit-fappening-ban-triggers-outragedresponse-nude-photo-distributor-1681708)
[4] T. Gopalakrishnan, and S. Ramakrishnan, "Image encryption in blockwise with multiple chaotic maps for permutation and diffusion," ICTAT Journal on Image and Video Processing, Vol. 6, No. 3, pp. 1220-1227, February 2016.
[5] S.S. Dharwadkar, and R.M. Jogdand, "A user identity management protocol using efficient dynamic credentials," International Journal of Scientific Engineering and Research, Vol. 2, pp. 42-47, June 2014.
[6] M.G. Charate, and S.R. Bhosale, "Cloud computing security using Shamir’s secret sharing algorithm from single cloud to multi cloud," International Journal of Advanced Technology in Engineering and Science, Vol. 3, pp. 349-357, April 2015.
[7] K.S. Seethalakshmi, Usha. B, Sangeetha. K. N, “Security Enhancement in Image Steganography Using Neural Networks and Visual Cryptography”, IEEE Int. Conf.Computation System and Information Technology for Sustainable Solutions (CSITSS), 2016.
[8] SadafBukhari, Muhammad ShoaibArif, M.R. Anjum, and SamiaDilbar, “Enhancing security of images by Steganography and Cryptography techniques”, IEEE Int. Conf. Innovative Computing Technology (INTECH), 2016.
[9] Ria Das, Indrajit Das, “Secure Data Transfer in IoT environment: adopting both Cryptography and Steganography techniques”, IEEE Int. Conf. on Research in Computational Intelligence and Communication Networks (ICRCICN), 2016.
[10] AnkitGambhir and SibaramKhara, “Integrating RSA Cryptography & Audio Steganography”, IEEE ICCCA, 2016.
[11] Kamaldeep Joshi, RajkumarYadav, “A New LSB-S Image Steganography Method Blend with Cryptography for Secret Communication”, IEEE ICIIP, 2015.
[12] Vipul Shanna and Madhusudan “Two New Approaches for Image Steganography Using Cryptography” IEEE Int. Conf. Image Information Processing, 2015.
[13] MoreshMukhedkar, PrajktaPowar and Peter Gaikwad, “Secure non real time image encryption algorithm development using cryptography & Steganography”, IEEE INDICON, 2015.
[14] RiniIndrayani, HanungAdiNugroho, RisanuriHidayat, IrfanPratama, “Increasing the Security of MP3 Steganography Using AES Encryption and MD5 Hash Function”, International Conference on Science and Technology-Computer (ICST), IEEE, 2016.
[15] Nikhil Patel, ShwetaMeena, “LSB Based Image Steganography Using Dynamic Key Cryptography”, International Conference on Emerging Trends in Communication Technologies (ETCT), 2016.
[16] Dan Gonzales, Jeremy M. Kaplan, Evan Saltzman, Zev Winkelman, And Dulani Woods, “Triple Security Of File System For Cloud Computing,” Ieee Transactions On Cloud Computing. 5 (3), P1-14, 2017.
[17] Mark Stieninger, Dietmar Nedbal, Werner Wetzlinger, Gerold Wagner And Michael A. Erskine, “Factors Influencing The Organizational Adoption Of Cloud Computing: A Survey Among Cloud Workers,” International Journal Of Information Systems And Project Management. 6 (1), P1-19, 2018.
[18] G. Preethi And N.P.Gopalan, “Data Embedding Into Image Encryption Using The Symmetric Key For Rdh In Cloud Storage,” International Journal Of Applied Engineering Research. 13, P3861-3866, 2018.
[19] C. Kaleeswari, P. Maheswari, Dr. K. Kuppusamy, Dr. Mahalakshmi Jeyabalu, “A Brief Review On Cloud Security Scenarios,” Ijsrst. 4 (5), P1-6, 2018.
[20] Zheng Yan,Robert H. Deng And Vijay Varadharajan, “Cryptography And Data Security In Cloud Computing,” Ieee, P1-5, 2017.
[21]Swapnil Rajesh Telrandhe And Deepak Kapgate, “Authentication Model On Cloud Computing,” International Journal Of Computer Sciences And Engineering. 2 (10), P1-5, 2014.
[22] Richa Arya, “Triple Security Of File System For Cloud Computing,” International Journal Of Computer Science And Engineering. 2 (3), P1-7, 2014.

Konakanti. Bhargavi, Thota. Bhaskara Reddy, "A Hybrid Multi-Stage Methodology for Secure Outsourcing of Confidential Data to Public Cloud," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.670-681, 2018.

Cross layer based approaches has given new dimensions to MANET (Mobile Adhoc Network) by releasing fixed layer boundary constraints. These new paradigm makes it possible to limit the issues such as low battery, limited bandwidth, link breakage of MANET. Still cross layer based designs are trying to remove such barriers and trying to make Manet more scalable. Though cross layer based designs are flexible but securing the network from malicious attack is definitely challenging task. This paper is an attempt to discuss about technique to optimize the performance of secure cross layer routing protocol. We have designed SCLPC (Secure cross layer based Power control) protocol. But when security is imposed using AASR (Authenticated and anonymous secure routing), the network metrics as end to end delay and routing overhead is disturbed. To optimize the network performance here we proposed OSCLPC (Optimized secure cross layer based power control protocol). The proposed OSCLPC has been evaluated using SHORT (Self healing and optimizing route technique). We also examined the OSCLPC with malicious code. The OSCLPC and M-OSCLPC (malicious OSCLPC) is simulated in ns2 and we also compared it with reactive routing protocol AODV.

Cross layer designs, CLPC, AODV

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Amit A. Bhusari,P.M. Jawandhiya, V.M.Thakare, "Performance Analysis of an Optimized and Secure Routing Protocol with impact of malicious behavior utilizing Cross Layer Design for Mobile Adhoc Networks," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.682-687, 2018.

The data mining is the technique to analyze the complex data. The prediction analysis is the technique which is applied to predict the data according to the input dataset. In the recent times, various techniques have been applied for the prediction analysis. In this paper, k-mean and SVM classifier based prediction analysis technique is improved to increase accuracy and execution time. In the prediction analysis based technique, k-mean clustering algorithm is used to categorize the data and SVM classifier is applied to classify the data. The back propagation algorithm has been applied with the k-mean clustering algorithm to increase accuracy of prediction analysis. The proposed algorithm is implemented in MATLAB and it is been tested that accuracy of clustering is increased, execution times is reduced for prediction analysis .

K-mean, SVM, Prediction, categorization, Classification

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[12] Marjia Sultana, Afrin Haider and Mohammad Shorif Uddin,” Analysis of Data Mining Techniques for Heart Disease Prediction”, 2016, IEEE
[13] Kamaljit Kaur and Kuljit Kaur,” Analyzing the Effect of Difficulty Level of a Course on Students Performance Prediction using Data Mining”, 2015 1st International Conference on Next Generation Computing Technologies (NGCT)

Bhupendra Kumar Jain, Manish Tiwari, "Prediction Analysis Technique based on Clustering and Classification," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.688-692, 2018.

Indian roads carry almost 90 per cent of the country’s passenger traffic and around 65 per cent of its freight. In India sales of automobiles and movement of freight by roads is growing at a rapid rate along with the increasing rate of traffic. Geo-spatial temporal data with geographical information explodes as the development of GPS-devices using mobiles. To dig out the video patterns behind the video data efficiently in huge spatial temporal data, using an OPTICS algorithm on gpsdata from the traffic video footage introduced. Through above cluster types provides number of cluster groups with identifying the video information from the existing archives video footages. This work deals with the clustering of the video data from the large geospatial temporal traffic videos using TRAFFICOPTICS algorithm organizing archives through information. In-order to identify the vehicles from the video footages in large traffic network that to identify the congestion through the spatiotemporal data mining method.

GPS, GEO, OPTICS, SPATIAL, GEO-SPATIAL, spatiotemporal, clustering

[1]. K.P. Agrawal, Sanjay Garg, Shashikant Sharma, and Pinkal Patel, “Development and validation of OPTICS based spatio-temporal clustering technique”, Inf. Sci. 369, C (November 2016), pp.388-401, 2016.
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[6]. Shashi Shekhar, Zhe Jiang, Reem Y. Ali, Emre Eftelioglu, Xun Tang, Venkata M. V. Gunturi and Xun Zhou , “Spatiotemporal Data Mining: A Computational Perspective”, ISPRS International Journal of Geo-Information 2015, 4, 2306-2338, 2015.
[7]. Tanvi Jindal, Prasanna Giridhar, Lu-An Tang, Jun Li, Jiawei Han, “Spatiotemporal Periodical Pattern Mining in Traffic Data”, UrbComp’13, Chicago, Illinois, USA, August 11–14, 2013.
[8]. Khamphao Sisaat, Hiroshi Ishii, Masato Terada, Chaxiong Yukonhiatou, Hiroaki Kikuchi, Surin Kittitornkun , “A Spatio-Temporal malware and country clustering algorithm: 2012 IIJ MITF case study”, International Journal of Information Security, Volume 16 Issue 5, Pages 459-473, October 2017.
[9]. Liu, C., Gong, Y., Laflamme, S., Phares, B., & Sarkar, S., “Bridge damage detection using spatiotemporal patterns extracted from dense sensor network”, Measurement Science and Technology, 28(1), 014011, 2017.
[10]. Wu, L., Liu, C., Huang, T., Sharma, A., & Sarkar, S., “Traffic sensor health monitoring using spatiotemporal graphical modelling” Proceedings of the 2nd ACM SIGKDD Workshop on Machine Learning for
Prognostics and Health Management, August 13-17, Halifax, Nova Scotia, Canada, 2017.
[11]. Jiang, Z., Liu, C., Akintayo, A., Henze, G., & Sarkar, S.,” Energy prediction using spatiotemporal pattern networks” Applied Energy, 206, 1022-1039, 2017.
[12]. Xiaojing Wu, Raul Zurita-Millab, Menno-Jan Kraakb, Emma Izquierdo-Verdiguier, “CLUSTERING-BASED APPROACHES TO THE EXPLORATION OF SPATIO-TEMPORAL DATA”, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-2/W7, 2017
ISPRS Geospatial Week 2017, 18–22 September 2017, Wuhan, China, 1387-1391.
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[14]. Nada Lavra, Domen Jesenovec, Nejc Trdin, and Neža Mramor Kosta,“Mining Spatio-temporal Data of TrafficAccidents and Spatial Pattern Visualization “, Metodološki zvezki, Vol. 5, No. 1, pp. 45-63, 2008.
[15]. Pawan S. Wasnik, S.D.Khamitkar, Parag Bhalchandra, S. N. Lokhande, Ajit S. Adte, “An Observation of Different Algorithmic Technique of Association Rule and Clustering”, International Journal of Scientific Research in Computer Science and Engineering, Vol.06, Issue.01, pp.28-30, 2018.
[16]. S. Kshirsagar, M. Jadhav, C. Bhagwat, “Real Time Road Inspection System with Distance Intimation Technique”, International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.1, pp.16-19, 2017.

Srikanth Lakumarapu, Rashmi Agarwal, "Cramming Identification through Spatiotemporal Data," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.693-701, 2018.

Nowadays, most of the researchers are focusing and inspiring the healthcare and medical industries. Because, globally humans are affected by various diseases. Especially, the heart diseases are major defect for humans, which is unpredictable and it may happen any moment in the human life. The Machine Learning (ML) algorithms and Big Data technologies are providing the complete and effective solutions for the healthcare and medical industries to predict and diagnosis the various diseases. Moreover, it helps to protect the human life by the accurate prediction results in real-time. Purpose of this paper, to predict the heart diseases automatically by segmenting and classifying the patient`s heart data in real-time with the help of machine learning algorithms, big data, wireless heart monitor and smart phones. Finally, this research helps to predict, visualize and monitor the patient`s data in remotely and alerting to the heart specialists and health care professionals to save the patient`s life.

machine learning, big data, predicting heart diseases, visualizing heart diseases

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R. Kannan, V. Vasanthi, "Predicting and Visualizing the Heart Diseases by Machine Learning Algorithms with Big Data," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.702-706, 2018.

With the emergence of distributed programming frameworks like Hadoop and cloud computing technology, big data and its analytics became a reality. As big data needs huge amount of storage and computing resources, cloud has given solution to the needs of big data. However, it is important to protect big data from privacy attacks. Disclosure of identity of an entity or organization or a person in the big data is an example for loss of privacy. In other words, non-disclosure of privacy of certain sensitive attributes is nothing but preserving privacy of big data. As traditional computing is replaced by Internet based computing, it became essential to deal with privacy of big data. Many techniques came into existence to protect big data. In this paper, we considered a specific case where an adversary launches attack to know the presence or absence of an entity in the big data. We proposed an algorithm based on differential privacy to withstand the aforementioned privacy attack on big data workload in MapReduce programming paradigm. We built a prototype application and deployed it in Elastic MapReduce (EMR) of Amazon Elastic Compute Cloud (EC2). The experimental results revealed the utility of the proposed algorithm and showed proof of the concept.

Big data, big data privacy, differential privacy, Elastic MapReduce (EMR)

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[16] Lizhe Wanga, Jie Taoc, Rajiv Ranjan D, Holger Martenc, Achim Streit C, Jingying Chene And Dan Chena, “G-Hadoop: Mapreduce Across Distributed Data Centres For Data-Intensive Computing”, Ieee, P1-14, 2013.
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Y. Sowmya, M. NagaRatna, C. Shoba Bindhu, "Differential Privacy Based Solution for Protecting Privacy of Big Data," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.707-713, 2018.

Fixed point algorithm is a powerful method to determine more accurate solutions to dynamical systems and widely used in analysis, algebra, geometry, and logic which is available all over the world anywhere and anytime. Convergence of fixed point iteration plays vital role in the solution of problems. This paper introduces about fixed point algorithm and fixed point iteration with it applications. We studied some fixed point iteration methods which can be used in parallel systems. We assumed that each problem of parallel systems can be expressed or solved using the fixed point algorithm. For generating the parallel grid of processor four iterative algorithms or methods can be used.

Fixed-Point, Fixed-Point Algorithm, Fixed-Point Iteration, Chain Point, Attractive Fixed-point.

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Surya Prakash Pandey, Rakesh Kumar Katare, "Application of Fixed-Point Algorithm in Parallel Systems," International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.714-719, 2018.