IJCTA-Volume 8 Issue 4 / July-August 2017
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BIG DATA Applications:A Technical Review
-Ankit Sarawagi,Rajeev Pandey,Raju Barskar
Big data are data sets which are beyond the power of storage and processing capacity. The huge quantity of information is generated from applications like social networks, Internet, sensors, Bio-informatics, Weather forecasting, etc. Processing of this much huge dataset using Traditional database systems is impractical. To process these data sets, two processing techniques Batch processing technique and non-batch processing technique are used. In Batch processing, huge data are gathered over a time-frame, processed and then produces output. Non-batch process involves continuous input of data and processed within a very little time-frame. With the presence of various documents, literatures and papers in the field of big data processing techniques, it was found difficult for the new scholars analyze the big data generated by various application areas with various processing techniques. In this paper, the suggestions of the most suitable and efficient processing techniques are given to process many types of datasets generated by various application areas, along with the challenges in processing and storing, and advantages of analyzing it. Finally, comparison table is made to suggest the efficient technique. Suggestions of more efficient techniques will help new scholars to opt better technique to handle big data generated by various applications and to give optimum results.
Keywords-Big Data, MapReduce, Apache Hadoop, Apache SPARK, Storm, S4.
A Survey on Sequence Alignment Based on Hadoop/MapReduce Big Data
-Prabhat Gupta,Rajeev Pandey,Anjna Deen
In Bioinformatics multiple sequence alignment (MSA) could be an essential step in a few bioinformatics examinations, and conjointly a NP-hard downside. To support the speed, precision and take into account the need of extensive scale arrangements arrangement, a wide Variety of MSA systems and programs are later created. We additionally consider future advancement of MSA techniques with connection to applying of all the more entirely unexpected advances and consequently the possibility of parallelization of MSA. All of those algorithms have demonstrated their potential to unravel several alignment issues. This paper provides AN in-depth survey of well-known sequence alignment algorithms and Hadoop map-reduce approach which is used to solve big data efficiently.
Keywords— Sequence Alignment, Multiple sequence Alignment, Big Data, Hadoop, Map-Reduce
IOT Enabled Immediate Response System for People in case of Road Accidents
-Vibhu Kapoor,Kopal Tripathi.Dr.Pradeep Kumar Singh
Every day, a large number of people die from accident injuries all over the globe. An effective approach to control the post accidents impact which may help in saving the life of the people by sending alert notifications to hospitals, police station and their relatives. Alert notification willhelp in getting the quick response in case of accident occurnce. Few systems are already in place as built in vehicle accident detection systems. However, these systems are very costly and lack in terms of availability. Whereas, to detect traffic accidents using smartphones is easily possible now because of the advances in connectivity and sensors deployed on the smartphones. The aim of this paper is to reduce the response time using Internet of Things(IOT) . The proposed system includes two phases; the detection phase and the notification phase. The detection phase detects car accident in all speeds. The notification phase is used to send detailed information such as the accident location to the hospital, police station and relatives of the person who met with an accident immediately after an accident is detected, for fast recovery. This paper includes two contributions; of using smartphone-based accident detection systems. First, it provides solutions to critical issues such as fake/false alerts by deploying onboard sensors todetect large accelerations. Second, it presents the system architecture of the prototype smartphonebased accident detection system.
Keywords-Internet of Things, Reponse Time, Sensors
A Survey on Differente Multiple Sequence Alignment and S.I Algorithm
-Renuka Devi,Aditya B,Abhinav Rajput
Multiple sequence alignment (MSA) could be a basic step in several bioinformatics analyses, and conjointly a NP-hard drawback. So as to boost the speed, accuracy and cater to the necessity of largescale sequences alignment, a wide variety of MSA strategies and software are afterwards developed. We also contemplate future development of MSA strategies with relation to applying of more totally different technologies and therefore the prospect of parallelization of MSA. Many swarm optimization algorithms are introduced since the first 60’s, biological process Programming to the foremost recent, gray Wolf optimization. All of those algorithms have demonstrated their potential to unravel several optimization issues. This paper provides AN in-depth survey of well-known optimization algorithms. Elect algorithms square measure shortly explained and compared with one another comprehensively through experiments conducted using thirty well-known benchmark functions. Their blessings and drawbacks also are discussed. Variety of applied mathematics tests square measure then dole out to work out the many performances. Keywords-Big Data, MapReduce, Apache Hadoop,Apache SPARK, Storm, S4.
Analysis of Scientific Paper Recommendation System Using Article Side Information
-Rachana R.Jadhav,Prof.N.R.Wankhade
Retrieving scientific article recommendation system plays important role for research in the field of academia. Most of the existing systems have designed integrated techniques for all target researchers therefore some of the algorithm generates recommendations for the researchers. In this paper we proposed different method to generate recommendation which is based on side information available in the papers such as citations and contents. The contents will be the abstracts of that paper. We use various similarity measurements like Euclidean Distance, cosine distance, Jaccard Coefficient, dice coefficient and SMTP for text processing distance measures calculating similarity between contents in the document. As a result we found that SMTP works better than other four similarity measures. We proposed a content based recommendation along with collaborative filtering which considers contents or unique words from the paper to recommendation purpose where top k recommendations were more closely similar to the target researcher’s document. We perform an experiment on real world dataset and compared results demonstrate that proposed system gives more accurate results than baseline system.
Keywords— Content based recommendation, SMTP, Unique words, text processing, Collaborative Filtering, Article Recommendation.
Millennium of Virtual Reality in e-Commerce: Proposed Virtual Environment and prototype
-Sakshi Taaresh Khanna
The research paper is aimed at examining the online shopping market from various angles as well as analysing and evaluating the effect of virtual reality on it. The paper begins with introducing various fundamentals of Virtual Reality to familiarize the reader with basic concepts and gradually explains the working of VR Systems. The paper also aims to focus on major developers in the VR industry and further to the myriad of applications that VR can have in various domains. The paper mainly aims at the application of VR in online shopping, its concepts and the current researches. This paper proposed the features of Virtual environment for virtual stores and prototype of a VR based online shopping system.
Keywords: Virtual Reality, Immersive experience, E-commerce
The Indian IT Act-2000 in context to addressing the needs of the Cyber Crimes in India
-Prashant Vats,Prof. (Dr.) Sanjay Singh
Rapid advancements in Information Technology sector have revolutionized work and personal lives of people globally. Technology has entered every sphere of life like banks, work place, social networking, stock markets, shopping etc. resulting in sharing of one’s personal information with every bit of machine one comes across. With the availability of personal information on a single click, the data is vulnerable to cyber-crime. In mid-90s liberalization of Indian economy resulted in manifold increase in e-transactions. Therefore, the need to bring technology under legislation was felt. With this objective in view, Parliament of India, passed the Information Technology Act in 2000. This paper describes IT Act 2000, and discusses important dimensions of amendments in 2008.Further, various notifications issued till date have also been discussed. An attempt has also been made to touch areas, left unaddressed in the foregoing legislations.
Keywords: IT Act 2000, Cyber Crime, IT Act Amendment 2008.
Cubic & Quartic Equation based Secure Authentication among Internet of Things with AES Encryption
-Dharminder Singh,Ambica Verma
The two major security paradigms for IOTs are authentication & encryption mechanisms, which have many variants. In this paper, the work has been carried over the enhancement of the proposed security model by designing the authentication model with set of algebraic equations. The multi-column based complex key generation is designed around the algebraic equations, specifically cubic and quartic equations. The authentication keys and data encryption is another security paradigm of the proposed model, which utilizes the advanced encryption standard (AES), which has been used for the implementation of the high security protocols. The performance of the proposed model has been analyzed under the different scenarios with variable number of nodes (50, 100 and 150) with decreasing transmission range of 75, 50 and 25 respectively. The proposed model has been recorded with minimum projected resource readings at 1.09, 5.49 and 10.96 percent in the scenarios with 50, 100 and 150 nodes respectively, whereas the maximum readings are 1.95, 9.81 and 19.63 percent for similar scenarios. The maximum value of entropy has been recorded at 2.98, 3.39 and 3.29 for proposed model against the 2.26, 2.53 and 2.39 existing model, which shows the robustness of the proposed security model for IOTs. The minimum values of entropy are recorded between 1.99 and 2.16 for proposed model against the existing range of 1.61 and 1.77 for the entropy, which again shows the similar trend to the latter analysis. Hence, it shows the clear improvement of proposed model against the existing model in all experiments.
Enhanced Text Recognition and Extraction Approach from Image Email
-Mallikka Rajalingam
Text extraction and text line detection is the foundation of document image analysis. Since many years, a large number of text detection methods have been proposed, where these methods depend on convinced assumptions of documents with various font style, font size, distorted text, uneven lighting, complex background and low resolution. In this paper, reveals k-nearest neighbor rule as a generic text-line detection and text extraction approach that can be applied on a complex mail document images. The performance evaluation of transition map generation and it compares with other two models is presented in this paper. Experimental analysis shows that image based text Optical Character Recognition (OCR) method is to extract the text from the colour image and detection of advertised mails is very efficient than that of the other existing methods.
Keywords- Text extraction, Text-line detection, Optical Character Recognition, KNN rule, and image mail document.
Face Sketch Recognition by Enhancing Evolutionary-Based Model
-Ali Salem Ali Bin Sama
Face sketch recognition models play a vital role for investigators in solving criminals. The task of these developed models is to perform matching between a drawn sketch image, and photo images at the database of law enforcement agencies. A forensic artist based on the description of an eyewitness draws the sketch image. However, one of the main challenges in problem of face sketch recognition is the variation between the drawn sketches and the original face photo. This work introduces an Evolutionary-Based Model (EBM) to tackle the problem of face sketch recognition. In particular, EBS is employed to perform two different operations, which are parameters tuning during the training phase, and localization of sketch facial components (e.g. face, eyes, nose, and mouth) at sketch recognition phase. To evaluate the effectiveness of the proposed model, a number of face sketch dataset images are used including CUHK, AR, and FERET. Experimental results show that the proposed method provides better identification performance compared to existing methods.
Keywords: Face Sketch Recognition, Evolutionary Algorithms, CUHK face sketch dataset, FERET sketches, AR sketches and HOG features.
Enhanced Feature Extraction Technique for Iris Template Generation
-Sarika B.Solanke,Ratnadeep R.Deshmukh
In the process of iris recognition localization and segmentation are the primary preprocessing step that locate the iris and segments it from the remaining part of the image. The normalization and feature extraction are very important and crucial stages which prepare the iris image to extract the required unique features and create the templates that can be compared to find the uniqueness among the two irises. Normalization allows transformation of iris region into a fixed size dimensions that can be compared. In short normalization produces constant dimension size images of every localized input iris image which are ready to further processing and comparison of such images is possible due to their nature of constant dimension size. In general the normalization process prepares the segmented image for feature extraction process. This paper discusses the enhanced normalization process based on Daugman’s rubber sheet model and feature extraction is based cumulative sum based change analysis. Iris features are extracted and the iris template is generated by horizontally and vertically grouping the iris texture features as iris codes.
Keywords : Iris Recognition ,Black hole search mehod, Camus & Wilde’s Method, Daugman’s Integro Differential operator, Rubber sheet model, Cumulative Sum Based Change Analysis
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