Journal of Artificial Intelligence vol 3 issue 3 by STM Journals

ISSN 2395-6720 (Online)

Journal of

Artificial Intelligence Research & Advances (JoAIRA) Septemberâ&#x20AC;&#x201C;December 2016

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Journal of Artificial Intelligence Research & Advances ISSN: 2395-6720 (online)

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It is my privilege to present the print version of the [Volume 3 Issue 3] of our Journal of Artificial Intelligence Research & Advances, 2016. The intension of JoAIRA is to create an atmosphere that stimulates vision, research and growth in the area of Artifecial Intelligence. Timely publication, honest communication, comprehensive editing and trust with authors and readers have been the hallmark of our journals. STM Journals provide a platform for scholarly research articles to be published in journals of international standards. STM journals strive to publish quality paper in record time, making it a leader in service and business offerings. The aim and scope of STM Journals is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high level learning, teaching and research in all the Scientific, Technical and Medical domains. Finally, I express my sincere gratitude to our Editorial/ Reviewer board, Authors and publication team for their continued support and invaluable contributions and suggestions in the form of authoring writeups/reviewing and providing constructive comments for the advancement of the journals. With regards to their due continuous support and co-operation, we have been able to publish quality Research/Reviews findings for our customers base. I hope you will enjoy reading this issue and we welcome your feedback on any aspect of the Journal.

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Journal of Artificial Intelligence Research & Advances

Contents

1. An Introduction on Virtual Reality and Its Challenges Jagannath Dixit, Shailendra Kumar, Prashant Mishra, V.S. Chandel

2. Goggle Mouse Afjal Ahmad, Anas Ahmad Khan, Qazi Ahmad Saeed

3. Social Media Blog Analysis using Watson Analytics Sindhu B. Jigali, Nirmala C.R.

4. Tweet Segmentation for Named Entity Recognition Krushnadeo Tanaji Belerao

5. Analysis of Image Coders Shefa Hasnain, Sadiya Bakhshi, Shazia Asif, Monauwer Alam

Journal of Artificial Intelligence Research & Advances ISSN: 2395-6720(online) Volume 3, Issue 3 www.stmjournals.com

An Introduction on Virtual Reality and Its Challenges Jagannath Dixit1, Shailendra Kumar2,*, Prashant Mishra3, V.S. Chandel4 1

Department of Mathematics, Integral University, Lucknow, Uttar Pradesh, India Department of Electronics and Communication Engineering, Integral University, Lucknow, Uttar Pradesh, India 3 Department of Physics, Bappa Sri Narain Vocational P.G. College, Lucknow, Uttar Pradesh, India 4 Department of Physics, Integral University, Lucknow, Uttar Pradesh, India 2

Abstract In the last few years virtual reality has become most popular than other technologies. In this paper, a short introduction of virtual reality, basic terminology, present and future of virtual reality and application of this technology in daily life are mentioned. Virtual reality makes users feel in a virtual environment (VE) by using computer hardware and software. Sometimes, virtual reality (VR) is also called virtual environment (VE). Keywords: Virtual reality, Sensorama, HMD, VCASS, BOOM, VR

INTRODUCTION The definition of virtual reality has come from ‘virtual’ and ‘reality’. The definition of ‘virtual’ is near and ‘reality’ is what we experience as human being. So, the term ‘virtual reality’ basically means ‘near reality’ [1]. In other words, virtual reality (VR) is the fantasy of a three-dimensional communication, PC produced reality, where sight, sound, and some of the time even touch are reproduced to make pictures, sounds, and protests that really appear to be genuine. Virtual reality has become enormous in the course of recent years; however, 2016 resembles the most essential year. Virtual reality (VR) is the utilization of personal computer innovation to make a recreated domain. Not at all like customary UIs, has virtual reality put the client inside an ordeal. Instead of viewing a screen in front of them, users are immersed and able to interact with three-dimension world. We know the five senses: smell, touch, taste, sight and hearing. These are however just our most clear sense organs. In all actuality, people have numerous or larger numbers of faculties than this, for example, a feeling of adjust for instance. Virtual reality involves giving our faculties a personal computer produced virtual

environment that we can investigate in some fashion. In specialized terms, virtual truth is the term used to depict a three-dimensional, personal computer created environment, which can be investigated and connected with by a man. That individual turns out to be a piece of this virtual world or is immersed within this environment and whilst there, is able to manipulate or perform a series of actions. In present time, virtual reality gives many opportunities to researcher and student to find something new. Virtual reality is a better user interface. In virtual world, most important input device used is trackers. Trackers are tracking three-dimensional positions. We can divide virtual reality into three groups according to the degree of immersion interactivity. These three groups are: immersive system, non-immersive system and hybrid virtual reality system. Immersive systems change our view of the real world with the PC produced pictures that connect to the position and introduction of the client's head. A non-immersive system leaves the users visually aware of the real world but is able to observe the virtual world through

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Journal of Artificial Intelligence Research & Advances ISSN: 2395-6720(online) Volume 3, Issue 3 www.stmjournals.com

Goggle Mouse Afjal Ahmad, Anas Ahmad Khan, Qazi Ahmad Saeed* Department of Electronics and Communications, Integral University, Lucknow, India

Abstract The essential thought of the undertaking is to fabricate Goggle by utilizing human machine interface which can be utilized to control mouse by utilizing head-tilt and eye-flicker. This mouse-copying gadget can be observed to be most helpful by physically debilitated and incapacitated persons who can no longer control the PCs by utilizing their hands. Since the gadget depends on person's head and eye movements, it can be utilized even by patients who are incapacitated from below the shoulder. There is less energy required for head movement and eye flickering. That's why user won't get drained from utilizing this gadget. In this gadget or goggle we are utilizing 2D-accelerometer for identifying the head movement, by this, the movement of the cursor has been finished. A photograph sensor distinguishes eye flickering. The infrared handset comprises of a 935 nm IR transmitter and a phototransistor mounted on a similar unit. This identifies a solid increment in the reflected signal upon deliberate long squint when contrasted with ordinary eye flicker. Duplicate hands and legs have been ended up being very helpful and palatable for a set number of exercises. Presently, computer can be easily found at home. The disappointment of these manufactured appendages in empowering the amputees to effectively handle a PC is obvious since one can practice a constrained control on the mechanical appendages connected. Besides, numerous amputees have an occupation and work in workplaces wherein they need to utilize a PC. Consequently, gadget ought to be considered which would permit simple and cover control up PC. Keywords: Handicapped, mouse, Goggle, accelerometer, micro controller

INTRODUCTION To build up a human machine interface copying capacity of a mouse for incapacitated or handicapped people. Since the gadget depends on client's head and eye developments, it can be utilized even by the patients who are deadened from shoulder descending [1, 2]. Straightforward head development doesn't require an excessive amount of vitality, and neither eyes squinting. Subsequently, client won't get drained from utilizing this gadget. We utilize accelerometer to distinguish the development. At the point when the leader of the client is tilted up/down or left/right, the perusing from the accelerometer is subtracted from the estimation of a pre-characterize reference point. The distinction decides the level of head tilt. A photograph sensor identifies eye flickering. The infrared handset comprises of a 935 nm IR transmitter and a phototransistor mounted on a similar unit. This distinguishes a solid increment in the reflected flag upon purposeful

long squint when contrasted with ordinary eye flicker. The yield of both the sensors is given to the ADC input and after switch on the microcontroller. After the signs are translated by the microcontroller, mouse guidelines are sent to the PCs. The handled advanced data is transmitted to the PC through the serial port. Since numerous years, different artificial limbs and administrations are offered worldwide to individuals who have lasting or long haul weakness. Fake hands and legs have been turned out to be very compelling and attractive for a set number of exercises. Presently a-days, a PC is a typical thing at home [3, 4]. The disappointment of these simulated appendages in empowering the amputees to effectively handle a PC is apparent since one can practice a restricted control on the mechanical appendages joined. In addition, numerous amputees have a vocation and work in workplaces wherein they need to utilize a PC. Consequently, gadget ought to be considered which would permit simple and cover control up PC. Along these

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Journal of Artificial Intelligence Research & Advances ISSN: 2395-6720(online) Volume 3, Issue 3 www.stmjournals.com

Social Media Blog Analysis using Watson Analytics Sindhu B. Jigali*, Nirmala C.R. Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davanagere, Karnataka, India Abstract Analytics is defined as the discovery, interpretation, and communication of meaningful patterns in data. A blog is a discussion or informational website published on the world wide web consisting of discrete, often informal diary-style text entries and may contain unstructured or semi-structured data. The analysis of unstructured data types is current challenge, getting attention in industry. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization and information privacy. Watson analytics is a cloud based smart data discovery tool from IBM analytics. Watson solutions aim to enhance, scale, and accelerate human expertise, targeting a wide range of complex challenges. AlchemyAPI is a collection of APIs that offer text analysis through natural language processing. The keyword extraction API works on URL’s, HTML documents and plain text. It automatically detects the language of the content and then performs the appropriate analysis. AlchemyAPI’s keyword extraction algorithm employs sophisticated statistical algorithms and natural language processing technology aided with machine learning techniques to analyze the content and identify the relevant keywords. The proposed blog analyzer application uses the Alchemy_API’s keyword extraction service, accepts the URL’s of the blogs and processes the content by employing sophisticated statistical algorithms and natural language processing aided with machine learning techniques, to retrieve the related/relevant and rank the keywords of the input content. Keywords: Blog, keywords, Watson analytics, Alchemy API, keyword extraction service

*Author for Correspondence E-mail: sindhubjigali94@gmail.com

INTRODUCTION Big data applies to the information that cannot be processed or analyzed using traditional processes or tools. Organizations have access to a wealth of information but they don’t know how to get value out of it because it is sitting in its most raw form, unstructured or semistructured format [1]. According to the survey conducted by IBM, it is found that half of the business leaders today realize that they don’t have access to the insights that they need to fulfill their jobs [1]. Characteristics of Big data are; volume, velocity, variety, validity, veracity, volatility and viability. Volume It is the quantity of generated and stored data. The size of the data determines the value and potential insight- and whether it can actually be considered big data or not [2]. The volume of big data is very high and it is much difficult to manage the data with traditional database systems.

Velocity Velocity refers to the rate at which the data is being generated continuously from various sources. Now a days social networking sites are producing data in high volume with high velocity, which requires a fast and real time processing to manage this data. Variety Big data is very heterogeneous in nature. This data can be structured, semi-structured and unstructured. Data being generated from different sources in different formats are stored to process and analyze [1]. Validity As the volume of the data is very high, validity is the most important requirement to fetch the accurate and relevant data for analysis purpose. This valid data would enhance the decision support system [1].

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Journal of Artificial Intelligence Research & Advances ISSN: 2395-6720(online) Volume 3, Issue 3 www.stmjournals.com

Tweet Segmentation for Named Entity Recognition Krushnadeo Tanaji Belerao* Department of Computer Science and Engineering, Shri Jagdishprasad Jhabarmal Tibrewala University, Jhunjhunu, Rajasthan, India

Abstract Twitter is having lots of users to allocate and distribute a large amount of recent information, various submission in Information Retrieval-IR and Natural Language Processing-NLP undergo harshly through the deafening and tinny kind of tweets. We recommend tweet segmentation framework in a group, called HybridSeg. By dividing tweets with significant segments, the background information is conserved and simply extract with the downstream applications. HybridSeg search the best segmentation of a tweet by increasing the addition of the stickiness score. Two tweet data sets is an experiment; it shows that tweet segmentation quality is extensively increased by learning both global as well as local contexts compared by using global context alone. Additional accuracy is able to name entity recognition by putting segment-based part-of-speech (POS) tagging. Keywords: Information Retrieval, Natural language Processing, Named Entity Recognition (NER), Part of Speech (POS)

MOTIVATION To increase the quality of tweet and finding the named entity. User may create tweets as Earthquake or now it is shaking, designed for earthquake or shaking might be keywords, but user might also make tweets such as we are going to Earthquake conference, or someone is shaking hands with me [1]. Existing System Currently we have lots of social networking sites. But we are using all sites for update states, videos and sharing photos and so on. There are no alert for floods, earthquakes, bad weather situation. Also the segmented data are not summarized so it increases the redundancy and there will be a loss of time [2]. Disadvantages of System  Time loss.  Quality of message reduced. Twitter, is a one of the social type of media, has seen tremendous growth in recent years. It has attracted very large interests from both industry and academic world [2]. Many private and public sector have been described to observe Twitter stream to bring together and realize user's opinions about organizations. To understand the user discussion we collect the tweet and preprocess

the collected tweet and perform the part of speech (POS) [3, 4]. Proposed System Tweets are sent for information, communication and also sharing. The named entities and semantic phrase is well conserved in tweets. The global context taken from Web pages, (e.g., Microsoft Web N-Gram corpus) or Wikipedia helps to recognize the important segments in tweets. The method realizing the planned framework that solely relies on global context is represented by HybridSegWeb. Tweets are highly time-sensitive; a variety of emerging phrases such as “She Playing” cannot be getting in external knowledge bases [5]. Though, taking into consideration a numerous tweets generated in short span, (e.g., a day) having the phrase, it is not problematic to identify “She running” as a meaningful segment and valid. We investigate two local contexts, namely local linguistic characteristics and local collocation. Note that tweets from various official accounts of news agencies, advertisers are likely well written and organizations.

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Journal of Artificial Intelligence Research & Advances ISSN: 2395-6720(online) Volume 3, Issue 3 www.stmjournals.com

Analysis of Image Coders Shefa Hasnain*, Sadiya Bakhshi, Shazia Asif, Monauwer Alam Electronics and Communication Department, Integral University, Lucknow, Uttar Pradesh, India Abstract In this paper we work on the performance analysis of well-known image compression algorithm i.e., wavelet based image compression which is Set Partition in Hierarchical Tree (SPIHT) and also no list SPIHT (NLS). As SPIHT uses three variable lists which require large hardware implementation and hence extra cost and high encoding and decoding time is required but NLS use marker instead of list which are placed on lower nodes of insignificant tree hence it requires less hardware and hence it is less complex then SPIHT and time of decoding and encoding is also inferior to SPIHT. The algorithm are implemented in MATLAB and compared using the parameter peak signal to noise ratio PSNR, encoding time and decoding time. Using the NLS technique the image obtained has less encoding as well as decoding time as compared to SPIHT but in context SNR SPIHT is better. Keywords: SPIHT, NLS, PSNR, Performance analysis, Bits per pixel

INTRODUCTION The SPIHT algorithm is a generalization of the Embedded Zero Wavelet (EZW) algorithm proposed by Amir Said and William Pearlman [1]. In EZW we transmit a lot of information for little cost when we declare an entire subtree to be insignificant and all the coefficients in it with a zero tree label zero. The SPIHT algorithms use a partitioning of the trees in a manner that tends to keep insignificant coefficient together in large subset. The partitioning decision are binary decision that are transmitted to the decoder, providing a significance map encoding that is more efficient than EZW. SPIHT uses three variable lists  List of significant pixel (LSP)  List of insignificant pixels (LIP)  List of insignificant set (LIS) No List SPIHT (NLS) uses the same set structures and partitioning rules as SPIHT. The trees are tested for significance breadth first. Significance tests are related in a different order than SPIHT because SPIHT performs significance tests roughly breadth first, while NLS performs the tests strictly breadth first. Because the set splitting rules are the same,

each coder produces the exact same output bits, though in a different order.

SPIHT ALGORITHM We need to know about some data notation before describing the algorithms. SPHIT algorithm use data structure which is similar to that used by EZW algorithm but still it is not that much same. Again divide the coefficient into trees which formulate from the lowest resolution band. These coefficients are grouped into array of 22 matrixes which except for coefficient in band 1 are offspring’s of a coefficient of a lower resolution band. The coefficient which is in lower band resolution (Figure 1) is also divided into array of 2x2 matrixes. The coefficient which is in top most left corner of the array doesn’t have any offspring. Algorithm Let Sn(t) is a function which decides the set of significance bit with respect to the threshold 2n. Sn(t), if max(i,j){[Ci,j]} ≥ 2n 0, else Whereas ci, j is the wavelet coefficient.

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ISSN 2395-6720 (Online)

Journal of

Artificial Intelligence Research & Advances (JoAIRA) Septemberâ&#x20AC;&#x201C;December 2016

STM JOURNALS Scientific

Technical

Medical