Volume-07 , Special Issue-11 , May - 2019 Go Back

Human society is developing with rapid momentum and achieved various successes for making its livelihood better. The civilization is witness for various changes related to it’s the development through different catalysts like industrial development, green revaluation, science and technology, etc. The present era is augmented on Information and Communication Technology. This technology has proved its potential in various sectors of development in urban and rural landscapes. Urban areas are seems to more inclined to accept and adopt Information and Communication Technology due to advantages of literacy and better infrastructure as compared to rural areas. Due to such suitable situations of urban landscapes good amount of success of this technology is visible in the form of smart cities and better livelihood of residing human beings. But the problems, consequences and opportunities in urban areas are different for effective utilization of Information and Communication Technology for sustainable development of rural masses. The present research article discusses about rural development in developing world for the up-liftment of livelihood of the rural masses and to take a ‘look ahead’ at scientific developments and technologies that might be influential over the next 10 -20 years. The driving motivation behind the concept on “Smart Village” is that the technology should acts as a catalyst for development, enabling education and local business opportunities, improving health and welfare, enhancing democratic engagement and overall enhancement of rural village dwellers. The “Smart Village” concept aims to realize its goal through providing policymakers with insightful, bottom–up analyses of the challenges of village development.

Information Technology, Rural, Smart Village, Sustainable Development

[1] Census 2000, Govt. of India Publication
[2] Census 2011, Govt. of India Publication
[3] Asian Development Bank (2008). Managing Asian Cities: Sustainable and inclusive urban solutions, Asian Development Bank Report, Asian Development Bank, 2008, Publication Stock No. 050608, ISBN 978-971-561-698-0. Available: http://www.adb.org/ Documents/ Studies/Managing-Asian-Cities/mac-report.pdf
[4] H. Chourabi, N. Taewoo,S. Walker,J. R. Gil-Garcia, S. Mellouli, K. Nahon, T.A. Pardo, H. J. Scholl (2012). Understanding Smart Cities: An Integrative Framework. System Science (HICSS), 2012 45th Hawaii International Conference, 4-7 Jan. 2012. Available: http://ieeexplore.ieee.org/xpl/ articleDetails.jsp?arnumber =6149291&abstractAccess=no&userType=inst
[5] M. N. Srinivas and A. M. Shah (1960). The Myth of Self-Sufficiency of the Indian Village. The Economic Weekly,1375- 1378. Available: http://www.epw.in/system/files/pdf/1960_12/37/ the_myth_of_selfsufficiency _of_the_indian _village.pdf
[6] S. Daniel, M. A. Doran (2013). geoSmartCity : Geomatics Contribution to the Smart City, In: The 14th ACMAnnual International Conference on Digital Government Research, Pp. 65-71. Available:dl.acm.org/ft_gateway.cfm?id=2479738
[7] R. Heeks, (2002). Information Systems and Developing Countries: Failure, Success, and Local Improvisations.The Information Society, 18 (2) pp 101-112.
[8] M. Vesisenaho, and E. Sutinen (2010). Smart Morning in an African Village: Diversifying Technologies within a Tanzanian Context. International Journal of Media, Technology and Lifelong Learning, 6 (1). Available: http://seminar.net/volume-6-issue-1-2010/ 138 -smart-morning-in-an-african-village-diversifying-technologieswithin-a-tanzanian-context
[9] Xun, LI (2008). Bottom-up: new features of socialist new village construction. Journal of City Planning Review,2008-12.Available: http://en.cnki.com.cn/Article_en/CJFDTOTAL-CSGH200812021.htm
[10] V. Sharma, V. Mansotra and F. S. Sambyal (2009). Computer Science and Information Technology, ICCSIT 2009. 2nd IEEE International Conference on Date8-11 Aug. 2009 Available:http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=5234376&queryText%3 Ddigital+village
[11] Verma S., Datta A., (2013), GIS-driven renewable energy framework for smart and sustainable cities - IndiaGeospatial Digest July 2013, Available: http://geospatialworld.net/Paper/Application/ArticleView.aspx?aid=30589#sthash.44KIadk8.dpuf

Mithlesh Prajapati, Asha Ambhaikar, "Smart Villages through Information Technology – Need of Emerging India", International Journal of Computer Sciences and Engineering, Vol.07, Issue.11, pp.85-89, 2019.

The process of image segmentation is defined as the technique via which a given image is segmented into several objects, in order to further analyze objects present in the image [9]. The popularity of image segmentation is because of its importance in the area of image processing. The prime task of the researchers working in the field is to develop a method for efficient and better image segmentation. There are certain factors that affect the process of image segmentation like the intensity of image to be segmented, color, type and the noise present in the image [12]. No algorithm has been developed till date that could keep a look at all the above listed factors and then segment the image effectively so that all the problems that can come in the way of image segmentation can be avoided. This paper presents a review of some of the techniques developed for image segmentation.

Image segmentation ,Techniques ,Visualization

[1] Chang-T sunli, Randy Chiao, “Multi-resolution genetic clustering algorithm for texture segmentation image and vision computing.” 2003,
[2] International conference on advance computer theory and engineering. (2010): image segmentation algorithm research and improvement.
[3] Kim, Eun Wi, Jung Keechul, “Genetic algorithm for video segmentation[J]”. Pattern recognition, January, 2005, 59-73.
[4] R. manavalan and K. Thangabel (2011), “TRUS image segmentation using morphological operators DBSCAN clustering.”
Mei Yean Choong, Wei YeangKow, YitKwong Chin, “Image segmentation via normalized cuts and clustering algorithm.” 2012 IEEE international conference on control system.
[5] Suganya1, Menaka, “Various Segmentation Techniques in Image Processing: A Survey,” IJIRCCE, Vol.2, Special Issue 1, March 2014.
[6] DibyaJyoti Bora (September, 2014) “A Novel Approach Towards Clustering Based Image Segmentation”, IJESE, Volume-2 Issue-11, pp 6-10.
[7] Yon Deng, Xuemei Cui, Shaolong Wu, “An improved image segmentation algorithm based on the watershed transform.”
[8] Rajiv Kumar (December, 2011) “Image Segmentation using Discontinuity-Based Approach”, IJMIP, Volume 1, Issues ¾, pp 72-78.
[9] AmanpreetKaur , “A Review Paper on Image Segmentation and its Various Techniques in Image Processing”, IJSR, Volume 3 Issue 12, December 2014, pp 12-14
[10] Muhammad Waseem Khan et al, “A Survey: Image Segmentation
Techniques”, International Journal of Future Computer and
Communication, Vol. 3, No. 2, April 2014, pp 89-93
[11] RohanKandwal, “Review: Existing Image Segmentation Techniques”, IJARCSSE, Volume 4, Issue 4, April 2014, pp 153-156
[12] Rajiv Bansal, Sona Kajla, “A Survey on Various Techniques for Image Segmentation’’, IJIRCSSE Vol. 4, Issue 4, April 2016
[13] Swapan Samaddar, Dr. A RamaSwamy Reddy, “Comparative Study Of Image Segmentation Techniques On Chronic Kidney Diseases,” IJPAM, Volume 118 No. 14 2018, 235-239.
[14] S.C.Zhu and A.Yuille, “Region competition: unifying snakes, region growing and Bayes/MDL for multiband image segmentation.” IEEE transaction on pattern analysis and machine intelligence, vol.18 september,1996, PP 884-900
[15] L.J.Shapiro and G.C.Stockman. Computer vision prentice hall,2001
[16] Nameirakpamdhanachandra,Khumanthemmanglam,“Image segmentation using k-means clustering algorithm and subtractive clustering algorithm”. 11th international multi-conference on information processing-2015(IMCIP-2015).
[17] G. Eason, B. Noble, and I.N. Sneddon, “On certain integrals of Lipschitz-Hankel type involving products of Bessel functions,” Phil. Trans. Roy.Soc. London, vol. A247, pp. 529-551, April 1955.

Manisha Bhagwat, Vivek Pise, "Image Segmentation Techniques: A Survey", International Journal of Computer Sciences and Engineering, Vol.07, Issue.11, pp.90-93, 2019.

This paper contains the review of different image processing techniques to detect various leaf diseases using machine learning. Now a day’s image processing technique is becoming a key technique for diagnosing the various features of the leaves. The diseases can touch part or area of the leaf. This paper mainly focuses detection of various leaf diseases and to classify them. The detection of leaf disease is mostly based on type of family leafs and same is approved by segmentation and classification. There are so many classification techniques such as Decision tree classifier, k-Nearest Neighbour classifier , k-means Classifier, Probabilistic Neural Network, Genetic Algorithm, Support Vector Machine, and Principal Component Analysis, Artificial neural network, Fuzzy logic. Assortment of classification method is always a difficult job because the quality of result can differ for dissimilar input data. This paper provides an overview of diverse classification techniques used for leaf disease classification [1].

image processing, k-means, neural network, Support Vector Machine

[1]. Rani Pagariya, Mahip Bartere “Review Paper on Identification of Leaf Diseases Using Image Processing Technique “, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 3 Issue 11, November 2014.
[2]. Sagar Patil , and Anjali Chandavale “A Survey on Methods of Leaf Disease Detection “,International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438.
[3]. Sujeet Varshney, Tarun Dalal “Plant Disease Prediction using Image Processing Techniques- A Review”, SujeetVarshney et al, International Journal of Computer Science and Mobile Computing, Vol.5 Issue.5, May- 2016, pg. 394-398.
[4]. Yashpal Sen, Chandra Shekhar Mithlesh, Dr. Vivek Baghel “ A SURVEY ON CROP DISEASE DETECTION USING IMAGE PROCESSING TECHNIQUE FOR ECONOMIC GROWTH OF RURAL AREA”, IJARIIT( ISSN: 2454-132X).
[5]. Mr. Viraj A. Gulhane, Dr. Ajay A. Gurjar, “Detection of Diseases on Cotton Leaves and Its Possible Diagnosis”, International Journal of Image Processing (IJIP), Volume (5) : Issue (5) : 2011.
[6].G. Savita, A. Parul, “Detection and classification of leafleaf diseases using image processing techniques: a review,” Int. J. Recent Adv. Eng. Technol., vol. 2, pp. 2347–812, 2014.
[7]. B. Dhaygude, N. P. Kumbhar, “Agricultural leafleaf disease detection using image processing,” Int. J. Adv. Res. Electr. Electron. Instrum. Eng., vol. 2, pp. 599-602, Jan. 2013.
[8]. Sumit Nema, Bharat Mishra,, Mamta Lambert “Advance App Design Methods of Leaf Disease Detection using Image Processing Approach – A Review”, IJIRSET, ISSN(Online) : 2319-8753.
[9]. S. Bashir, and N. Sharma, “Remote area leaf disease detection using image processing,” IOSR J. Electron. Commun. Eng., vol. 2, pp. 31-35, Sep. 2012.

Ajay Kumar, "Leaf Disease Detection using Image Processing Technique- A Survey", International Journal of Computer Sciences and Engineering, Vol.07, Issue.11, pp.94-97, 2019.

Smartphone plays a crucial role in our daily life. Day by day there are advancements in technology which import changes in architecture of mobile phones. Low power, communication and performance largely affects the processor architecture of mobile phones. Processor architecture is now become complex to support the digital telephony. Mobile phones Processor design growing rapidly with respect to last generations . The objective of this paper is to overview the architecture of processor in Smart phones.

Processor architecture, ARM Processors, SoC

[1] Mahendra Pratap Singh, Manoj Kumar Jain, Ph. D “Evolution of Processor Architecture in Mobile Phones” International Journal of Computer Applications (0975 – 8887) Volume 90 – No 4, March 2014
[2] Masuma Akter Rumi,1 Asaduzzaman,1 D. M. Hasibul Hasan2 “CPU Power Consumption Reduction in Android Smartphone” 2015 IEEE
[3] Nayeem Islam, Qualcomm , Roy Want, Google “Smartphones: Past, Present, and future”
[4] Trevor Mudge “The Architecture of Smart Phones” 2015 IEEE 22nd International Conference on High Performance Computing
[5] Steven Swanson and Michael Bedford Taylor, University of California “Green Droid: Exploring the Next evolution in Smartphone Application Processors”
[6] Farinaz Koushanfar, Vandana Prabhu , Miodrag Potkonjak , Jan M. Rabaey ” Processors for Mobile Applications”
[7] Alan Gatherer, Trudy Stetzler, Mike McMahan, and Edgar Auslander, Texas Instruments "”DSP based Architectures for Mobile Communications: Past ,Present and Future”
[8] Dr. Margarita “Trends in Hardware Architecture for mobile Devices” Berlin November 2004
[9] Masuma Akter Rumi,1 Asaduzzaman,1 D. M. Hasibul Hasan2 “CPU Power Consumption Reduction in Android Smartphone” 2015 IEEE
[10] Leonid Ryzhynk “The ARM Architecture”
[11] SoC Consortium “ ARM Processor Architecture”
[12] Georgescu M.D. “Evolution of Mobile Processors “, communications , computers and signal Processing , 2003 PACRIM 2003 IEEE Pacific Rim conference.

Hemlata Kohad, Asha Ambhaikar, "Smartphone Processor Architecture", International Journal of Computer Sciences and Engineering, Vol.07, Issue.11, pp.98-103, 2019.

This paper takes an initiative to show how the technology and technology based system and approach towards education has impacted learning any language as well as acquiring linguistics skills. To attain effectiveness in learning and acquiring the language related skills & awareness, a number of methods are being used but those methods without technologies are rarely successful to the beginners and adult learners. Mostly, technologies in education such as Computer Assisted Language Learning (CALL) & Mobile Assisted Language Learning (MALL) have kept widely influenced to the Technology Assisted Education (TAE). TAE has a close relationship with modern science and technology in this regard. Not only inside but also outside the classroom, Teaching associated with TAE helps instructors and the young and the adult learners using the MALL technology. Smart Information technologies have made the classroom educative, skillful and informative. TAE makes both the teachers and the students skillful in the regard of language learning by smart-innovative and modern technologies. It teaches them how to manage the time; to get information and to earn knowledge. At last visualization adds a new era in the language learning system.

Acquiring, Change, Informative, Impact, Learning, Technology, Visualizing, TAE

[1] Aldoodie. Nada., “Technology Integration and Learning Theory”, Amerian International Journal of Contemporary Research. Vol. 5, No. 6. December. 2015.
[2] Baran. Evrin., “A Review of Research on Mobile Learning in Teacher Education”. Educational Technology & Society. October, 2014.
[3] Bhattacharya. Dr. Shilpi., “Soft Skills and English language Teaching: A Tool to Global Placements”. Literati. Vol. XI, Summer. 2012. Raipur. C.G. pp. 65-70.
[4] Cano. V. Esteban., “Mobile Distance learning with Smartphones and Apps in Higher Education”. Educational Consultancy and Research Center: 2014. www.edam.com.tr/estp
[5] Das. Dipankar., “Modern Education with Smart Classroom”. RAY: International Journal of Multidisciplinary Studies. Vol. I, No. 1. April, 2016, pp. 67-79.
[6] http://en.m.wikipedia.org/wiki/Signified_and_signifier
[7] “Reimaging the Role of Technology in Education”. National Education Technology Plan Update. January. 2017.http://tech.ed.gov
[8] Saussure. F. De, Course in General Linguistics, French: 1916
[9] Sharhan. A. Salah, “Smart Classrooms in the context of Technology Enhanced Learning (TEL) Environment: A Holistic Approach”. 2016 www.reserchgate.net/publication/288000218
[10] Unwin. Tim., “Paper commissioned for the EFA Global Monitoring Report 2015”. Education for All 2000-2015: achievements and challenges. UNESCO. 2015.
[11] Wikramanayake. G.N., “Impact of Digital Technology on Education”. August. 2005. www.researchgate.net/publication/216361364
[12] Wulystan. P. Mtega., Ronald. Bernard., Andrew. C. Msungu., & Rachel. Sanare., “Using Mobile Phones for Teaching and Learning Purposes in Higher Learning Institutions: the Case of Sokoine University of Agriculture in Tanzania”. Conference Paper: January. 2012. www.researchgate.net/publication/275340682
[13] Zamfir. Andreea., “Impact of Using Computer Applications in Education on Teaching-Learning Process”. 7th WSEAS Int. Conf. on Applied Computer & Applied Computational Science (ACACOS ’08). Hangzhou. China. April 6-8. 2008.

Md. Eftekhairul, M. S. Mishra, "Impact of Technology Assisted Education for Improving Learning Skills", International Journal of Computer Sciences and Engineering, Vol.07, Issue.11, pp.104-107, 2019.