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The digital image data is rapidly growing in quantity and heterogeneity. The existing information retrieval techniques does not meet the user’s demand, so there is need to develop an efficient system for content based image retrieval. Content Based Image Retrieval (CBIR) is a technique which uses visual features of image such as color, shape, texture, etc... to search user required image from large annotated image database according to user`s requests, in the form of a query image. In this paper we present a study on some technical aspects of current content-based image retrieval systems and feature extraction. Features such as color, shape and texture are analysed to develop a high retrieval accurate cbir system.

CBIR, visual database, texture, feature extraction, color correlogram

[1] D. A. Kumar and J. Esther, “Comparative Study on CBIR based by Color Histogram, Gabor and Wavelet Transform”, Int’l Journal of Computer Applications (0975 – 8887), vol. 17, no. 3, (2011) March, pp. 37.
[2] Khan,W., Kumar,S., Gupta,N., Khan,N., A Proposed Method for Image Retrieval using Histogram values and Texture Descriptor Analysis, IJSCE, ISSN: 231-2307, Volume-I Issue-II,( May 2011).
[3] F. Long, H. J. Zhang and D. D. Feng, “Fundamentals of Content-based Image Retrieval, Multimedia Information Retrieval and Management”, D. Feng Eds, Springer, (2003).
[4] L. Haldurai and V. Vinodhini, "Parallel Indexing on Color and Texture Feature Extraction using R-Tree for Content Based Image Retrieval", International Journal of Computer Sciences and Engineering, Vol.3, Issue.11, pp.11-15, 2015.
[5] L. Zheng, S. Wang, and Q. Tian, “Lp-norm IDF for scalable image ns. Image Process., vol. 23, no. 8, pp. 3604–3617, Aug. 2014

Nadira T., Rehna K., Fepslin Athish Mon, "A Study and Analysis on Feature Extraction in Content-Based Image Retrieval," International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.305-307, 2017.

There are many technologies and methodologies present to support existing wireless mobile communication. We propose a concept to integrate best methodologies and technologies that suits the future generation in terms of high system, spectral efficiency, and energy efficiency etc. Our approach to achieve requirement of next or upcoming generation 1stly we analyze best technology and methodologies (like multi input multi output (MIMO), orthogonal frequency division multiple access (OFDMA), Direct-device to device (D2D) communication, MIMO, Mm wave, Spatial modulation, Radio access technology etc.) of each generation and then check the possibility of integration of technologies and methodologies. And design architecture with integrated technologies and methodologies with respect to future generation. So, we check the possibility and try to integrate various technologies and methodologies of different generation to fulfill the requirement of next generation.

Cognitive radio, SDR, Spectrum Secrecy, Spectrum Efficiency, MIMO, Mm Wave, D2D

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[9] Mansour Zuair, 31st May 2013, Development of an Access Mechanism For Femto Cell Networks , Journal of Theoretical and Applied Information Technology, Vol. 51 No.3 .
[10] Dieter Ederle , LTE vs. Wi-MAX 4th generation telecommunication networks,
[11] Halil Saygili, September 2013, A comparison of spatial modulation and spatial multiplexing systems in multipath fading channels.
[12] Marja Matinmikko (editor), Marko Höyhtyä, Miia Mustonen, Heli Sarvanko, Atso Hekkala, Marcos Katz, Aarne Mämmelä, Markku Kiviranta, Aino Kautio, Cognitive radio: An intelligent wireless communication system, Research Report VTT-R-02219-08
[13] Singh S, Mushtaq G, Tiwari NK, Singh AP (2015) Cognitive Radio With Software Defined Radio and Mimo for Future Generation Wireless Communication. J Comput Sci Syst Biol 8:166-169. doi:10.4172/jcsb.1000184.
[14] Goutam Ghosh1 , Prasun Das2 and Subhajit Chatterjee3, March 2014, Cognitive Radio And Dynamic Spectrum Access – A Study, International Journal of Next-Generation Networks (IJNGN) Vol.6, No.1.
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[17] Shashank Singh, Prashant Kumar Tripathi, Gowher Mushtaq, Neeraj Kumar Tiwari, April 2015, Integration of Existing Wireless Communication Technologies in Respect to Future Generation, MAIOJET, ISSN:2348 – 3326.

Shashank Singh, Himanshu Kumar Shukla, Rohit Sharma , "Integration of Different Wireless Technology and Methodology for Future Generation of Wireless Communication," International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.308-313, 2017.

Sorting is an important technique of data structure which finds its place in many real-life applications. There are various sorting algorithms are in existence till date. In this paper, we have tried to improve upon execution time of the Bubble Sort algorithm by implementing the algorithm using an enhancement of it. An extensive analysis has been done by us on the new algorithm and the algorithm has been compared with the traditional method of Bubble Sort. Observations have been obtained on comparing this new approach with the existing approaches of Bubble Sort. The new proposed approach was tested for Average Case analysis, Best Case analysis and Worst case analysis. It has been analysed that the new approach has given very good results on Average Case and Worst Case analysis. The new approach was tested on random data of various ranges from small to large. It has been observed that the new approach has given efficient results in terms of execution time. Hence, we have reached to the conclusion through the experimental observations that the new algorithm given in this paper is better than the traditional Bubble Sort.

Sorting, Bubble sort

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Harsh N. Nankani, Mukesh Bhandari, "An Enhancement of Bubble Sorting Algorithm," International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.314-316, 2017.

A non-constant envelope with high peaks is a main disadvantage of Orthogonal Frequency Division Multiplexing (OFDM). These high peaks produce signal excursions into non-linear region of operation of the Power Amplifier (PA) at the transmitter, thereby leading to non-linear distortions and spectral spreading. Many Peak to Average Power Ration (PAPR) reductions methods have been proposed in the literature. The objective of this review is to give a clear understanding of different techniques to reduce PAPR of the signal.

OFDM,PAPR,PA

[1]. Md. Mahmudul Hasan et.al, “An Overview of PAPR Reduction Techniques in OFDM Systems”, International Journal of Computer Applications, vol. 60, no. 15,pp. 33-37, dec. 2012.
[2]. Aparna P. More et.al , “ The reduction of PAPR in OFDM system using clipping and SLM method”, IEEE , vol. 1, year 2011.
[3]. Brijesh Ahirwar and Vishal Pasi, "A Survey Paper on Inter-carrier Interference Reduction Techniques in OFDM Systems", International Journal of Computer Sciences and Engineering, Vol.3, Issue.6, pp.26-29, 2015.
[4]. Komal Gupta et.al , “PAPR reduction of OFDM using a new phase sequence in SLM technique”,IEEE, vol. 2, no. 2 , pp. 125-129, year 2013.
[5]. Gagandeep Kaur et.al, “Compare SLM (selective mapping) and PTS (partial transmit) technique for PAPR reduction of an MC-CDMA (multi-carrier complex division multiple access)”, IJERA, vol. 2, no. 4, pp. 779-784, jul-aug 2012.
[6]. Arpit Maheshwari, Puneet Khanna and Neelu Trivedi, "PAPR Reduction in OFDM System by Using Discrete Cosine Transform and µ-law Companding", International Journal of Computer Sciences and Engineering, Vol.3, Issue.6, pp.22-25, 2015.
[7]. Md. Ibhrahim Abdullah et.al, “Comparative Study of PAPR Reduction Techniques in OFDM”,ARPN journal of system and software, vol. 1, no. 8 ,pp 263-269, nov 2011.
[8]. Komal Gupta et. al. , “PAPR reduction of OFDM using a new phase sequence in SLM technique”, IJAEEE, vol-2, issue-2 , pp.125-109, 2013.
[9]. Filbert H. Juwano et.al , “ PAPR reduction using Huffman coding combined with clipping and filtering for OFDM transmitter to mitigate PAPR (peakto-average power ratio) in OFDM”, (CITISIA 2009), vol. 8 , PP. 344-347, year 2009.
[10]. Chavvi Sharma et.al , “ A modified iterative amplitude clipping and filtering technique for PAPR reduction in OFDM system”, IEEE , vol. 2 , pp. 365-367, year 2011

Shaik.Rasool Saheb, K.Krishna Murthy, "PAPR in OFDM Systems Different Techniques," International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.317-321, 2017.

Dementia is a general term for a gathering of brain disorders. Alzheimer`s disease is the most widely recognized sort of dementia, representing 60 to 80 percent of cases. This fact sheet quickly talks about Alzheimer`s and some different dementias. A wide range of dementia includes mental decrease that: Influences more than one of the following four core mental abilities Recent memory, Language, Visuospatial function, Executive capacity. The paper likewise introduces a Rule-based Expert System for Memory Loss Disease with the assistance of principles and truths. It is an endeavor to concentrate on some of critical illnesses identified with memory loss like Alzheimer`s disease, Parkinson`s disease, Huntington`s disease and dementia which are among the most widely recognized sorts of memory loss diseases. This Expert System will help the patients to get the required guidance about the diverse issue assault to them because of their nervous system disorders. The expert rules were developed on the symptoms of each type of neurological disease, and they were presented using decision tree and inferred using forward-chaining method. The knowledge base comprises of data about the memory loss and all the diseases related to it identified with it which is gathered from books and specialists (area specialists) about neurology and its disorders.

Rule-based Expert System, Alzheimer’s, Dementia

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T.M. Girish1, V.K. Sing, D.K. Sreekantha, "A Study on Neurological Diseases like Alzheimer’s, Dementias, its Causes and an attempt To Develop a Rule-Based Expert System," International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.322-328, 2017.

Cloud computing is defined as that type of computing that relies on sharing computing resources rather than having local servers or personal devices to handle applications. Cloud computing is used to achieve coherence and economy of scale over a network. Basically, cloud computing is a general term for the delivery of hosted services over the internet. Various characteristics which comes under cloud computing includes its location independent, multi-tenancy, its reliability and security, and its on-demand self service etc. Cloud Computing is spreading through IT world with innovative start-ups. Companies in the financial sector are also adopting cloud computing for specific workloads. Various strategies are used for optimization in cloud computing in which particle swarm optimization is one of them. It is used to achieve task scheduling algorithm. To achieve better results and performance, we used Particle Swarm Optimization.

Cloud computing, architecture, scheduling, computing in IT sector, Particle Swarm Optimization

[1] Dr. M. Sridhar and Dr. G. Rama Mohan Babu, R.V.R & J.C College of
Engineering, Guntur, INDIA, 2015 IEEE International Advance Computing Conference (IACC).
[2] Zhi-hui Zhan, Jun Zhang, Yun Li, and Henry Chung, “Adaptive particle swarm optimization”, IEEE Transactions on System, Man, and Cybernetics, Vol. 39, No. 6, pp. 1362-1381, 2006
[3] Xingquan Zuo, Member, IEEE, Guoxiang Zhang, and Wei Tan, Member, IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, VOL. 11, NO. 2, APRIL 2014.
[4] Nuttapong Netjinda, Booncharoen Sirinaovakul, Tiranee Achalakul Departmet of Computer Engineering King Mongkut’s University of Technology Thonburi Bangkok, Thailand, Thailand Research Fund through the Royal Golden Jubilee Ph.D. Program (grant no. PHD/0031/2553).
[5] BU Yanping1, 2 ZHOU Wei3 YU Jinshou1 1.Research Institute of Automation, East China University of Science and Technology, Shanghai 200237 China; 2. School of Technology, Shanghai Jiaotong University, Shanghai 201101 China; 3. School of Business, East China University of Science and Technology, Shanghai 2002 37 China, 2008 International Symposium on Computer Science and Computational Technology.
[6] A. Salman, “Particle swarm optimization for task assignment Problem”, Microprocessors and Microsystems, Vol. 26, No.8, pp.363–371, 2009.
[7] Azadi Khalili and Seyed Morteza, School of Electrical and Computer Engineering Kashan University, Babamir, 2015 23rd Iranian Conference on Electrical Engineering (ICEE).
[8] L. Zhang, Y.H. Chen, R.Y Sun, S. Jing, and B. Yang, “A task scheduling algorithm based on PSO for Grid Computing", International Journal of Computational Intelligence Research, pp.37-43, 2008.
[9] Lizheng Guo, Shuguang Zhao, Shigen Shen, and Changyuan Jiang, “Task Scheduling Optimization in Cloud Computing Based on Heuristic Algorithm”, Journal of Networks, Vol.7, No.3, 2012.
[10] ChienHung Chen, JennWei Lin, and SyYen Kuo, Fellow, IEEE.
[11] Zahraa Tarek, Magdy Zakria and Fatma A. Omara, “PSO Optimization algorithm for Task Scheduling on The Cloud Computing Environment”, international Journal of Computers and Technology, Vol. 13, No. 9, 2014.
[12] Himani, Global Institute of management & emerging technology, Amritsar, India and Harmanbir Singh Sidhu, Chandigarh Group Of Colleges, India, 2015 Second International Conference on Advances in Computing and Communication Engineering.

Shruti, Meenakshi Sharma, "Task Scheduling and Resource Optimization in Cloud Computing Using Deadline-Aware Particle Swarm Technique: A Review," International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.329-332, 2017.

Our world runs on software. Every business depends on it, every mobile phone uses it, and even every new car relies on code. Without software, modern civilization would fall apart. Given this reality, the quality of that software really matters. Because it’s so widely used and so important, low-quality software just isn’t acceptable. But what exactly is software quality? It’s not an easy question to answer, since the concept means different things to different people. One useful way to think about the topic is to divide software quality into three aspects: functional quality, structural quality, and process quality. Doing this helps us see the big picture, and it also helps clarify the trade-offs that need to be made among competing goals.

Quality, Methodologies, six sigma, innovation

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N. Rajasekhar Reddy, M. Vinaya Babu, "Software Quality Modeling by Process," International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.333-334, 2017.

The use of wireless networks is widely increasing. One of these networks, ad hoc mobile networks (Mobile ad hoc networks) is. Mobile Ad hoc Network known as network short-lived. Nature-inspired algorithms (swarm intelligence) such as ant nest optimization algorithms and genetic algorithms to solve the routing problem in recent years have introduced mobile-specific networks.

Mobile Ad hoc networks, genetic algorithms, algorithms ant nest

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[2] K. Subramanian, R. Gnanakumaran , "Analysis of Power Complexity in Existing Algorithms Against Ad-Hoc On demand Distance Vector Routing Protocol (AODV)", International Journal of Computer Sciences and Engineering, Vol.4, Issue.12, pp.36-45, 2016.
[3] Umesh Kumar Singh, Jalaj Patidar and Kailash Chandra Phuleriya, "On Mechanism to Prevent Cooperative Black Hole Attack in Mobile Ad Hoc Networks", International Journal of Scientific Research in Computer Science and Engineering, Vol.3, Issue.1, pp.11-15, 2015.
[4] Abhinav Gupta and Prabhdeep Singh, "Improving the performance of Mobile Wireless Sensor Networks using modified DBSCAN", International Journal of Computer Sciences and Engineering, Vol.3, Issue.8, pp.6-10, 2015.
[5] Kritika Sood and Payal Kaushal, "Client Adaptive Load Balancing in DSR", International Journal of Scientific Research in Network Security and Communication, Vol.1, Issue.1, pp.26-28, 2013.
[6] Pradeep Kumar Sharma, Shivlal Mewada and Pratiksha Nigam, "Investigation Based Performance of Black and Gray Hole Attack in Mobile Ad-Hoc Network", International Journal of Scientific Research in Network Security and Communication, Vol.1, Issue.4, pp.8-11, 2013.
[7] J. Amol B.Suryawanshi, Baljit Kaur Saini, "Survey on Various Routing Protocols in Ad-hoc Networks", International Journal of Scientific Research in Network Security and Communication, Vol.5, Issue.3, pp.174-178, 2017.
[8] Pradeep Sharma, Shivlal Mewada and Aruna Bilavariya, "Group Rekeying Management Scheme for Mobile Ad-hoc Network", International Journal of Scientific Research in Network Security and Communication, Vol.1, Issue.5, pp.5-12, 2013.
[9] Leena Pal, Pradeep Sharma, Netram Kaurav and Shivlal Mewada, "Performance Analysis of Reactive and Proactive Routing Protocols for Mobile Ad-hoc –Networks", International Journal of Scientific Research in Network Security and Communication, Vol.1, Issue.5, pp.1-4, 2013.
[10] Deepesh Tamrakar, Sreshtha Bhattacharya and Shitanshu Jain, "A Scheme to Eliminate Redundant Rebroadcast and Reduce Transmission Delay Using Binary Exponential Algorithm in Ad-Hoc Wireless Networks", International Journal of Scientific Research in Network Security and Communication, Vol.2, Issue.2, pp.1-5, 2014.
[11] R. Kachal, S. Suri, "Comparative Study and Analysis of DSR, DSDVAND ZRP in Mobile Ad-Hoc Networks", International Journal of Computer Sciences and Engineering, Vol.2, Issue.5, pp.148-152, 2014.
[12] P. R. Gundalwar and Bhaskar Y. Kathane, "A Comprehensive Analysis on Route Discovery and Maintenance Features of DSDV, AODV and IERF Ad-hoc Routing Protocols", International Journal of Computer Sciences and Engineering, Vol.4, Issue.2, pp.75-78, 2016.

Mohsen Davoudi Monfared, Shadie Zeinali, "Intelligent Routing Algorithms Assess Mobile Network," International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.335-339, 2017.