Over the concept of Ride-Sharing (RS) is very important valuables of environment because it saving energy and destroy the traffic pressure or traffic congestion. In this paper, we propose a new model for maximizing the shared route. In this model, where each driver or rider requests, that driver shares a ride with a rider, and shared route percentage increased expectation rate of the driver. Shared route percentage is nothing but the radio of the shared route‟s distance to the driver‟s total distance. It proposes the best-first algorithm that it selected the drivers with high probability to be in the top-k results. Then, the drivers are already pruned, but that cannot be in the top-k results.........

Keywords: Ride sharing, Combine BV Edges, IABFM, Active_seg.

[1]. Asghari, Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, Yaguang Li. "Price-aware real-time rides-sharing at scale an auction-based approach". Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. ACM, 2016.
[2]. Ece kamar, Eric Horvitz. "Collaboration and shared plans in the Open World: Studies of Ridesharing". IJCAI. Vol. 9. 2009.
[3]. Leyla Kazemi, Cyrus Shahabi. "GeoCrowd: Enabling Query Answering with Spatial Crowdsourcing". Proceedings of the 20th international conference on advances in geographic information systems. ACM, 2012.
[4]. Pedro M. d‟Orey, Ricardo Fernands, Michel Ferrreira. "Empirical Evaluation of a Dynamic and Distributed Taxi-Sharing System". Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on. IEEE, 2012.
[5]. Shiyou Qian, Yanmin Zhu, Minglu Li. "Smart Recommendation by Mining Large-scale GPS Traces". Wireless Communications and Networking Conference (WCNC), 2012 IEEE. IEEE, 2012.

Structural construction requires to forfeit attention in specific stresses generation due to various loads in buildings via different acting load. Seismic forces are occasionally deep earth occurring vibrations but have high impact on the surfacial structural proficient unity of the building. Structural lightweight concretes incorporation offer design flexibility, ductility and substantial economy by providing less dead load. The ductility of a reinforced structure is one of the most vital factors affecting its seismic act and behaviour. This work concentrate on analysis of structures with high-rise building under seismic effect based on Normal and Light weight RCC work, this study includes in structural sections. Reinforced light weight concrete section can provide an effective and economic solution to most of problems in average to high-rise buildings.

Keywords: Seismic Loads, Light weight concrete, Flexibility & Ductility.

[1]. Abdel hamid Charif et. Al. [1], "Ductility of reinforced lightweight concrete beams and columns" in Latin American Journal of Solids and Structures, vol.11 no.7; Rio de Janeiro Dec. 2014.
[2]. H. Bomhard (1980), [1] "Lightweight concrete structures potentialities, limits and realities" The International Journal of Lightweight Concrete, Volume 2, No – 4 Dec, Page No. 193 - 196.
[3]. Celik Ozyildirim (2009), [2] "Durability of Structural Lightweight Concrete" published in ESCSI Special Workshop on Lightweight Aggregate Concrete Bridges that was held May 7, 2008, Page No. 1 - 14.
[4]. CPWD (2007), [3] "How to make building earthquake – safe" A white paper issued by and IIT- Madras which stated that Building structure must be well planned and simple and well interconnected to be sufficiently ductile to bear seismic disturbances.
[5]. C. V. R. Murty (2002), [4] "Some Concepts in Earthquake Behaviour of Buildings" a book published by Gujarat State Disaster Management Authority, shows the structural behaviour of various building members under various condition of seismic loading.

In any video surveillance applications moving object detection is an important and basic step. The detected object has been used as an input to higher level tasks such as event detection, object tracking and behavioral analysis. Several challenges such as illumination changes, occlusion, shadow, bootstrap, dynamic background etc. occur while detecting an object. It is very difficult to detect moving object when the background is moving. In this case, false detection occurs in which moving background is also detected as an object. In this paper, different techniques were implemented for detecting moving object fromthedynamic background and their qualitative and quantitative results are obtained.

Keywords: Background subtraction, dynamic background, Gaussian, moving object detection, video surveillance.

[1] C. Stauffer and W.E.L. Grimson,"Adaptive background mixture models for real-time tracking", Computer Vision and Pattern Recognition, IEEE Computer Society Conference, volume 2,1999.
[2] A. Elgammal, D. Harwood, and L. Davis, "Non-parametricModel for Background Subtraction", ECCV 2000, pages 751–767. Springer, 2000.
[3] M. Heikkila and M. Pietika,"A texture-based method for modeling the background and detecting moving objects," IEEE Trans. PatternAnal. Mach. Intell., vol. 28, no. 4, pp. 657– 662, Apr. 2006.
[4] J. Guo,C.Hsia,Min-Hsiung Shih, Y. Liu, and Jing-Yu Wu, "Fast Background Subtraction Based on a Multilayer Codebook Model for Moving Object Detection," vol. 23, no. 10, pp. 1809–1821, 2013.
[5] J. Xiang, H. Fan, H. Liao, J. Xu, W. Sun, and S. Yu, "Moving Object Detection And Shadow Removing Under Changing Illumination Condition", Mathematical Problems In Engineering, pp 1-10, February 2014.

The Traditional networking system follows the methodologies such as (i) aggregate routing, (ii) decentralized control. These two methodologies are used into achieve the scalability. In this networking concept is to achieve the (i) optimal network performance (ii) policy-based management. The policy-based management is performed via per-flow routing and centralized control. The centralized control is take the scalability challenge is used to some limitation concept like, (i) The ternary content addressable are limitedly used in the memory. (ii) Use the On-die memory (to store the forwarding table). (iii) The controllers, overhead position includes the per-flow communication/computation. In this SDN based concept provides a novel Hybrid Switching (HS) design. The Hybrid Switching (HS) combines the concepts like, (i) traditional switching, (ii) Software-Defined Network (SDN) switching.............

Keywords: Software-Defined Networks, scalable routing, flow table constraint, load balancing, approximation, Hybrid switching, decentralized control.

[1]. Nanyang Huang, Qing Li, Dong Lin, Xiaowen Li, Gengbiao Shen, Yong Jiang. "Software-Defined Label Switching: Scalable Per-Flow Control in SDN".
[2]. Veeramani Shamugam, I Murray, J A Leong and Amandeep S Sidhu. "Software Defined Networking challenges and future direction: A case study of implementing SDN features on OpenStack private cloud". IOP Conf. Series: Materials Science and Engineering 121 (2016) 012003 doi:10.1088/1757-899X/121/1/012003.
[3]. Arpitha T, Usha K Patil. "A Hybrid Hierarchica Contro Plane for Software-Defined Network".
[4]. Manju Lahare, Kauleshwar Prasad and Sudip Bhattacharya. "Software Defined Network". Research Journal of Computer and Information Technology Sciences. ISSN: 2320-6527. Vol. 5(7), 15-18, September-2017.
[5]. Sakir Sezer, Sandra Scott-Hayward, and Pushpinder Kaur Chouhan. "Implementation Challenges for Software-Defined Networks". 0163-6804/13/$25.00©2013 IEEE.

Melanoma is the most common type of skin cancer. At first, for the diagnosis of melanoma, clinical screening is performed and then diagnosis is made by clinical imaging. It is followed up by dermoscopic analysis, biopsy and histopathological examination. Early diagnosis is important in the treatment of melanoma. Automatic recognition of melanoma from dermoscopy images is a difficult task. Therefore, computer aided systems are recommended to reduce time ,cost and accuracy diagnosis. In this paper, a deep learning-based system is used to classify melanoma in color images taken from dermoscopy devices. With this system, differentiation from previous studies can be done with good accuracy without segmentation step and feature extraction.............

Keywords: Deep learning, image classification, melanoma, CNN.

[1]. Schmidhuber, J. (2015). Deep learning in neural networks: An overview. Neural Networks, 61, 85–117.
[2]. Yan, X., Tao, M., Qiwei, F., & others. (2014). Deep Learning Of Feature Representtation With Multiple Instance Learning For Medical Image Analysis. IEEE International Conference on Acoustic,Speech and Signal Processing(ICASSP), IEEE, 1626-1630.
[3]. Ying, W., & Rouzbeh, R. (2015). An Introduction to Deep Learning, Examining the Advantages of Hierarchical Learning.
[4]. Deng, L., & Dong, Y. (2014). Deep Learning Methods and Applications. Foundations and Trends Signal Processing , 7, 198-250.
[5]. Litjens, G., Kooi, T., Bejnordi, B. E., Setio, A.A.A., Ciompi, F., Ghafoorian, M., &S ánchez, C. I. (2017). A survey on deep learning in medical image analysis. Medical image analysis, 42, 60-88.

A Cloud storage service model generally demands security of data with least cost. Different Cloud computing security threats expected to be resolved Cloud environment incorporating Data Access Controllability, Data Confidentiality, and Data Integrity. This paper proposes the cost-aware Cloud storage system using information dispersal algorithm. This proposed system does not use the same as existing methodologies of replication to address data availability and security issues. The proposed system stores the file parts using redundant data encoded with erasure code on multi-cloud environment. This proposed system helps in recreating the user file even when certain threshold numbers of file parts are not available. The proposed approach provides storage of data with-in user‟s budget and empowers to recover user data if some natural or men made disaster occurs.

Keywords: Cloud computing, Information dispersal, Erasure code, Cloud data storage plan chart.

[1]. H. Xu ,D. Bhalerao, "Reliable and secure Distributed Cloud data storage using Reed Solomon codes", International Journal of Software Engineering and Knowledge Engineering ,(2015).
[2]. M.O.Rabin, "Efficient Dispersal of Information for Security,Load Balancing, and Fault Tolerance", Journal of the Association for Computing Machinery, April 1989.
[3]. L. B. Gomez, B. Nicolae, N. Maruyama, F. Cappello and S. Matsuoka, "Scalable Reed-Solomon-based reliable local storage for HPC applications on IaaS Clouds", in Proc. of the 18th International Euro-Par Conference on Parallel Processing (Euro-Par ‟12), Rhodes, Greece, August 2012, pp. 313-324.
[4]. O. Khan, R. Burns, J. Plank and W. Pierce, "Rethinking erasure codes for Cloud file systems: minimizing I/O for recovery and degraded reads", in Proc. of the 10th USENIX Conference on File and Storage Technologies (FAST-2012), San Jose, CA, USA, February 2012, pp. 20-33.
[5]. K. Hwang and D. Li, "Trusted Cloud computing with secure resources and data coloring", IEEE Internet Computing 14 (5) (2010) 14-22.

Wireless access networks like WiMAX provide an excellent opportunity for operators to participate in the rapid growth opportunities that exist in emerging markets. The mobile Worldwide Interoperability for Microwave Access (WiMAX) is based on IEEE 802.16 standard and is used for wireless Metropolitan Area Network (MAN). The inclusion of Multiple Input Multiple Output (MIMO) in mobile WiMAX system provides a robust platform for space, time and frequency selective fading conditions and increases both data rate and system performance. The performance of mobile MIMO WiMAX system has been carried out using Space Time Block Code for different modulation schemes under different channel conditions like AWGN, Rayleigh channels etc. The result are encouraging because with respect to other services the WiMax getting better responses in term of WiMAX's users and operators. The simulation of MIMO-mobile WiMAX model is done by using MATLAB.

[1]. IEEE Std 802.16TM-2004, "Part 16: Air interface for fixed broadband wireless access systems", October 2004
[2]. P.Samundiswary, Ravi Ranjan Prasad ," Performance Analysis of MIMO-Mobile WiMAX System using Space Time Block Codes under Different Channels", International Journal of Innovative Technology and Exploring Engineering (IJITEE) , Volume-2, January 2013 .
[3]. Sunil Singh* and RanjeetPrajapat" A Review WiMAX in Orthogonal Space Time Block Coding", International Journal of Electrical, Electronics and Computer Engineering, November, 2014.
[4]. IEEE Std 802.16a2003 (Amendment to IEEE Std 802.162001), "IEEE Standard for Local and etropolitan area networks Part 16: Air Interface for Fixed Broadband Wireless Access Systems Amendment 2: Medium Access Control Modifications and Additional Physical Layer Specifications for 211 GHz", January 2003Mobile.
[5]. WiMAX – Part I: A Technical Overview and Performance Evaluation, http://www.wimaxforum.org/technology/downloads/Mobile_WiMAX _Part1_Overview_and_Performance.pdf ,

Identifying node failures in multipurpose wireless networks is unrealistically troublesome because of the topology is extremely unique, the network may not be always associated, thus the assets are confined. All through this paper, we tend to have a tendency to require a probabilistic methodology and propose a couple of node disappointment recognition conspires that efficiently consolidate confined recognition, location estimation and node cooperation. Contrasted with methodologies that utilization brought together recognition, our methodology has up to eighty pace bring down correspondence overhead, and alone marginally bring down identification rates and somewhat higher false positive rates..............

Keywords: Network Tomography, Failure Localization, Identifiability Condition, Maximum Identifiability Index.

[1]. Liang Ma ; Ting He ; Ananthram Swami ; Don Towsley ; Kin K. Leung, Network Capability in Localizing Node Failures via End-to-End Path Measurements.IEEE/ACM Transactions on Networking ( Volume: 25, Issue: 1, Feb. 2017 )
[2]. A. E. Gamal, J. Mammen, B. Prabhakar and D. Shah, "Throughput-Delay Trade-off in Wireless Networks," Twenty-third Annual Joint Conference of the IEEE Computer and Communications Societies, INFOCOM 2004, vol.1, 2004.
[3]. 802.11e IEEE Std. Inform. Technol.–Telecommun. and Inform. Exchange Between Syst.-Local and Metropolitan Area Networks-Specific Requirements Part II: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: Amendment 8: Medium Access Control (MAC) Quality Service Enhancements, IEEE 802.11 WG, 2005.
[4]. Wei Liu, Nishiyama, Ansari, Jie Yang, Kato, "ClusterBased Certificate Revocation with Vindication Capability for Mobile Ad Hoc Networks", IEEE Transactions on Parallel and Distributed Systems, Vol.24, No.2, pp. 239 - 249, 2013.

Cellular Sensor Network is usually a network of little battery driven sensing devices (referred to as sensing nodes), with the capacity of sensing the physical parameters like temperature, humidity, pressure, motion, etc. from its environment of deployment and statement it to a central node called foundation station. These nodes collaborate with one another to satisfy their job. As the power source is usually constrained in WSNs, it must be used correctly. Clustering is among the methods which are becoming used effectively to reduce energy dissipation in WSNs. Clustering protocols result in improvement in the intake of energy, lower cost of conversation in the network and improved effectiveness. In this paper, we present an excellent grained study on LEACH centered hierarchical clustering protocols, specifically in a heterogeneous network where in fact the energy of the nodes is usually different and at the end we present assessment in tabular type, based on base station area, contribution, advantages, drawbacks and improvement accomplished with the compared protocols.

Keywords: Clustering, energy efficient, lifetime, heterogeneous; hierarchical, wireless sensor network.

[1]. I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E.Cayirci, "Wireless sensor networks: a survey," 2009 International Conference on Advanced Information Networking and Applications Workshops , Computer Networks, vol. 38, pp. 393-422, 2002.
[2]. Wendi B. Heinzelman, Anantha P. Chandrakasan, and HariBalakrishnan, "An Application-Specific Protocol Architecture for Wireless Microsensor Networks," IEEE transactions on wireless communications, vol. 1, no. 4, pp. 660-670, October 2002.
[3]. SudhanshuTyagia and Neeraj Kumar, "A systematic review on clustering and routing techniques based upon LEACH protocol for wireless sensor networks," Journal of Network and Computer Applications, vol. 36, no. 2, pp. 623–645, March 2013.
[4]. OlutayoBoyinbode, Hanh Le, Audrey Mbogho, Makoto Takizawa, and Ravi Poliah, "A Survey on Clustering Algorithms for Wireless Sensor Networks," in 13th International Conference on Network-Based Information System, 2010, pp. 358-364.
[5]. Vinay Kumar, Sanjeev Jain, and Sudarshan Tiwari, "Energy Efficient Clustering Algorithms in Wireless Sensor Networks: A Survey," International Journal of Computer Science Issues, vol. 8, no. 5-2, pp. 259-268, September 2011.

Recent technologies and developments on Wireless Body Area Networks (WBANs) emphasize remote control health monitoring and continuous, real-time individual care. WBAN is usually a challenging style concern. Since such systems contain small sensors positioned on the body, they impose source and computational limitations, therefore making the usage of advanced encryption algorithms infeasible. This hassles the algorithms with a robust important generation administration scheme, which are reasonably resource ideal. The main reason for the WBAN is definitely to create it easy for individuals who need long term monitoring to become fully cellular. The WBAN can be worn by an individual and basically includes a couple of lightweight products that monitor and wirelessly transmit particular bio signals (essential indicators) to a Backend Program at a Health care middle.............

Keywords: Healthcare, Healthcare applications, Implant communication, Low power MAC, Personal area networks, Physiological signal device, Sensor networks, WBAN applications.

[1] Adrian Perrig, Robert Szewczyk, J. D. Tygar, Victor Wen, and David E. Culler. "SPINS: Security protocols for sensor networks." Wireless networks 8, no. 5 (2002): 521-534.
[2] Ali Peiravi, and Maria Farahi. "Reliability of Wireless Body Area Networks used for Ambulatory Monitoring and Health Care." LifeScienceJoumal 7 (2005): 85.
[3] Ameen, M. A., Niamat UUah, and Kyungsup Kwak. "Design and analysis of a MAC protocol for wireless body area network using wakeup radio." In Communications and Information Technologies (ISCIT), 2011 11th International Symposium on, pp. 148-153. IEEE, 2011.
[4] Anirudh Natarajan, Mehul Motani, Buddhika de Silva, Kok-Kiong Yap, and K. C. Chua. "Investigating network architectures for body sensor networks." In Proceedings of the 1st ACM SIGMOBILE international workshop on Systems and networking supportfor healthcare and assisted living environments, pp. 19-24. ACM, 2007.