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This paper gives the one of the best solution for the video surveillance in the fire detection. In the market there are most popular two software tools are used to detect the fire and smoke that are “VPlayer” for the fire and smoke detection and another one is “Precise Vision Fire Detection Graphics System” is these system one of the major drawback comes that is, user can get some times false positive result. And in this proposed system we try to reduce the false positive result. And in this system the technique involves fire features, fuzzy logic. And this proposed system is totally software based not any embedded system is used here.

RGB Model, Temperal Difference, Fire Morphology, Fuzzy Logic

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[9] Liang-Hua Chen, Wei-cheng Haung, “Fire Detection Using Spatial-Temporal Analysis,” in World Congress on Engineering, volume III, 2013, pp. 2078-0958.

Mangesh S. Tambat, Namrata Kodre, Shubhangi Shelke, Kimaya Chavan, Laxman Deokate, "An Efficient Framework for Fire Detection using Morphological Features," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.118-124, 2016.

Data and objects in databases often contain detailed information at primitive concept levels. It is useful to summarize a large set of data and present it at a high conceptual level. Attribute Oriented Induction(AOI) is a set-oriented data base mining method which generalizes the task-relevant subset of data attribute-by-attribute compresses it into a generalized relation and extracts from it the general features of data. The power of AOI is extraction from relational databases of different kinds of patterns including characteristic rules, discriminant rules, cluster description rules and multilevel association rules. The method is efficient, robust with wide applications and extensible to knowledge discovery in advanced database systems, including object-oriented, deductive and spatial database systems. This paper describes the broad classification of data mining techniques using AOI.

AOI, Clustering, Data mining, generalization

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Relevance Analysis”,International Journal of Computer Theory and Engineering, Vokume 2,No.4,August 2010,1793-8201.
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[13] Lukas Tanutama.,” Frequency Count Attribute Oriented Induction of Corporate Network Data for Mapping Business Activity” ;EPJ Web of Conferences;2014.
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[16] Spits Warnars.,” Mining Frequent and Similar Patterns with Attribute Oriented Induction High Level Emerging Pattern (AOI-HEP) Data Mining Technique”, International Journal of Emerging Technologies in computational and Applied Sciences(IJETCAS), 266-276,2015.
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Transactions on Knowledge and Data Engineering, Vol,26,No.8,Aug 2014.
[18] Rafal A.Angryl, Jacck Czerniak, “Heuristic algorithm for interpretation of multi-valued attributes in similarity-based fuzzy relational databases”, International Journal of Approximate Reasoning,2010.
[19] J.Isabella and Dr.R.M.Suresh,”Analysis and evaluation of feature selectors in opinion mining”, International Journal of Computer Science and Engineering”,Vol.3,No.6,Dec 2012-jan 2013.

S. Radha Priya and M. Devapriya, "Survey on Attribute Oriented Induction Using Data Mining Techniques," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.125-129, 2016.

High-speed and satellite networks are emerging fast in the communication domain. Bandwidth Delay Products (BDP) plays an important role in the design of a congestion control algorithm for the effective usage of network resources. Bandwidth-delay products (BDPs) are referred as the maximum amount of unacknowledged data that allowed in flight at any moment in the network. TCP is originally designed for a general wired network. In case of BDP, packet losses rarely occur. TCP can no longer guarantee good bandwidth utilization. For MANETs having extremely small BDPs and frequent packet losses cannot use the existing transport protocol. Numerous solutions proposed to provide reliable packet delivery in MANETs in recent years. Solutions proposed to provide reliable packet delivery in MANETs are non-TCP variants and TCP variants. Non-TCP variants focus on the modification of congestion control algorithms in the transport protocol. It requires complicated mathematical computation and incur excessive network overhead. Although relatively accurate congestion information obtained, it cannot retain the end-to-end semantics of a transport protocol. TCP variants adopts Additive Increase Multiplicative Decrease (AIMD) congestion control algorithm with unnecessary large transmission windows. The proposed model develops an improved Datagram Transport Protocol over Ad Hoc Networks (DTPA) for MANETs. The improvement is carried out in the direction of achieving fairness in the TCP flow of the MANET. Adaptive Max-Min Fairness algorithm is deployed in the proposed DTPA improvement. The proposal work provides an effective datagram-oriented end-to-end reliable transport protocol DTPA (Datagram Transport Protocol over Ad Hoc Networks) incorporating, a fixed-size window- based flow-control algorithm and a cumulative bit-vector-based SACK (selective ACK) strategy. The proposal also guarantees reliable transmission and recovering packet losses. It improves the network performance in terms of throughput, round-trip time, number of retransmissions, and IP queue size demonstrated by simulation conducted using NS2.

[1] sSarah Riahi Ali El Hore and Jamal El Kafi, “Optimization of Resource Allocation in wireless systems based on Game Theory”, Int. Journal of Computer Sciences and Engineering, Volume-04, Issue-01, Page No (1-13), Jan 2016.
[2] Chen K Xue Y and Nahrstedt K, “On Setting TCP’s Congestion window Limit in Mobile Ad Hoc Networks,” Journal of Wireless Comm. and Mobile Computing, volume -02, Issue-01, Page No (85-100), 2002.
[3] Umesh K S , Shivlal M , Lokesh L and Kamal B , “An Overview & Study of Security Issues in Mobile Ado Networks”, International Journal of Computer Science and Information Security (IJCSIS) USA, Vol-9, No.4, pp (106-111), April 2011.
[4] Anastasi G Ancillotti E Conti M and Passarella A, “TPA: A Transport Protocol for Ad Hoc Networks,” Proc. 10th IEEE Symp. Computers and Comm. (ISCC ’05), Page No (51-56), 2005.
[5] Chen K Nahrstedt K and Vaidya N, “The Utility of Explicit Rate-Based Flow Control in Mobile Ad Hoc Networks,” Proc. IEEE Wireless Comm. and Networking Conf. (WCNC ’04), no. 1, Page No (1904-1909), 2004.
[6] Zhai H Chen X and Fang Y, “Rate-Based Transport Control for Mobile Ad Hoc Networks,” Proc. IEEE Wireless Comm And Networking Conf. (WCNC ’05), Page No (2264-2269), 2005.
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[8] Fu Z Greenstein B Meng X and Lu S, “Design and Implementation of a TCP-Friendly Transport Protocol for Ad Hoc Networks”, Proc. 10th IEEE International Conf. Network Protocols (ICNP ’02), Page No ( 216-225), 2002.
[9] EIRakabawy S Klemm A and Lindemann C, “TCP with Adaptive Pacing for Multihop Wireless Networks,” Proceedings of ACM MobiHoc ’05, Page No (288-299), 2005
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[13] Kettimuthu R and Allcock W, “Improved Selective Acknowledgment Scheme for TCP,” Proceedings of Int’l Conf. Internet Computing (IC ’04), Page No (913-919), 2004.
[14] Mathis M Mahdavi J Floyd S and Romanow A, “TCP Selective Acknowledgement Options”, IETF RFC 2018, 1996.

M. Senthil Kumaran, "Adaptive Datagram Transport Protocol Over Ad-hoc Network – TCP Fairness," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.130-134, 2016.

The integration of wireless sensor network (WSN) and Mobile cloud computing (MCC) is a research topic that is attracting growing interest in both academia and industry. In this new paradigm, WSN provides data to the cloud, and mobile users request data from the cloud. This paper first identifies the critical issues that affect the usefulness of sensory data and the reliability of WSN, then proposes a novel WSN-MCC integration scheme named TPSS, which consists of two main parts: 1) TPSDT (Time and Priority based Selective Data Transmission) for WSN gateway to selectively transmit sensory data that are more useful to the cloud, considering the time and priority features of the data requested by the mobile user; 2) PSS (Priority-based Sleep Scheduling) algorithm for WSN to save energy consumption so that it can gather and transmit data in a more reliable way.

Wireless sensor networks, mobile cloud computing, integration, usefulness, reliability

[1] I. F. Akyildiz, W. Su, Y. Sankara subrama niam, and E. Cayirci, “Wireless sensor networks: a survey,” Comput. Netw., vol. 38, no. 4, pp. 393–422, Mar. 2002.
[2] Shamneesh Sharma, Dinesh Kumar and Keshav Kishore, "Wireless Sensor Networks- A Review on Topologies and Node Architecture", International Journal of Computer Sciences and Engineering, Vol.-01(2), pp. (19-25), Oct -2013
[3] C. Zhu, V. C. M. Leung, X. Hu, L. Shu, and L. T. Yang, “A review of key issues that concern the feasibility of mobile cloud computing,” in Proc. IEEE Int. Conf. Cyber, Phys. and Soc. Comput. (CPSCom), 2013, pp. 769–776
[4] A. Benharref and M. A. Serhani, “Novel cloud and soa-based framework for e-health monitoring using wireless biosensors,” IEEE J. Biomed. Health Inform., vol. 18, no. 1, pp. 46–55, Jan. 2014.
[5] L. D. P. Mendes, J. J. P. C. Rodrigues, J. Lloret, and S. Sendra, “Cross-layer dynamic admission control or cloud-based multimedia sensor networks,” IEEE Syst. J., vol. 8, no. 1, pp. 235– 246, Mar. 2014.
[6] A. Alamri, W. S. Ansari, M. M. Hassan, M. S. Hossain, A. Alelaiwi, and M. A. Hossain, “A survey on sensor-cloud: Architecture, applications, and approaches,” Int. J. Distrib. Sens. Netw., pp. 1–18, 2013.

[7] F. Wang, J. Liu, and M. Chen, “Calms: Cloud-assisted live media streaming for globalized demands with time/region diversities,” in Proc. IEEE Int. Conf. Comput. Commun. (Infocom), 2012, pp. 199–207.
[8] F. Hu, Y. Xiao, and Q. Hao, “Congestion-aware, loss-resilient bio-monitoring sensor networking for mobile health applications,” IEEE J. Sel. Areas Commun., vol. 27, no. 4, pp. 450–465, May 2009.
[9] C. Zhu, H. Wang, X. Liu, L. Shu, L. T. Yang, and V. C. M. Leung, “A novel sensory data processing framework to integrate sensor networks with mobile cloud,” IEEE Syst. J., 2014.
[10] R. Arroyo-Valles, A. G. Marques, and J. Cid-Sueiro, “Optimal selective transmission under energy constraints in sensor networks,” IEEE Trans. Mobile Comput., vol. 8, no. 11, pp. 1524– 1538, Nov. 2009
[11] C. Zhu, L. T. Yang, L. Shu, J. J. P. C. Rodrigues, and T. Hara, “A geographic routing oriented sleep scheduling algorithm in duty-cycled sensor networks,” in Proc. IEEE Int. Conf. Commun. (ICC), 2012, pp. 7001–7005.
[12] Er. Satish Kumar, "A Study of Wireless Sensor Networks- A Review", International Journal of Computer Sciences and Engineering, Volume-04, Issue-03, Page No (23-27), Mar -2016, E-ISSN: 2347-2693

Mahantesh Mathapati, Kavita K. Patil, Jyoti Metan, Chandramohan B, "“Sensor-cloud”: Offering Useful Data Reliably to Mobile Cloud from Wireless Sensor Network," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.50-139, 2016.

Recent wireless sensor networks (WSNs) are becoming increasingly complex with the growing network scale and the dynamic nature of wireless communications. Many measurement and diagnostic approaches depend on per-packet routing paths for accurate and fine-grained analysis of the complex network behaviors. In this paper, we propose a Path, a novel path inference approach to reconstructing the per-packet routing paths in dynamic and large-scale networks. The basic idea of the Path is to exploit high path similarity to iteratively infer long paths from short ones. The Path starts with an initial known set of paths and performs path inference iteratively. In order to further improve the inference capability as well as the execution efficiency, it includes a fast bootstrapping algorithm to reconstruct the initial set of paths. We also implement the Path and evaluate its performance using traces from large-scale WSN deployments as well as extensive simulations. Results show that it achieves much higher reconstruction ratios under different network settings compared to other state-of- the-art approaches.

Measurement, path reconstruction, wireless sensor Network

[1] R.Nathiya and S.G.Santhi, "Energy Efficient Routing with Mobile Collector in Wireless Sensor Networks (WSNs)", International Journal of Computer Sciences and Engineering, Volume-02, Issue-02, Page No (36-43), Feb -2014
[2] Emara, K. A. A. E. S. Integrating Wireless Sensor Networks with IP-based Network. Diss. Masters Thesis. Department of Computer Science, Ain Shams University, Cairo, 2009.
[3] Vergados, Dimitrios J., Nikolaos A. Pantazis, and Dimitrios D. Vergados. "Energy-efficient route selection strategies for wireless sensor networks." Mobile Networks and Applications 13.3-4 (2008): 285-296.
[4] Doherty, Lance, Jonathan Simon, and Thomas Watteyne. "Wireless sensor network challenges and solutions." Microwave Journal 55.8 (2012): 22-34.
[5] Shamneesh Sharma, Dinesh Kumar and Keshav Kishore, "Wireless Sensor Networks- A Review on Topologies and Node Architecture", International Journal of Computer Sciences and Engineering, Volume-01, Issue-02, Page No (19-25), Oct -2013
[6] Akyildiz, Ian F., and Ismail H. Kasimoglu. "Wireless sensor and actor networks: research challenges." Ad hoc networks 2.4 (2004): 351-367.
[7] Samanta, Tuhin Subhra. Routing in Dynamic Tree Based Sensor Network. Diss. 2012.

Payel Ray, Ranjan Kumar Mondal, Debabrata Sarddar, "Efficient Path Reconstruction for Wireless Sensor Network," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.140-146, 2016.

Lung nodules are small masses in the human lung and are usually spherical however they can be distorted by surrounding anatomical structures such as vessels and adjacent pleura. There are different methods evolved for the detection of lung nodules. In this paper, different techniques that are used for the detection of lung nodules are introduced.

Juxtra-Pleural;Nodule;Pleural-Tail;Vascularized;Well-Circumscribed

[1] A. Farag, A. Ali, J. Graham, S. Elshazly, and R. Falk, “Evaluation of geometric feature descriptors for detection and classification of lung nodules in low dose CT scans of the chest”, in Proc. ISBI,pp 169–172, 2011.
[2] K. Kanazawa, Y. Kawata, N. Niki et al., (2012), “Computer-aided diagnosis for pulmonary nodules based on helical CT images”, Computerized Medical Imaging and Graphics, vol-22, no-2, pp 157–167, 1998.
[3] K. Suzuki, S. G. Armato, F. Li, S. Sone, and K. Doi, “Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography”, Medical Physics, vol-30, no-7,pp 1602–1617, 2003.
[4] Y. Mekada, T. Kusanagi, Y. Hayase et al., “Detection of small nodules from 3D chest X-ray CT images based on shape features,” In Proceedings of the Computer Assisted Radiology and Surgery (CARS), vol-1256, pp 971–976, 2003.
[5] D. S. Paik, C. F. Beaulieu, G. D. Rubin et al., “Surface normal overlap: a computer-aided detection algorithm with application to colonic polyps and lung nodules in helical CT”, IEEE Transactions on Medical Imaging, vol-23, no-6, pp 661–675, 2004.
[6] A Roozgard et al., “Malignant Nodule Detection on Lung CT Scan Images with Kernel RX algorithm”, proc. IEEE-EMBS International Conference on Biomedical and Health Informatics, pp 449-502, 2012.
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[8] Amal Farag er.al, “An AAM Based Detection Approach of Lung Nodules from LDCT scans”, IEEE, pp 1040-1043, 2012.
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[10] Si Guang-lei et al., “A Novel Method for Lung Nodule Segmentation Based on CT Images”, proc. 2nd IEEE International Conference on Applied Robotics for the Power Industry, pp 826-830, 2012.
[11] Maria Evelina et al., “Algorithms for automatic detection of lung nodules in CT scans”, IEEE International Workshop on Medical Measurement and Applications, MEMEA, 2011.
[12] V.G Aswathy and Mrs.T.Johncy Rani,” A Supervised Lung Nodule Classification method using patch based context analysis in LDCT image,” International Journal of Engineering Research and General Science Volume 3, Issue 1, January-February, 2015 ISSN 2091-2730.

Abhinao A Somnathe, Devendra G Ingale, "Lung Nodule Detection Methods," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.147-149, 2016.

Since the demand for data storage is increasing day by day and by the industry analysis we can say that digital data is increasing gradually, but the storage of redundant data is excess which results in most of the storage used unnecessary to keep identical copies. So this survey paper introduces various de-duplication techniques to efficiently utilize the cloud storage system.

Cloud Computing, De-Duplication, Cloud Storage, Data Availability, Data Integrity, Confidentiality, Authorization, Cloud Service Provider

[1]NIST Cloud Computing Standards Roadmap Working Group NIST Cloud Computing Program Information Technology Laboratory.
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Rajani Sajjan, Gayatri Chavan, Vijay R. Ghorpade, "Survey on De-Duplication Techniques at Public Cloud," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.150-152, 2016.

This study proposes an intelligent traffic light system that would be capable of adjusting the traffic light based on density of traffic at a particular time. Fuzzy logic could be used to manage the flow of vehicles at traffic signals and ensure efficient flow of vehicles, reducing traffic congestions at peak time. This could be done by analyzing traffic density by analyzing inputs via sensor that could be fitted at signals. This will then be used by microcontroller to set the green signal for varying intervals of time so as to clear the traffic at signals as efficiently as possible. This approach could be implemented to dynamically manage the traffic signal and would prove efficient to help reduce the day to day traffic congestion problems. This study mainly aims to overcome this problem.

Arduino Mega 2560 microcontroller, Embedded software, Fuzzy logic, Fuzzy control, Ultrasonic transducers, Zigbee

[1] Md. Shabiul Islam, ; M. S. Bhuyan ; Md. Anwarul Azim ; L. k. Teng, “Hardware Implementation of Traffic Controller using Fuzzy Expert System” in IEEE conference Multimedia University Malaysia, E-ISBN : 0-7803-9719-3, September 2006.
[2] Bilal Ahmed Khan, Nai hyan Lai, “An Intelligent Traffic Controller Based on Fuzzy Logic” in AsiaPacific University of Technology and Innovation, ISBN: 978-0-9853483-8-0 ©2013 SDIWC, 1996.
[3] Ms. Promila Sinhmar, Rawal Institute of Engineering And Technology Zakopur “Intelligent Traffic Light And Density Control Using IR Sensors And Microcontroller” in International Journal of Advanced Technology & Engineering Research (IJATER), ISSN NO: 2250-3536, 2012.
[4] Monish Puthran, Sangeet Puthur, and Radhika Dharulkar “Smart Traffic Signal” in (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 6 (2), 2015, 1360-1363, 2015.
[5] Ashwini Basavaraju, Senhalata Doddigarla, Navitha Naidu, Shruti Malgatti “Vehicle density sensor system to manage traffic” in IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308, 2014.
[6] Abdelrasoul Jabar Alzubaidi, Arwa Abdel Mohsen Ahmed Hassan, “Design of semi-automatic traffic light control system” in International Journal Of Scientific & Technology Research Volume 3, Issue 10, October 2014 Issn 2277-8616, 2014.

Yashodhan Kumthekar, Ankit Narendra Patil, Yash Notani, Jayshri Fating, Soumitra Das, "Traffic Signal Optimization and Flow Control using Fuzzy Logic," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.153-156, 2016.

In wireless multi-hop sensor networks, an intruder may launch some attacks due to packet dropping in order to disrupt the communication. To tolerate or mitigate such attacks, some of the schemes have been proposed. But very few can effectively and efficiently identify the intruders. The Packet Droppers and Modifiers are common attacks in wireless sensor networks. It is very difficult to identify such attacks and this attack interrupts the communication in wireless multi-hop sensor networks. Today wireless communication technique has become an essential tool in any application that requires communication between one or more sender(s) and multiple receivers. Since multiple users can use this technique simultaneously over a single channel, security has become a huge concern. Even though there are numerous ways to secure a wireless network and protect the network from numerous attacks, providing 100% security and maintaining confidentiality is a huge challenge in recent trends. This paper is all about various attacks that can affect WSN. Some attacks disturb nodes, some disturbs network, some drops packets, some theft information. Different remedies and precautions are taken to overcome different attacks.

WSN, Node, Routing, Attack

[1] Er. Satish Kumar, "A Study of Wireless Sensor Networks- A Review", International Journal of Computer Sciences and Engineering, Volume-04, Issue-03, Page No (23-27), Mar -2016
[2] Shamneesh Sharma, Dinesh Kumar and Keshav Kishore, "Wireless Sensor Networks- A Review on Topologies and Node Architecture", International Journal of Computer Sciences and Engineering, Volume-01, Issue-02, Page No (19-25), Oct -2013
[3] Sonam Jai, Deepak Singh Tomar and Rachana Kamble, "Survey of Attacks and Security Schemes in Wireless Sensor Network", International Journal of Computer Sciences and Engineering, Volume-03, Issue-05, Page No (122-128), May -2015
[4] N.Vanitha1, G.Jenifa, “Detection of Packet Droppers in Wireless Sensor Networks Using Node Categorization Algorithm”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 3, March 2013
[5] A. Babu Karuppiah1* and S. Rajaram, “False Misbehavior Elimination of Packet Dropping Attackers during Military Surveillance using WSN”, Advances in Military Technology, Vol. 9, No. 1, June 2014
[6] S.Ranjitha and D. Prabakar and S. Karthik, "A Study on Security issues in Wireless Sensor Networks", International Journal of Computer Sciences and Engineering, Volume-03, Issue-09, Page No (50-53), Sep -2015
[7] Devdatt Nadre, Balaso N. Jagdale, “Security for Source Node Privacy in Wireless Sensor Network”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 5, Issue 2, February 2015

Amandeep Kaur and Sandeep Singh Kang, "Attacks in Wireless Sensor Network- A Review," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.157-162, 2016.

The text-based password has been the default security medium for years. However, the difficulty of memorizing secure strong passwords often leads to insecure practices. In this fast computer era, the Internet users are increasing on each second. Now mostly people are using different online service provided by Banks, Schools, Hospitals, online utility bill payment and online shopping sites. The text-based authentication scheme faces some drawbacks with usability and security issues that bring troubles to users. For example, if the user is not intelligently constructed the password with extra security measures, it is very easy for hacker to hack. On the contrary, if a password is hard to guess, then it is often hard to remember. A person has to memorize as many passwords as many different websites he/she is using. So he/she gets confused and/or forgets the correct user Id/password combinations. We should have an alternative system to overcome these problems. In this paper, a comprehensive study of existing graphical password scheme and shoulder surfing problem is performed. The best way in One Time Password authentication is proposed for enhancement in security and privacy.

One Time Password (OTP), Authentication, Usability, Security, Shoulder Surfing

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Salim Istyaq, Lovish Agrawal , "A New Technique For User Authentication Using Numeric One Time Password Scheme," International Journal of Computer Sciences and Engineering, Vol.4, Issue.5, pp.163-165, 2016.