iosr-JECE   A Conference on Wireless Communication and Android Apps "WiCAA–15"

Abstract: Image recognition systems requiring a low recognition latency or high through-put could benefit from a hardware implementation. Furthermore, if the systems are applied in time-varying environments, evolvable hardware (EHW) would seem to be a promising approach. In the field of evolvable hardware systems, evolutionary algorithms (EA) are combined with reconfigurable devices to either automatically design or adapt hardware. Since all candidate circuits are generated by an embedded evolutionary algorithm and implemented by means of dynamic partial reconfiguration, enabling evaluation in the final hardware. The reconfiguration time and a suitable granularity of reconfiguration are the key factors that determine the overall performance of evolvable systems. Evolvable hardware system can be implemented on an array of processing elements (PEs). These arrays follow a systolic approach, and PEs does not contain extra logic thus performance speed is high. This Paper presents application of EHW in digital image filtering and edge detection. The evolved filters yield better quality than classic linear and nonlinear filters using mean absolute error as standard comparison metric Keywords - Evolvable Hardware, Image Recognition, Latency, Processing Element, Reconfiguration

[1] F. Cancare, M. Santambrogio, and D. Sciuto, "A Direct Bit stream Manipulation Approach for Virtex4-Based Evolvable Systems, "Proc. IEEE Int'l Symp. Circuits and Systems (ISCAS), pp. 853-856,2010. [2] J. Torresen, G.A. Senland, and K. Glette, "Partial Reconfiguration Applied in an On-line Evolvable Pattern Recognition System," Proc. NORCHIP, pp. 61-64, 2008. [3] A. Upegui, "Dynamically Reconfigurable Bio-inspired Hardware," PhD thesis, EPFL Lausanne, Thesis no. 3632, 2006. [4] F. Cancare, M. Santambrogio, and D. Sciuto, "A Direct BitstreamManipulation Approach for Virtex4-Based Evolvable Systems,"Proc. IEEE Int'l Symp. Circuits and Systems (ISCAS), pp. 853-856,2010. [5] K. Glette, "Design and Implementation of Scalable OnlineEvolvable Hardware Pattern Recognition Systems," PhD thesis,Univ. of Oslo, 2008.

Abstract: Video surveillance means to use cameras and other surveillance equipments to monitor properties and assets from a different location. In this paper ,I will be implementing video surveillance using wireless networks. The main objective is to create an application for interfacing surveillance camera with mobile device so that the manager/user of the company can have an eye on the staff. It is often used as a force multiplier or asset protection device for areas where it is not possible, practical, or affordable to install a cable network. It is commonly deployed in city and campus applications, or any place where it is difficult to monitor the surroundings using common means. Remote surveillance is a great opportunity to use wireless technologies for connectivity due to the flexibility they provide. A video surveillance system is only as reliable as the network it is connected to, so careful planning of the network technologies and equipment choices are crucial. Staff monitoring is the main result of this project which will help the manager/user to get a view of the happenings inside the company.

[1] Yusuf Simonson, Robert Fowler, Designing smart camera networks using smartphone platforms: a case study_ Renaissance Computing Institute,Chapel Hill, North Carolina 27517 Lobaton, Ron Alterovitzthe Departmentof Computer Science of The University of North Carolina.
[2] Dr. Peter L Fuhr, Wireless sensor systems: security implications for theindustrial environment
Rae Systems, Sunnyvale.
[3] Lauren Darcey, Shane Conder, Android wireless application development.
[4] Introduction to image and video compression.

Abstract: The quality testing and assurance has over the last decades increasingly gained importance and is one of the most important tasks in all areas of industrial production. Today industries produce more than thousand products at a time, testing of each and every product manually becomes difficult which ultimately decreases the speed, accuracy and leads to humans error. Thus manual inspection needs to be replaced by automated visual inspection. As it is the key factor behind all the industrial application of digital image processing. Automated visual inspection uses digital camera that captures image which is coming out of product line. The captured image is then fed to computer for further processing.

[1]. Gonzales, R.C. and R.E. Woods, "Digital Image Processing", Prentice Hall, Harlow, pp.: 954, ISBN: 013168728X,2008. [2]. Pedro, F.F., "Representation and detection of deformable shapes", IEEE T. Pattern Anal., 27(2):208-220, 2005.
[3]. C. L. Novak and S. A. Shafer, "Color edge detection," in Proc.DARPA Image Understanding Workshop, 1987, pp. 35–37. [4] Detection of Surface Defects on Sheet Metal Parts Using One-Shot Deflectometry in the Infrared Range, ZoltanSarosi, Wolfgang Knapp, Andreas Kunz, Konrad Wegener IWF, ETH Zurich, Switzerland.

Abstract: Wireless MANET Mobile AD-HOC Network is an emerging technology and have great strength to be applied in critical situations such as military applications, battlefields commercial and most important and critical applications. Every node in MANET has its own routing capability and free to move in any direction as it does not have centralized infrastructure. However, the open medium and wide distribution of nodes in MANET faces security. Chances of attack on MANET increases as wireless sensor nodes are in unattended environment; there are many types of attacks for example wormhole denial of service, black hole etc.; the DDOS is one of them. DDOS affects network by increasing routing load, end to end delay, packet drop and many other parameters. So it is very important to design and develop effective intrusion-detection system to protect MANET from DDOS attacks. In this paper, we discuss DDOS attack on MANET, and propose and implement a enhanced intrusion-detection system to detect DDOS type of attack and provide security against it using hybrid cryptology for acknowledged packets.

1] Elhadi M. Shakshuki, Senior Member, IEEE, Nan Kang, and Tarek R. Sheltami, Member, IEEE ―EAACK—A Secure Intrusion-Detection System for MANETs‖ IEEE Transactions on Industrail Electronics, VOL. 60, NO. 3, March 2013
[2] K. Liu, J. Deng, P. K. Varshney, and K. Balakrishnan, ―An acknowledgment-based approach for the detection of routing misbehaviourin MANETs,‖ IEEE Trans. Mobile Comput., vol. 6, no. 5,pp. 536–550, May 2007.
[3] S. Marti, T. J. Giuli, K. Lai, and M. Baker, ―Mitigating routing misbehaviourin mobile ad hoc networks,‖ in Proc. 6th Annu. Int. Conf. MobileComput. Netw., Boston, MA, 2000, pp. 255–265.
[4] T. Sheltami, A. Al-Roubaiey, E. Shakshuki, and A. Mahmoud, ―Videotransmission enhancement in presence ofmisbehaving nodes inMANETs,‖Int. J. Multimedia Syst., vol. 15, no. 5, pp. 273–282, Oct. 2009.[26]

Abstract: Almost in food/pharmaceutical industries there is a mounting need for quality, efficiency and machine environment monitoring systems. Moreover, so many industrial operation monitoring is necessary to record, analyze or control in order to have implementations of proper, cost-effective and wastage free or maintenance free Production and also to reduce repair/replacing overheads. Therefore, here "The Prolong Montroller System" using Wireless Technology is proposed as important system engineering.

[1] JIANG YongXiang, QIN LinLin, SHI Chun, WU Gang "Design and Implementation of the Measurement and Control System Based on CAN Bus in Modern Greenhouse" Chinese control conference, July 25-26,2012.
[2] C. Petrescu, C. Lupu, F.S. Tudor and M. Azzouzi, "Data Acquisition System for Recording of Photovoltaic Panel Power"2013 2nd International Conference on Systems and Computer Science (ICSCS)Villeneuve d'Ascq, France, August 26-27, 2013 IEEE 2013.
[3] Hongmin Wang , Zhu jie , XufeiNie and Dandan Li"Design of PIC microcontroller-based high-capacity multi-channel data acquisition module" 2012 International Conference on Measurement, Information and Control (MIC) IEEE 2012.
[4] AryuantoSoetedjo, Yusuf Ismail Nakhoda, Dana Suryadi "Development of Data Acquisition System for Hybrid Power Plant" IEEE 2013.

Abstract: Online social networks, such as Facebook, LinkedIn are increasingly use by many people. These networks allow users to give details about themselves and allow connecting to their friends. Some of the information visible inside these networks is meant to be private. It is possible to use learning algorithms on released data to predict private information. We explore how to launch inference attacks using released social networking data to predict private information. We devise three possible sanitization techniques that could be used in various situations. Then, we define the effectiveness of these techniques and attempt to use methods of collective inference to discover sensitive attributes of the data set. We also show that we can decrease the effectiveness of both local and relational classification algorithms by using the sanitization methods we described.

[1] R. Heatherly, M. Kantarcioglu, and B. Thuraisingham, Fellow "Preventing Private Information Inference Attacks on Social Networks" IEEE transactions on knowledge and data engineering ,VOL. 25, NO. 8, august, 2013.
[2] M. Hay, G. Miklau, D. Jensen, P. Weis, and S. Srivastava, "Anonymizing Social Networks," Technical Report 07-19,Univ. of Massachusetts Amherst, 2007.
[3] K. Liu and E. Terzi, "Towards Identity Anonymization on Graphs," Proc. ACM SIGMOD Int'l Conf. Management of Data (SIGMOD '08), pp. 93-106, 2008.
[4] J. He, W. Chu, and V. Liu, "Inferring Privacy Information from Social Networks," Proc. Intelligence and Security Informatics, 2006.

Abstract:Information Security has become important aspect now-a-days. For hiding secret information in images, there are various steganographic techniques. Some of them are more complex than others & all of them have strong & weak points. Algorithm for information hiding is design to obtain the three important parameters capacity, robustness & invisibility. This paper propose a novel reversible data hiding technique for digital color image. This technique guarantees effective retrieval of hidden data in color image without degradation in the quality of color image. The propose method makes use of Least Significant Bit (LSB) of three color channels that is red, green, and blue for embedding the secret data. The cryptographic methods are used to encrypt & decrypt the data to increase the security. The Genetic Algorithm (GA) is used for selection of optimized regions for hiding multiple data files.

[1] Kede Ma, Weiming Zhang, Xianfeng Zhao, Nenghai Yu, and Fenghua Li, "Reversible data hiding in encrypted images by reserving room before encryption," IEEE Transactions on Information Forensics And Security, vol. 8, no. 3, pp. 553-562, March 2013
[2] W. Zhang, B. Chen, and N. Yu, "Improving various reversible data hiding schemes via optimal codes for binary covers," IEEE Trans.Image Process., vol. 21, no. 6, pp. 2991–3003, June. 2012.
[3] J. Fridrich, M. Goljan, and D. Rui, "'Invertible Authentication", In Proc. of SPIE Photonics West, Security and Watermarking of Multimedia Contents III, San Jose, California, USA, Vol. 3971, pp. 197-208, January 2001.
[4] J. Tian, "Reversible data embedding using a difference expansion,"IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 8, pp. 890–896,August. 2003.
[5] . Ni, Y. Shi, N. Ansari, and S. Wei, "Reversible data hiding," IEEE Trans. Circuits Syst. Video Technol., vol. 16, no. 3, pp. 354–362, March.2006.

Abstract: This project is based on the concept of "Region-based Crop and Plant disease detection System". It has a social aspect as the resultant project will be used as a utility for the Farmers. Technical aspects include the processing of the image of an object placed in front of camera. Many of the image processing measures will be utilized during the implementation of the project like image capturing, pre-processing, storing in database, comparison from database etc. On a successful match, the Voice processing feature will activate and a word corresponding to the object will be heard. Also the designed system will provide additional information regarding the objects. The project will also utilize the internet facility to retrieve the object information. Implementation on detecting and recognizing an object and it voice display is the main focus of the project. Keywords -Edge detection, Image processing, CBIR, Color histogram

[1] Jayamala K. Patil, Raj Kumar, [2011] ―Advances in image processing for detection of plant
diseases‖, Journal of Advanced Bioinformatics Applications and Research ISSN 0976-2604 Vol 2, Issue 2, pp 135-141
[2] Y Liua, D Zhanga, G Lua,Wei-Ying Mab, ―Asurvey of content-based image retrieval with high-level semantics‖, Pattern Recognition 40 (2007),pp. 262 – 282.
[3] H Müller, N Michoux, D Bandon, A Geissbuhler, ―A review of content-based image retrieval systems in medical applications–clinical benefits and future directions‖, International Journal of Medical Informatics (2004) 73, pp. 1—23.
[4] H.-W. Dehne, G. Adam, M. Diekmann, J. Frahm, A. Mauler-Machnik, P. van Halteren, ―Diagnosis and Identification of Plant Pathogens (Developments in Plant Pathology)‖, October 31, 1997, Edition-1, pp 1-4.
[5] H Al-Hiary, S Bani-Ahmad, M Reyalat, M Braik and Z ALRahamneh, ―Fast and Accurate Detection and Classification of Plant Diseases‖, International Journal of Computer Applications 17(1): pp. 31-38, March 2011. Published by Foundation of Computer Science.

Abstract: Space-time adaptive processing (STAP) is a signal processing technique most commonly used in radar systems. It involves adaptive array processing algorithms to aid target detection. Radar signal processing uses STAP in areas where interference is a problem (i.e. ground clutter, jamming, etc.). In Space-time adaptive processing the primary aim of the processor is to remove the effects of clutters, jammers etc. from the received signal and to make the signal useful. For this purpose filters are used. There are different methods for filtering out the unwanted signals from received signal. In this paper different approaches to STAP depending upon various factors like strength of the received signal, application area, computational easiness, etc. are explained in detail. The performance of different algorithms are compared and analyzed based on complexity, detection of signal, degrees of freedom etc. Once an algorithm is selected according to our needs, then a processor can be developed using this and many processors can be combined and embedded in the system to make the whole process object detection easier. Keywords -STAP, Clutter Suppression, Clutter Subspace, Jammer Subspace, Subspace Projection

[1] L. E. Brennan and L. S. Reed, ―Theory of adaptive radar‖, Aerospaceand Electronic Systems, IEEE Transactions on, vol. AES-9, no. 2, pp.237–252, 1973.
[2] J. Ward, ―Space-Time Adaptive Processing for Airborne Radar‖, Technical Report 1015, MIT LincolnLaboratory, Lexington, MA, USA, 1994 (available: http://handle.dtic.mil/100.2/ADA293032)
[3] D. Rabideau and A. Steinhardt, ―Improved Adaptive Clutter Cancellation through Data-Adaptive Training‖, IEEE Transactions on Aerospace and Electronic Systems, vol. 35, no. 3 (1999), pp. 879-891
[4] A. M. Haimovich and Y. Bar-Ness, ―An Eigen analysis interference canceller‖, Signal Processing, IEEE Transactions on, vol. 39, no. 1,pp. 76–84, 1991.
[5] A. Haimovich, ―The Eigen canceller: adaptive radar by Eigen analysis methods‖, Aerospace and Electronic Systems, IEEE Transactions on,vol. 32, no. 2, pp. 532–542, 1996.
[6] A. M. Haimovich and M. Berin, ―Eigen analysis-based

Abstract: Location-based technologies allow users with increasing, interconnected location- based data services with each other and with the Internet.GeolocationImplementation can be deriving at many different points in an application request's lifecycle. To understand the extreme rate through the largest range of use cases, collection of geolocationinformation is bestcompetentlyderived when a demand is first made for a given resource.Accurately determining the geographic location of an Internet host is important for location-based applications such as location-based publicity and network diagnostics. Despite their fast response time, widely used database-driven geolocation approaches provide only inaccurate locations.In this paper, we propose an efficient methodology for Reliability Analysis of Client-independent Intenet Protocol Geolocation,which can be very helpful for evolution in Advertising, weather forecast, crime scene investigation, android mobile applications and many more. Keywords: Geolocation, Geolocation Applications,Geolocation Techniques

[1] Ionescu, Daniel. "Geolocation 101: How It Works, the Apps, and Your Privacy". PCWorld.Retrieved March 29, 2010. [2] http://en.wikipedia.org/wiki/Geolocation [3] Skyhook. http://www.skyhookwireless.com/. [4] S. S. Intille, K. Larson, E. Tapia, et al. Using a Live-in Laboratory for Ubiquitous Computing Research. In Pervasive, 2006. [5] Google Maps with My Location. http://www.google.com/ mobile/gmm/mylocation/index.html . [6] Y. Wang, D. Burgener, M. Flores, A. Kuzmanovic, and C. Huang.Towards Street-level Client-independent IP Geolocation.In NSDI, 2011.

Abstract: Mobility prognostication for individual way is a fascinating topic. Mobility foretelling in Mobile River advertizement -hoc meshing is a simpleton and effective dodging to predict when the exploiter will leave from the current emplacement and where he will move to next future position. The prediction of the mobility of node s in mobile ad hoc networks becomes a key solution for the delivery of data in real time operations; which enables the reclamation of the path s just prior to the modify of the topology which occurs a seamless and well-organized data delivery that meet the expected value of the real time constraints. The mobility prediction is very significant for equally homogeneous networks and heterogeneous networks, determined by applications in mobility management, smooth handoffs, shout admission control, and resource reservation for improved timber of serving. One way to reference the truth of node mobility is devising proactive solvent that make use of mobility prediction algorithms to estimate the cause of the nodes. At the application level, drug user mobility prediction in combination with user's profile may provide the user with enhanced location-based wireless services, such as route counsel, local traffic info and on-line advertising. In this newspaper we present the most significant mobility prediction techniques for Edouard Manet focusing on their major design rule and description.

[1] Yohan Chon, Elmurod Talipov, Hyojeong Shin, and Hojung Cha,"SmartDC: Mobility Prediction-based AdaptiveDuty Cycling for Everyday Location Monitoring", IEEE Trans. Mobile Comput., Volume:PP , Issue: 99,Jan. 2013.
[2] Sebastien Gambs, Marc-Olivier Killijian, "Next Place Prediction using Mobility Markov Chains", ACM MPM'12,April 2012.
[3] Basu, P., Khan, N. & Little, T. (2001). A Mobility Based Metric for Clustering in Mobile Ad Hoc Networks. Proc. of the 21st International Conference on Distributed Computing Systems Workshops (ICDCSW '01), 413–418.
[4] Camp T., Boleng, J. & Davies, V. (2002). A Survey of Mobility Models for Ad Hoc Network Research. Wireless Communication & Mobile Computing (WCMC): Special issue on Mobile Ad Hoc Networking: Research, Trends, Applications. Vol. 2(5), 483–502
[5] Chellapa-Doss, R., Jennings, A. & Shenoy, N. (2003a). User Mobility Prediction in Hybrid and Ad Hoc Wireless Networks. Proc. of