iosr-JCE   International Conference on RECENT TRENDS IN ENGINEERING AND MANAGEMENT

Abstract: Fingerprint-based methods are widely adopted for indoor localization purpose because of their cost-effectiveness compared to other infrastructure-based positioning systems. However, the popular location fingerprint, Received Signal Strength (RSS), is observed to differ significantly across different devices' hardware even under the same wireless conditions. We derive analytically a robust location fingerprint definition, the Signal Strength Difference (SSD), and verify its performance experimentally using a number of different mobile devices with heterogeneous hardware. Our experiments have also considered both Wi-Fi and Bluetooth devices, as well as both Access-Point (AP)-based localization and Mobile-Node (MN)-assisted localization. Also compare these SSD-based localization algorithms' performance against that of two other approaches in the literature that are designed to mitigate the effects of mobile node hardware variations, and show that SSD-based algorithms have better accuracy. To justify this we make a data transfer between the nodes using the SSD-based and it proves the accuracy.

[1]. P. Tao, A. Rudy's, A.M. Ladd, and D.S. Wallach, Wireless LAN Location-Sensing for Security Applications, Proc. Second ACM Workshop Wireless security, Wise 03, pp. 11-20, Sept. 2003.
[2]. M.B.Kjaergaard, Indoor Location Fingerprinting with Heterogeneous Clients, Pervasive and Mobile Computing, vol. 7, no. 1, pp. 31-43, Feb. 2011.
[3]. C.-T. Huang, C.-H.Wu, Y.-N. Lee and J.-T. Chen, A Novel Indoor RSS-Based Position Location Algorithm Using Factor Graphs, IEEE Trans. Wireless Comm., vol.8, no. 6, pp. 3050- 3058, June 2009.
[4]. M.B. Kjærgaard and C.V. Mink, Hyperbolic Location Fingerprinting: A Calibration-free Solution for Handling Differences in Signal Strength, Proc. IEEE Sixth Ann. Int'l Conf. Pervasive computing and Comm. (PerCom '08), Mar. 2008.
[5]. M. Hossain, W.S. Soh, A Comprehensive Study of Bluetooth Signal Parameters for Localization, Proc. IEEE 18th Int'l Symp. Personal, Indoor and Mobile Radio Comm. (PIMRC), Sept. 2007.
[6]. M.B.Kjærgaard, Automatic Mitigation of Sensor Variations for Signal Strength Based Location Systems, Proc.Second Int'l Workshop Location and Context Awareness, Mar.2006.
[7]. K. Yedavalli, B. Krishnamachari, S. Ravula, and B. Srinivasan, Ecolocation: A Sequence Based Technique for RF Localization in Wireless Sensor Networks, Proc.Fourth Int'l Symp. Information Processing in Sensor Networks
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[9]. A. Haeberlen, E. Flannery, A.M. Ladd, A. Rudy's, D.S. Wallach, and L.E. Kavraki, Practical Robust Localization over Large-Scale 802.11 Wireless Networks, Proc. ACM MobiCom, pp. 70-84, 2004
[10]. R. Battiti, M. Brunato, and A. Villani, Statistical Learning Theory for Location Fingerprinting in Wireless LANs, Technical Report DIT-02-0086, Universita di Trento, Dipartimento di Informatica e Telecomunicazioni, Oct. 2002.

Abstract:The Classification for Pap smear Diagnosis aims at classifying the Pap smear cells whether it is affected or not. The term "Pap-Smear" refers to samples of human cells stained by the so-called Papanicolaou method. The Papanicolaou method is a medical procedure to detect pre-cancerous cells in the uterine cervix. The median filter is used to remove the noises in the cell, and then the features are extracted using gray level co-occurrence matrix technique. k-NN classifier, Baye's classifier and ANN classifiers are used for the classification problem.. The classified cells are normal and abnormal.
Keywords:- Bayesian classifier, Genetic Algorithms, Nearest Neighbor based Classifiers, Neural Network, Pap-Smear Classification.

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Abstract: The Tamil Nadu factor in India-Sri Lanka relations that had been quiet for long has come to the fore in the form of the fishermen issue. Frequent incidents of fishermen from Tamil Nadu getting shot in the Sri Lankan's maritime boundary have enraged all citizen of the state. From Tamil Nadu about 18,000 boats of different kinds conduct fishing along the India - Sri Lanka maritime border. Ever since violence broke out in Sri Lanka two decades ago, fishing activity has not been peaceful. Tamil Nadu fishermen are arrested, or shot, by the Sri Lankan Navy. In this problem will be solved by using An Intelligent Boundary Alert System (IBAS).An IBAS system induces the new methodology for saving the fishermen valuable life and their properties from the Sri Lankan's navy. The main objective of this system is used to help the fishermen to navigate inside our maritime country border.
Keywords - GPS, ARM7, WSN

[1] Keisha Wu, Lin Go, Lionel M. Ni, Zhanjiang Lou and Zhongwen Goo(2012) "Ship Detection with Wireless Sensor Networks" IEEE Trans. Vol. 23 No.7.
[2] Abid khan and Ravi Mishra (2012) , "GPS – GSM Based Tracking System" International Journal of Engineering Trends and Technology Volume3Issue2.
[3] Mohammad A. Al-Khedher and Al-Balqa (2011)," Hybrid GPS-GSM Localization of Automobile Tracking System"- International Journal of Computer Science & Information Technology (IJCSIT) Vol 3, No 6.
[4] Francis Enejo Idachaba (2011) , " Design of a gps/gsm based tracker for the location of stolen items and kidnapped or missing persons in nigeria"-ARPN Journal Of Engineering And Applied Sciences Vol. 6, No. 10.
[5] Kunal Maurya 1, Mandeep Singh 2, Neelu Jain 3 (2011) "Real Time Vehicle Tracking System using GSM and GPS Technology- An Anti-theft Tracking system" International Journal of Electronics and Computer Science Engineering ISSN., 2277-1956/V1N3-1103-1107
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[8] Mohammad A. Al – Khedher, Montaser N. Ramadan and Sharaf A. Al – Kheder (2012), "Intelligent Anti-Theft and Tracking System for Automobiles"International Journal of Machine Learning and Computing, Vol. 2, No. 1

Abstract: This research work is to develop an efficient and powerful medical search engine to classify and search the radiographic medical images. It focuses on bag of visual words image representation and a similarity matching technique to represent match and retrieve the similar images. This work addresses the issues in content based image retrieval for medical images. In this system can handles different categories of medical images in organ level and the pathology level for chest X-ray images. This simple, efficient medical image categorization and retrieval system in large radiographic archives (IRMA database) is developed for a medicine physicians and researchers those who are interested in being able to retrieve medical images based on low level features. This would make these systems more helpful for radiologists in medical settings, researches in medical analysis and medical students as well as teachers in academic healthcare environments. The methodology presented is based on local patch representation of the image content using a bag of visual words approach with a kernel based SVM classifier. The system supports the classification of X-ray images and retrieval of similar medical images for given input query image.
Key terms: CBIR, IRMA, Picture archiving and Communication System, Bag of Visual Words, Computer Aided Diagnosis, Chest Radiography, image Patches.

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[3] Jialu Liu (2013), "Image Retrieval based on Bag-of-Words model", arXiv: 1304.5168 v1[cs.IR], pp. 1-10.
[4] Lehmann.T.M, Guld.M.O,Thies.C, Fischer.B, Spitzer.K, Keysers.B, Ney.H, ohnen.H, Schubert and Wein.B (2004)," Content Based Image Retrieval In Medical Applications", Methods Inf Med, 43(4):pp. 354-361.
[5] Mahalakshmi.S and Mr.Raghuraman.G (2012)," Medical Image Categorization and Retrieval System In Radiology Using Bag of Visual Words Framework", AJCST Vol.1, No. 1, pp.149-156.
[6] Mohammad Reza Zare and Ahmed Mueen (2013)," Automatic Classification of Medical X-Ray Images Using A Bag of Visual Words", IET Comput.Vis.,Vol. 7, Issue no. 2, pp. 105-114.
[7] Mohammad Reza Zare (2013)," Automatic Classification of Medical X-Ray Images", Malaysian Journal of Computer Science., Vol. 26(1), pp.9-22.
[8] Mohammad Reza Zare and Ahmed Mueen (2013), "Automatic Classification of Medical X-Ray Images: Hybrid Generative - Discriminative Approach", IET Image Process., Vol. 7, Issue no. 5, pp. 523–532.
[9] Pavani.S, Shivani , T.Venkat Narayana Rao and Deva Shekar (2013),"Similarity Analysis of Images Using Content Based Image Retrieval System", International Journal Of Engineering And Computer Science ISSN:2319-7242, Vol. 2, Issue no.1,pp. 251-258.
[10] Uri Avni, Hayit Greenspan, Eli Konen, Michal Sharon, and Jacob Goldberger (2011),"X-Ray Categorization and Retrieval on The Organ and Pathology Level, Using Patch-Based Visual Words", IEEE transactions on medical imaging, Vol. 30, Issue no. 3, pp. 733-745.

Abstract: Recognition and classification of human actions for the purpose of safety from video sequences is always a challenging problem because of the variations in its environment, different backgrounds used in videos, appearance of actors and their clothing, so in our work we propose a method for constructing effective and appropriate codebooks for action categorization. In the formation of codebook fuzzy C-means clustering algorithm and Pairwise Nearest Neighbor algorithm (PNN), is used and hence the performance of these methods are compared and analyzed on Weizmann dataset.
Keywords - Video Surveillance, Action Recognition, Bag of Visual Words (BoVW), frame differencing, feature extraction, Vector Quantization, fuzzy C-means clustering, Pairwise Nearest Neighbor (PNN),codewords, codebook.

[1] E. Shabaninia ,and Sh. Kasaei ," Codebook appearance representation for vehicle handover across disjoint-view multicameras", Scientia Iranica, Transactions D: Computer Science & Engineering ,Elsevier,(2011).
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[3] Makhalova Elena," Fuzzy C - Means Clustering In Matlab", The 7th International Days of Statistics and Economics, Prague, September 19-21, 2013.
[4] Lamberto Ballan, Lorenzo Seidenari, Giuseppe Serra, Marco Bertini and AlbertoDel Bimbo," Recognizing Human Actions by using Effective Codebooks and Tracking", IEEE Transactions on Multimedia [4],2013.
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[6] Lingqiao Liu, Lei Wang, and Chunhua Shen, "A Generalized Probabilistic Framework for Compact Codebook Creation ", IEEE Conf.Comp.Vis.Pattern Recogn.2011.
[7] M. S. Ryoo, "Human Activity Prediction: Early Recognition of Ongoing Activities from Streaming Videos", IEEE International Conference on Computer Vision(ICCV),Nov 2011.
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[9] Yang Wang, Student Member IEEE, and Greg Mori, Member IEEE, "Human Action Recognition by Semi-Latent Topic Models", IEEE Transactions on Pattern Analysis and Machine Intelligence,2012.
[10] Mingyuan Jiu Christian Wolf , Christophe Garcia ,and Atilla Baskurt, "Supervised Learning and Codebook Optimization for Bag-of-Words Models", Springer Science+ business Media,LLC ,2012.

Abstract: The usage of medical images has been increasing tremendously due to a collection of thousands of medical images every day in medical institutions. Due to the increase in medical images there is a rising need of managing the data properly and accessing it accurately. Finding the correct boundary in noisy images is still a difficult task. It introduces a new edge following technique for boundary detection in noisy images. Use of the proposed technique demonstrates its application to diverse cases of medical images. The proposed technique can detect the boundaries of objects in noisy images using the information the fracture detection on the x-ray images is founded. The proposed technique for the canny edge detector in the x-ray image locates the edges and using the boundary detection, the system which detect the fracture automatically. The boundary detection techniques also implemented in the models are Active Contour Model, Geodesic Active Contour Model and compare the accuracy of detecting is analyzed and tested by using Mat lab 2013 version.
Keywords:- Boundary extraction, Edge vector field model, Edge mapping model, Edge following technique.

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Abstract: For as long as we've been imagining emotionally intelligent machines, we have pictured something at least mildly resembling human form. From George Lucas' C-3PO, to the recently-developed Robokind Zeno R25, our vision for robotic companionship has typically involved two arms and two legs. Taking a different approach is inventor of the Emo Spark console Patrick Levy Rosenthal, who aims to bring artificial intelligence to consumers in the form of a cube small enough to fit in the palm of your hand. Emo Spark is an Android powered Wi-Fi/Bluetooth cube that allows users to create and interact with an emotionally concise intelligence through conversation, music, and visual media. Emo Spark will take not only gaming, but also your TV, smart phone or computer to an entirely different level from anything ever experienced before. media. Over time, the cube creates a customized Emotional Profile Graph (EPG) which collects and measures a unique emotional input from the user. The EPG allows the cube to virtually "feel" senses such as pleasure and pain; and "expresses" those desires according to the user. The future of AI interactions is here. Emo Spark is a brand new innovation from Emo Shape, Ltd. that allows you to transfer your real life emotions and desires directly onto a digital platform using state of the art AI measurements and technology. The digital world will never be the same again. This is the world's first "Emotional Intelligence" device and its capabilities and benefits are unlimited. The Emo Spark uses emotion text and content analysis to measure the emotional responses of several people all at the same time.
Keywords:- Android powered Wi-Fi/Bluetooth cube, Artificial Intelligence, Emotional Profile Graph, Haywire, Webee Automation.

[1] http://photos.prnewswire.com/prnh/20140106/PH40168-b
[2] www.emospark.com
[3] www.emoshape.com.

Abstract: In Cloud Storage, users can remotely store their data and enjoy the on-demand high quality applications and services. The integrity of cloud data is subject to skepticism due to the existence of hardware/software failures and human errors. Several mechanisms have been designed to allow both data owners and public verifiers to efficiently audit cloud data integrity without retrieving the entire data from the cloud server. However, public auditing on the integrity of shared data with these existing mechanisms will supports public auditing on shared data stored in the cloud that exploit ring signature to compute verification metadata needed to audit the correctness of shared data.so that a third party auditor (TPA) is able to verify the integrity of shared data for users without retrieving the entire data. Meanwhile, the identity of the signer on each block inshared data is kept private from the TPAalso able to perform multiple auditing tasks simultaneously instead of verifying them one byone.In this paper, we proved the data freshness(proved the cloud possesses the latest version of shared data)while still preserving identity privacy.Our experimental result ensures that retrieved data always reflects the most recent updates and prevents rollback attacks.
Index terms - AFS (Authenticated File System); data freshness; public auditing; shared dat

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