iosr-JCE   Volume-16 ~ Issue-5 ~ Sep-Oct 2014

Abstract: This document gives an insightinto HMM and its application in context of Multiple sequence alignment (MSA). Various computational approaches proliferatedin response to resolve the complexities of Human Genome sequence. An HMM is probabilistic competitive approachthat can be applied to resolve the key issues like Gene prediction, multiple sequence alignment, pattern recognition .This paper describe HMM approach of MSA and its significance.

Keywords: HMM, Multiple sequence alignment, Pattern recognition,Maximum likelihood,R,Viterbi algorithm ,Back Propagation.

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Abstract : In the tracking scheme illustrated, where the sensors are deployed in a triangular fashion in a hexagonal mesh such that the hexagon is divided into a number of equilateral triangles. Where the technique is used for detection is the trilateration technique in which intersection of three circles is used to determine through the object location. While the object was tracked by the three sensors, distance where it from a fourth sensor and it is also being calculated simultaneously. Here the difference is that closest of three sensors detect at a frequency of one second while the fourth sensor detects the object location at twice the frequency. By using the distance information from the fourth sensor and a simple mathematical technique, location of object is to be predicted for every half second as well. Where the key thing that is to note the forth sensor node is not used for detection but only for estimation of the object at half second intervals and hence does not utilizes much power. By using these techniques, tracking capability of the system is increased.

Keywords: Application-Specific, Data-Centric, Negotiation Based Protocols, Target Sensor Tracking.

[1] S. Banerjee and S. Khuller, "A clustering scheme for hierarchical control in multi-hop wireless networks," Proceedings of IEEE INFOCOM, pp. 1028-1037, Anchorage AK, April 2001.
[2] D. Estrin, L. Girod, G. Pottie and M. Srivastava, "Instrumenting the world with wireless sensor networks," Proceedings of ICASSP, pp. 2033-2036, Salt Lake City, UT, May 2001.
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[5] L. M. Kaplan, Q. Le and P. Molnar, "Maximum likelihood methods for bearings-only target localization," Proceedings of IEEE ICASSP, pp. 554-557, Salt Lake City, UT, May, 2001.

Abstract : Detection of image forgery is always a crucial factor in image forensic and security applications. Usually this detection is possible with the help of local or global features of an image. We can ensure the credibility of an image with a hashing method by fusing local and global features together. So that it is possible to detect even sensitive image forgeries. Here, we are proposing an improved hashing method for the detection of Copy-move forgery detection and Spliced Image Detection.

Key words: Zernike moments,Local features, Saliency Map,

[1] Yan Zhao, Shuozhong Wang, Xinpeng Zhang, and Heng Yao, "Robust Hashing for Image Authentication Using Zernike Moments and Local Features" ieee transactions on information forensics and security, vol. 8, no. 1, january 2013
[2] V. Monga, A. Banerjee, and B. L. Evans, "A clustering based approach to perceptual image hashing," IEEE Trans. Inf. Forensics Security, vol. 1, no. 1, pp. 68–79, Mar. 2006.
[3] S. Xiang, H. J. Kim, and J. Huang, "Histogram-based image hashing scheme robust against geometric deformations," in Proc. ACM Multimedia and Security Workshop, New York, 2007, pp. 121–128.
[4] Z. Tang, S.Wang,X. Zhang, W.Wei, and S. Su, "Robust image hashing for tamper detection using non-negative matrix factorization," J. Ubiquitous Convergence Technol., vol. 2, no. 1, pp. 18–26, May 2008.
[5] A. Swaminathan, Y. Mao, and M. Wu, "Robust and secure image hashing," IEEE Trans. Inf. Forensics Security, vol. 1, no. 2, pp.215–230, Jun. 2006.

Abstract : Image watermarking is a method that embeds a watermark in the digital image by making small changes in the host data. In watermarking applications, the robustness of the watermark to the common signal processing and geometric desynchronization attacks(DAs) is essential to the system. Most image watermarking resynchronization schemes can survive global DAs (e.g., rotation, scaling, translation, and other affine transforms), but few are resilient to cropping and local DAs. In this paper, We present a watermarking resynchronization scheme against local transform attack. It uses a local invariant transform called Local Daisy Feature Transform(LDFT) and Binary Space Partitioning(BSP) Tree to partition the LDFT space. Watermark is embedded in the leaf nodes of the BSP tree. Here, attacks to the watermarked image can also be detected using SHA-1 algorithm.

Keywords: desynchronization attack ; resynchronization ; transform.

[1] Huawei Tian, Yao Zhao, Rongrong Ni ,Lunming Qin, and Xuelong Li, , "LDFT based Watermarking resilient to Local
Desynchronizationn Attcks," IEEE Transactions On Cybernetics January 31, 2013.
[2] J. Ruanaidh and T. Pun, "Rotation, scale and translation invariant spread spectrum digital image watermarking," Signal Process.,
vol. 66, no. 3, pp. 303–317, May 1998.
[3] C. Tang and H. Hang, "A feature-based robust digital image watermarking scheme," IEEE Trans. Signal Process., vol. 51, no. 4, pp.
950–959, Apr. 2003.
[4] P. Dong, J. G. Brankov, N. P. Galatsanos, Y. Yang, and F. Davoine, "Digital watermarking robust to geometric distortions," IEEE
Trans. Image Process., vol. 14, no. 12, pp. 2140–2150, Dec. 2005.
[5] S. S. Jin and D. Y. Chang, "Image watermarking based on invariant regions of scale-space representation," IEEE Trans. Signal
Process., vol. 54, no. 4, pp. 1537–1549, Apr. 2006

Abstract : Lung cancer seems to be the common cause of death among people throughout the world. Early detection of lung cancer can increase the chance of survival among people. The overall 5-year survival rate for lung cancer patients increases from 14 to 49% if the disease is detected in time. Although Computed Tomography (CT) can be more efficient than X-ray. However, problem seemed to merge due to time constraint in detecting the present of lung cancer regarding on the several diagnosing method used. Hence, a lung cancer detection system using image processing is used to classify the present of lung cancer in a CT- images. In this study, MATLAB have been used through every procedures made. In image processing procedures, process such as image pre-processing, segmentation and feature extraction have been discussed in detail. We are aiming to get the more accurate results by using various enhancement and segmentation techniques.

Keywords: LCDS, Watershed Segmentation, ROI, Thresholding, morphologic, Metastasis, CT

[1]. Ilya Levner, Hong Zhangm ,"Classification driven Watershed segmentation ", IEEE TRANSACTIONS ON IMAGE PROCESSING VOL. 16, NO. 5, MAY 2007
[2]. Anita chaudhary, Sonit Sukhraj Singh,"Lung Cancer Detection on CT Images Using Image Processing ", International transaction on Computing Sciences, VOL 4, 2012
[3]. B.V. Ginneken, B. M. Romeny and M. A. Viergever, "Computer-aided diagnosis in chest radiography: a survey", IEEE, transactions on medical imaging, vol. 20, NO.12,DEC-2001
[4]. Disha Sharma, Gagandeep Jindal,"Identifying Lung Cancer Using Image Processing Techniques ", International Conference on Computational Techniques and Artificial Intelligence (ICCTAI'2011), vol: 17, pp: 872-880,2011
[5]. Nguyen, H. T.,et al,"Watersnakes: Energy-Driven Watershed Segmentation", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 25, Number 3, pp.330-342, March 2003

Abstract : The escalation of internet has increased the usage of multimedia contents for wide range of functions. The easy access of the digital contents paves way to manipulate, edit and duplicate the contents using available image processing software. Watermarking process ensures copy protection and data authentication to the multimedia content by embedding watermark. The present paper proposes fidelity analysis of additive and multiplicative watermarked images in the integrated domain using Peak Signal to Noise Ratio measures. This paper first embeds additive watermark in spatial domain and multiplicative watermark in frequency domain, then vice versa. The later one provides good fidelity and less image degradation by achieving acceptable Peak Signal to Noise Ratio values. Keywords: Digital watermarking, Discrete Wavelet transform, Peak Signal to Noise Ratio

[1] Ming-Shing Hsieh, Din-Chang Tseng et al, Hiding Digital Watermarks using Multiresolution Wavelet Transform, IEEE Transactions on Industrial Electronics, Vol.48,No.5, October 2001.
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[3] Prabhishek Singh, R.S Chadha, A Survey of Digital Watermarking Techniques, Applications and Attacks, International Journal of Engineering and Innovative Technology, 2277-3754, Vol.2, Issue 9 March 2013
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Abstract : Dynamic queries are a novel approach to information seeking that may enable users to cope with information overload. They allow users to see an overview of the database, rapidly explore and conveniently filter out unwanted information. Users fly through information spaces by incrementally adjusting a query while continuously viewing the changing results. The main drawback of a form-based query interface is that it is restrictive. Modern scientific databases and web databases maintain large and heterogeneous data. These real-world databases contain over hundreds or even thousands of relations and attributes. Traditional predefined query forms are not able to satisfy various ad-hoc queries from users on those databases. So a Dynamic Query Form (DQF) system was proposed. Dynamic queries interfaces suggest that they offer a dramatic change from existing methods for querying databases. DQF, a query interface which is capable of dynamically generating query forms for users. Different from traditional document retrieval users in database retrieval are capable of performing different round of actions iteratively by filling in forms and retrieving results based on users desire and conditions at run time. Each iteration consists of two types of user interactions: Query Form Endowment and Query Execution. In Query Form Endowment DQF recommends the user selects the desired form components into the current query form and the form components selected by the user will be in ranked order. In Query Execution the user fills out the current query form and submits a query

Key words: Dynamic Query, Skyline Queries, Query Forms

[1]. Liang Tang, Tao Li, Yexi Jiang, and Zhiyuan Chen, "Dynamic Query Forms for Database Queries," IEEE Transactions On Knowledge And Data Engineering Vol:Pp No:99 Year April 2013
[2]. M. Jayapandian and H. V. Jagadish. "Expressive query specification through form customization. In Proceedings of International Conference on Extending Database Technology (EDBT), pages 416–427, Nantes, France, March 2008.
[3]. M. Jayapandian and H. V. Jagadish. "Automating the design and construction of query forms". IEEE TKDE, 21(10):1389–1402, 2009.
[4]. N. Khoussainova, Y. Kwon, M. Balazinska, and D. Suciu. "Snipsuggest: Context-aware autocompletion for sql". PVLDB, 4(1):22–33, 2010..
[5]. E. Chu, A. Baid, X. Chai, A. Doan, and J. F. Naughton. "Combining keyword search and forms for ad hoc querying of Databases". In Proceedings of ACM SIGMOD Conference, pages349–360, Providence, Rhode Island, USA, June 2009.

Abstract :Extraction of text from natural scene images is a challenging problem because of its complex backgrounds and large variations of text patterns. In this paper, we presents an innovative scene text detection algorithm with the help of two machine learning classifiers: one for candidate generation and the other which filters out non text ones. And the enhancement technique followed by a text string detection with arbitrary orientations based on structure- based partition and grouping. To extracted the connected components (CCs) in images an algorithm us used ,popularly known as maximally stable extremal region algorithm. These extracted CCs are partitioned into clusters and generate candidate regions. However, the methods use AdaBoost classifier to training the samples and improve the text detection accuracy. The scale, skew, and color of each candidate can be estimated from CCs, and filtered the non text from the normalized images. To find the text string consists of two steps: A) Image partition to detect the text character candidates by using gradient magnitude of character components and B)Text character grouping to detect text strings by using structural analysis of text characters and then merges them into text string for example size of character,distance between neighboring characters.To improve efficiency and accuracy, our algorithms are carried out in multi-scales. The proposed system yield very high identification accuracy and take less time for detection as compared to the existing system.

Keywords: Connected component based approach, character grouping, image partition, text string detection

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Abstract : The KDD CUP '99 data set has been widely used for intrusion detection and pattern mining in the last decade or so. Umpteen number of experiments pertaining to classification have been conducted on it.Many researchers have dedicated their resources for analysing this data set. But it has yet to be analysed by using Ensemble methods of classification. This paper contains experimental results obtained after classifying 10 % of the KDD CUP '99 data set using ensemble methods like Bagging,Boosting and compares their performance with the standard J-48 classification algorithm.Weka experimenter has been used to classify the 494020 records using the aforementioned classifiers and the advantages of ensembling have been discussed in accordance with the obtained results..

Keywords: Bagging, Boosting, Data mining, Ensemble classifiers, KDD CUP '99 data set, Weka

[1] Mohammad Khubeb and Shams Naahid, Analysis of KDD CUP '99 Dataset using Clustering based Mining, International Journal of Database Theory and Application, 6(5), 2013, 23-34.

[2] Mahbod Tavallaee,Ebrahim Bagheri,Wei Lu and Ali .A.Ghorbani, A Detailed Analysis of the KDD CUP '99 Dataset, Proc.of 2009 IEEE Symposium on Computational Intelligence in Security and Defense Applications,978-1-4244-3764-1/09.

[3] Maheshkumar Sabhnani and Gursel Serpen, Application of Machine Learning Algorithms to KDD Intrusion Detection Dataset within Misuse Detection Context, Proc .Of the International Conference on Machine Learning;models,Technologies and Applications, Las Vegas,Nevada,USA 1-932415-11-4.

[4] Yan-Shi Dong and Ke-Song Han, Boosting SVM Classifiers by Ensemble, Proc.of 2005 ACM WWW Conference,Chiba,Japan 1-59593-051-5/05/0005.

[5] Lior Rokach, Ensemble based Classifiers, Springer Science+Business Media, 2009.

Abstract : Underwater object detection has a considerable impact in the field of ocean technology. This paper presents a techniqueto detect a submerged object based on the medium's spectral attenuation coefficient by applying Beer-Lambert Law. The value of this coefficient is a function of the medium's composition, depth of the object,and wavelength of incident light. Experiments were performed in a swimming pool using objects of different colors at different depths to validate the mathematical model for object detection. Keywords: Attenuation Coefficient, Beer-Lambert Law, Color Attenuation, Object Detection

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Abstract : Over the course of time many data replication strategy has been used in grid. Replication of data increases the access to data by reducing the data latency, it also increases reliability by maintaining multiple copies of data. This paper introduces three strategies that can be used to replicate data in the grid using the concepts of graph centrality and betweenness.

Keywords: centrality; betweenness; replication; data grid

[1]. Kavitha Ranganathan and Ian Foster , ―Identifying Dynamic Replication Strategies for a High- Performance Data Grid ,‖Grid Computing — GRID 2001 Lecture Notes in Computer Science Volume 2242, 2001, pp 75-86
[2]. Bill Allcock, Joe Bester, John Bresnahan, Ann L. Chervenak, Ian Foster, Carl Kesselman, Sam Meder, Veronika Nefedova, Darcy Quesnel, Steven Tuecke, ―Secure, Efficient Data Transport and Replica Management for High-Performance Data-Intensive Computing‖ in Mass Storage Systems and Technologies, IEEE,2001
[3]. Chai Deng-feng, Zhang Deng-rong―Algorithm and its application of N shortest paths problem ―Info-tech and Info-net, 2001. Proceedings. ICII 2001 – Beijing IEEE
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Abstract : Mobile ad hoc network (MANET) is an infrastructureless mobile networks where nodes can freely move and join. MANET has attracted much attention in recent years owing to the increased focus on wireless communication. It is a highly flexible network, vulnerable to various types of security attacks by malicious nodes. Ensuring network security is a major concern in the case of MANET. Certificate revocation play an important role in securing the network by isolating attackers from further participating in network activities. Certification Authority (CA) is responsible for revoking the certificates of attacker nodes. CA maintains two lists, warning list and black list to keep accusing and accused nodes respectively inorder to perform revocation process by considering the first arrived accusation packet. In this paper we focus on the problems of certificate revocation based on first accusation. A threshold based approach is proposed for certificate revocation with better performance, but there is some sort of overhead exist. Inorder to make the communication in MANET more secure we propose a reduced overhead based approach that enhances threshold based approach which introduce an additional list, intermediate list in the CA. The scheme is evaluated and results demonstrate that the proposed scheme is effective and efficient to provide secure communication in mobile ad hoc network.

[1] Wei Liu, Hiroki Nishiyama, Nirwan Ansari, Jie Yang, and Nei Kato, "Cluster-BasedCertificate Revocation with Vindication Capability for Mobile Ad Hoc Networks," IEEE Transactions on Parallel and Distributed Systems, vol. 24, no. 2, Feb. 2013.
[2] H. Luo, J. Kong, P. Zerfos, S. Lu, and L. Zhang, "URSA: Ubiquitous and Robust Access Control for Mobile Ad Hoc Networks," IEEE/ACM Trans. Networking, vol. 12, no. 6,pp. 1049-1063, Oct. 2004.
[3] G. Arboit, C. Crepeau, C.R. Davis, and M. Maheswaran, "A Localized Certificate Revocation Scheme for Mobile Ad Hoc Networks," Ad Hoc Network, vol. 6, no. 1, pp. 17-31, Jan. 2008.
[4] J. Clulow and T. Moore, "Suicide for the Common Good: A New Strategy for Credential Revocation in Self-organizing Systems," ACMSIGOPS Operating Systems Rev., vol. 40, no. 3, pp. 18-21, July 2006.
[5] K. Park, H. Nishiyama, N. Ansari, and N. Kato, "Certificate Revocation to Cope with False Accusations in Mobile Ad Hoc Networks," Proc. IEEE 71st Vehicular Technology Conf. (VTC '10), May 16-19, 2010.

Abstract : analysis of blood samples for counting leukemia cells is discussed in this paper. support vector machine and nearest neighbour concept is presented in this paper. The identification of blood disorders, it can lead to classification of certain diseases related to blood. Several classification techniques are investigated till today. One of the best methods for classification techniques nearest neighbour and SVM (Support Vector Machine).By identifying and counting blood cell within the blood smear using classification techniques it's quite possible to detect so many diseases. If one of the new classifier is used i.e. nearest neighbour and SVM it is quiet possible to detect the cancer cell from the blood cell counting.

Keyword: Blood, Classification technique, Nearest Neighbour Network, SVM

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