NS2 NS3 MATLAB ANDROID JiST CLOUDSIM

2012 IEEE NS2 TITLES	DOMAIN
1.    A Statistical Mechanics-Based Framework to Analyze Ad Hoc Networks with Random Access	NS2
2.    A Trigger Identification Service for Defending Reactive Jammers in WSN	NS2
3.    Capacity Scaling of Wireless Ad Hoc Networks Shannon Meets Maxwell	NS2
4.    Connectivity of Multiple Cooperative Cognitive Radio Ad Hoc Networks	NS2
5.    CORMAN A Novel Cooperative Opportunistic Routing Scheme in Mobile Ad Hoc Networks	NS2
6.    DSDMAC Dual Sensing Directional MAC Protocol for Ad Hoc Networks with Directional Antennas	NS2
7.    FESCIM Fair  Efficient and Secure Cooperation Incentive Mechanism for Multihop Cellular Networks	NS2
8.    Improving QoS in High-Speed Mobility Using Bandwidth Maps	NS2
9.    Local Broadcast Algorithms in Wireless Ad Hoc Networks Reducing the Number of Transmissions	NS2
10.  TAM A Tiered Authentication of Multicast Protocol for Ad-Hoc Networks	NS2

2012 IEEE MATLAB TITLES	DOMAIN
11.  A Complete Processing Chain for Shadow Detection and Reconstruction in VHR Images	MATLAB
12.  A Generalized Logarithmic Image Processing Model Based on the Gigavision Sensor Model	MATLAB
13.  Automated Multiscale Morphometry of Muscle Disease From Second Harmonic Generation Microscopy Using Tensor-Based Image Processing	MATLAB
14.  Classification of Dielectric Barrier Discharges Using Digital Image Processing Technology	MATLAB
15.  Hyperconnections and Hierarchical Representations for Grayscale and Multiband Image Processing	MATLAB
16.  ISP An Optimal Out-Of-Core Image-Set Processing Streaming Architecture for Parallel Heterogeneous Systems	MATLAB
17.  Low-Complexity Image Processing for Real-Time Detection of Neonatal Clonic Seizures	MATLAB
18.  Reducing DRAM Image Data Access Energy Consumption in Video Processing	MATLAB
19.  Toward a Unified Color Space for Perception-Based Image Processing	MATLAB
20.  View-invariant action recognition based on Artificial Neural Networks	MATLAB

2012 IEEE ANDROID TITLES	DOMAIN
21.  Ensuring Distributed Accountability for Data Sharing in the Cloud Computing	ANDROID
22.  Scalable and Secure Sharing of Personal Health Records in Cloud Computing using Attribute-based Encryption	ANDROID
23.  SPOC A Secure and Privacy preserving Opportunistic Computing Framework for Mobile Healthcare Emergency	ANDROID
24.  The Three-Tier Security Scheme in Wireless Sensor Networks with Mobile Sinks	ANDROID
25.  Efficient Audit Service Outsourcing for Data Integrity in Clouds	ANDROID
26.  Ranking Model Adaptation for Domain-Specific Search	ANDROID
27.  Defenses Against Large Scale Online Password Guessing Attacks by using Persuasive click Points	ANDROID
28.  Network Assisted Mobile Computing with Optimal Uplink Query Processing	ANDROID
29.  Payments for Outsourced Computations	ANDROID
30.  Query Planning for Continuous Aggregation Queries over a Network of Data Aggregators	ANDROID

2012 IEEE JIST TITLES	DOMAIN
31.  Improving QoS in High-Speed Mobility Using Bandwidth Maps	JiST
32.  Local Broadcast Algorithms in Wireless Ad Hoc Networks Reducing the Number of Transmissions	JiST
33.  Connectivity of Multiple Cooperative Cognitive Radio Ad Hoc Networks	JiST
34.  Handling Selfishness in Replica Allocation over a Mobile Ad Hoc Network	JiST
35.  Smooth Trade-Offs between Throughput and Delay in Mobile Ad Hoc Networks	JiST

2012 IEEE CLOUDSIM TITLES	DOMAIN
36.  Distributed Private Key Generation for Identity Based Cryptosystems in Ad Hoc Networks	CLOUDSIM
37.  Local Broadcast Algorithms in Wireless Ad Hoc Networks Reducing the Number of Transmissions	CLOUDSIM
38.  Routing Architecture for Vehicular Ad-Hoc Networks	CLOUDSIM
39.  SenseLess A Database-Driven White Spaces Network	CLOUDSIM
40.  Throughput and Energy Efficiency in Wireless Ad Hoc Networks With Gaussian Channels	CLOUDSIM

PSF Estimation via Gradient Domain Correlation	January 11 2012
This paper finds its application in image processing where a blurred image is reconstructed. The PSF is Point Spread Function which needs to be estimated to get the lens characteristics. But In practice, finding the true PSF is impossible, and usually an approximation of it is used, theoretically calculated or based on some experimental estimation. Here we propose PSF Estimation via Gradient Domain Correlation

PSF Estimation via Gradient Domain Correlation

ABSTRACT

This paper proposes an efficient method to estimate the point spread function (PSF) of a blurred image using image gradients spatial correlation. A patch-based image degradation model is proposed for estimating the sample covariance matrix of the gradient domain natural image. Based on the fact that the gradients of clean natural images are approximately uncorrelated to each other, we estimated the autocorrelation function of the PSF from the covariance matrix of gradient domain blurred image using the proposed patch-based image degradation model. The PSF is computed using a phase retrieval technique to remove the ambiguity introduced by the absence of the phase. Experimental results show that the proposed method significantly reduces the computational burden in PSF estimation, compared with existing methods, while giving comparable blurring kernel.

Existing system

           PSF Estimation using Sharp Edge Prediction, Godard algorithm, random noise target, coded exposure Deblurring are all proposed on this scenario but they don’t take into account the following

·        High Computational Overhead

·        In Accuracy of  Correlated Pixels

·        Ambiguity in absence of  Phase

PROPOSED SYSTEM

        In this proposed system  new algorithms for solving the problem with an optimized PSF calculation with Image gradients Spatial Correlation is used.

This algorithm takes into account that the gradients of clean natural images are approximately uncorrelated to each other.

Hence an Auto correlation Function of the PSF from the the covariance matrix of gradient domain blurred image is taken into consideration. Computaion of PSF with a phase retrieval technique to remove the ambiguity introduced by the absence of the phase

Experiments show that the proposed system gives an edge over other existing methods with reduced computational requirements and overweighs the existing system by a large margin.

Advantages over Existing Methods,

·        Reduced Computational Overhead

·        Applicable to Low powered Devices

·        Optimal Estimation in blurred images

·        Scales well with all Image scenarios

module’s IN PROJECT

IMage Handler

IMAGE ANALYSER

BLUR ESTIMATOR

PSF ESTIMATOR

SYSTEM REQUIREMENTS:

HARDWARE MINIMUM REQUIREMENTS:

PROCESSOR        :    PENTIUM IV 2.8 GHz

RAM                      :    512 MB

MONITOR             :    19”

HARD DISK         :     20 GB

CDDRIVE              :    52X

SOFTWARE REQUIREMENTS:

FRONT END                  :    C# .Net , VS 2008

FRAMEWORK USED    :    .net 2.0

OPERATING SYSTEM:    WINDOWS XP

           IEEE 2012 Java and .Net Titles

1.    A Novel Data Embedding Method Using Adaptive Pixel Pair Matching

2.    A Probabilistic Model of Visual Cryptography Scheme With Dynamic Group

3.    A Secure Intrusion detection system against DDOS attack in Wireless Mobile Ad-hoc Networks

4.    Active Visual Segmentation

5.    AMPLE An Adaptive Traffic Engineering System Based on Virtual Routing Topologies

6.    An Efficient Adaptive Deadlock-Free Routing Algorithm for Torus Networks

7.    Characterizing the Efficacy of the NRL Network Pump in Mitigating Covert Timing Channels

8.    Cooperative download in vehicular environments

9.    Defenses Against Large Scale Online Password Guessing Attacks by using Persuasive click Points

10. Design and Implementation of TARF A Trust-Aware Routing Framework for WSNs

11. Discovering Characterizations of the Behavior of Anomalous Sub-populations

12. Efficient Audit Service Outsourcing for Data Integrity in Clouds

13. Ensuring Distributed Accountability for Data Sharing in the Cloud

14. Fast Matrix Embedding by Matrix Extending

15. FireCol A Collaborative Protection Network for the Detection of Flooding DDoS Attacks

16. Learn to Personalized Image Search from the Photo Sharing Websites

17. Load Balancing Multipath Switching System with Flow Slice

18. Network Assisted Mobile Computing with Optimal Uplink Query Processing

19. Outsourced Similarity Search on Metric Data Assets

20. Privacy- and Integrity-Preserving Range Queries in Sensor Networks

21. Query Planning for Continuous Aggregation Queries over a Network of Data Aggregators

22. Ranking Model Adaptation for Domain-Specific Search

23. Risk-Aware Mitigation for MANET Routing Attacks

24. Scalable and Secure Sharing of Personal Health Records in Cloud Computing using Attribute-based Encryption

25. Semi supervised Biased Maximum Margin Analysis for Interactive Image Retrieval

26. SPOC A Secure and Privacy preserving Opportunistic Computing Framework for Mobile Healthcare Emergency

27. The Three-Tier Security Scheme in Wireless Sensor Networks with Mobile Sinks

28. Topology Control in Mobile Ad Hoc Networks with Cooperative Communications

29. Towards Accurate Mobile Sensor Network Localization in Noisy Environments

30. View-invariant action recognition based on Artificial Neural Networks

31. Fast Data Collection in Tree-Based Wireless Sensor Networks

32. Packet-Hiding Methods for Preventing Selective Jamming Attacks

33. Distributed Throughput Maximization in Wireless Networks via Random Power Allocation

34. Automatic Reconfiguration for Large-Scale Reliable Storage Systems

35. A New Cell Counting Based Attack Against Tor

Collaborative Filtering with Personalized Skylines

Collaborative filtering (CF) systems exploit previous ratings and similarity in user behavior to recommend the top-k objects/records which are potentially most interesting to the user assuming a single score per object. However, in various applications, a record (e.g., hotel) maybe rated on several attributes (value, service, etc.), in which case simply returning the ones with the highest overall scores fails to capture the individual attribute characteristics and to accommodate different selection criteria. In order to enhance the flexibility of CF, we propose Collaborative Filtering Skyline (CFS), a general framework that combines the advantages of CF with those of the skyline operator. CFS generates a personalized skyline for each user based on scores of other users with similar behavior. The personalized skyline includes objects that are good on certain aspects, and eliminates the ones that are not interesting on any attribute combination. Although the integration of skylines and CF has several attractive properties, it also involves rather expensive computations. We face this challenge through a comprehensive set of algorithms and optimizations that reduce the cost of generating personalized skylines. In addition to exact skyline processing, we develop an approximate method that provides error guarantees. Finally, we propose the top-k personalized skyline, where the user specifies the required output cardinality.

Skyline Processing

Assume records with attributes, each taking values from a totally ordered domain. Accordingly, a record can be represented as a point in the d-dimensional space (in the sequel, we use the terms record, point, and object

Interchangeably). The skyline contains the best points according to any function that is monotonic on each attribute. Conversely, for each skyline record r, there is such a function that would assign it the highest score. These attractive properties of skylines have led to their application in various domains including multi objective optimization maximum vectors and the contour problem. They introduced the skyline operator to the database literature and proposed two disk-based algorithms for large data sets. The first, called D&C (for divide and conquer) divides the data set into partitions that fit in memory, computes the partial skyline in every partition, and generates the final skyline by merging the partial ones. The second algorithm, called BNL, applies the concept of block-nested loops. It improves BNL by sorting the data. Other variants of all these methods do not use any indexing and, usually, they have to scan the entire data set before reporting any skyline point. Another set of algorithms utilizes conventional or multidimensional indexes to speed up query processing and progressively report skyline points. Such methods include Bitmap, In addition to conventional databases; skyline processing has been studied in other scenarios. For instance, Morse et al. uses spatial access methods to maintain the skyline in streams with explicit deletions. Efficient skyline maintenance has also been the focus of in distributed environments; several methods query independent subsystems, each in charge of a specific attribute, and compute the skylines using the partial results. In the data mining context, identify the combinations

http://www.youtube.com/watch?v=sKwa0n_ilxI