Ravindra Patel

Region Duplication Forgery Detection Technique Based on SURF and HAC

Region duplication forgery detection is a special type of forgery detection approach and widely used research topic under digital image forensics. In copy move forgery, a specific area is copied and then pasted into any other region of the image. Due to the availability of sophisticated image processing tools, it becomes very hard to detect forgery with naked eyes. From the forged region of an image no visual clues are often detected. For making the tampering more robust, various transformations like scaling, rotation, illumination changes, JPEG compression, noise addition, gamma correction, and blurring are applied. So there is a need for a method which performs efficiently in the presence of all such attacks. This paper presents a detection method based on speeded up robust features (SURF) and hierarchical agglomerative clustering (HAC). SURF detects the keypoints and their corresponding features. From these sets of keypoints, grouping is performed on the matched keypoints by HAC that shows copied and pasted regions.

The Cost effective Location Management Scheme using Mobility Information and Received Signal Strength of Mobile Users in Wireless Mobile Networks

Recent advances in cellular mobile communications have touched every aspect of our lives. In mobile computing, Mobile hosts or Mobile terminals (MTs) move randomly from one place to another within a well-defined geographical area. To provide timely services to mobile users, a challenging task is to track the location of the mobile user effectively so that the connection establishment delay is low. This can be done only if available system resources are used optimally. In most of the available schemes, when a call arrives, the target MT is searched using a method calledpaging even when the target MT is in such a low coverage area where it can not bear a call. This wastage of network resources puts extra burden on the network and increases the total location management (LM) cost. The proposed scheme tries to cut off this resource wastage up to a significant amount by not paging those MTs that can not bear a call due to low received signal strength (RSS) value. The Performance of proposed scheme is evaluated using an analytical model and is compared with Sun-Jin-Ohs LM scheme[1].

Reducing overhead in movement based dynamic location management scheme for cellular networks

One of the key issues in cellular mobile communication is to find the current location of mobile terminal (MT) to deliver the services, which is called location management (LM). Much research has been done on dynamic LM that reduced the LM cost up to a large extent. In movement based dynamic LM scheme, the location area is defined in the form of ring of cells for individual user. Whenever an MT visits a cell outside of its current location area (LA), it triggers location update (LU). For this purpose, network must inform the mobile terminal about ID of all the cells present in its current location area. In this paper, a simple way of cell-ID assignment is proposed under which, network sends only the ID of center cell of LA ring to MT and then MT can compute IDs of all other cells in its location area. This saves a significant amount of wireless bandwidth by minimizing the signaling traffic at VLR level and thus reduces the mobility management overhead.

An Inference Mechanism Framework for Association Rule Mining

Available approaches for Association Rule Mining (ARM) generates a large number of association rules, these rules may be trivial and redundant and also such rules are difficult to manage and understand for the users. If we consider their complexity, then it consumes lots of time and memory. Sometimes decision making is impossible for such kinds of association rules. An inference approach is required to resolve this kind of problem and to produce an interesting knowledge for the user. In this paper, we present an inference mechanism framework for ARM, which would be capable enough for resolving such problems, it would also predict future possibilities using Markov predictor by analyzing available fact and inference rules. Keywords—Inference rules; ARM; Knowledgebase; Expert System

Intertwining cognitive and affective intelligence into digital artifacts: An infrastructural approach

Designing and developing digital technological systems and their interactive interfaces as better companion with hominine characteristics is an active research hot-spot. Exploring the domain of facilitating machines with affective and cognitive intelligence and understanding the users is increasingly attracting the interest of researchers who are working in the field of human-computer interaction. If the interactive interfaces of digital system are enriched with human-like characteristics and such systems have an understanding of users affective state (personality, mood and emotions) along with the ability to respond accordingly during interaction then definitely these intelligent hominine interfaces will be more natural, enjoyable, friendly and believable. The key challenge is to determine most appropriate techniques and models for generating these futuristic harmonious intelligent affective interfaces and services which may be quite different from their present GUI counterparts. This paper presents an infrastructural approach for machines to first realize the users affective space and then creating its own cognitive and affective space to respond appropriately and harmoniously to the user. The proposed work suggests the methods and models to identify/determine users personality (through AN-ECHO model), emotions (through facial expression recognition method) and mood (through computational model). The proposed approach uses personality along with user-profiling method to understand users interests, preferences, characteristics, expectations etc. in order to incorporate cognitive intelligence. In this way, the proposed approach facilitates the machine to assess personality, mood and emotions of the user to express personalized and adaptive behavior to the user.

Effects of Clustering and Successive Paging on Reporting Center Scheme: A Cost Analysis

One of the key issues in cellular mobile communication is to find current location of mobile terminals to deliver the service, which is known as location management. Although dynamic location management schemes show better performance but static schemes are more popular due to their simplicity. One such static scheme is reporting center in which some cells are designated as reporting centers. This paper proposes a basic criteria for performing clustering and successive paging in reporting center scheme and also analyzes the cost effectiveness of three different versions of reporting center scheme: Simple, Clustered, and Combination of clustering with successive paging. Simulation results show that the combination of clustering with successive paging outperforms the other two versions independent of call to mobility ratio. General Terms Location management.

ART and Modular Neural Network Architecture for Multilevel Categorization and Recognition of Fingerprints

ART1 based clustering approach is used for classification, which groups fingerprints into more compact classes. ART1 is a efficient technique for grouping fingerprints in to N number of classes, which speedup the process of fingerprint recognition. After classification of fingerprints the key-fingerprint class is used for the purpose of fingerprint identification. The key-fingerprint is recognized by using Monolithic and Modular Neural Network and their performance has been compared on the bases of time and accuracy. Due to modularity, Modular Neural Network gives better performance on the classified databases as compared to Monolithic Neural Network even with poor quality fingerprints. Monolithic Neural Network takes average of 44.7 seconds with an accuracy of 98%, correct recognition where as Modular Neural Network takes average time 1.84 seconds with an accuracy of 100% correct recognition

Redefining and Extending the Scope of System Development Life Cycle: Perspective of Today's and Futuristic Human-System Interaction Environment

With the latest innovations in the field of digital computing, communication and interconnecting technology, a new and of its own type of pervasive physical-digital ecosystem has started to emerge and in future it will be more ubiquitous, more dominant, more potent, more useful, more helpful, more usable. Finally, it will emerge as inevitable and indispensable part of our mundane interaction environment and everyday lifestyle experience. The designers, developers and practitioners of human-system interaction design have got a vital role to play in this transformation. The system development life cycle is the fundamental iterative reference cycle that specifies how to design and develop such technological systems. This work first focuses on those aspects which are of most significance from point of view of human-human concerns mediated by human-system interaction and are not appropriately addressed by canonical interaction-system development life cycle. This work then extends it along with specifying the realizing methodologies, in order to broaden the scope of the canonical system development life cycle to fulfil the present and future requisites in relation to people’s interaction with the totality of ubiquitous environment in all respects.

An Efficient Binary to Decimal Conversion Approach for Discovering Frequent Patterns

Association Rule Mining(ARM) is a most vital field of data mining to discover interesting relationship between items from huge transaction databases it analysis the data and discover strong rules using different measures such as (support, confidence, lift, conviction) etc, various ARM algorithms are available in literature for discovering frequent patterns. Market Basket analysis is one of the most essential applications of ARM; other applications are pattern recognition, weblog data mining and special data analysis etc. In this paper we proposed B2DCARM algorithm to discover frequent pattern which use Boolean matrix based technique. This algorithm adopts binary to decimal conversion approach to discover frequent itemsets from huge transaction database which outperforms in both of the cases where support threshold is low or high and also better performs from efficiency point of view compare to available tree based approaches.

Critical evaluation of reverse engineering tool Imagix 4D

IntroductionThe comprehension of legacy codes is difficult to understand. Various commercial reengineering tools are available that have unique working styles, and are equipped with their inherent capabilities and shortcomings. The focus of the available tools is in visualizing static behavior not the dynamic one. Therefore, it is difficult for people who work in software product maintenance, code understanding reengineering/reverse engineering. Consequently, the need for a comprehensive reengineering/reverse engineering tool arises. We found the usage of Imagix 4D to be good as it generates the maximum pictorial representations in the form of flow charts, flow graphs, class diagrams, metrics and, to a partial extent, dynamic visualizations.Case description and evolutionWe evaluated Imagix 4D with the help of a case study involving a few samples of source code. The behavior of the tool was analyzed on multiple small codes and a large code gcc C parser. Large code evaluation was performed to uncover dead code, unstructured code, and the effect of not including required files at preprocessing level. The utility of Imagix 4D to prepare decision density and complexity metrics for a large code was found to be useful in getting to know how much reengineering is required. At the outset, Imagix 4D offered limitations in dynamic visualizations, flow chart separation (large code) and parsing loops.ConclusionThe outcome of evaluation will eventually help in upgrading Imagix 4D and posed a need of full featured tools in the area of software reengineering/reverse engineering. It will also help the research community, especially those who are interested in the realm of software reengineering tool building.