An analysis of a distributed multiresolution vision system
This paper analyzes a distributed vision system that uses a multiresolution imagery to achieve computational savings in dynamic scene analysis. The system basically contains a set of processes that asynchronously work on a pyramid image structure. The system also contains a blackboard that provides inter-process communications as well as an overall scene interpretation. The paper examines the capability of each component in the system and proposes an underlying architecture. Finally, a performance evaluation is provided by comparing the present system with a conventional vision system.

title: Document Flattening through Grid Modeling and Regularization
abstract: For document images captured by a digital camera, perspective and geometric distortions make it hard to recognize the document content properly. In this paper, we propose an integrated document restoration technique, which is capable of removing perspective and geometric distortions, and producing a flattened and fronto-parallel text image that is friendly to the generic OCR systems. The proposed document restoration is accomplished through grid modeling, which divides camera images into multiple quadrilateral grids using vertical text directions and the x lines and base lines. The global distortions are then removed through grid regularization that transforms the quadrilateral grids together with the pixel contents to the regular square grids. Experimental results show the proposed method is fast and easy for implementation

title: Improving Pronoun Resolution Using Statistics-Based Semantic Compatibility Information
abstract: In this paper we focus on how to improve pronoun resolution using the statistics-based semantic compatibility information. We investigate two unexplored issues that influence the effectiveness of such information: statistics source and learning framework. Specifically, we for the first time propose to utilize the web and the twin-candidate model, in addition to the previous combination of the corpus and the single-candidate model, to compute and apply the semantic information. Our study shows that the semantic compatibility obtained from the web can be effectively incorporated in the twin-candidate learning model and significantly improve the resolution of neutral pronouns.

title: Chart analysis and recognition in document images
abstract: Hidden Markov models are a probabilistic modeling tool for time series data. It has been successfully applied to many areas, such as speech recognition, hand-written character recognition, etc. In this paper, we present a novel statistical approach using ergodic hidden Markov models to recognize scientific charts. We also present a newly developed feature extraction method for chart images. Unlike traditional primitive-based diagram recognition method, our approach need not recognize the graphic primitives in charts thus bypassing the recognition error problem caused by the inaccurate primitive extraction that is also a major obstacle to the construction of a general chart recognition system.

title: Correcting document image warping based on regression of curved text lines
abstract: Image warping is a common problem when one scans or photocopies a document page from a thick bound volume, resulting in shading and curved text lines in the spine area of the bound volume. This will not only impair readability, but will also reduce the OCR accuracy. Further to our earlier attempt to correct such images, this paper proposes a simpler connected component analysis and regression technique. Compared to our earlier method, the present system is computationally less expensive and is resolution independent too. The implementation of the new system and improvement of OCR accuracy are presented in this paper.

title: Motion deblurring for optical character recognition
abstract: This paper investigates the problem of blurring caused by motion during image capture of text documents. Motion blurring prevents proper optical character recognition of the document text contents. One area of such applications is to deblur name card images obtained from handheld cameras. In this paper, a complete motion deblurring procedure for document images has been proposed. The method handles both uniform linear motion blur and uniform acceleration motion blur. Experiments on synthetic and real-life blurred images prove the feasibility and reliability of this algorithm provided that the motion is not too irregular. The restoration procedure consumes only small amount of computation time.

title: Low-power group key agreement for heterogeneous wireless networks
abstract: Heterogeneous wireless networks are gaining popularity as users can be connected to these networks without any cables and even when they are mobile. The high power nodes in heterogeneous wireless networks do not have energy constraints but the user nodes, which can be large in numbers, are usually low power energy constrained devices. Therefore, the GKA protocol used to secure group communications in these networks has to take into consideration both the low power nature of the user nodes and the network size. In this paper, we present an energy efficient and scalable GKA protocol, which uses our proposed Contributory Ring-Centralized (ContRi-Central) group model. Besides providing complexity analysis, we also show the computational and communication energy consumption costs analysis of all nodes running our proposed scheme and four other efficient GKA protocols. Both the complexity analysis and energy consumption costs analysis indicate that our proposed scheme is more efficient and suitable for heterogeneous wireless networks.

title: A CCA2 Secure Key Encapsulation Scheme Based on 3rd Order Shift Registers
abstract: In 1998, Cramer and Shoup proposed the first practical and provable cryptosystem against adaptive chosen ciphertext attack under the standard assumption in the standard model, that is, decisional Diffie-Hellman assumption. Recently, Lucks extended the Cramer-Shoup cryptosystem to a group of quadratic residues modulo a composite number and showed that the scheme is provably secure in the standard model. In this paper, we extend Lucks' key encapsulation scheme to a third order linear feedback shift register and is based on a new assunmption which is called shift register based decisional Diffie-Hellman assumptions (SR-DDH). The proposed scheme is provably secure against adaptive chosen ciphertext attack based on the hardness of shift register based decisional Diffie-Hellman assumption in the standard model and not in random oracle model. Furthermore, the size of public key and ciphertext are shorter than Cramer-Shoup cryptosystem and the computational complexity is also more efficient than Cramer-Shoup cryptosystem and Lucks scheme.

title: The use of bigrams to enhance text categorization
abstract: In this paper, we present an efficient text categorization algorithm that generates bigrams selectively by looking for ones that have an especially good chance of being useful. The algorithm uses the information gain metric, combined with various frequency thresholds. The bigrams, along with unigrams, are then given as features to two different classifiers: Naive Bayes and maximum entropy. The experimental results suggest that the bigrams can substantially raise the quality of feature sets, showing increases in the break-even points and F1 measures. The McNemar test shows that in most categories the increases are very significant. Upon close examination of the algorithm, we concluded that the algorithm is most successful in correctly classifying more positive documents, but may cause more negative documents to be classified incorrectly.

title: A Human Capital Perspective of Organizational Intention to Adopt Open Source Software
abstract: This study adopts the human capital perspective as a theoretical lens to understand the factors that influence organizational intention to adopt open source software (OSS). We posit that availability of internal human capital and accessibility to external human capital significantly affect an organization’s intention to adopt OSS either directly or indirectly through switching cost. We analyze survey responses from 81 chief information officers or information systems managers and the results indicate that organizational availability of internal human capital has an indirect effect on an organization’s intention to adopt OSS through switching cost whereas accessibility to external human capital has a direct effect on an organization’s intention to adopt OSS. This study has both theoretical and practical implications. Theoretically, the unique approach from the human capital perspective adds to the extant literature on organizational adoption of innovation and calls for more attention to be directed at understanding the influence of human capital in an increasingly technologically complex environment. Practically, our findings suggest that potential OSS adopters and proponents should develop the human capital necessary for effective exploitation of OSS.

title: A Distributed Throttling Approach for Handling High Bandwidth Aggregates
abstract: Public-access networks need to handle persistent congestion and overload caused by high bandwidth aggregates that may occur during times of flooding-based DDoS attacks or flash crowds. The often unpredictable nature of these two activities can severely degrade server performance. Legitimate user requests also suffer considerably when traffic from many different sources aggregates inside the network and causes congestion. This paper studies a family of algorithms that "proactively" protect a server from overload by installing rate throttles in a set of upstream routers. Based on an optimal control setting, we propose algorithms that achieve throttling in a distributed and fair manner by taking important performance metrics into consideration, such as minimizing overall load variations. Using ns-2 simulations, we show that our proposed algorithms 1) are highly adaptive by avoiding unnecessary parameter configuration, 2) provide max-min fairness for any number of throttling routers, 3) respond very quickly to network changes, 4) are extremely robust against extrinsic factors beyond the system control, and 5) are stable under given delay bounds.