38977435
Sharing and Visualizing Infectious Disease Datasets Using the WNV-BOT Portal System
Infectious disease outbreaks are critical threats to public health and national security. Information systems play a central role in developing an effective comprehensive approach to prevent, detect, respond to, and manage infectious disease outbreaks of plants, animals, and humans.
40127439
Authorship Analysis in Cybercrime Investigation
Criminals have been using the Internet to distribute a wide range of illegal materials globally in an anonymous manner, making criminal identity tracing difficult in the cybercrime investigation process. In this study we propose to adopt the authorship analysis framework to automatically trace identities of cyber criminals through messages they post on the Internet. Under this framework, three types of message features, including style markers, structural features, and content-specific features, are extracted and inductive learning algorithms are used to build feature-based models to identify authorship of illegal messages. To evaluate the effectiveness of this framework, we conducted an experimental study on data sets of English and Chinese email and online newsgroup messages. We experimented with all three types of message features and three inductive learning algorithms. The results indicate that the proposed approach can discover real identities of authors of both English and Chinese Internet messages with relatively high accuracies.
40149048
An International Perspective on Fighting Cybercrime
Cybercrime is becoming ever more serious. Findings from the 2002Computer Crime and Security Survey show an upward trend that demonstrates aneed for a timely review of existing approaches to fighting this new phenomenonin the information age. In this paper, we provide an overview of cybercrimeand present an international perspective on fighting cybercrime. We review currentstatus of fighting cybercrime in different countries, which rely on legal, organizational,and technological approaches, and recommend four directions forgovernments, lawmakers, intelligence and law enforcement agencies, and researchersto combat cybercrime.
350148
Visualization tools for self-organizing maps
Various statistical and pattern recognition techniques, such as concept spaces and category maps in the Illinois Digital Library project, has been explored to solve the semantic interoperability problem in DLI-1. Self-organizing category map is identified as a powerful tool for information summarization. However, visualizing a large-scale self-organizing map in a restricted size of window is difficult. For smaller regions, displaying labels is infeasible. In this paper, two visualization tools, fisheye view and fractal view, are presented. It assists users to visualize a largescale self-organizing map geographically and semantically.
7975073
A Collection of Visual Thesauri for Browsing Large Collections of Geographic Images
Digital libraries of geo-spatial multimedia content are currently deficient in providing fuzzy, concept-based retrieval mechanisms to users. The main challenge is that indexing and thesaurus creation are extremely laborintensive processes for text documents and especially for images. Recently, 800,000 declassified satellite photographs were made available by the United States Geological Survey. Additionally, millions of satellite and aerial photographs are archived in national and local map libraries. Such enormous collections make human indexing and thesaurus generation methods impossible to utilize. In this article we propose a scalable method to automatically generate visual thesauri of large collections of geo-spatial media using fuzzy, unsupervised machine-learning techniques.
35410760
Collaborative Workflow Management for Interagency Crime Analysis
To strengthen homeland security, there is a critical need for new tools that can facilitate real time collaboration among various law enforcement agencies. Through a field study, we find that law enforcement work is knowledge intensive and involves complex collaborative processes interrelating a large number of disparate units in a loosely defined virtual organization. To support knowledge intensive collaboration, we propose a new workflow centric framework to seamlessly integrate previously separate techniques from the fields of information retrieval and workflow management. Specifically, we develop a collaborative workflow management framework for interagency crime analysis. The key contribution of our research is that by integrating various state-of-the-art techniques innovatively, the proposed system can support real time collaboration processes in a virtual organization that evolves dynamically.
53306841
Dental Biometrics: Alignment and Matching of Dental Radiographs
Dental biometrics utilizes dental radiographs for human identification. The dental radiographs provide information about teeth, including tooth contours, relative positions of neighboring teeth, and shapes of the dental work (e.g., crowns, fillings, and bridges). The proposed system has two main stages: feature extraction and matching. The feature extraction stage uses anisotropic diffusion to enhance the images and a mixture of Gaussians model to segment the dental work. The matching stage has three sequential steps: tooth-level matching, computation of image distances, and subject identification. In the tooth-level matching step, tooth contours are matched using a shape registration method and the dental work is matched on overlapping areas. The distance between the tooth contours and the distance between the dental works are then combined using posterior probabilities. In the second step, the tooth correspondences between the given query (postmortem) radiograph and the database (antemortem) radiograph are established. A distance based on the corresponding teeth is then used to measure the similarity between the two radiographs. Finally, all the distances between the given postmortem radiographs and the antemortem radiographs that provide candidate identities are combined to establish the identity of the subject associated with the postmortem radiographs.
16963632
Agents Making Sense of the Semantic Web
Effective use of the vast quantity of available information and services on the Internet will require multi-agent systems to be tightly integrated with existing web infrastructure. This however will be impossible unless the information on the web is presented in a semantic language, such as the DARPA Agent Markup Language (DAML), which is one aim of the “Semantic Web”. As part of our exploration of Semantic Web technology, and DAML in particular, we have constructed ITTALKS, a web-based system for automatic and intelligent notification of information technology talks. In this paper, we describe the ITTALKS system, and discuss the numerous ways in which the use of Semantic Web concepts and DAML extend its ability to provide an intelligent online service to both the human community and, more interestingly, the agents assisting them.
10299300
On the development of a fully automated cryosection image registration system
The CCD cryosection images for the male collected in the National Library of Medicine's Visible Human Project were registered through a procedure involving significant human intervention. In addition, several large misalignments were visible in the registered CCD data for the male. To expedite the exploitation of the visible human cryosection data sets, there is a need to develop a highly accurate yet efficient image registration tool. In this paper, we present the current status of the development of such a fully automated registration system. This system is based on the maximization of mutual information criterion. One key issue of this approach is a robust optimization scheme. The method developed in this paper is to estimate the initial search point through segmentations of regions of interest for each cryosection image slice. Experimental results using the 70 mm cryosection image data for the male are presented in this paper.
41746629
Quick Buddy-Subcube Compaction in Hypercubes
After repeated subcube allocation and deallocation, the hypercube system tends to become fragmented, which can be taken care of by using subcube compaction. Basic buddy-subcube compaction deals with compacting free buddy-subcubes with the same dimension concurrently. All migration paths are pairwise disjoint and contain no links of active subcubes, so that task migration can be performed without suspending the execution of other jobs. This paper considers quick buddy-subcube compaction in that not only can free subcubes with two adjacent dimensions be compacted concurrently, but two disjoint paths can be established between every pair of source-target nodes. Parallel subcube compaction with two concurrent dimensions apparently speeds up subcube compaction by a factor of two. The use of double disjoint paths between each pair of source-target nodes also speeds up subcube compaction by a factor of nearly two. Thus, our approach can speed up subcube compaction by a factor of nearly four.
30915392
An HCI method to improve the human performance reduced by local-lag mechanism
Local-lag mechanism can maintain consistency for replicated continuous applications, but with a tradeoff of adding delay to local operations. To relieve the negative effects of the delay, this paper proposes an HCI method named echo. With the help of the echo method users can immediately perceive the results of their operations and how large the lag is. In order to evaluate the proposed method, a desktop collaborative virtual environment (CVE) system and a virtual object control task were employed to study the effects of the echo method on human performance (including task completion time, error count, and interaction quality). Experimental results indicate that when the lag exceeds 100ms the echo method can improve human performance with the effects becoming more evident when a larger lag is used.