12630328
Creating a large-scale content-based airphoto image digital library
This paper describes a content-based image retrieval digital library that supports geographical image retrieval over a testbed of 800 aerial photographs, each 25 megabytes in size. In addition, this paper also introduces a methodology to evaluate the performance of the algorithms in the prototype system. There are two major contributions: we suggest an approach that incorporates various image processing techniques including Gabor filters, image enhancement and image compression, as well as information analysis techniques such as the self-organizing map (SOM) into an effective large-scale geographical image retrieval system. We present two experiments that evaluate the performance of the Gabor-filter-extracted features along with the corresponding similarity measure against that of human perception, addressing the lack of studies in assessing the consistency between an image representation algorithm or an image categorization method and human mental model.
770502
Visualizing the archive of a computer mediated communication process
The archive of computer-mediated communication (CMC) process contains knowledge shared and information about participants' behavior patterns. However, most CMC systems focus only on organizing the content of discussions. We propose to demo a prototype system that integrates a social visualization technique with existing information analysis technologies to graphically summarize both the content and behavior of a CMC process.
14675043
Using 3D interfaces to facilitate the spatial knowledge retrieval: a geo-referenced knowledge repository system
Retrieving knowledge from a knowledge repository includes both the process of finding information of interest and the process of converting incoming information to a person's own knowledge. This paper explores the application of 3D interfaces in supporting the retrieval of spatial knowledge by presenting the development and the evaluation of a geo-referenced knowledge repository system. As computer screen is crowded with high volume of information available, 3D interface becomes a promising candidate to better use the screen space. A 3D interface is also more similar to the 3D terrain surface it represents than its 2D counterpart. However, almost all previous empirical studies did not find any supportive evidence for the application of 3D interface. Realizing that those studies required users to observe the 3D object from a given perspective by providing one static interface, we developed 3D interfaces with interactive animation, which allows users to control how a visual object should be displayed. The empirical study demonstrated that this is a promising approach to facilitate the spatial knowledge retrieval.
11070478
elpfulMed: Intelligent searching for medical information over the internet
Medical professionals and researchers need information from reputable sources to accomplish their work. Unfortunately, the Web has a large number of documents that are irrelevant to their work, even those documents that purport to be "medically-related." This paper describes an architecture designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, or "concept space," and Kohonen-based Self-Organizing Map (SOM) technologies to provide searchers with fine-grained results. Initial results indicate that these systems provide complementary retrieval functionalities. HelpfulMed not only allows users to search Web pages and other online databases, but also allows them to build searches through the use of an automatic thesaurus and browse a graphical display of medical-related topics. Evaluation results for each of the different components are included. Our spidering algorithm outperformed both breadth-first search and PageRank spiders on a test collection of 100,000 Web pages. The automatically generated thesaurus performed as well as both MeSH and UMLS--systems which require human mediation for currency. Lastly, a variant of the Kohonen SOM was comparable to MeSH terms in perceived cluster precision and significantly better at perceived cluster recall.
45804784
A new one-and-half layer channel routing algorithm based on assigning resources for CMOS gate array
It is demonstrated that sufficient and reasonable utilization of the constrained horizontal and vertical routing resources is the key to achieving a high completion rate in this one-and-one-half layer routing approach. By using the minimum intersection graph to order the nets, the number of intersections among the nets is minimum, the number of intersection columns is as small as possible, and the total length of poly-bars used in wiring is as short as possible. From this the requirements for the horizontal and vertical routing resources are as few as possible. A reasonable assignment of the horizontal routing resources can be achieved by operating the active track matrices of the nets at the predicted columns, while the optimal assignment of the vertical routing resources is obtained by using the cluster assignment algorithm of the incidence intersection columns. Guided by the wiring tracks in the predicted columns and using the poly-bars assigned, the channel routing can be implemented with high performance by scanning the channel from left to right and column by column. >
18103320
Image Completion from Low-Level Learning
We present a learning-based approach to complete the missing parts of an image. Besides the conventional adopted image continuity and coherency heuristics, learnt image patches are used to better regularize the completion result. Through the learning process from a collection of commonly encountered natural images, we built a synthetic world consisting of scenes and their corresponding images. We further model the inter-patch relationships with a Markov Network. A belief propagation scheme is then used to choose and update a latent scene structure based on a maximal posterior probability estimation of the given image. The above operation usually converges within a few iterations. The obtained image is visually realistic.
4515160
Alert Correlation for Extracting Attack Strategies
Alert correlation is an important technique for managing large the volume of intrusion alerts that are raised by heterogenous Intrusion Detection Systems (IDSs). The recent trend of research in this area is towards extracting attack strategies from raw intrusion alerts. It is generally believed that pure intrusion detection no longer can satisfy the security needs of organizations. Intrusion response and prevention are now becoming crucially important for protecting the network and minimizing damage. Knowing the real security situation of a network and the strategies used by the attackers enables network administrators to launches appropriate response to stop attacks and prevent them from escalating. This is also the primary goal of using alert correlation technique. However, most of the current alert correlation techniques only focus on clustering inter-connected alerts into different groups without further analyzing the strategies of the attackers. Some techniques for extracting attack strategies have been proposed in recent years, but they normally require defining a larger number of rules. This paper focuses on developing a new alert correlation technique that can help to automatically extract attack strategies from a large volume of intrusion alerts, without specific prior knowledge about these alerts. The proposed approach is based on two different neural network approaches, namely, Multilayer Perceptron (MLP) and Support Vector Machine (SVM). The probabilistic output of these two methods is used to determine with which previous alerts this current alert should be correlated. This suggests the causal relationship of two alerts, which is helpful for constructing attack scenarios. One of the distinguishing feature of the proposed technique is that an Alert Correlation Matrix (ACM) is used to store correlation strengthes of any two types of alerts. ACM is updated in the training process, and the information (correlation strength) is then used for extracting high level attack strategies.
19870915
Research on Network-Based Collaborative Commodity Development
In this paper, a detailed method is proposed to make the transformation of a product model to a commodity model. A collaborative commodity development theory based on the three properties of physical, energy and information is proposed. An integrated model composed of four sub-models is analyzed: designing sub-model, supplying sub-model, managing sub-model, and profit sub-model. The key techniques in the system development are discussed, including the network-based parts application technology and the commercial model optimization and evaluation technology. For the former, a search engine using the functional agent technology for network-based parts searching is described. A prototype system has been implemented to validate the proposed approach.
32302991
Image coding by folding
We propose an image coding algorithm which employs data hiding techniques to "fold" an image into itself. Data hiding is a process of encoding extra information into a host image by making small modifications to its pixels. In our approach, an image is split into two parts of equal size: a host image and a residual image. The residual image is compressed into a bit stream and then embedded into the host image. The host image, which is 50% of the size of the original image, is coded using standard compression techniques. The embedded data does not increase the bit rate of the coded image. As a result, one may code only 50% pixels of the original image and still have perfect reconstruction. Experimental results indicate that the algorithm has a lot of potential in image coding.