9935268
Case and Constraint-Based Apartment Construction Project Planning System: FASTrak-APT
To effectively generate a fast and consistent apartment construction project network, Hyundai and KAIST have developed a case and constraint based project planning expert system for apartment domain, FASTrak-APT, inspired by the fact that human expert project planner uses previous cases for planning a new project and modifies them using her/his knowledge on domain constraints. This largescale, case based and mixed-initiative planning system integrated with intensive constraint-based adaptation utilizes semantic level meta-constraints and human decisions for compensating incomplete cases imbedding specific planning knowledge. The case and constraint based architecture inherently supports cross-checking cases with constraints during the system development and maintenance. This system has drastically reduced the time and effort required for initial project planning, improved the quality and completeness of the generated plans, and is expected to give the company the competitive advantage in contract bids for new contracts.
9952889
Extraction of Structured Rules from Web Pages and Maintenance of Mutual Consistency: XRML Approach
Web pages provide valuable knowledge for human comprehension in text, tables, and mathematical notations. However, the extraction and maintenance of structured rules from the Web pages are not easy tasks. To tackle these problems, we adopt the eXtensible Rule Markup Language framework. The RIML (Rule Identification Markup Language) and RSML (Rule Structure Markup Language) are two compliant representations in XRML for this purpose. RIML identifies the implicit rules in the Web pages possibly using multiple pages to make a rule or rule group. RSML specifies the complete rule structure to be processed by software agents or expert systems. 
 
In this study, we cover the natural text, tables, and implicit numeric functions in the texts. In order to fulfill the research goal, we define the necessary tags for the rule extraction and maintenance in XRML. Typical ones include tags for rule grouping, tabular rules, numeric operators, and functions. The rule acquisition process consists of rule base design, rule identification with RIML, and rule structuring with RSML. The maintenance process for the revisions that may occur either in Web pages and structured rules is also described. The approach is demonstrated with the shipping cost comparison on the electronic book stores.
9094168
Microscopic examination of TCP flows over transatlantic links
Much of the recent research and development in the area of high-speed TCP is focused on the steady state behavior of TCP flows. However, our experience with the first research only transatlantic 2.5 Gbps Lambda link clearly demonstrates the need to focus on the initial stages of TCP. The work we present here examines the behavior of TCP flows at microscopic level over high-bandwidth long delay networks. This examination has led us to study the influence of the minute properties of the underlying network on bursty protocols such as TCP at these very high speeds combined with high latency. In this paper we briefly describe the requirements for such an extreme network environment to support high-speed TCP flows. We also present results collected using transatlantic links at iGrid2002 where we tuned various host parameters and used modified TCP stacks.
35344991
Spatial Analysis of Linguistic Data with GIS Functions
Abstract During the 1980s techniques for analysis of geographical patterns have been refined to the point that they may be applied to data from many fields. Quantitative spatial analysis and existing functions available in geographical information systems (GIS) enable computerized implementations of these spatial analysis methods. This paper describes the application of quantitative spatial analysis and GIS functions to analysis of language data, using the extensive files of the Linguistic Atlas of the Middle and South Atlantic States (LAMSAS). A brief review of recent development of using quantitative and statistical methods for analysing linguistic data is also included.
17811625
A Graph-Based Approach for Modeling and Indexing Video Data
In this work, we propose new graph-based data model and indexing to organize and manage video data. To consider spatial and temporal characteristics of video, we introduce a new graph-based data model called spatio-temporal region graph (STRG). Unlike existing graph-based data structures which provide only spatial features, the proposed STRG further provides temporal features, which represent temporal relationships among spatial objects. The STRG is decomposed into its subgraphs object graphs (OGs) and background graphs (BGs). In addition, a new distance measure, called extended graph edit distance (EGED), is introduced in metric space for matching and indexing. Based on clustering and EGED, we propose a new indexing method STRG-index, which is faster and more accurate. We compare the STRG-Index with the M-tree, which is a popular tree-based indexing method for multimedia data. The STRG-index outperforms the M-tree in terms of cost and speed
12830619
Image is everything: advancing HCI knowledge and interface design using the system image
As the field of human-computer interaction matures, the need for proven, dependable engineering processes for interface development becomes apparent. Our continuing work in developing LINK-UP, an integrated design and reuse environment, suggests that a better understanding of the system image is key to the successful evaluation of design prototypes, and an aide in applying knowledge from the repository. This paper describes our ongoing work to enhance LINK-UP by developing and augmenting the system image to make it the central communication point between different stages of design and between different stakeholders. We report on a study of the new task flow that demonstrated the value of the system image within a broader design context. Overall, our findings indicate that the effective creation and use of knowledge repositories by novice HCI designers hinges on successful application of existing HCI design concepts within a practical integrated design environment.
6995681
Quasi-optimal case-selective neural network model for software effort estimation
Abstract A number of software effort estimations have attempted using statistical models, case based reasoning, and neural networks. The research results showed that the neural network models perform at least as well as the other approaches, so we selected the neural network model as the estimator. However, since the computing environment changes so rapidly in terms of programming languages, development tools, and methodologies, it is very difficult to maintain the performance of estimation models for the new breed of projects. Therefore, we propose a search method that finds the right level of relevant cases for the neural network model. For the selected case set, the scale of the neural network model can be reduced by eliminating the qualitative input factors with the same values. Since there exist a multitude of combinations of case sets, we need to search for the optimal reduced neural network model and corresponding case set. To find the quasi-optimal model from the hierarchy of reduced neural network models, we adopted the beam search technique and devised the case-set selection algorithm. We have shown that the resulting model significantly outperforms the original full model for the software effort estimation. This approach can be also used for building any case-selective neural network.