Acronym-Expansion Disambiguation for Intelligent Processing of Enterprise Information

An acronym is an abbreviation of several words in such a way that the abbreviation itself forms a pronounceable word. Acronyms occur frequently throughout various documents, especially those of a technical nature, for example, research papers and patents. While these acronyms can enhance document readability, in a variety of fields, they have a negative effect on business intelligence. To resolve this problem, we propose a method of acronym-expansion disambiguation to collect high-quality enterprise information. In experimental evaluations, we demonstrate its efficiency through the use of objective comparisons

Development of the Korean Spine Database and Automatic Surface Mesh Intersection Algorithm for Constructing e

By 2026, Korea is expected to surpass the UN’s definition of an aged society and reach the level of a superaged society. With an aging population come increased disorders involving the spine. To prevent unnecessary spinal surgery and support scientific diagnosis of spinal disease and systematic prediction of treatment outcomes, we have been developing e-Spine, which is a computer simulation model of the human spine. In this paper, we present the Korean spine database and automatic surface mesh intersection algorithm to construct e-Spine. To date, the Korean spine database has collected spine data from 77 cadavers and 298 patients. The spine data consists of 2D images from CT, MRI, or X-ray, 3D shapes, geometry data, and property data. The volume and quality of the Korean spine database are now the world’s highest ones. In addition, our triangular surface mesh intersection algorithm automatically remeshes the spine-implant intersection model to make it valid for finite element analysis (FEA). This makes it possible to run the FEA using the spine-implant mesh model without any manual effort. Our database and surface mesh intersection algorithm will offer great value and utility in the diagnosis, treatment, and rehabilitation of patients suffering from spinal diseases

Multilingual Question Answering with High Portability on Relational Databases

This paper describes a highly-portable multilingual question answering system on multiple relational databases. We apply semantic category and pattern-based grammars, into natural language interfaces to relational databases. Lexico-semantic pattern (LSP) and multi-level grammars achieve portability of languages, domains, and DBMSs. The LSP-based linguistic processing does not require deep analysis that sacrifices robustness and flexibility, but can handle delicate natural language questions. To maximize portability, we drive various dependent parts into two tight corners, i.e., language-dependent part into front linguistic analysis, and domain-dependent and database-dependent parts into backend SQL query generation

Finding Optimal Stations Using Euclidean Distance and Adjustable Surrounding Sphere

Air quality monitoring network (AQMN) plays an important role in air pollution management. However, setting up an initial network in a city often lacks necessary information such as historical pollution and geographical data, which makes it challenging to establish an effective network. Meanwhile, cities with an existing one do not adequately represent spatial coverage of air pollution issues or face rapid urbanization where additional stations are needed. To resolve the two cases, we propose four methods for finding stations and constructing a network using Euclidean distance and the k-nearest neighbor algorithm, consisting of Euclidean Distance (ED), Fixed Surrounding Sphere (FSS), Euclidean Distance + Fixed Surrounding Sphere (ED + FSS), and Euclidean Distance + Adjustable Surrounding Sphere (ED + ASS). We introduce and apply a coverage percentage and weighted coverage degree for evaluating the results from our proposed methods. Our experiment result shows that ED + ASS is better than other methods for finding stations to enhance spatial coverage. In the case of setting up the initial networks, coverage percentages are improved up to 22%, 37%, and 56% compared with the existing network, and adding a station in the existing one improved up by 34%, 130%, and 39%, in Sejong, Bonn, and Bangkok cities, respectively. Our method depicts acceptable results and will be implemented as a guide for establishing a new network and can be a tool for improving spatial coverage of the existing network for future expansions in air monitoring

Improving the Energy Efficiency of a Cluster Head Election for Wireless Sensor Networks

Sensor Networks can perceive the extensive area by applying many sensor nodes because the size of sensor nodes is relatively small and cheap. Sensor nodes can transfer multi-hop data to sink nodes which are far away than sending and receiving distance. Generally sensor nodes are composed of a large size so it is difficult that much capacity is loaded on nodes. Many routing methods are proposed in order to raise energy efficiency in sensor networks field. There is a routing method based on structure as a composing method of network by cluster. Cluster technology consisting and maintaining network topology based on cluster is mostly studied in routing protocol. There are demerits that LEACH, EACHS shall be rest energy of all nodes and HEED does not guarantee the number of cluster head. Proposed energy efficiency of selected cluster head guarantees the number of cluster head which is a demerit of HEED and minimizes the node of DEAD