• Journal of Information Technology Services
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• v.8 no.1
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• pp.203-215
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• 2009

This paper illustrates the application of co-occurrence theory to generate lightweight ontologies semi-automatically. The proposed model includes three steps of a (Semi-) Automatic creation of Ontology; (they are conceptually named as) the Syntactic-based Ontology, the Semantic-based Ontology and the Ontology Refinement. Each of these three steps are designed to interactively work together, so as to generate Lightweight Ontologies. The Syntactic-based Ontology step includes generating Association words using co-occurrence in web documents. The Semantic-based Ontology step includes the Alignment large Association words with small Ontology, through the process of semantic relations by contextual terms. Finally, the Ontology Refinement step includes the domain expert to refine the lightweight Ontologies. We also conducted a case study to generate lightweight ontologies in specific domains(news domain). In this paper, we found two directions including (1) employment co-occurrence theory to generate Syntactic-based Ontology automatically and (2) Alignment large Association words with small Ontology to generate lightweight ontologies semi-automatically. So far as the design and the generation of big Ontology is concerned, the proposed research will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.

• Journal of KIISE:Databases
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• v.32 no.1
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• pp.86-99
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• 2005

In this paper, we suggest a system which automatically verifies and tunes transaction processing database applications based on program analysis technology. This system automatically verifies two kinds of transaction processing errors. The first case is the un-closed transaction. In this case, data is not updated as expected or performance of overall system can decrease seriously by locking some database tables until the process terminates. The second case is the miss-use of transaction isolation(inking) level. This causes runtime exception or abnormal termination of the program depending on runtime environment. This system automatically tunes two kinds of inefficient definition of transaction processing which decrease the performance of overall system. The first case happens when opened transaction is closed too late. And the second case happens when transaction isolation level is set too high.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.255-259
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• 2009

In this paper, we present AGE(Automatic Grid Environments), which is a middleware system in which Grid resources can automatically participate in a Grid environment. While other existing systems need the configuration of each Grid node to deploy a Grid environment, AGE offers automatic installation and execution of necessary middleware for participating in a Grid environment. And Grid applications in AGE do not need to be pre-installed and pre-configured. When an application is to be executed in participating Grid nodes, this system can download, install, and execute the application automatically. Therefore, AGE provides users with convenience such as deploying a Grid environment, executing the application, and releasing nodes or resources from the Grid environment automatically.

• Food Science and Industry
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• v.54 no.3
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• pp.160-170
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• 2021

A recent advance in communication technologies accelerates the spread of food safety issues once presented by the news media. To respond to those safety issues and take steps in a timely manner, automatically detecting related information from the news data matters. This work presents an AI-based system that detects risk information within a food-related news article. Experts in food safety areas participated in labeling risk information from the food-related news articles; we acquired 43,527 articles in which food names and risk information are marked as labels. Based on the news document, our system automatically detects food names and risk information by analyzing similarities between words within a text by leveraging learned word embedding vectors. Our AI-based system shows higher detection accuracy scores over a non-AI rule-based system: achieving an absolute gain of +32.94% in F1 for the food name category and +41.53% for the risk information category.

• Genomics & Informatics
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• v.17 no.2
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• pp.15.1-15.7
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• 2019

Automatically detecting mentions of pharmaceutical drugs and chemical substances is key for the subsequent extraction of relations of chemicals with other biomedical entities such as genes, proteins, diseases, adverse reactions or symptoms. The identification of drug mentions is also a prior step for complex event types such as drug dosage recognition, duration of medical treatments or drug repurposing. Formally, this task is known as named entity recognition (NER), meaning automatically identifying mentions of predefined entities of interest in running text. In the domain of medical texts, for chemical entity recognition (CER), techniques based on hand-crafted rules and graph-based models can provide adequate performance. In the recent years, the field of natural language processing has mainly pivoted to deep learning and state-of-the-art results for most tasks involving natural language are usually obtained with artificial neural networks. Competitive resources for drug name recognition in English medical texts are already available and heavily used, while for other languages such as Spanish these tools, although clearly needed were missing. In this work, we adapt an existing neural NER system, NeuroNER, to the particular domain of Spanish clinical case texts, and extend the neural network to be able to take into account additional features apart from the plain text. NeuroNER can be considered a competitive baseline system for Spanish drug and CER promoted by the Spanish national plan for the advancement of language technologies (Plan TL).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.271-274
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• 2019

In this paper, we proposed a detailed address acquisition scheme for automatically collecting data of a web page in a frame that is difficult to access by a general web access method. Using the Python language and the Beautiful Soup library, which can utilize the proposed address resolution technique and the HTML selector, we were able to automatically collect all the bulletin board text data written in several pages. By using the proposed method, we can collect large amount of data automatically by Python web scraping program for web pages of any form of address, and we expect that it can be used for big data analysis.

• Progress in Medical Physics
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• v.31 no.4
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• pp.153-162
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• 2020

Purpose: We aim to evaluate the accuracy and effectiveness of an automatically converted radiation therapy plan between Radixact machines by comparing the original plan with the transferred plan. Methods: The study involved a total of 20 patients for each randomly selected treatment site who received radiation treatment with Radixact. We set up the cheese phantom (Gammex RMI, Middleton, WI, USA) with an Exradin A1SL ion chamber (Standard Imaging, Madison, WI, USA) and GAFCHROMIC EBT3 film (International Specialty Products, Wayne, NJ, USA) inserted. We used three methods to evaluate an automatically converted radiation therapy plan using the features of the Plan transfer. First, we evaluated and compared Planning target volume (PTV) coverage (homogeneity index, HI; conformity index, CI) and organs at risk (OAR) dose statistics. Second, we compared the absolute dose using an ion chamber. Lastly, we analyzed gamma passing rates using film. Results: Our results showed that the difference in PTV coverage was 1.72% in HI and 0.17% in CI, and majority of the difference in OAR was within 1% across all sites. The difference (%) in absolute dose values was averaging 0.74%. In addition, the gamma passing rate was 99.64% for 3%/3 mm and 97.08% for 2%/2 mm. Conclusions: The Plan transfer function can be reliably used in appropriate situations.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.635-640
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• 2021

In this paper, we describe a parking space identification system that can automatically identify empty parking lot spaces from a parking lot photo. This system is based on a deep learning technique, and the accuracy of the identification result is good by learning various existing parking lot images. It could be applied to the existing parking management system. This system was also developed as a smartphone application for easy testing. Therefore, if you take a picture of a parking lot through a smartphone camera, the captured image is automatically recognized and an empty parking space can be automatically identified.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.5
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• pp.42-52
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• 1997

Computer aided process planning and Offline programming are decisive factors in successful implementation of automated robotic production. However, conventional offline programming procedure has proven ineffective due to time-consuming teaching process for robot programming and due to inefficient system modeling. The paper presents an efficient procedure to semi-automatically generate robot job programs for ship block welding applications. In the research, the teaching positions are automatically determined by predefined rules which are functions of the type and the dimensions of the given welding section of ship block. And a sequence of robot movements and welding conditions such as welding type, welding current, welding speed, and welding torch orientation, are determined by use of Standard Program which is experimentally proved to work well for the welding wection group. Finally, a robot program for the welding section is generated automatically. Based on the algorithm, a offline automatic teaching software is developed. The paper presents also the algorithm and structure of the software.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.52-61
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• 2017

Considering its significant impact on the cost and schedule of construction projects, formwork as one part of temporary facility categories in construction should be arranged precisely. Current practice in the formwork planning is often conducted manually and repetitively, causing low efficiency and time waste. This study proposes an automated framework to generate more accurate and detailed formwork plans by utilizing information from building information modeling (BIM) considering the adequate geometric and semantic information provided by the BIM model. The dimensions and quantities information of elements in a building can be extracted automatically. Then, a rule is prepared for calculating the required forms erected around elements based on the contact areas. Finally, an algorithm of integrating first fit decreasing (FFD) with coordinated bottom left (CBL) is applied to automatically generate the formwork plan. The BIM-based automated planning framework is demonstrated by an illustrative example. The results show that the proposed framework can generate the formwork plan accurately and automatically, and significantly improve the efficiency in the formwork plan and reuse.