• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.105-112
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• 2021

In the era of big data, interest in data is exploding. In particular, the development of the Internet and social media has led to the creation of new data, enabling the realization of the era of big data and artificial intelligence and opening a new chapter in convergence technology. Also, in the past, there are many demands for analysis of data that could not be handled by programs. In this paper, an analysis model was designed and verified for classification of unstructured data, which is often required in the era of big data. Data crawled DBPia's thesis summary, main words, and sub-keyword, and created a database using KoNLP's data dictionary, and tokenized words through morpheme analysis. In addition, nouns were extracted using KAIST's 9 part-of-speech classification system, TF-IDF values were generated, and an analysis dataset was created by combining training data and Y values. Finally, The adequacy of classification was measured by applying three analysis algorithms(random forest, SVM, decision tree) to the generated analysis dataset. The classification model technique proposed in this paper can be usefully used in various fields such as civil complaint classification analysis and text-related analysis in addition to thesis classification.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.649-661
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• 2020

Cut-slope management system (CSMS) has been investigated all slopes on the road of the whole country to evaluate risk rating of each slope. Based on this evaluation, the decision-making for maintenance can be conducted, and this procedure will be helpful to establish a consistent and efficient policy of safe road. CSMS has updated the database of all slopes annually, and this database is constructed based on a basic and detailed investigation. In the database, there are two type of data: first one is an objective data such as slopes' location, height, width, length, and information about underground and bedrock, etc; second one is subjective data, which is decided by experts based on those objective data, e.g., degree of emergency and risk, maintenance solution, etc. The purpose of this study is identifying an data application plan to utilize those CSMS data. For this purpose, logistic regression, which is a basic machine-learning method to construct a prediction model, is performed to predict a judging-type variable (i.e., subjective data) based on objective data. The constructed logistic model shows the accurate prediction, and this model can be used to judge a priority of slopes for detailed investigation. Also, it is anticipated that the prediction model can filter unusual data by comparing with a prediction value.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.27-46
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• 2022

Today, public libraries are contributing deeply to our society by strengthening their ability and services to identify and respond to users' needs through various programs. However, it is difficult to find a study that analyzed the research status of public library programs or changes over time. Therefore, for the purpose of systematically grasping research trends in the field of overseas public library programs, an intellectual structure analysis based on keyword profiling was performed. Specifically, subject terms analysis, network analysis and cluster analysis, and analysis by period/year were performed based on the controlled keywords (subject terms) of journal articles papers searched in the LISTA database. As a result, first, it was found that 9 subjects corresponding to all global/hot/local topics are leading the research in the field of overseas public library programs. Second, five research areas in the field of overseas public library programs(cultural programs, outreach programs, activity programs, public services, community) could be visualized and clearly identified. Third, research in the field of overseas public library programs began in earnest in the late 1990s and was active from the mid-2000s to the early 2010s, and after that, it was found to be somewhat stagnant until recently. This study is the result of specifically identifying research trends on programs that recently emerged as a major task of public libraries, and can be used as basic data and prior knowledge to explore the development direction of public library programs in the future.

• Therapeutic Science for Rehabilitation
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• v.10 no.2
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• pp.23-36
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• 2021

Objective : The purpose of this study was to analyze group programs for the elderly living in communities and to provide basic data for applying effective occupational therapy programs for the elderly in the community. Methods : From January 2009 to December 2019, articles on group programs for the elderly in the community were searched for in the NDSL, DBPia, Riss, and PubMed databases. Based on the inclusion and exclusion criteria, a total 16 out of the 147 identified studies were selected and analyzed. This review analyzed the characteristics of the participants, contents of the group program, session and duration of the intervention, outcome measures, and effect of the group program. Results : Single group pre-post test studies with evidence level III were most common (8, 50.0%), and five (31.3%) of the studies were conducted on the community-dwelling elderly. Across all the 16 studies, there were 10 types of group programs, and the most frequently used was an exercise group program (25.0%). According to the analysis of the group program period, sessions and time, the intervention period was most commonly 12 weeks (37.5%), with 8 sessions or 12 sessions (25.0%). The intervention time in the group program was most commonly 60 minutes (43.8%). Conclusion : This study can be used as a basis for the development of effective group programs for the elderly and patients with dementia in community-based long-term care services.

• The KIPS Transactions:PartA
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• v.10A no.5
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• pp.469-478
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• 2003

Internet information search engines using web robots visit servers conneted to the Internet periodically or non-periodically. They extract and classify data collected according to their own method and construct their database, which are the basis of web information search engines. There procedure are repeated very frequently on the Web. Many search engine sites operate this processing strategically to become popular interneet portal sites which provede users ways how to information on the web. Web search engine contacts to thousands of thousands web servers and maintains its existed databases and navigates to get data about newly connected web servers. But these jobs are decided and conducted by search engines. They run web robots to collect data from web servers without knowledge on the states of web servers. Each search engine issues lots of requests and receives responses from web servers. This is one cause to increase internet traffic on the web. If each web server notify web robots about summary on its public documents and then each web robot runs collecting operations using this summary to the corresponding documents on the web servers, the unnecessary internet traffic is eliminated and also the accuracy of data on search engines will become higher. And the processing overhead concerned with web related jobs on web servers and search engines will become lower. In this paper, a monitoring system on the web server is designed and implemented, which monitors states of documents on the web server and summarizes changes of modified documents and sends the summary information to web robots which want to get documents from the web server. And an efficient web robot on the web search engine is also designed and implemented, which uses the notified summary and gets corresponding documents from the web servers and extracts index and updates its databases.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.281-290
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• 2020

With the spread of smartphones, services that want to use personalized data are increasing. In particular, healthcare-related services deal with a variety of data, and data visualization techniques are used to effectively show this. As data visualization techniques are used, interactions in visualization are also naturally emphasized. In the PC environment, since the interaction for data visualization is performed with a mouse, various filtering for data is provided. On the other hand, in the case of interaction in a mobile environment, the screen size is small and it is difficult to recognize whether or not the interaction is possible, so that only limited visualization provided by the app can be provided through a button touch method. In order to overcome the limitation of interaction in such a mobile environment, we intend to enable data visualization interactions through conversations with chatbots so that users can check individual data through various visualizations. To do this, it is necessary to convert the user's query into a query and retrieve the result data through the converted query in the database that is storing data periodically. There are many studies currently being done to convert natural language into queries, but research on converting user queries into queries based on visualization has not been done yet. Therefore, in this paper, we will focus on query generation in a situation where a data visualization technique has been determined in advance. Supported interactions are filtering on task x-axis values and comparison between two groups. The test scenario utilized data on the number of steps, and filtering for the x-axis period was shown as a bar graph, and a comparison between the two groups was shown as a line graph. In order to develop a natural language processing model that can receive requested information through visualization, about 15,800 training data were collected through a survey of 1,000 people. As a result of algorithm development and performance evaluation, about 89% accuracy in classification model and 99% accuracy in query generation model was obtained.

• Korean Security Journal
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• no.19
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• pp.105-138
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• 2009

This study's purpose is to present the improvement of effectiveness of security activity for international conference among Several Countries which can be held hereafter. On the basis of security activity problems originating in APEC that had been held in Busan in 2005. I made up questions three times to on the members of the police, military, fire figher and national intelligence service who had experienced in Busan APEC and recognition of possible problem and possibility of improvement on each item of questions was analyzed by Delphi Method. Also interviews with 4 security experts selected from each security agency were conducted to present improvement in each part of problem. The results obtained from the face to face interview with four experts of security-enforcement agency about the role and importance of site activity stage for international conference among several countries are as followings ; First, the system that experienced security-enforcement agents can be selected for the next national security event is needed, by data-basing the security-enforcement agents who were experienced in security event as man power management. Second, the middle-term plan for the introduction of high-tech equipment and joint inspection with relevant security agents are needed for the efficient explosive technical detection. Third, high-tech security equipment could be introduced through the international high-tech security equipment exhibition. Fourth, an anti-terrorism plan should be measured by sharing information through the cooperation with domestic and international intelligence agency. Fifth, public relations should be measured systematically by organization rather than agents' individual public relations. Sixth, political consideration to secure integrative coordination with other agency is needed for security activity, through normal cooperation with fire fighting related agency such as an electric, gas, elevator company. Seventh, a definite press guideline is needed for a convenient news coverage and safety during security event.

• Journal of KIISE:Information Networking
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• v.29 no.3
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• pp.286-298
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• 2002

The Remote Procedure Call(RPC) has been traditionally used for Inter Process Communication(IPC) among precesses in distributed computing environment. As distributed applications have been complicated more and more, the Mobile Agent paradigm for IPC is emerged. Because there are some paradigms for IPC, researches to evaluate and compare the performance of each paradigm are issued recently. But the performance models used in the previous research did not reflect real distributed computing environment correctly, because they did not consider the evacuation elements for providing security services. Since real distributed environment is open, it is very vulnerable to a variety of attacks. In order to execute applications securely in distributed computing environment, security services which protect applications and information against the attacks must be considered. In this paper, we evaluate and compare the performance of the Remote Procedure Call with that of the Mobile Agent in IPC paradigms. We examine security services to execute applications securely, and propose new performance models considering those services. We design performance models, which describe information retrieval system through N database services, using Petri Net. We compare the performance of two paradigms by assigning numerical values to parameters and measuring the execution time of two paradigms. In this paper, the comparison of two performance models with security services for secure communication shows the results that the execution time of the Remote Procedure Call performance model is sharply increased because of many communications with the high cryptography mechanism between hosts, and that the execution time of the Mobile Agent model is gradually increased because the Mobile Agent paradigm can reduce the quantity of the communications between hosts.

• Journal of KIISE:Databases
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• v.30 no.4
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• pp.381-396
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• 2003

Subsequence matching is an operation that finds subsequences whose changing patterns are similar to a given query sequence from time-series databases. This paper points out the performance bottleneck in subsequence matching, and then proposes an effective method that improves the performance of entire subsequence matching significantly by resolving the performance bottleneck. First, we analyze the disk access and CPU processing times required during the index searching and post processing steps through preliminary experiments. Based on their results, we show that the post processing step is the main performance bottleneck in subsequence matching, and them claim that its optimization is a crucial issue overlooked in previous approaches. In order to resolve the performance bottleneck, we propose a simple but quite effective method that processes the post processing step in the optimal way. By rearranging the order of candidate subsequences to be compared with a query sequence, our method completely eliminates the redundancy of disk accesses and CPU processing occurred in the post processing step. We formally prove that our method is optimal and also does not incur any false dismissal. We show the effectiveness of our method by extensive experiments. The results show that our method achieves significant speed-up in the post processing step 3.91 to 9.42 times when using a data set of real-world stock sequences and 4.97 to 5.61 times when using data sets of a large volume of synthetic sequences. Also, the results show that our method reduces the weight of the post processing step in entire subsequence matching from about 90% to less than 70%. This implies that our method successfully resolves th performance bottleneck in subsequence matching. As a result, our method provides excellent performance in entire subsequence matching. The experimental results reveal that it is 3.05 to 5.60 times faster when using a data set of real-world stock sequences and 3.68 to 4.21 times faster when using data sets of a large volume of synthetic sequences compared with the previous one.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.1
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• pp.42-55
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• 2023

A methodology to predict the carbon performance of newly created urban greening plans is required as policies based on quantifying carbon performance are rapidly being introduced in the face of the climate crisis caused by global warming. This study developed a tree carbon calculator that can be used for carbon reduction designs in landscaping and attempted to verify its effectiveness in landscape design. For practical operability, MS Excel was selected as a format, and carbon absorption and storage by tree type and size were extracted from 93 representative species to reflect plant design characteristics. The database, including tree unit prices, was established to reflect cost limitations. A plantation experimental design to verify the performance of the tree carbon calculator was conducted by simulating the design of parks in the central region for four landscape design, and the causal relationship was analyzed by conducting semi-structured interviews before and after. As a result, carbon absorption and carbon storage in the design using the tree carbon calculator were about 17-82% and about 14-85% higher, respectively, compared to not using it. It was confirmed that the reason for the increase in carbon performance efficiency was that additional planting was actively carried out within a given budget, along with the replacement of excellent carbon performance species. Pre-interviews revealed that designers distrusted data and the burdens caused by new programs before using the arboreal carbon calculator but tended to change positively because of its usefulness and ease of use. In order to implement carbon reduction design in the landscaping field, it is necessary to develop it into a carbon calculator for trees and landscaping performance. This study is expected to present a useful direction for ntroducing carbon reduction designs based on quantitative data in landscape design.