• Journal of KIISE:Databases
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• v.33 no.7
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• pp.693-707
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• 2006

To improve performance using a multidimensional index in similar sequence matching, we transform a high-dimensional sequence to a low-dimensional sequence, and then construct a low-dimensional MBR that contains multiple transformed sequences. In this paper we propose a formal method that transforms a high-dimensional MBR itself to a low-dimensional MBR, and show that this method significantly reduces the number of lower-dimensional transformations. To achieve this goal, we first formally define the new notion of MBR-safe. We say that a transform is MBR-safe if a low-dimensional MBR to which a high-dimensional MBR is transformed by the transform contains every individual low-dimensional sequence to which a high-dimensional sequence is transformed. We then propose two MBR-safe transforms based on DFT and DCT, the most representative lower-dimensional transformations. For this, we prove the traditional DFT and DCT are not MBR-safe, and define new transforms, called mbrDFT and mbrDCT, by extending DFT and DCT, respectively. We also formally prove these mbrDFT and mbrDCT are MBR-safe. Moreover, we show that mbrDFT(or mbrDCT) is optimal among the DFT-based(or DCT-based) MBR-safe transforms that directly convert a high-dimensional MBR itself into a low-dimensional MBR. Analytical and experimental results show that the proposed mbrDFT and mbrDCT reduce the number of lower-dimensional transformations drastically, and improve performance significantly compared with the $na\"{\i}ve$ transforms. These results indicate that our MBR- safe transforms provides a useful framework for a variety of applications that require the lower-dimensional transformation of high-dimensional MBRs.

• Economic and Environmental Geology
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• v.42 no.3
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• pp.273-282
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• 2009

To render more valuable information, a spatial database is being constructed from digitalized maps in the geographic areas. Transferring file-based maps into a spatial database, facilitates the integration of larger databases and information retrieval using database functions. Geological mapping is the graphical interpretation results of the geological phenomenon by geological surveyors, which is different from other thematic maps produced quantitatively. These features make it difficult to construct geologic databases needing geologic interpretation about various meanings. For those reasons, several organizations in the USA and Australia are suggesting the data model for the database construction. But, it is hard to adapt to a domestic environment because of the representation differences of geological phenomenon. This paper suggests the data model adaptive in domestic environment analyzing 1:50,000 scales of geologic maps and more detailed mine geologic maps. The suggested model is a logical data model for the ArcGIS GeoDatabase. Using the model it can be efficiently applicable in the 1:50,000 scales of geological maps. It is expected that the geologic data model suggested in this paper can be used for integrated use and efficient management of geologic maps.

• The Journal of Korean Philosophical History
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• no.31
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• pp.321-346
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• 2011

This is a preliminary study in order to deal intensively with the overall characteristics of Korean military science in the future days. First off, the history of military science of China based on the precedent studies was recapitulated, and a comparative study on the acceptance process of the books on military art and science, as well as on understanding patterns of literati on the subject through literature searches, ranging from the Three Kingdoms Period to the Goryeo Dynasty in Korean peninsula, was conducted. In case of Korea, the Chinese books on military strategy, including Sun Tzu's the Art of War, had already been passed down during the Three Kingdoms Period, and broadly read by scholarly people. They had utilized diverse methods based on their knowledge of Confucianism. In the reference materials, the authors of Korean military strategy books had greatly relied upon the Chinese books on military strategies, however, they had made the military principles run in their own way. At the end of Goryeo Dynasty, 'Military Science' had been well established as a subject in academia, and this curriculum had been taught not only at the National Confucian Academy, Seonggyun-gwan, in the capital but also at the country public school ("Hyanggyo") in the province together with Confucianism. Because of the limits of reference materials, however, it was difficult to confirm whether or not such strategic experiences were actually led to the publication of the books on military art and science, or how many books on military strategies and tactics had been published up until the end of Goryeo Dynasty. But, the facts that there were not many publications of the books on military strategies during the era of Three Kingdoms and of Goryeo Dynasty don't mean that Korean military science had entirely relied upon the Chinese military art and science. For instance, such strategies, tactics and leaderships as exhibited in the process of the Great Victory at Salsu River ("Salsu Daecheop") achieved by General Eulji Mun-deok, as well as the Great Victory at Gwiju ("Gwiju Daecheop") achieved by General Kang Gam-chan could never happen by chance.

• Korean Journal of Social Welfare Studies
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• v.49 no.3
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• pp.247-275
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• 2018

In the absence of a research study on meta-analysis in terms of program development, the purpose of the study is to analyze the contents of the meta-analysis research studies which has been conducted for 18 years, and is to identify the level of program component evidence for the development of social work program. In order to achieve these purposes, the study analyzed the feature and usefulness of the 110 meta-analysis studies(5,781 program evaluation studies)published from 2010 to June 2017 in major academic journals related to the areas of the social welfare, psychology, counseling and health. The major findings are as follows. The 110 meta-analysis studies tended to narrow down the scope of the population, problems, and program types, but they also included a lot of heterogeneous types. In the statistical methods, there were relatively few studies to explain the factors behind the heterogeneity of program effectiveness. In addition, researchers tended to select program components arbitrarily with bias on specific components. The important program components with the statistical validity are as follows; the age of the subjects, the severity of the problem, the expertise of the providers, and the strength and activities of the intervention, The academic meanings of the study results was discussed, and the direction of future research was presented to increase the usefulness of the metaanalysis for program development.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.459-466
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• 2018

Gendered innovations is a term used by policy makers and academics to refer the process of creating better research and development (R&D) for both men and women. In this paper, we analyze the literatures in image and speech signal processing that can be used in ICT, examine the importance of gendered innovations through case study. Therefore the latest domestic and foreign literature related to image and speech signal processing based on gender research is searched and a total of 9 papers are selected. In terms of gender analysis, research subjects, research environment, and research design are examined separately. Especially, through the case analysis of algorithms of the elderly voice signal processing, machine learning, machine translation technology, and facial gender recognition technology, we found that there is gender bias in existing algorithms, and which leads to gender analysis is required. We also propose a gendered innovations method integrating sex and gender analysis in algorithm development. Gendered innovations in ICT can contribute to the creation of new markets by developing products and services that reflect the needs of both men and women.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.321-335
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• 2023

Monitoring sediment loads in natural rivers is the key process in river engineering, but it is costly and dangerous. In practice, suspended loads are directly measured, and total loads, which is a summation of suspended loads and bed loads, are estimated. This study proposes a real-time sediment discharge monitoring system using the horizontal acoustic Doppler current profiler (H-ADCP) and support vector regression (SVR). The proposed system is comprised of the SVR model for suspended sediment concentration (SVR-SSC) and for total loads (SVR-Q_TL), respectively. SVR-SSC estimates SSC and SVR-Q_TL mimics the modified Einstein procedure. The grid search with K-fold cross validation (Grid-CV) and the recursive feature elimination (RFE) were employed to determine SVR's hyperparameters and input variables. The two SVR models showed reasonable cross-validation scores (R²) with 0.885 (SVR-SSC) and 0.860 (SVR-Q_TL). During the time-series sediment load monitoring period, we successfully detected various sediment transport phenomena in natural streams, such as hysteresis loops and sensitive sediment fluctuations. The newly proposed sediment monitoring system depends only on the gauged features by H-ADCP without additional assumptions in hydraulic variables (e.g., friction slope and suspended sediment size distribution). This method can be applied to any ADCP-installed discharge monitoring station economically and is expected to enhance temporal resolution in sediment monitoring.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.215-220
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• 2023

Network technology used as a physical interface to retrieve, store, and exchange data is leading the era of data capitalism in the 21st century. The capacity of network technology dominates almost all communication in everyday life, and makes social understanding and experiences in the physical world visible in cyberspace. The movements of human bodies and objects in cyberspace are placed in a social context. This paper paid attention to these phenomena and examined the cases of activism that raised real problems through cyberspace. In particular, the focus of the study is the digital activism of the Electronic Disturbance Theater, which combines critical art and thinking for democracy with the realm of information and demonstrates aesthetic imagination. The first chapter of the main body briefly outlines the meaning activism as a social movement in cyberspace. The second chapter looks back on the alternatives of <FloodNet>, which represents the early activism performance of EDT. And then in the last chapter, the poetic significance of the <Transborder Immigrant Tool> is analyzed. Through this process, this paper demonstrates that the activism performance of the EDT is a critical aesthetics that encourages imagination for alternatives. It also argues that Electronic Disturbance Theater has contemporary value as an avant-garde art that actively utilizes the medium of network technology and integrates performance art and politics.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.149-162
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• 2014

Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.985-996
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• 2006

As the internet technologies develop, the geographic information system environment is changing to the web-based service. Since geospatial information of the existing Web-GIS services were developed independently, there is no interoperability to support diverse map formats. In spite of the same geospatial information object it can be used for various proposes that is duplicated in GIS separately. It needs intelligent strategies for optimal replica selection, which is identification of replication geospatial information objects. And for management of replication objects, OMG, GLOBE and GRID computing suggested related frameworks. But these researches are not thorough going enough in case of geospatial information object. This paper presents a model of location service, which is supported for optimal selection among replication and management of replication objects. It is consist of tree main services. The first is binding service which can save names and properties of object defined by users according to service offers and enable clients to search them on the service of offers. The second is location service which can manage location information with contact records. And obtains performance information by the Load Sharing Facility on system independently with contact address. The third is intelligent selection service which can obtain basic/performance information from the binding service/location service and provide both faster access and better performance characteristics by rules as intelligent model based on rough sets. For the validity of location service model, this research presents the processes of location service execution with Graphic User Interface.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.