• Journal of Korea Entertainment Industry Association
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• v.13 no.2
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• pp.37-45
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• 2019

The This study aimed at clarifying that the cognitive interpretation code is essential for college students to read the correct culture while discussing the producer's story production system for creative advertising content and the process of interpreting the meaning of advertisers and the formation of principles and beliefs. The production of advertising content aimed at persuasion should first identify anachronistic reason system based on the target audience's perception principle. A concise analysis of the experiment found key clues that confirmed that a sample of the producer's intended story would be inconsistent with the clues of information that a college student could remember. I have tried to organize a semantic analysis tool that combines these key clues and as a tool for reading culture of the right time for college students. As a result, university student inmates were able to identify one side of positive communication: reading a new cognitive symbol culture based on their subjective experience and beliefs, rather than analyzing cross-sectional analysis of the primary language and non-verbal expressions of their advertising contents. In the future, if an advertising content story producer works to identify such a process in advance, it will help persuade inmates.

• Journal of KIISE:Databases
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• v.33 no.7
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• pp.754-765
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• 2006

In XML keyword search, a search result is defined as a set of the smallest elements (i.e., least common ancestors) containing all query keywords and a granularity of indexing is an XML element instead of a document. Under the conventional index structure, all least common ancestors produced by the combination of the elements, each of which contains a query keyword, are considered as a search result. In this paper, to avoid unnecessary operations of producing the least common ancestors and reduce query process time, we describe a way to construct a partitioned index composed of several partitions and produce a search result by merging those partitions if necessary. When a search result is restricted to be composed of the least common ancestors whose depths are higher than a given minimum depth, under the proposed partitioned index structure, search systems can reduce the query process time by considering only combinations of the elements belonging to the same partition. Even though the minimum depth is not given or unknown, search systems can obtain a search result with the partitioned index, which requires the same query process time to obtain the search result with non-partitioned index. Our experiment was conducted with the XML documents provided by the DBLP site and INEX2003, and the partitioned index could reduce a substantial amount of query processing time when the minimum depth is given.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.5
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• pp.465-473
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• 2002

Images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in radiography is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in reading. We have proposed adaptive weighted median(AWM) filters based on local statistics. We show two ways of realizing the AWM filters. One is a simple type of AWM filter, whose weights are given by a simple non-linear function of three local characteristics. The other is the AWM filter which is constructed by homogeneous factor(HF). Homogeneous factor(HF) from the quantum noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the detection systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by visual C++ language on a IBM-PC Pentium 550 for testing purposes, the effects and results of the noise filtering were proposed by comparing with images of the other existing filtering methods.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.127-138
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• 2021

The aim of this study is to demonstrate interaction as a describable field and tries to understand interaction from the perspective of attributes, thus building a theoretical to help interactive designer understand this field by common rule, rather than waste huge time and labor cost on iteration. Since the concept of interaction language has been brought out in 2000, there are varies of related academical studies, but all with defect such as proposed theoretical models are built on a non-uniform scale, or the analyzing perspective are mainly based on researcher's personal experience and being too unobjective. The value of this study is the clustered resource of research which mainly based on academical review. It collected 21 papers researched on interaction paradigm or interaction attributes published since 2000, extracting 19 interaction attribute models which contains 174 interaction attributes. Furthermore, these 174 attributes were re-clustered based on a more unified standard scale, and the two theoretical models summarized from it are respectively focuses on interaction control and interaction experience, both of which covered 6 independent attributes. The propose of this theoretical models and the analyzation of the cluster static will contribute on further revealing of the importance of interaction attribute, or the attention interaction attribute has been paid on. Also, in this regard, the interactive designer could reasonably allocate their energy during design process, and the future potential on various direction of interaction design could be discussed.

• Journal of the Korean Society for information Management
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• v.40 no.2
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• pp.157-182
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• 2023

This study analyzed the structure and utilization of subject headings in the National Library of Korea Subject Headings List (NLSH) based on an analysis of subject headings assigned to 1,218,867 national bibliographies from 2003 to 2022. The findings of the study are as follows: Firstly, among all subject headings in the NLSH, there were 257,103 preferred terms, accounting for 50.2% of the total terms. Foreign language terms constituted 33% (169,466), while non-preferred terms comprised 12% (61,442). Among the preferred terms, 57,312 subject headings were used, accounting for 22.3%. However, it was observed that 54.7% (31,351) of these subject headings were assigned less than 5 times, indicating that only a small number of subject headings were frequently utilized. Secondly, the frequency of relationship indicators appeared in the order of RT, BT, and NT. The NLSH consisted of 12,602 top-level subject headings and 143,704 lowest-level subject headings, with a maximum depth of 17 levels. Thirdly, on average, 1.72 subject headings were assigned per bibliographic record. The number of subject headings assigned and the depth of the hierarchy increased for materials with more specific contents. Recent bibliographic records have been assigned more subject headings and deeper into the hierarchy of the NLSH. It was also found that the number of subject headings assigned per bibliography varied depending on the main class of KDC. Based on the findings, it is recommended to evaluate the coverage of terms in the NLSH, reorganize hierarchical relationships and depth of subject headings, and enhance the development of subdivisions within the NLSH.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.11 no.2
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• pp.240-251
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• 2000

This study was a preliminary study on the adolescent psychiatric patients that show the characteristics of peer group neglect or rejection. We divided the adolescent psychiatric patients(n=25) into neglect-reject group(n=15) and non-neglect group(n=10). Each patient answered 8 scales and several questions about general relationships with friends. And, both the score of each 8 scales and answer about qusetions were examined. Lastly, records of 5 cases from neglect-reject group were analyzed. The depression dimension score of SCL-90-R, anxiety dimension score of SCL-9O-R, paranoid dimension score of SCL-90-R, interaction anxiousness scale(IAS) score were significantly different between 2 groups. On the result of case analysis about 5 patients of neglect-reject group, the adolescent psychiatric patients had a tendency to be rejected or neglected in case of having developmental problems(for example, language development or cognitive impairment).

• KIPS Transactions on Software and Data Engineering
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• v.7 no.8
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• pp.287-296
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• 2018

In the recent commercial DBMS market, as the users' burden and complaint which are related to high price licensing policy and late technical support service are increasingly rising, the concern for use of open source DBMS which has no problem with compatibility or stability is escalating. Due to the fact, the cases saving the cost are growing by converting Oracle Corporation's applications, which has about 60% share in the DBMS market, to an open source DBMS. However, in converting non-interchange sentences to an ANSI standard-based open source DBMS because of the use of PL/SQL in Oracle Corporation provides, a lot of manual work accompanies, so there is a lot of loss of time and money. Therefore, a tool that automatically converts PL/SQL to standard SQL is required. The proposed automation tool for the conversion of applications converts PL/SQL to Java Stored Procedure, an open source DBMS-based ANSI standard programming language. Through carrying out a test on the automation tool, it is proved that the tool will contribute to shortening time and saving cost by verifying the identity of input-output data and its reliability after correcting errors in converting to Java Stored Procedure.

• Child Health Nursing Research
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• v.20 no.2
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• pp.75-86
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• 2014

Purpose: The purpose of this study was to describe the components and content of nursing intervention studies on mother-infant interactions and to present strategies for future studies. Methods: Four electronic databases in the Korean language were searched to identify studies done between January 1998 and December 2011. The search yielded 145 articles. From these articles, 19 studies met the inclusion criteria. Results: Mother-infant interactions in these studies were found to include verbal and non-verbal communication basic for optimal growth and development of the child. Six kinds of interventions for mother-infant interactions were identified as follows: sensory stimulation, education program, whole body massage, kangaroo care, visiting support, and music therapy. Conclusion: Further studies with well designed clinical trials need to be done in the area of child nursing to provide evidence based data for the development of strategies to promote positive mother-infant interactions.

• The KIPS Transactions:PartA
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• v.19A no.3
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• pp.129-138
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• 2012

In distributed memory architectures like clusters, each node stores a portion of data. How data is distributed across nodes influences the performance of such systems. The data distribution scheme is the strategy to distribute data across nodes and realize parallel data processing. Due to various reasons such as maintenance, scale up, upgrade, etc., the performance of nodes in a cluster can often become non-identical. In such clusters, data distribution without considering performance cannot efficiently distribute data on nodes. In this paper, we propose a new data distribution scheme based on the number of cores in nodes. We use the number of cores as the performance factor. In our data distribution scheme, each node is allocated an amount of data proportional to the number of cores in it. We implement our data distribution scheme using the Chapel language. To show our data distribution is effective in reducing the execution time of parallel applications, we implement Mandelbrot Set and ${\pi}$-Calculation programs with our data distribution scheme, and compare the execution times on a cluster. Based on experimental results on clusters of 8-core and 16-core nodes, we demonstrate that data distribution based on the number of cores can contribute to a reduction in the execution times of parallel programs on clusters.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.347-364
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• 2022

Fraudulent companies or sellers strategically manipulate reviews to influence customers' purchase decisions; therefore, the reliability of reviews has become crucial for customer decision-making. Since customers increasingly rely on online reviews to search for more detailed information about products or services before purchasing, many researchers focus on detecting manipulated reviews. However, the main problem in detecting manipulated reviews is the difficulties with obtaining data with manipulated reviews to utilize machine learning techniques with sufficient data. Also, the number of manipulated reviews is insufficient compared with the number of non-manipulated reviews, so the class imbalance problem occurs. The class with fewer examples is under-represented and can hamper a model's accuracy, so machine learning methods suffer from the class imbalance problem and solving the class imbalance problem is important to build an accurate model for detecting manipulated reviews. Thus, we propose an OpenAI-based reviews generation model to solve the manipulated reviews imbalance problem, thereby enhancing the accuracy of manipulated reviews detection. In this research, we applied the novel autoregressive language model - GPT-3 to generate reviews based on manipulated reviews. Moreover, we found that applying GPT-3 model for oversampling manipulated reviews can recover a satisfactory portion of performance losses and shows better performance in classification (logit, decision tree, neural networks) than traditional oversampling models such as random oversampling and SMOTE.