• International Journal of Knowledge Content Development & Technology
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• v.7 no.3
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• pp.5-27
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• 2017

Retrieval of scholarly articles about a specific research issue is a routine job of researchers to cross-validate the evidence about the issue. Two articles that focus on a research issue should share similar terms in their core contents, including their goals, backgrounds, and conclusions. In this paper, we present a technique CCSE ($\underline{C}ore$ $\underline{C}ontent$ $\underline{S}imilarity$ $\underline{E}stimation$) that, given an article a, recommends those articles that share similar core content terms with a. CCSE works on titles and abstracts of articles, which are publicly available. It estimates and integrates three kinds of similarity: goal similarity, background similarity, and conclusion similarity. Empirical evaluation shows that CCSE performs significantly better than several state-of-the-art techniques in recommending those biomedical articles that are judged (by domain experts) to be the ones whose core contents focus on the same research issues. CCSE works for those articles that present research background followed by main results and discussion, and hence it may be used to support the identification of the closely related evidence already published in these articles, even when only titles and abstracts of the articles are available.

• Transactions on Electrical and Electronic Materials
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• v.15 no.1
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• pp.7-11
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• 2014

The Polarization and Depolarization Current (PDC) measurement is an efficient and effective diagnostic technique based on time domain measurement, for evaluating the high voltage insulation condition. This paper presents a review and comparison results from several published papers on the application of the PDC method to finding the conductivity and moisture content of various types of insulators. For solid insulation, the study was focused on cable insulation, electric machine stator insulation, and paper insulator in transformer insulation with different conditions. For liquid insulation, the review and comparison was done on biodegradable and mineral transformer oils, with fresh oil condition, and aged condition. The results from previous researchers tests were complied, analyzed and discussed, to evaluate the application of the PDC method to monitor the conductivity and moisture of HV equipment insulation systems. From the review results, the PDC technique successfully gives an indication of the conductivity and moisture level of high voltage insulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1166-1186
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• 2022

Artistic font design has become an integral part of visual media. However, without prior knowledge of the font domain, it is difficult to create distinct font styles. When the number of characters is limited, this task becomes easier (e.g., only Latin characters). However, designing CJK (Chinese, Japanese, and Korean) characters presents a challenge due to the large number of character sets and complexity of the glyph components in these languages. Numerous studies have been conducted on automating the font design process using generative adversarial networks (GANs). Existing methods rely heavily on reference fonts and perform font style conversions between different fonts. Additionally, rather than capturing style information for a target font via multiple style images, most methods do so via a single font image. In this paper, we propose a network architecture for generating multilingual font sets that makes use of geometric structures as content. Additionally, to acquire sufficient style information, we employ multiple style images belonging to a single font style simultaneously to extract global font style-specific information. By utilizing the geometric structural information of content and a few stylized images, our model can generate an entire font set while maintaining the style. Extensive experiments were conducted to demonstrate the proposed model's superiority over several baseline methods. Additionally, we conducted ablation studies to validate our proposed network architecture.

• Journal of Korea Water Resources Association
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• v.31 no.2
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• pp.123-132
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• 1998

Monitoring solute transport has been known to be difficult especially for the unsaturated soil. The object of this study is to investigate the TDR application to monitoring solute concentration in the vadose zone. The TDR calibration test was conducted for soil samples with various water contents and concentrations. The voltage attenuation of electromagnetic wave of TDR was used to estimate the bulk electrical conductivity of a soil. The relationship between the bulk soil electrical conductivity and the solute concentration was assumed to be linear at a constant volumetric soil water content. In this study four proposed relationships were compared using data obtained from KCI solution at three different concentrations. Relationships given by Topp, Daltaon, Yanuka showed the linearity between the bulk soil electrical conductivity and the solute concentration, which were more pronounced than Zegelin's. The three relationships were found to be useful to measure the solute concentration in the vadose zone. In addition, TDR method was proven to be a viable technique in monitoring solute transport through unsaturated soils in transient flow condition.

• Communications of Mathematical Education
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• v.26 no.3
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• pp.317-338
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• 2012

This paper compared and contrasted the views of effective mathematics instruction by 223 elementary school teachers and 151 middle school mathematics teachers using a questionnaire with 4 main domains (i.e., curriculum and content, teaching and learning, classroom environment and atmosphere, and assessment) and a total of 48 sub-elements. The analysis of results showed that elementary school teachers put their priority on the curriculum and content domain, while middle school counterparts did on the teaching and learning domain. The teachers commonly agreed with instruction which fosters students' self-directed learning ability, reconstructs the curriculum tailored to students' diverse levels, and establishes appropriate interaction between the teacher and students. However, elementary school teachers agreed more than middle school teachers with regard to the 23 elements related to effective mathematics instruction. In contrast, middle school teachers agreed more than their counterparts as for only 2 elements (instruction fostering mathematical representation and instruction eliciting students' learning motivation). This paper includes suggestions and implications related to Korean teachers' perception of effective mathematics instruction.

• Journal of Educational Research in Mathematics
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• v.14 no.1
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• pp.71-88
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• 2004

The purpose of this study was to examine particular variables that play a significant role in the difficulty of math test items in College Scholastic Ability Test (CSAT). The study also aimed to develop a model of measuring the item difficulty. Variables correlated to item difficulty were drawn from the review of the related literature and the analysis of the content and difficulty of the past test items of CSAT. The first instrument was designed by using the correlated variables. According to the results of correlation analysis, the second instrument was made by deleting the variables which showed relatively low correlation with item difficulty and by refining some variables. Several models were proposed by using the revised instrument. The comparison of the R square and cross validity of each model reveals that integrated regression model was the most stable and accurate among the proposed models. The study also showed that statistically significant predictors were choice format, content domain, behavior domain, and the degree of item familiarity in the order of proportion of variance accounted by the predictors. Despite the limited scope of the present research, it can be suggested that its findings provide useful insights into predicting math test item difficulty.

• Journal of Korea Multimedia Society
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• v.5 no.4
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• pp.415-425
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• 2002

In this paper, we present a content-based image retrieval method which is based on the feature extraction in the wavelet transform domain. In order to overcome the drawbacks of the feature vector making up methods which use the global wavelet coefficients in subbands, we utilize the energy value of wavelet coefficients, and the shape-based retrieval of objects is processed by moment which is invariant in translation, scaling, rotation of the objects The proposed methods reduce feature vector size, and make progress performance of classification retrieval which provides fast retrievals times. To offer the abilities of region-based image retrieval, we discussed the image segmentation method which can reduce the effect of an irregular light sources. The image segmentation method uses a region-merging, and candidate regions which are merged were selected by the energy values of high frequency bands in discrete wavelet transform. The region-based image retrieval is executed by using the segmented region information, and the images are retrieved by a color, texture, shape feature vector.

• Journal of Information Science Theory and Practice
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• v.9 no.2
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• pp.66-82
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• 2021

Recommender Systems have gained immense popularity due to their capability of dealing with a massive amount of information in various domains. They are considered information filtering systems that make predictions or recommendations to users based on their interests and preferences. The more recent technology, Linked Open Data (LOD), has been introduced, and a vast amount of Resource Description Framework data have been published in freely accessible datasets. These datasets are connected to form the so-called LOD cloud. The need for semantic data representation has been identified as one of the next challenges in Recommender Systems. In a LOD-enabled recommendation framework where domain awareness plays a key role, the semantic information provided in the LOD can be exploited. However, dealing with a big chunk of the data from the LOD cloud and its integration with any domain datasets remains a challenge due to various issues, such as resource constraints and broken links. This paper presents the challenges of interconnecting and extracting the DBpedia data with the MovieLens 1 Million dataset. This study demonstrates how LOD can be a vital yet rich source of content knowledge that helps recommender systems address the issues of data sparsity and insufficient content analysis. Based on the challenges, we proposed a few alternatives and solutions to some of the challenges.

• Research in Community and Public Health Nursing
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• v.32 no.4
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• pp.555-565
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• 2021

Purpose: This study was conducted to develop the contents of disaster nursing education in community health nursing at universities. Methods: To validate contents, the Delphi method was used. We categorized two domains(indirect disaster management and direct disaster management) and developed 48 draft items. This study applied two round surveys and 23 experts participated in this study. The content validity was calculated using content validity ratio and coefficient of variation. Results: Indirect disaster management domain was composed of three categories including 12 items: 1) Understanding of the disaster, 2) disaster management system, and 3) response by disaster stage and recovery. Direct disaster management domain was composed of nine categories including 30 items: 1) Ethical considerations, 2) communication in disasters, 3) nursing activity by disaster stage, 4) emergency nursing in disasters, 5) patient severity classification in disasters, 6) disaster nursing for vulnerable groups, 7) disaster nursing for victims, 8) psychosocial nursing and health in disasters, and 9) cases of disaster nursing in communities. Conclusion: This Delphi study identified the contents of disaster nursing education curriculum, and confirmed the validity for disaster education program in community health nursing. Based on the results, it will be helpful for training the disaster nursing and improving the competency on disaster nursing of the nursing students.

• Computers and Concrete
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• v.31 no.4
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• pp.293-306
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• 2023

This study proposes and demonstrates a smart monitoring system that uses transmission lines embedded in a reinforced concrete structure to detect the presence of defects through changes in the electromagnetic waves generated and measured by a time-domain reflectometer. Laboratory experiments were first conducted to identify the presence of voids in steel-concrete composite columns. The results indicated that voids in the concrete caused a positive signal reflection, and the amplitude of this signal decreased as the water content of the soil in the void increased. Multiple voids resulted in a decrease in the amplitude of the signal reflected at each void, effectively identifying their presence despite amplitude reduction. Furthermore, the electromagnetic wave velocity increased when voids were present, decreased as the water content of the soil in the voids increased, and increased with the water-cement ratio and curing time. Field experiments were then conducted using bored piles with on-center (sound) and off-center (defective) steel-reinforcement cage alignments. The results indicated that the signal amplitude in the defective pile section, where the off-center cage was poorly covered with concrete, was greater than that in the pile sections where the cage was completely covered with concrete. The crosshole sonic logging results for the same defective bored pile failed to identify an off-center cage alignment defect. Therefore, this study demonstrates that electromagnetic waves can be a useful tool for monitoring the health and integrity of reinforced concrete structures.