• International journal of steel structures
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• v.18 no.5
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• pp.1801-1817
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• 2018

This paper presents the numerical parametric analysis on the loading capacity of Channel purlins with screw-fastened sheeting, in which the effects of anti-sag bar and corrugated steel sheet on the ultimate capacity are studied. Results show that the setup of anti-sag bars can reduce the deformations and improve the ultimate capacity of C purlins. The traditional method of setting the anti-sag bars in the middle of the web is favorable. The changing of sheeting type, sheeting thickness and rib spacing has significant effects on the ultimate capacity of C purlins without anti-sag bars, compared with those with anti-sag bars. The proposed design formulas are relatively consistent with the calculations of EN 1993-1-3:2006, which is different from those of GB 50018-2002.

• Journal of Integrative Natural Science
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• v.14 no.4
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• pp.183-188
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• 2021

Collaborative filtering is one of the commonly used methods in the web recommendation system. Numerous researches on the collaborative filtering proposed the numbers of measures for enhancing the accuracy. This study suggests the movie recommendation system applied with Word2Vec and ensemble convolutional neural networks. First, user sentences and movie sentences are made from the user, movie, and rating information. Then, the user sentences and movie sentences are input into Word2Vec to figure out the user vector and movie vector. The user vector is input on the user convolutional model while the movie vector is input on the movie convolutional model. These user and movie convolutional models are connected to the fully-connected neural network model. Ultimately, the output layer of the fully-connected neural network model outputs the forecasts for user, movie, and rating. The test result showed that the system proposed in this study showed higher accuracy than the conventional cooperative filtering system and Word2Vec and deep neural network-based system suggested in the similar researches. The Word2Vec and deep neural network-based recommendation system is expected to help in enhancing the satisfaction while considering about the characteristics of users.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.6
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• pp.572-579
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• 2022

The analysis of foreign aircraft appearing suddenly in air defense identification zones requires a lot of cost and time. This study aims to develop a pre-trained model that can identify neighboring military aircraft based on aircraft photographs available on the web and present a model that can determine which aircraft corresponds to based on aerial photographs taken by allies. The advantages of this model are to reduce the cost and time required for model classification by proposing a pre-trained model and to improve the performance of the classifier by data augmentation of edge-detected images, cropping, flipping and so on.

• Journal of the Korean Wood Science and Technology
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• v.19 no.2
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• pp.40-55
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• 1991

To investigate the influence of cross section geometries on the behavior of composite beams in the case of small span to depth ratio and deep beams. the static flexural behavior of composite I-beams and Box- beams was evaluated. 12 types of composite I -beams composed of LVL flanges and particleboard or plywood web and 3 types of composite Box-beams composed of LVL flanges and plywood web were tested under one-point loading. The load-deflection curves were almost linear to failure, therefore, the behavior of tested composite beams was elastic. The theoretical flexural rigidity of composite beams was calculated and compared with observed flexural rigidity. The highest value was found in I-W type beams and the lowest value was found in G-P type beams. The difference between theoretical and observed flexural rigidity was small. Theoretical total deflection of tested composite beams was calculated using flexural rigidity and compared with actual deflection. Shear deflection of these beams was evaluated by the approximation method, solid crosss section method and elementary method. The difference between actual deflection and expected deflection was not found in D, E and F type beams. This defference was small in G, H and I type beams or Box-beam.

• The Korean Journal of Health Service Management
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• v.11 no.4
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• pp.213-224
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• 2017

Objectives : The purpose of this study was to analyze representative topics and topic trends of papers in Korean Society and Health Service Management(KSHSM) Journal. Methods : We collected English abstracts and key words of 516 papers in KSHSM Journal from 2007 to 2017. We utilized Python web scraping programs for collecting the papers from Korea Citation Index web site, and RStudio software for topic analysis based on latent Dirichlet allocation algorithm. Results : 9 topics were decided as the best number of topics by perplexity analysis and the resultant 9 topics for all the papers were extracted using Gibbs sampling method. We could refine 9 topics to 5 topics by deep consideration of meanings of each topics and analysis of intertopic distance map. In topic trends analysis from 2007 to 2017, we could verify 'Health Management' and 'Hospital Service' were two representative topics, and 'Hospital Service' was prevalent topic by 2011, but the ratio of the two topics became to be similar from 2012. Conclusions : We discovered 5 topics were the best number of topics and the topic trends reflected the main issues of KSHSM Journal, such as name revision of the society in 2012.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4300-4314
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• 2019

With the development of video-related applications, media content has increased dramatically through applications. There is a substantial amount of near-duplicate videos (NDVs) among Internet videos, thus NDVR is important for eliminating near-duplicates from web video searches. This paper proposes a novel NDVR system that supports large-scale retrieval and contributes to the efficient and accurate retrieval performance. For this, we extracted keyframes from each video at regular intervals and then extracted both commonly used features (LBP and HSV) and new image features from each keyframe. A recent study introduced a new image feature that can provide more robust information than existing features even if there are geometric changes to and complex editing of images. We convert a vector set that consists of the extracted features to binary code through a set of hash functions so that the similarity comparison can be more efficient as similar videos are more likely to map into the same buckets. Lastly, we calculate similarity to search for NDVs; we examine the effectiveness of the NDVR system and compare this against previous NDVR systems using the public video collections CC_WEB_VIDEO. The proposed NDVR system's performance is very promising compared to previous NDVR systems.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.7
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• pp.49-57
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• 2019

Recently, the use of deep deck plate has been increased in various structures, such as underground parking lots, logistics warehouses, because it can reduce construction periods and labor costs. In this study, a newly developed Double Deck (D-deck) plate which can leads to save story heights has been introduced, and experimental tests on a total of five D-deck plates under construction loads have been carried out to investigate their structural performance at construction stage. The loads were applied by sands and concrete to simulate the actual distributed loading conditions, and the vertical deflection of D-Deck and the horizontal deformation of web were measured and analyzed in detail. As a result, it was confirmed that all the D-decks showed very small vertical deflection of less than 5.34 mm under construction loads, which satisfies the maximum deflection limit of L / 180. In addition, the D-Deck plate was found to have a sufficient rigidity to resist construction loads in a stable manner.

• Journal of Korean Society of Forest Science
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• v.109 no.1
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• pp.23-30
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• 2020

The use of increased computing power, machine learning, and deep learning techniques have dramatically increased in various sectors. In particular, image detection algorithms are broadly used in forestry and remote sensing areas to identify forest types and tree species. However, in South Korea, machine learning has rarely, if ever, been applied in forestry image detection, especially to classify tree species. This study integrates the application of machine learning and forest image detection; specifically, we compared the ability of two machine learning data collection methods, namely image data captured by forest experts (D1) and web-crawling (D2), to automate the classification of five trees species. In addition, two methods of characterization to train/test the system were investigated. The results indicated a significant difference in classification accuracy between D1 and D2: the classification accuracy of D1 was higher than that of D2. In order to increase the classification accuracy of D2, additional data filtering techniques were required to reduce the noise of uncensored image data.

• Journal of the Korea Concrete Institute
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• v.18 no.4 s.94
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• pp.469-477
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• 2006

Models to predict the ultimate strength of simply supported or continuous deep beams with web openings are proposed. The derived equations are based on upper-bound theorem. The concrete is assumed as a perfectly plastic material obeying the modified Coulomb failure criteria with zero tension cutoff. Reinforcing bar is considered as elastic-perfectly plastic material and its stress is calculated from the limiting principal compressive strain of concrete. The governing failure mechanisms based on test results are idealized as rigid moving blocks separated by a hyperbolic yield line. The effective compressive strength of concrete is calculated from the formula proposed by Vecchio and Collins. Comparisons with existing test results are performed, and they show good agreement.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.137-144
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• 2016

The purpose of this study is to investigate the structural relationships among goal orientation, teaching presence, approaches to leaning, satisfaction and academic achievement. For this study, the web survey was administered to 235 learners who participated in distance lifelong education centers of A, B, and C university in South Korea. Structural equation modeling (SEM) analysis was conducted in order to examine the causal relationships among the variables. The results indicated that first, mastery-approach goal and teaching presence had positive effects on deep approach. Second, mastery-approach goal showed negative effects on surface approach, while teaching presence did not. Third, deep approach had positive effects on satisfaction, Fourth, surface approach had negative effects on satisfaction. Fifth, deep approach showed positive effects. Last, surface approach showed negative effects on academic achievement. Based on the result of the research, the study propose the constructive foundation for providing strategies raising the satisfaction and academic achievement in distance life-long education.