• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6C
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• pp.259-266
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• 2009

The steel pipe of steel-concrete composite piles increases the pile strength and induces the ductile failure by constraining the deformation of the inner concrete. In this research, the numerical models and the related input parameters were analyzed to simulate the axial load-movement relations, which were obtained from the compression loading tests for the cylindrical specimens of the steel pipe, the concrete, and the steel-concrete composite. As the results, the behavior of the steel pipe was simulated by the von-Mises model and that of the concrete by the strain-softening model, which decreases cohesion and dilation angles as the function of plastic strains. In addition, the reinforcing bars in the concrete were simulated by applying the yielding moment and decreasing the sectional area of the bars. The applied numerical models properly simulated the yielding behavior and the reinforcement effect of the steel-concrete composite piles. The parametric study for the real-size piles showed that the material strength of the steel-concrete composite pile increased about 10% for the axial loading and about 20~45% for the horizontal loading due to the reinforcement effect by the surrounding steel pipe pile.

• 한국노년학
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• v.32 no.2
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• pp.631-647
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• 2012

The purpose of this study was to examine the impact of climacteric women's attitude to developmental phenomena and their menopausal symptoms on their meaning of life in an attempt to provide some information on the improvement of climacteric women's quality of life. The subjects in this study were 313 women who resided in different regions involving a large city D and another city C. They were aged between 40 and 60 and were going through their menopause. They were aged between 40 and 60 and were going through their menopause. The subjects were selected by convenient sampling, which was one of nonprobability sampling methods. The collected data were analyzed by the statistical package SPSS. The major findings of the study were as follows: First, the climacteric women didn't take a positive attitude toward developmental phenomena. They occasionally suffered severe menopausal symptoms, and they didn't find a great meaning in their life. Second, the climacteric women found a more meaning in their life when they took a more positive attitude to developmental phenomena, and those who underwent severer menopausal symptoms found a less meaning in their life. Third, the climacteric women's meaning of life was under the influence of their attitude toward developmental phenomena and menopausal symptoms. Specifically, their attitude to menopause and mental symptoms had a large impact on that. Given the findings of the study, social welfare intervention should be provided for climacteric women to promote their physical health related to menopausal symptoms and psychological health related to attitude toward developmental phenomena to find a more meaning in their life. Besides, local welfare centers should be open to climacteric women as one of governmental policies so that they could lead a healthy life. Education should be provided for them to be ready for their own menopause, and social welfare counseling service should be offered from diverse angles

• Asia Marketing Journal
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• v.10 no.2
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• pp.71-98
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• 2008

Considerably many numbers of studies on country-of-origin(hereafter COO) effects have been presented in international business and marketing areas. Recent studies have been included the effects of COO of manufacture, parts, and design, as well as the effects of brand origin, reflected by the accelerating convergent manufacture circumstances and increasingly competitive environments. Moderating constructs such as knowledge of product category and involvement as individual variables, have been also introduced and researched in various angles. In addition, how the effects of COO occur as processes is also argued in previous studies. This research has attempted to explain business corporation's strategic decisions on choosing a domain of its product manufacturing for several critical reasons, for cost reduction or better image. We displayed two constructs of brand and manufacture in a positive and negative country image group to reconfirm the existence of the effects of COO. Additionally, the effects of respondents' regulatory fit between their motivational focus and the contents of product messages, have been declared. Furthermore the respondents' motivational focus moderates the main effect of COO on product evaluations in a positive 'made-in' combination, while, surprisingly, it does not statistically moderate in a negative, except attitude. Based on the results, implications and suggestions on how to plan and execute more effective marketing strategies regarding COO dimensions, especially COO of manufacture, are separately presented for each situations when it has already been determined and when it is to be.

• Communications of Mathematical Education
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• v.37 no.4
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• pp.635-652
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• 2023

This study conducts a comprehensive analysis of the curricular progression of the concepts and learning sequences of 'lines', specifically, 'line segments', 'straight lines', and 'rays', at the elementary school level. By examining mathematics curricula and textbooks, spanning from 2nd to 7th and 2007, 2009, 2015, and up to 2022 revised version, the study investigates the timing and methods of introducing these essential geometric concepts. It also explores the sequential delivery of instruction and the key focal points of pedagogy. Through the analysis of shifts in the timing and definitions, it becomes evident that these concepts of lines have predominantly been integrated as integral components of two-dimensional plane figures. This includes their role in defining the sides of polygons and the angles formed by lines. This perspective underscores the importance of providing ample opportunities for students to explore these basic geometric entities. Furthermore, the definitions of line segments, straight lines, and rays, their interrelations with points, and the relationships established between different types of lines significantly influence the development of these core concepts. Lastly, the study emphasizes the significance of introducing fundamental mathematical concepts, such as the notion of straight lines as the shortest distance in line segments and the concept of lines extending infinitely (infiniteness) in straight lines and rays. These ideas serve as foundational elements of mathematical thinking, emphasizing the necessity for students to grasp concretely these concepts through visualization and experiences in their daily surroundings. This progression aligns with a shift towards the comprehension of Euclidean geometry. This research suggests a comprehensive reassessment of how line concepts are introduced and taught, with a particular focus on connecting real-life exploratory experiences to the foundational principles of geometry, thereby enhancing the quality of mathematics education.

• The Korean Journal of Applied Statistics
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• v.36 no.6
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• pp.515-528
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• 2023

With the growth of the e-commerce market, consumers increasingly rely on user reviews to make purchasing decisions. Consequently, researchers are actively conducting studies to effectively analyze these reviews. Among the various methods of sentiment analysis, the aspect-based sentiment analysis approach, which examines user reviews from multiple angles rather than solely relying on simple positive or negative sentiments, is gaining widespread attention. Among the various methodologies for aspect-based sentiment analysis, there is an analysis method using a transformer-based model, which is the latest natural language processing technology. In this paper, we conduct an aspect-based sentiment analysis on multilingual user reviews using two real datasets from the latest natural language processing technology model. Specifically, we use restaurant data from the SemEval 2016 public dataset and multilingual user review data from the cosmetic domain. We compare the performance of transformer-based models for aspect-based sentiment analysis and apply various methodologies to improve their performance. Models using multilingual data are expected to be highly useful in that they can analyze multiple languages in one model without building separate models for each language.

• Journal of the Microelectronics and Packaging Society
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• v.29 no.4
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• pp.29-34
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• 2022

A fabrication process of smart windows with controllable visible light transmittance by using retardation films is proposed. The 𝛌/4-phase retardation films that can convert a linearly polarized light into circularly polarized light are achieved through photo-alignment layers and reactive mesogen (RM) coating process. Two sheets of the fabricated retardation films with different orientation angles induced to light transmission mode (45°/-45°) and light blocking mode (45°/45°) for visible wavelength. We evaluated retardation characteristics according to the thickness of the birefringent RM material and found out the optimal condition for the film with 𝚫n·d of 𝛌/4-phase. The proposed structure of the smart window exhibited the light blocking ratio improved by more than 20% in the visible wavelength (380 nm to 780 nm). Finally, it was confirmed that the feasibility of the window structure by applying to a prototype for a smart window with a size of 150 × 150 mm².

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1517-1522
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• 2023

This study evaluates the impact of Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) expected error (EE) on the accuracy of surface reflectance (SR) derived from the KOMPSAT-3A satellite, utilizing the Second Simulation of the Satellite Signal in the Solar Spectrum Vector radiative transfer model. By considering a range of ground-based AOD and the resultant MODIS AOD EE, the research identifies significant influences on SR accuracy, particularly under high solar zenith angles(SZA) and shorter wavelengths. The study's simulations reveal that SR errors increase with shorter wavelengths and higher SZAs, highlighting the necessity for further research to improve atmospheric correction algorithms by incorporating wavelength and SZA considerations. Additionally, the study provides foundational data for better understanding the use of AOD data from other satellites in atmospheric correction processes and contributes to advancing atmospheric correction technologies.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.91-99
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• 2024

Piping systems are crucial facilities used in various industries, particularly in areas related to daily life and safety. Piping systems are fixed to the main structures of buildings and facilities but do not support external loads and serve as non-structural elements performing specific functions. Piping systems are affected by relative displacements owing to phase differences arising from different behaviors between two support points under seismic loads; this can cause damage owing to the displacement-dominant cyclic behavior. Fittings and joints in piping systems are representative elements that are vulnerable to seismic loads. To evaluate the seismic performance and limit states of fittings and joints in piping systems, a high-stroke actuator is required to simulate relative displacements. However, this is challenging because only few facilities can conduct these experiments. Therefore, element-level experiments are required to evaluate the seismic performance and limit states of piping systems connected by fittings and joints. This study proposed a method to evaluate the seismic performance of an elbow specimen that includes fittings and joints that are vulnerable to seismic loads in vertical piping systems. The elbow specimen was created by connecting straight pipes to both ends of a 90° pipe elbow using flexible groove joints. The seismic performance of the elbow specimen was evaluated using a cyclic loading protocol based on deformation angles. To determine the margin of the evaluated seismic performance, the limit states were assessed by applying cyclic loading with a constant amplitude.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.1-15
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• 2024

The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.

• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.35-49
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• 2024

Video captioning technology, as a significant outcome of the integration between computer vision and natural language processing, has emerged as a key research direction in the field of artificial intelligence. This technology aims to achieve automatic understanding and language expression of video content, enabling computers to transform visual information in videos into textual form. This paper provides an initial analysis of the research trends in deep learning-based video captioning and categorizes them into four main groups: CNN-RNN-based Model, RNN-RNN-based Model, Multimodal-based Model, and Transformer-based Model, and explain the concept of each video captioning model. The features, pros and cons were discussed. This paper lists commonly used datasets and performance evaluation methods in the video captioning field. The dataset encompasses diverse domains and scenarios, offering extensive resources for the training and validation of video captioning models. The model performance evaluation method mentions major evaluation indicators and provides practical references for researchers to evaluate model performance from various angles. Finally, as future research tasks for video captioning, there are major challenges that need to be continuously improved, such as maintaining temporal consistency and accurate description of dynamic scenes, which increase the complexity in real-world applications, and new tasks that need to be studied are presented such as temporal relationship modeling and multimodal data integration.