• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제13권1호
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• pp.10-20
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• 2024

매년 증가하는 온라인 상거래 시장과, 점차 다양해지는 상품과 콘텐츠로 인해 사용자들은 선택 과정에 어려움을 느낀다. 이에 여러 기업들은 온라인 쇼핑몰에서 사용자가 선호할 상품을 선별하여 제공하기 위해 추천 시스템에 대한 지속적인 연구를 진행하고 있다. 대다수의 추천 시스템 연구에서는 비교적 획득하기 쉬운 사용자의 이벤트 데이터를 기반하여 연구를 진행하였으나 한 종류의 사용자 행동만을 고려하기 때문에 사용자의 선호도를 파악하는 것에 오차가 발생한다. 이에 본 논문에서는 여러 종류의 사용자 행동 데이터의 상관관계를 고려하여 사용자의 선호도를 분석하는 추천 시스템을 제안한다. 제안하는 추천 시스템은 사용자의 사용자 행동 데이터의 상관관계를 분석하고 가중치를 생성하여 추천 모델을 학습한다. 실험에서는 기존 연구의 알고리즘과의 성능 비교를 통해 제안하는 시스템의 복잡도와 성능 향상을 확인하였다.

• Structural Engineering and Mechanics
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• 제46권2호
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• pp.213-229
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• 2013

Although performance based assessment procedures are mainly developed for reinforced concrete and steel buildings, URM (Unreinforced Masonry) buildings occupy significant portion of buildings in earthquake prone areas of the world as well as in IRAN. Variability of material properties, non-engineered nature of the construction and difficulties in structural analysis of masonry walls make analysis of URM buildings challenging. Despite sophisticated finite element models satisfy the modeling requirements, extensive experimental data for definition of material behavior and high computational resources are needed. Recently, nonlinear equivalent frame models which are developed assigning lumped plastic hinges to isotropic and homogenous equivalent frame elements are used for nonlinear modeling of URM buildings. The equivalent frame models are not novel for the analysis of masonry structures, but the actual potentialities have not yet been completely studied, particularly for non-linear applications. In the present paper an effective tool for the non-linear static analysis of 2D masonry walls is presented. The work presented in this study is about performance assessment of unreinforced brick masonry buildings through nonlinear equivalent frame modeling technique. Reliability of the proposed models is tested with a reversed cyclic experiment conducted on a full scale, two-story URM building at the University of Pavia. The pushover curves were found to provide good agreement with the experimental backbone curves. Furthermore, the results of analysis show that EFM (Equivalent Frame Model) with Dolce RO (rigid offset zone) and shell element have good agreement with finite element software and experimental results.

• 한국지진공학회논문집
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• 제19권5호
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• pp.239-246
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• 2015

Reinforced concrete shear walls are effective for resisting lateral loads imposed by wind or earthquakes. Observed damages of the shear wall in recent earthquakes in Chile(2010) and New Zealand(2011) exceeded expectations. Various analytical models have been proposed in order to incorporate such response features in predicting the inelastic response of RC shear walls. However, the model has not been implemented into widely available computer programs, and has not been sufficiently calibrated with and validated against extensive experimental data at both local and global response levels. In this study, reinforced concrete shear walls were modeled with fiber slices, where cross section and reinforcement details of shear walls can be arranged freely. Nonlinear analysis was performed by adding nonlinear shear spring elements that can represent shear deformation. This analysis result will be compared with the existing experiment results. To investigate the nonlinear behavior of reinforced concrete shear walls, reinforced concrete single shear walls with rectangular wall cross section were selected. The analysis results showed that the yield strength of the shear wall was approximately the same value as the experimental results. However, the yielding displacement of the shear wall was still higher in the experiment than the analysis. The analytical model used in this study is available for the analysis of shear wall subjected to high axial forces.

• 수산경영론집
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• 제42권2호
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• pp.85-96
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• 2011

Oliver flounder population density affect Oliver flounder growth and mortality rate. In laboratory pilot experiment, Oliver flounder growth rate is inversely proportional to stocking density. But previous study has not proved external validity. This study is aimed to analyze the effect of stocking density on the Oliver flounder culture farms in Jeju Island. In order to do this, I selected 13 farms in Jeju island as a sample. In the study, various analytical methods including productivity analysis, regression analysis, statistical analysis were conducted for 13 Oliver flounder culture farms. The result of analysis can be summarized as follows. First, in case of the Oliver flounder culture farms, Bertalanffy equation is not applicable to the Oliver flounder growth. Second, the Oliver flounder stocking density, defined as the surface area of Oliver flounder per $m^2$ of water surface area, is preferred to density definition defined as the weight of Oliver flounder per $m^2$ of water surface area on the Oliver Flounder Culture Farms case. Third, growth rate and production weight on the Oliver flounder culture farms are inversely proportional to stocking density on spearman rank correlation test. When extensive comparable biological and culture condition data become available, analysis model can be easily modified to yield more accurate results.

• Computers and Concrete
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• 제25권4호
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• pp.369-382
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• 2020

This paper presents a discussion of the Finite Element Analysis (FEA) when applied for the analysis of concrete elements reinforced with glass fibre reinforced polymer (GFRP) bars. The purpose of such nonlinear FEA model development is to create a tool that can be used for numerical parametric studies which can be used to extend the existing (and limited) experiment database. The presented research focuses on the numerical analyses of concrete beams reinforced with GFRP longitudinal and shear reinforcements. FEA of concrete members reinforced with linear elastic brittle reinforcements (like GFRP) presents unique challenges when compared to the analysis of members reinforced with plastic (steel) reinforcements, which are discussed in the paper. Specifically, the behaviour and failure of GFRP reinforced members are strongly influenced by the compressive response of concrete and thus modelling of concrete behaviour is essential for proper analysis. FEA was performed using the commercial software ABAQUS. A damaged-plasticity model was utilized to simulate the concrete behaviour. The influence of tension, compression, dilatancy, mesh, and reinforcement modelling was studied to replicate experimental test data of beams previously tested at the University of Waterloo, Canada. Recommendations for the finite element modelling of beams reinforced with GFRP longitudinal and shear reinforcements are offered. The knowledge gained from this research allows for the development of a rational methodology for modelling GFRP reinforced concrete beams, which subsequently can be used for extensive parametric studies and the formation of informed recommendations to design standards.

• 산업경영시스템학회지
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• 제46권4호
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• pp.142-151
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• 2023

Sentiment analysis is a method used to comprehend feelings, opinions, and attitudes in text, and it is essential for evaluating consumer feedback and social media posts. However, creating sentiment dictionaries, which are necessary for this analysis, is complex and time-consuming because people express their emotions differently depending on the context and domain. In this study, we propose a new method for simplifying this procedure. We utilize syntax analysis of the Korean language to identify and extract sentiment words based on the Reason-Sentiment Pattern, which distinguishes between words expressing feelings and words explaining why those feelings are expressed, making it applicable in various contexts and domains. We also define sentiment words as those with clear polarity, even when used independently and exclude words whose polarity varies with context and domain. This approach enables the extraction of explicit sentiment expressions, enhancing the accuracy of sentiment analysis at the attribute level. Our methodology, validated using Korean cosmetics review datasets from Korean online shopping malls, demonstrates how a sentiment dictionary focused solely on clear polarity words can provide valuable insights for product planners. Understanding the polarity and reasons behind specific attributes enables improvement of product weaknesses and emphasis on strengths. This approach not only reduces dependency on extensive sentiment dictionaries but also offers high accuracy and applicability across various domains.

• IMMUNE NETWORK
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• 제23권5호
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• pp.36.1-36.16
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• 2023

Thymic epithelial cells (TECs) play a critical role in thymic development and thymopoiesis. As individuals age, TECs undergo various changes that impact their functions, leading to a reduction in cell numbers and impaired thymic selection. These age-related alterations have been observed in both mice and humans. However, the precise mechanisms underlying age-related TEC dysfunction remain unclear. Furthermore, there is a lack of a comprehensive study that connects mouse and human biological processes in this area. To address this gap, we conducted an extensive transcriptome analysis of young and old TECs in mice, complemented by further analysis of publicly available human TEC single-cell RNA sequencing data. Our analysis revealed alterations in both known and unknown pathways that potentially contribute to age-related TEC dysfunction. Specifically, we observed downregulation of pathways related to cell proliferation, T cell development, metabolism, and cytokine signaling in old age TECs. Conversely, TGF-β, BMP, and Wnt signaling pathways were upregulated, which have been known to be associated with age-related TEC dysfunctions or newly discovered in this study. Importantly, we found that these age-related changes in mouse TECs were consistently present in human TECs as well. This cross-species validation further strengthens the significance of our findings. In conclusion, our comprehensive analysis provides valuable insight into the biological and immunological characteristics of aged TECs in both mice and humans. These findings contribute to a better understanding of thymic involution and age-induced immune dysfunction.

• Advances in Energy Research
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• 제4권1호
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• pp.1-28
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• 2016

A grid-connected photovoltaic (PV) system comprised of multicrystalline silicon (mc-Si) modules was installed in a cold climate region in the U.S. This roof-mounted stationary PV system is a real-world application of PV for building energy generation in International Energy Conservation Code (IECC) Climate Zone 5 (and possibly similar climate zones such as 6, 7 and 8), and it served the purposes of research, demonstration, and education. The importance of this work is highlighted by the fact that there has been less emphasis on solar PV system in this region of the U.S. because of climate and latitude challenges. The system is equipped with an extensive data acquisition system capable of collecting performance and meteorological data while visually displaying real-time and historical data through an interactive online interface. Experimental data was collected and analyzed for the system over a one-year period with the focus of the study being on measurements of power production, energy generation, and efficiency. The annual average daily solar insolation incident upon the array was found to be $4.37kWh/m^2$. During the first year of operation, the PV system provided 5,801 kWh (1,264 kWh/kWp) of usable AC electrical energy, and it was found to operate at an annual average conversion efficiency and PR of 10.6 percent and 0.79, respectively. The annual average DC to AC conversion efficiency of the inverter was found to be 94 percent.

• Structural Engineering and Mechanics
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• 제77권4호
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• pp.495-508
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• 2021

This study devises a novel approach, namely quadruple 1D convolutional neural network, for detecting connection stiffness reduction in steel truss bridge structure using experimental and numerical modal data. The method is developed based on expertise in two domains: firstly, in Structural Health Monitoring, the mode shapes and its high-order derivatives, including second, third, and fourth derivatives, are accurate indicators in assessing damages. Secondly, in the Machine Learning literature, the deep convolutional neural networks are able to extract relevant features from input data, then perform classification tasks with high accuracy and reduced time complexity. The efficacy and effectiveness of the present method are supported through an extensive case study with the railway Nam O bridge. It delivers highly accurate results in assessing damage localization and damage severity for single as well as multiple damage scenarios. In addition, the robustness of this method is tested with the presence of white noise reflecting unavoidable uncertainties in signal processing and modeling in reality. The proposed approach is able to provide stable results with data corrupted by noise up to 10%.

• International Journal of Internet, Broadcasting and Communication
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• 제15권2호
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• pp.227-239
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• 2023

Online marketing is a rapidly growing industry that heavily depends on digital technologies and data analysis to effectively reach and engage consumers. For that, artificial intelligence (AI) has emerged as a crucial tool for online marketers, enabling marketers to analyze extensive consumer data and automate decision-making processes. The purpose of this study was to investigate the ethical implications of using AI in online marketing, focusing on its impact on consumer privacy and decision-making. AI has created new possibilities for personalized marketing but raises concerns about the collection and use of consumer data, transparency and accountability of decision-making, and the impact on consumer autonomy and privacy. In this study, we reviewed the relevant literature and case studies to assess the potential risks and make recommendations for improving consumer protection. The findings provide insights into ethical considerations and offer a roadmap for balancing the advantages of AI in online marketing with the protection of consumer rights. Companies should consider these ethical issues when implementing AI in their marketing strategies. In this study, we explored the concerns and provided insights into the challenges posed by AI in online marketing, such as the collection and use of consumer data, transparency, and accountability of decision-making, and the impact on consumer autonomy and privacy.