• Journal of Climate Change Research
• /
• v.9 no.4
• /
• pp.385-398
• /
• 2018

Although the importance of developing reliable and systematic GHG inventory has increased, the GIS/RS-based national scale LULUCF (Land Use, Land-Use Change and Forestry) sector analysis is insufficient in the context of the Paris Agreement. In this study, the change in $CO_2$ storage of forest land due to land use change is estimated using two GIS/RS methodologies, Sampling and Wall-to-Wall methods, from 2000 to 2010. Particularly, various imagery with sampling data and land cover maps are used for Sampling and Wall-to-Wall methods, respectively. This land use matrix of these methodologies and the national cadastral statistics are classified by six land-use categories (Forest land, Cropland, Grassland, Wetlands, Settlements, and Other land). The difference of area between the result of Sampling methods and the cadastral statistics decreases as the sample plot distance decreases. However, the difference is not significant under a 2 km sample plot. In the 2000s, the Wall-to-Wall method showed similar results to sampling under a 2 km distance except for the Settlement category. With the Wall-to-Wall method, $CO_2$ storage is higher than that of the Sampling method. Accordingly, the Wall-to-Wall method would be more advantageous than the Sampling method in the presence of sufficient spatial data for GHG inventory assessment. These results can contribute to establish an annual report system of national greenhouse gas inventory in the LULUCF sector.

• The Korean Journal of Archival Studies
• /
• no.75
• /
• pp.5-39
• /
• 2023

More than 20 years after introducing the public records management system in Korea, the criteria and methodologies for archival appraisal and selection are still unclear. Modern archival appraisal theories have developed in two orientations, such as provenance and pertinence. This study aims to investigate the methodological implications of each theoretical orientation of archival appraisal and to suggest some directions for improving the appraisal practices and policies. Firstly, archival appraisal theories are analyzed according two orientations. Secondly, four methodologies are derived from combining the macro/micro dimension and theoretical orientations. Thirdly, the methodological orientations of the criteria for selecting permanent records presented in the Public Records Management Act are analyzed. Finally, based on these analyses, appraisal policies and practices for selecting the records with permanent value are proposed to be improved.

• International Commerce and Information Review
• /
• v.15 no.2
• /
• pp.387-410
• /
• 2013

The competition aspect of business has been transformed from competition among companies to competition among ecosystem, and has been grown to platform based business, which is defined as ecosystem among business. Coming to the spotlight with the advantages of platform business combined software and hardware like Apple, platform business have been emerging in many fields. In this research, we define platform and platform based business, and then review related researches. After this, we review four representative research methodologies which are Yin(2011)' s case analysis research, Eisenhardt(2007)' s case analysis research, Romano etc' s web based qualitative data analysis method(2003), and Creswll(2010)' s open coding technique. And then, we suggest this research' s natural methodology combined with the advantages of four research methodologies. Based on our research methodology, we choose three high commercialized categories, which are smartphone platform business, social platform business, and search engine platform business. And then, we choose seven companies in three categories with success cases & failure cases, and analysis each case in perspective of our research methodology. And then, we suggest critical success & failure elements. Based on our findings, we suggest three strategic elements for the longevity of platform based business. Finally, we suggest the limitations of our research and further research issues.

• Journal of the Korea Concrete Institute
• /
• v.23 no.5
• /
• pp.667-674
• /
• 2011

This paper discusses the analysis method of prestressed concrete girder integral abutment bridges for a 75-year bridge life and the development of prediction models for abutment displacements under thermal loading due to annual temperature fluctuation and time-dependent loading. The developed nonlinear numerical modeling methodologies considered soil-structure interaction between supporting piles and surrounding soils and between abutment and backfills. Material nonlinearity was also considered to simulate differential rotation in construction joints between abutment and backwall. Based on the numerical modeling methodologies, a parametric study of 243 analysis cases, considering five parameters: (1) thermal expansion coefficient, (2) bridge length, (3) backfill height, (4) backfill stiffness, and (5) pile soil stiffness, was performed to established prediction models for abutment displacements over a bridge life. The parametric study results revealed that thermal expansion coefficient, bridge length, and pile-soil stiffness significantly influenced the abutment displacement. Bridge length parameter significantly influenced the abutment top displacement at the centroid of the superstructure, which is similar to the free expansion analysis results. Developed prediction model can be used for a preliminary design of integral abutment bridges.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.24 no.1
• /
• pp.25-44
• /
• 2013

The purpose of this study was to analyze the trends of Classification Studies in Korea from 205 research articles in five scholarly journals in Library and Information Science during the period 1986-2011. Individual article was analyzed in the aspects of specific research topics, research methodologies, data collection & analysis, and the characteristics of classification research was suggested. The amount of research paper has increased during the period and the focus of the study was on practical use and most of the papers were about new classification schedules or modification of current classification systems. Most of the papers were literature research and comparative research on classification systems by professors or graduate students. Top 9 authors in classification research were professors or lecturers and a few authors were computer science major. Therefore, various research topics, research methodologies and collaborations with other disciplines are necessary for future classification research.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.35 no.2
• /
• pp.163-168
• /
• 2011

Robust optimization or reliability-based design optimization are some of the methodologies that are employed to take into account the uncertainties of a system at the design stage. For applying such methodologies to solve industrial problems, accurate and efficient methods for estimating statistical moments and failure probability are required, and further, the results of sensitivity analysis, which is needed for searching direction during the optimization process, should also be accurate. The aim of this study is to employ the function approximation moment method into the sensitivity analysis formulation, which is expressed as an integral form, to verify the accuracy of the sensitivity results, and to solve a typical problem of reliability-based design optimization. These results are compared with those of other moment methods, and the feasibility of the function approximation moment method is verified. The sensitivity analysis formula with integral form is the efficient formulation for evaluating sensitivity because any additional function calculation is not needed provided the failure probability or statistical moments are calculated.

• Journal of the Korean Society of Safety
• /
• v.18 no.2
• /
• pp.104-118
• /
• 2003

It has been criticized that conventional human reliability analysis (HRA) methodologies for probabilistic safety assessment (PSA) have been focused on the quantification of human error probability (HEP) without detailed analysis of human cognitive processes such as situation assessment or decision-making which are crticial to successful response to emergency situations. This paper introduces a new human reliability analysis (HRA) methodology, AGAPE-ET (A guidance And Procedure for Human Error Analysis for Emergency Tasks), focused on the qualitative error analysis of emergency tasks from the viewpoint of the performance of human cognitive function. The AGAPE-ET method is based on the simplified cognitive model and a taxonomy of influencing factors. By each cognitive function, error causes or error-likely situations have been identified considering the characteristics of the performance of each cognitive function and influencing mechanism of PIFs on the cognitive function. Then, overall human error analysis process is designed considering the cognitive demand of the required task. The application to an emergency task shows that the proposed method is useful to identify task vulnerabilities associated with the performance of emergency tasks.

• Journal of Information Processing Systems
• /
• v.15 no.3
• /
• pp.500-519
• /
• 2019

The blooming of social media has simulated interest in sentiment analysis. Sentiment analysis aims to determine from a specific piece of content the overall attitude of its author in relation to a specific item, product, brand, or service. In sentiment analysis, the focus is on the subjective sentences. Hence, in order to discover and extract the subjective information from a given text, researchers have applied various methods in computational linguistics, natural language processing, and text analysis. The aim of this paper is to provide an in-depth up-to-date study of the sentiment analysis algorithms in order to familiarize with other works done in the subject. The paper focuses on the main tasks and applications of sentiment analysis. State-of-the-art algorithms, methodologies and techniques have been categorized and summarized to facilitate future research in this field.

• Proceedings of the Earthquake Engineering Society of Korea Conference
• /
• 2005.03a
• /
• pp.236-243
• /
• 2005

Nonlinear static analysis is used to quantify the resistance of the structure to lateral deformation and to gauge the mode of deformation and intensity of local demands. A simple method for the nonlinear static analysis of complex building structures subjected to monotonically increasing horizontal loading(pushover analysis) is presented. The method is designed to be a part of new methodologies for the seismic design and evaluation of structures. A variety of existing pushover analysis procedures are currently being consolidated under programs such as ATC 40 and FEMA 273. And various techniques have been recommended, including the use of constant lateral force profiles and the use of adaptive and multimodal approaches. In this paper a modal pushover analysis using design response spectra of UBC 97 is proposed. Proposed method is compared against the method in FEMA 273 and ATC 40, and results of time history analysis.

• International Journal of Computer Science & Network Security
• /
• v.24 no.9
• /
• pp.12-20
• /
• 2024

Sentiment analysis has become a pivotal component in understanding public opinion, market trends, and user experiences across various domains. The advent of GPT (Generative Pre-trained Transformer) models has revolutionized the landscape of natural language processing, introducing a new dimension to sentiment analysis. This comprehensive roadmap delves into the transformative impact of GPT models on sentiment analysis tasks, contrasting them with conventional methodologies. With an increasing need for nuanced and context-aware sentiment analysis, this study explores how GPT models, known for their ability to understand and generate human-like text, outperform traditional methods in capturing subtleties of sentiment expression. We scrutinize various case studies and benchmarks, highlighting GPT models' prowess in handling context, sarcasm, and idiomatic expressions. This roadmap not only underscores the superior performance of GPT models but also discusses challenges and future directions in this dynamic field, offering valuable insights for researchers, practitioners, and AI enthusiasts. The in-depth analysis provided in this paper serves as a testament to the transformational potential of GPT models in the realm of sentiment analysis.