• 한국문헌정보학회지
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• 제42권1호
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• pp.45-61
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• 2008

메타분석(Meta-Analysis)이란 분석에 대한 분석(analysis of analysis)이란 의미로, 특정 연구문제에 대해 독립적으로 수행된 선행연구들의 일치하지 않은 결과들을 통합하여 결론을 내리기 위해 개개 연구의 분석결과들을 수학적으로 합성하여 통계적으로 결론을 내리는 방법이다. 본 연구는 메타분석의 특성과 기본원리, 분석 절차, 대표적인 분석모델을 소개하고, 문헌정보학분야에서의 메타분석연구를 고찰하였다. 다른 학문에 비해 문헌정보학에서 메타분석연구는 매우 소량 수행되었고 국내 문헌정보학분야에서는 전무한 상태이다. 문헌정보학에서 메타분석을 수행하는데 문제점과 메타분석연구를 활성화하기 위해 연구자가 보고서 작성시 유의해야 할 내용을 논의하였다.

• 한국산학기술학회논문지
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• 제9권5호
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• pp.1095-1101
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• 2008

본 연구에서는 LNG 저장탱크에 대하여 내진해석을 수행하였다. 해석 모델은 관통 파이프만을 고려한 경우와 관통 파이프, 내부 벽체, 가이드를 고려한 경우에 대하여 해석을 수행하였다. 내진 해석법으로 등가정적 해석법과 응답 스펙트럼 해석법을 두 가지 해석 모델에 대하여 각각 적용하였다. 변형량과 응력을 계산하고, 그 결과를 비교하였다. 해석 결과, 응답 스펙트럼 해석법이 등가정적 해석법에 비하여 LNG 저장탱크를 보다 잘 모사하는 방법임을 알 수 있었다.

• International Journal of Precision Engineering and Manufacturing
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• 제4권4호
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• pp.5-12
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• 2003

This paper discusses about the thickness effects on the structural durability of a bileaflet mechanical heart valve (MHV). In the study on the design and the mechanical characteristics of a bileaflet mechanical heart valve, the fluid mechanics analysis on the blood flow passing through leaflets, the kinetodynamics analysis on the rigid body motion of the leaflet induced by the pulsatile blood flow, and the structural mechanics analysis for the deformed leaflet are required sequentially and simultaneously. Fluid forces computed in the fluid mechanics analysis on the blood flow are used in the kinetodynamics analysis for the leaflet motion. Thereafter, the structural mechanics analysis for the deformed leaflet follows to predict the structural strength variation of the leaflet as the leaflet thickness changes. Analysis results show that structural deformations and stresses increase as the fluid pressure increases and the leaflet thickness decreases. Analysis results also show that the leaflet becomes structurally weaker and weaker as the leaflet becomes thinner and thinner.

• 대한간호학회지
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• 제34권1호
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• pp.35-44
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• 2004

Purpose: This article explored issues arising from secondary analysis of qualitative data and analyzed the results of qualitative secondary analysis studies published in English, focusing on the methodological aspects. Method: A total of 29 studies were identified as qualitative secondary analysis studies, retrieving from the CINAHL database from 1982 to 3rd week of April 2003. These studies were analyzed by publication year, research method, and type of approach to secondary analysis. Result: The year that the qualitative secondary analysis study first published was 1992 and the number of the studies using secondary analysis has increased after the middle of 1990s. Grounded theory was the one the most frequently used(n=11, 37.9%) and phenomenological study the second most(n=6, 20.7%). In terms of types of approach, fifteen studies(51.7%) focused on the specific concepts that were not explored in the primary studies. Nine(31.0%) focused on the specific types of participants. Six were aimed to integrate contexts or perspectives to generate more general and abstract analysis of qualitative data. Conclusion: The results of this article will stimulate methodological discussion of qualitative secondary analysis and activate qualitative studies using secondary analysis.

• 기술혁신학회지
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• 제7권1호
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• pp.182-206
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• 2004

This is the review of 2,500 cases on the trend analysis of technology and market. We find the fact that the patterns of trend analysis are defined by the purpose and size of the series and analysis, not by the difference of experience, educational background, country or organization. Based on these facts, we define 14 types of the analysis of technology and market. Also we conceptualize several patterns of the analysis in methodology, techniques, analytical index, structure, information source and the value by types of trend analysis.

• Communications for Statistical Applications and Methods
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• 제28권2호
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• pp.135-150
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• 2021

We propose principal differential analysis based classification methods. Computations of squared multiple correlation function (RSQ) and principal differential analysis (PDA) scores are reviewed; in addition, we combine principal differential analysis results with the logistic regression for binary classification. In the numerical study, we compare the principal differential analysis based classification methods with functional principal component analysis based classification. Various scenarios are considered in a simulation study, and principal differential analysis based classification methods classify the functional data well. Gene expression data is considered for real data analysis. We observe that the PDA score based method also performs well.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.185-192
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• 2022

Forecasting and time series modelling plays a vital role in the data analysis process. Time Series is widely used in analytics & data science. Forecasting stock prices is a popular and important topic in financial and academic studies. A stock market is an unregulated place for forecasting due to the absence of essential rules for estimating or predicting a stock price in the stock market. Therefore, predicting stock prices is a time-series problem and challenging. Machine learning has many methods and applications instrumental in implementing stock price forecasting, such as technical analysis, fundamental analysis, time series analysis, statistical analysis. This paper will discuss implementing the stock price, forecasting, and research using prophet and LSTM models. This process and task are very complex and involve uncertainty. Although the stock price never is predicted due to its ambiguous field, this paper aims to apply the concept of forecasting and data analysis to predict stocks.

• International Journal of Computer Science & Network Security
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• 제24권9호
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• pp.12-20
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• 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.

• Journal of Welding and Joining
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• 제19권5호
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• pp.492-498
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• 2001

In the previous study, temperature monitoring of case about shrinkage fit process was performed and heat transfer model was developed in detail by feedback and tuning among monitoring result, process investigation, and analysis result. The gap element in contact between case and core was effectively used in analysis model. In present study, following things are performed to solve deformation of case due to shrinkage fit process on the basis of previous result. Above all, mechanical material properties of case are measured by case specimen for deformation analysis considering weldment of case. Deformation of case before and after shrinkage fit process is measured, too. Three dimensional deformation model is developed by the comparison and inspection between these experimental data and analysis results. Deformation analysis is simulated with the result of heat transfer analysis, in other words, non-coupled analysis is used. Finally the countermeasure for deformation is brought up through those.

• 대한안전경영과학회지
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• 제15권2호
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• pp.55-61
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• 2013

For years, many studies have mainly been investigated in a complicated human motion analysis. Recently, many motion analysis equipments have been studied and developed. Therefore, the more complex human movement analyses are possible, we have enabled us to perform more and more complicated human movement analyses. A Three-dimensional(3D) motion analysis on of the several methods is a useful tool for analyzing the human motion analysis. The purpose of this study was to develop the 3D human motion analysis using a kalman filter algorithm and a gyro sensor. The algorithm and sensor were used to human motion analysis with high-speed motion capture. In this study, the developed system will be adapted to facilitate golf swing analysis. Using the developed system, golfers and coaches who do not have advanced biomechanical knowledge can easily be used to their golf swing analysis. Future study is necessary for more practical and efficient area such as other sports industries, 3D game industries, rehabilitation training, etc..