• Korean Journal of Environment and Ecology
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• 제20권2호
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• pp.159-169
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• 2006

Interpretive sign is a communication medium that is often used in self-guided interpretation. Understanding interpretive signs and their users is important to maximize the effectiveness of interpretation. This study evaluated design attributes of interpretive signs by visitor's personal characteristics and visiting patterns using Importance-Performance Analysis(IPA). Data were collected from August to September of 2003 at the self-guided trail in Naejangsan National Park, Korea. Visitors using the trail participated in a questionnaire survey, and a total of 276 subiects was used for data analysis. The IPA results showed that female(23.3%) than male(13.3%), low age group(43.3%) than middle(0.0%) and high age group(0.0%), higher education group(36.7%) than lower education group(0.0%), medium size group(33.3%) than large(10.0%) or small group(16.7%), 'with child' group(66.7%) than 'without child' group(20.0%) rated higher importance and lower performance on more design attributes of the interpretive signs. These groups also showed higher rate of 'Concentrate Here(CH)' attributes that require urgent improvement. The 'with child' group showed the especially high rate of 'CH' attributes. The results suggest that interpretive signs need to be designed considering diverse user groups. It is also necessary to develop some standardized items of the sign design attributes for more efficient and reliable implementation of IPA and other evaluative works.

• Structural Engineering and Mechanics
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• 제46권3호
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• pp.433-445
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• 2013

Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.

• Journal of Information Processing Systems
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• 제19권4호
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• pp.474-482
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• 2023

Data mining is a technique for extracting valuable information from vast amounts of data by analyzing statistical and mathematical operations, rules, and relationships. In this study, we employed data mining technology to analyze the data concerning the painting poetry of Maehwado (plum blossom paintings) from the early Joseon Dynasty. The data was extracted from the Hanguk Munjip Chonggan (Korean Literary Collections in Classical Chinese) in the Hanguk Gojeon Jonghap database (Korea Classics DB). Using computer information processing techniques, we carried out web scraping and classification of the painting poetry from the Hanguk Munjip Chonggan. Subsequently, we narrowed down our focus to the painting poetry specifically related to Maehwado in the early Joseon Dynasty. Based on this, refined dataset, we conducted an in-depth analysis and interpretation of the text data at the syllable corpus level. As a result, we found a direct correlation between the corpus statistics for each syllable in Maehwado painting poetry and the symbolic meaning of plum blossoms.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제11권9호
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• pp.1771-1780
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• 2007

The necessity of Information integration has emphasized by advancement of internet and change of enterprise environment. In enterprises, it usually integrates the multi-database constructing by M&A. For this integration of information it must guarantee interpretation and integration which is stabilized with solving heterogeneous characteristic problem. In this paper, we propose the method that change the global XML query to local XML query for interpretation. It is based on XMDR(eXtended Meta-Data Registry) which expresses the connection between the standard and the local for solve the interoperability problem in heterogeneous environment. Thus, we propose the legacy model that can search and modify by one Query with creating global XML Query by XMDR. and for his, we use the 2PC technique which is the distributed transaction control technique of existing.

• Journal of Korean Society of Water and Wastewater
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• 제36권4호
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• pp.239-248
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• 2022

The prediction of algal bloom is an important field of study in algal bloom management, and chlorophyll-a concentration(Chl-a) is commonly used to represent the status of algal bloom. In, recent years advanced machine learning algorithms are increasingly used for the prediction of algal bloom. In this study, XGBoost(XGB), an ensemble machine learning algorithm, was used to develop a model to predict Chl-a in a reservoir. The daily observation of water quality data and climate data was used for the training and testing of the model. In the first step of the study, the input variables were clustered into two groups(low and high value groups) based on the observed value of water temperature(TEMP), total organic carbon concentration(TOC), total nitrogen concentration(TN) and total phosphorus concentration(TP). For each of the four water quality items, two XGB models were developed using only the data in each clustered group(Model 1). The results were compared to the prediction of an XGB model developed by using the entire data before clustering(Model 2). The model performance was evaluated using three indices including root mean squared error-observation standard deviation ratio(RSR). The model performance was improved using Model 1 for TEMP, TN, TP as the RSR of each model was 0.503, 0.477 and 0.493, respectively, while the RSR of Model 2 was 0.521. On the other hand, Model 2 shows better performance than Model 1 for TOC, where the RSR was 0.532. Explainable artificial intelligence(XAI) is an ongoing field of research in machine learning study. Shapley value analysis, a novel XAI algorithm, was also used for the quantitative interpretation of the XGB model performance developed in this study.

• Asia-Pacific Journal of Business
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• 제14권1호
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• pp.365-379
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• 2023

Purpose - Our previous study (Chang & Lee, 2023) presented observations on the recent changes in the year-on-year (YoY) Consumer Price Index (CPI) of the Republic of Korea (ROK) after the COVID-19 pandemic. The purpose of this article is to present an integrated analysis and interpretation of the recent changes in CPI and the Aggregate Import Price Index (IPI) by incorporating recent data, specifically data from September 2022 to December 2022. Design/methodology/approach - This study collected CPI (YoY) data in the ROK from January 2019 to December 2022 using e-National Indicator System provided by the ROK. Statistical analysis was employed to analyze the data. Findings - First, we confirm the extended results of the existing study by Chang and Lee (2023). Second, we demonstrate that the Aggregate IPI in ROK increased significantly in 2022 compared to 2021. We then provide an integrated interpretation on the significant increase in CPI and aggregate IPI in ROK, which complements Chang and Lee (2023) that limits their discussion to YoY CPI. Moreover, we show that the IPI of the semiconductor in ROK decreased significantly in 2022 compared to 2021. Research implications or Originality - Our results provide important insights into the recent changes in the CPI in the ROK. The results suggest that these changes can be partially attributed to various factors, such as the global supply chain disruptions resulting from the spread of the COVID-19 pandemic and the prolonged war between Russia and Ukraine, the side effect of quantitative easing by the US Federal Reserve, heat waves and droughts caused by climate change in ROK, a surge in demand following a gradual daily recovery, US-China trade conflict, etc. Our study shows statistically comprehensive results compared to the studies that limit their discussion to YoY average growth rate.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제26권3C호
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• pp.157-170
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• 2006

Downhole method is considered as giving a little unreliable Vs profile when the signal to noise ratio(S/N) is low and the travel time information is erroneous although it is economical and ease of operation. Direct method has been applied for obtaining adequate result in this case. But it is difficult to determine optimum result by using direct method which is subjective and considering straight ray path. Therefore, in this paper, Mean Refracted Ray Path Method(MRM) was proposed, which is automated and considering refracted ray path. Artificial travel time data adding some travel time error was generated by forward modeling based on Snell's Law and travel time data was also obtained from numerical signal traces using FEM modelling. Using these travel time data, reliability of MRM was verified in the manner of comparing the results determined by MRM with the model. Finally, proposed method was applied to the real field data and it was considered as improved method for obtaining the optimum result in downhole seismic method.

• Geophysics and Geophysical Exploration
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• 제27권2호
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• pp.129-143
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• 2024

In magnetotelluric (MT) surveys, small inhomogeneities near the surface cause a static shift in which apparent resistivities shift regardless of frequency. As the static shift in MT data leads to errors in subsurface structure interpretation, many studies have been conducted over the past few decades to mitigate or remove the distortions it caused. The most representative method involves removing static shifts from the data before inversion. Conversely, static shifts can be corrected during inversion or included in the inversion process. In addition, other geophysical data can be used to remove static shifts. However, the correction methods are limited to one-dimensional (1D) static responses, and limitations remain in two- or three-dimensional (2D or 3D) interpretation of distorted MT data owing to static shifts. This study provides a foundation for future studies on static shift by analyzing several previously published methods.

• Anxiety and mood
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• 제3권2호
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• pp.116-122
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• 2007

Objective : The purpose of this study was to investigate the strategies used to cope with stress and the cognitive characteristics of somatic symptom perception in patients with panic disorder. Methods : A total of 101 patients who met the DSM-IV criteria for panic disorder and 60 normal controls were recruited for participation in this study. We evaluated the subjects using The Way of Stress Coping Questionnaire (SCQ), Somato-Sensory Amplification Scale (SSAS), Symptom Interpretation Questionnaire (SIQ), and the Panic Disorder Severity Scale (PDSS). We analyzed the data using an independent t-test and Pearson correlation analysis (p<0.05). Results : The patients who used emotionally focused coping strategies scored significantly lower on the SCQ. The patients with panic disorder showed greater amplification of body sensations in the SSAS, a significantly higher score on the physical interpretation subset of the SIQ, and a lower score on the environmental interpretation subset of the SIQ than the normal controls. The PDSS scores were positively correlated with the SSAS score and physical interpretation score on the SIQ. Conclusion : These results show that patients with panic disorder have poor emotionally focused strategies for coping with stress, greater amplification of body sensations, and a tendency towards a physical interpretation of somatic symptoms.

• Journal of the Korean Society of Radiology
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• 제16권5호
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• pp.649-660
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• 2022

In 1959, Satomura used spectral Doppler ultrasound to express the velocity of red blood cells according to time change, and Kato defined a zero-base line that could tell the direction of blood flow, making it possible to know the direction of blood flow. This became the basis for the widely used classifications of Triphasic, Biphasic, and Monophasic. However, the above classification has limitations that confuse users with the meaning and timing of use in a clinical environment. As a result, the American Society for Vascular Medicine (SVM) and the Society for Vascular Ultrasound (SVU) A consensus document on Doppler waveform analysis was declared by the joint committee. This study tried to review this consensus and to suggest nomenclature and modifiers that can be used in the domestic vascular ultrasound clinical field. The joint committee formed by SVM and SVU recommended that the use of the triphasic waveform and the biphasic waveform be used as a multiphasic waveform rather than being used due to the ambiguity of interpretation. In addition, it was agreed to name the hybrid-type waveform, which is a monophasic and high-resistance waveform, which has always been a problem of interpretation in a clinical environment, as an intermediate resistive waveform. In addition, in order to increase the communication efficiency between the interpreter and the sonographer, waveform analysis was classified into a main descriptor and a modifier, and it was recommended to use a single nomenclature by unifying various synonyms. It is expected that this literature review will provide accurate arterial spectral Doppler waveform interpretation and an agreed-upon nomenclature to radiologists performing vascular ultrasound examination in clinical practice, and will be utilized as basic data that can contribute to the improvement of public health.