• Journal of Digital Convergence
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• v.20 no.3
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• pp.283-295
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• 2022

The number of citations in a patent is one of the indicators of the qualitative value of a patent. In this study, negative binomial regression model analysis was performed focusing on 47,354 US patents of 14 global top automotive makers in order to examine the major factors affecting the number of patent citations. As a result of the review, it was found that, elapsed years since filing, the number of patent claims, the number of claim letters, the number of inventors, the number of patent family countries, and the number of patent families, as well as IPC diversity, had a positive and significant effect on the number of citations. The results of this study are expected to provide a basic basis for considering the IPC diversity index together in analyzing and evaluating future patents and establishing strategies for creating excellent patents.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3B
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• pp.311-317
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• 2009

Similarity indices between sampling sites are calculated and cluster analysis of fish community is carried out by UPGMA based on investigating fish fauna and water environment. The restoration indicators as target species of Wonju stream are selected Cottus poecilopus, Zacco temmincki, and Zacco platypus along upper, middle, and lower streams, respectively. For better habitat suitability, low flow increasing and induced water quality improving must be secured by sewer system rearrangement and watershed management. Composite habitat suitability of Zacco temmincki as target species at middle stream of Wonju stream improve significantly by low flow increasing, which is very important factor to improve habitat suitability. The changes of hydraulics of depth and velocity govern the habitat suitability in general, but the effects are not significant. Low flow increasing with the change of 10% reducing of lower channel improves the composite habitat suitability of 0.37~0.78 to their origin of 0.1~0.25, which represent the channel restoration scheme of Wonju stream for enhancing the habitat suitability of fish community.

• Korean Journal of Organic Agriculture
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• v.31 no.3
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• pp.167-189
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• 2023

Korea has become the highest nitrogen balance (228 kg/ha) among 34 OECD member countries, and has the stigma of being a 'Nutrient overload country' as of 2019. Accordingly, research on the derivation and utilization of nutrient balance indicators and the 'regional nutrient management system' are being promoted to improve Korea's nutrient balance. It is necessary to support these policies and studies, form a public consensus on improving the nutrient balance, and evaluate the function of the public benefit. This paper aims to estimate the public benefit value of improving the nutrient balance based on an analysis of consumers' willingness to pay and recognition of Korea's nutrient excess for 600 consumers nationwide. As results, 21.2% of the respondents said they were aware of excessive nutrients in Korea, and 76.7% of the respondents said they were aware of the need for nutrient management. The average amount of intention to pay for the improvement of three pollution (soil, water quality, and air) that can occur due to a nutrient overload was ￦2,321.1 for soil pollution improvement, ￦2,391.2 for water pollution improvement, and ￦2,377.9 for air pollution improvement. The average willingness to pay for the three pollution reduction was ￦6,002.3. These results are expected to be used to form a public consensus on the balance of payments and to establish measures to enhance public interest values in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2768-2787
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• 2023

As an important research direction of the application of computer science in the medical field, the automatic generation technology of radiology report has attracted wide attention in the academic community. Because the proportion of normal regions in radiology images is much larger than that of abnormal regions, words describing diseases are often masked by other words, resulting in significant feature loss during the calculation process, which affects the quality of generated reports. In addition, the huge difference between visual features and semantic features causes traditional multi-modal fusion method to fail to generate long narrative structures consisting of multiple sentences, which are required for medical reports. To address these challenges, we propose a multi-feature optimization Transformer (MFOT) for generating radiology reports. In detail, a multi-dimensional mapping attention (MDMA) module is designed to encode the visual grid features from different dimensions to reduce the loss of primary features in the encoding process; a feature pre-fusion (FP) module is constructed to enhance the interaction ability between multi-modal features, so as to generate a reasonably structured radiology report; a detail enhanced attention (DEA) module is proposed to enhance the extraction and utilization of key features and reduce the loss of key features. In conclusion, we evaluate the performance of our proposed model against prevailing mainstream models by utilizing widely-recognized radiology report datasets, namely IU X-Ray and MIMIC-CXR. The experimental outcomes demonstrate that our model achieves SOTA performance on both datasets, compared with the base model, the average improvement of six key indicators is 19.9% and 18.0% respectively. These findings substantiate the efficacy of our model in the domain of automated radiology report generation.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1017-1029
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• 2023

A large amount of transactions are taking place through Blockchain. Among them, the proportion of transactions through smart contracts is increasing. Accordingly, problems such as vulnerability attacks on smart contracts and fraud using smart contracts are increasing. Through security audits of smart contracts, developers can discover and resolve vulnerabilities, and users can distinguish whether smart contracts are fraudulent. However, there are currently no regulations and standards for security auditing of smart contracts, so services that perform security auditing are uneven. In this paper, we analyze security audit trends for smart contracts and identify what services are being provided. We investigate what elements are analyzed from smart contracts, focusing on security audit reports. Also, investigate what vulnerabilities can be detected. Finally, we investigate quality indicators for smart contracts and visualization elements of design extraction. Through this, we hope to be able to find visualization elements specialized for smart contracts.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.215-228
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• 2023

The State Space Representation (SSR) method provides individual corrections for each Global Navigation Satellite System (GNSS) error components. This method can lead to less bandwidth for transmission and allows selective use of each correction. Precise Point Positioning (PPP) - Real-Time Kinematic (RTK) is one of the carrier-based precise positioning techniques using SSR correction. This technique enables high-precision positioning with a fast convergence time by providing atmospheric correction as well as satellite orbit and clock correction. Currently, the positioning service that supports PPP-RTK technology is the Quazi-Zenith Satellite System Centimeter Level Augmentation System (QZSS CLAS) in Japan. A system that provides correction for each GNSS error component, such as QZSS CLAS, requires monitoring of each error component to provide reliable correction and integrity information to the user. In this study, we conducted an analysis of the performance of residual error bounding for each error component. To assess this performance, we utilized the correction and quality indicators provided by QZSS CLAS. Performance analyses included the range domain, dispersive part, non-dispersive part, and satellite orbit/clock part. The residual root mean square (RMS) of CLAS correction for the range domain approximated 0.0369 m, and the residual RMS for both dispersive and non-dispersive components is around 0.0363 m. It has also been confirmed that the residual errors are properly bounded by the integrity parameters. However, the satellite orbit and clock part have a larger residual of about 0.6508 m, and it was confirmed that this residual was not bounded by the integrity parameters. Users who rely solely on satellite orbit and clock correction, particularly maritime users, thus should exercise caution when utilizing QZSS CLAS.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.129-148
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• 2023

This study verifies the effect of self-awareness on life satisfaction, depression, and anxiety as mental health indicators. An online survey, including self-awareness, life satisfaction, depression, and anxiety, was conducted on 300 adolescents, and the relationship between variables was observed through multiple regression analysis. As a result, adolescents' overall self-awareness significantly affected life satisfaction, depression, and anxiety. Moreover, the effect of self-awareness was confirmed on mental health by dividing it into private, public, and situational self-awareness: life satisfaction was predicted by public and situational self-awareness, while depression and anxiety were predicted through private self-awareness. The result shows that adolescents' self-awareness generally affects their mental health; however, positive and negative emotional factors are differentially affected by different types of self-awareness. This study confirms the importance of self-awareness in the process of improving mental health and quality of life in adolescence.

• Journal of Oriental Neuropsychiatry
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• v.34 no.4
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• pp.403-420
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• 2023

Objectives: This study investigated the effectiveness of herbal medicine for generalized anxiety disorder (GAD) based on recent clinical studies. Methods: Studies were searched through four databases. Clinical research studies on herbal medicine treatment for GAD patients were included. The studies were analyzed according to study design, diagnostic criteria, population, and intervention. A risk of bias assessment was performed to assess the quality of the included randomized controlled trials (RCT). If the intervention applied to the treatment and control groups was the same and two or more studies were reporting the same items as outcome indicators, a meta-analysis was performed. Results: A total of 19 studies, including 12 RCTs were selected. The most common pattern identification was 'Phlegm fire disturbing upward' (痰熱上擾), and the most used herb for therapeutic purposes was 'Rhizome of Poria cocos' (茯苓). Meta-analysis results of three studies showed that there were no significant differences in effectiveness between the herbal medicine intervention and the Western medicine intervention. Meta-analysis results of five studies showed that the Hamilton Anxiety Rating Scale was significantly reduced in the case of herbal medicine intervention compared to Western medicine intervention. Conclusions: The results of our study demonstrated that herbal medicine treatment for GAD is effective in alleviating anxiety symptoms and chief symptoms of GAD. However, this study has several limitations; there was a lack of placebo-controlled RCT and an absence of objective diagnostic criteria in case reports. Therefore, further well-designed clinical studies, conducted based on the results of this study, are recommended.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3218-3241
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• 2023

Financial fraud undermines the sustainable development of financial markets. Financial statements can be regarded as the key source of information to obtain the operating conditions of listed companies. Current research focuses more on mining financial digital data instead of looking into text data. However, text data can reveal emotional information, which is an important basis for detecting financial fraud. The audit opinion of the financial statement is especially the fair opinion of a certified public accountant on the quality of enterprise financial reports. Therefore, this research was carried out by using the data features of 4,153 listed companies' financial annual reports and audits of text opinions in the past six years, and the paper puts forward a financial fraud detection model integrating audit opinions. First, the financial data index database and audit opinion text database were built. Second, digitized audit opinions with deep learning Bert model was employed. Finally, both the extracted audit numerical characteristics and the financial numerical indicators were used as the training data of the LightGBM model. What is worth paying attention to is that the imbalanced distribution of sample labels is also one of the focuses of financial fraud research. To solve this problem, data enhancement and Focal Loss feature learning functions were used in data processing and model training respectively. The experimental results show that compared with the conventional financial fraud detection model, the performance of the proposed model is improved greatly, with Area Under the Curve (AUC) and Accuracy reaching 81.42% and 78.15%, respectively.

• Journal of the Korean Institute of Rural Architecture
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• v.26 no.1
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• pp.1-9
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• 2024

This study was motivated by the need to identify the characteristics of professionals involved in planning exterior spaces in urban development projects and to provide guidelines for maintaining the identity of urban images. Urban development's impact on external spaces can alter the image of the urban structure, especially due to the many boundaries between urban and rural areas. Therefore, there is a need for public standards for external spaces in such projects. This study collects and analyzes experts' opinions to understand the characteristics of each professional, selects the relative importance of each, and uses this as a guideline for step-by-step deliberation in planning external spaces. The research scope includes analyzing each expert's characteristics based on the external space evaluation items from Lee Limjeong's 2023 study, which builds upon existing research, and presenting the importance and priority of each expert. As a methodology, a questionnaire was conducted for each expert group using the indicators established in Lee Lim Jung's 2023 study for external spaces in urban development projects. An in-depth analysis was performed using the Analytic Hierarchy Process (AHP) for each expert. Using AHP analysis, the composite weight for each of the 17 detailed items was first adjusted by the number of item weights to account for the classification level of the large and detailed items. Then, the composite importance was calculated by multiplying the importance of the large, medium, and detailed classifications. The calculated composite importance was finally adjusted by applying the number of item weights again, ensuring the sum of the 17 importance values equals 1. The final importance calculated through this process was then presented by occupation.