• Smart Structures and Systems
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• v.31 no.5
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• pp.485-500
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• 2023

Machine learning-based structural health monitoring (ML-based SHM) methods are researched extensively in the recent decade due to the availability of advanced information and sensing technology. ML methods are well-known for their pattern recognition capability for complex problems. However, the main obstacle of ML-based SHM is that it often requires pre-collected historical data for model training. In most actual scenarios, damage presence can be detected using the unsupervised learning method through anomaly detection, but to further identify the damage types would require prior knowledge or historical events as references. This creates the cold-start problem, especially for new and unobserved structures. Modal-based methods identify damages based on the changes in the structural global properties but often require dense measurements for accurate results. Therefore, a two-stage hybrid modal-machine learning damage detection scheme is proposed. The first stage detects damage presence using Principal Component Analysis-Frequency Response Function (PCA-FRF) in an unsupervised manner, whereas the second stage further identifies the damage. To solve the cold-start problem, mode shape assessment using the first mode is initiated when no trained model is available yet in the second stage. The damage identified by the modal-based method would be stored for future training. This work highlights the performance of the scheme in alleviating the cold-start issue as it transitions through different phases, starting from zero damage sample available. Results showed that single and multiple damages can be identified at an acceptable accuracy level even when training samples are limited.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.1-6
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• 2023

Morphological analysis is a branch of natural language processing, is now a rapidly growing field. The fundamental tenet of morphological analysis is that it can establish the roots or stems of words and enable comparison to the original term. Arabic is a highly inflected and derivational language and it has a strong structure. Each root or stem can have a large number of affixes attached to it due to the non-concatenative nature of Arabic morphology, increasing the number of possible inflected words that can be created. Accurate verb recognition and extraction are necessary nearly all issues in well-known study topics include Web Search, Information Retrieval, Machine Translation, Question Answering and so forth. in this work we have designed and implemented an algorithm to detect and recognize Arbic Verbs from Arabic text.The suggested technique was created with "Python" and the "pyqt5" visual package, allowing for quick modification and easy addition of new patterns. We employed 17 alternative patterns to represent all verbs in terms of singular, plural, masculine, and feminine pronouns as well as past, present, and imperative verb tenses. All of the verbs that matched these patterns were used when a verb has a root, and the outcomes were reliable. The approach is able to recognize all verbs with the same structure without requiring any alterations to the code or design. The verbs that are not recognized by our method have no antecedents in the Arabic roots. According to our work, the strategy can rapidly and precisely identify verbs with roots, but it cannot be used to identify verbs that are not in the Arabic language. We advise employing a hybrid approach that combines many principles as a result.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.315-320
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• 2021

In order to prepare for future social changes, SW·AI education is essential. In this paper, after conducting non-face-to-face SW·AI education for pre-service teachers, the effectiveness of SW education before and after education was measured using the measurement tool on the software educational effectiveness. As a result of the analysis, the overall average and the average of the 'computational thinking' and 'SW literacy' domains increased significantly, and the difference between the averages before and after education was statistically significant in decomposition, pattern recognition, abstraction, and algorithm, which are sub domains of 'computational thinking'. Through SW·AI education, students not only recognize the necessity of SW education and the importance of computational thinking, but also understand the process of decomposing information, recognizing and extracting patterns, and expressing problem-solving processes. It can be seen that non-face-to-face SW·AI education has the effect of improving computational thinking and SW literacy beyond recognizing the importance of SW.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.151-154
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• 2021

Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study was analyzed for 21 papers in the March 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 305 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.326-327
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• 2021

Newly, big data utilization has been widely interested in a wide variety of industrial fields. Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study were analyzed for 29 papers in a specific journal. In the final analysis results, the most frequently mentioned keyword was "Research", which ranked first 743 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• The Journal of Internal Korean Medicine
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• v.44 no.4
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• pp.703-725
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• 2023

Objectives: This study investigated Korean medicine doctors' perspectives on clinical practice patterns in the process of developing Korean medicine clinical practice guidelines for benign prostatic hyperplasia. Methods: A questionnaire was developed for Korean medicine doctors. A total of 323 oriental medicine doctors participated in the survey, which was live for a total of 9 days from September 22, 2022, to September 30, 2022. Results: Regarding awareness of treatments for benign prostatic hyperplasia, 63.8% of respondents showed high awareness of Korean medical treatments. However, items such as diagnostic criteria (17.7%), evaluation methods (17.0%), and Western medical treatments (22.9%) showed low recognition rates. In clinical practice, 76.2% of respondents were found to treat five or fewer patients with benign prostatic hyperplasia per month, and the average treatment period was 1 to 3 months for most at 41.2%. Korean medicine doctors diagnosed benign prostatic hyperplasia based on clinical features. The main interventions used were acupuncture, herbal medicine (prescription medicine), and moxibustion. This study has several limitations because of the low response rate for this survey; therefore, the participants are not representative of all Korean medicine doctors. In addition, because the study was conducted broadly on various topics related to benign prostatic hyperplasia, sufficient quality management was not carried out. Further studies that include a larger sample size and more in-depth studies on benign prostatic hyperplasia are needed. Conclusions: It is necessary to develop appropriate and reasonable Korean medicine clinical practice guidelines for benign prostatic hyperplasia.

• Journal of agricultural medicine and community health
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• v.18 no.1
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• pp.77-91
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• 1993

This study was conducted to assess health medical center utilization pattern and its related factors among the rural inhabitants for the purpose of contribution to establishment of health medical center institutions. A questionnaire survey was carried out for object of 3,754 population of three primary school and three middle school student's parents (total 832 household) in Kyungbook Ulchin Gun rural area from 24 to 28 September, 1990. The summarized result are as follows, Respondents are 60.3% in male, 39.7% in female and 30-40s 81.3% in age, high school graduates 40.3% in education level and a regional medical insurance scheme in 44.1% in forms of health insurance. Recognition for health medical center was showed higher according to high educational, high income level, and short distance for location of health medical center of respondents (p < 0.01). Recognition for health medical center services was showed higher about care of medicaid in medical treatment services and higher preventive vaccination in health prevention services by respondents. Utilization rates of health medical center by out-patient care and preventive care service were 11.1 and 4.5 per 100 persons by year, but admission utilization rate was 34.6 per 10.000 persons by year. Motivations of health medical center utilization were showed a good care(45.7%), a good drugs(45.2%), and nearby health medical center(42.9%). In comparison health service levels of health medical center with general clinic was better (16.3%), similar(38.7%), 7(19.0%), and worse(19.0%) in view of health medical center utilizators. Inconvinience about health medical center utilized was the most higher longtime waiting, the next was limited utilization times. Transportation utilited were on foot(55%), by bus(35.5%), and so on. As mentioned above, there are many inhabitants who less understanding and less acknowledgement about health medical center and even mistake health center for health medical center. Therefore, there must be more information about health medical center. For higher utilization of health medical center, there must be considered expansion of health equipment, facilities, accomplishment with reinforcement of health staffs and efficiency management.

• Cartoon and Animation Studies
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• s.50
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• pp.349-382
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• 2018

China is a great civilization which is a combination of various ethnic groups with long history change. As one of these important components of traditional culture, the lucky shape has been going through the ideological upheaval of the history change of China. Up to now, it has become the important parts which can stimulate the emotion of Chinese nation. The lucky shape becomes the basis of the rich traditional culture by long history of the Chinese nation. Even say it is the centre of this traditional culture resource. The lucky shape is a way of expressing the Chinese history and national emotions. It is the important part of people's living habits, emotion, as well as the cultural background. What's more, it has the value of beliefs of Surname totem. Meanwhile, it also has the function of passing on information. The symbol of information finally was created by the being of lucky shape to indicate its conceptual content. There are various kinds of lucky shapes. It will have its limitations when researching all kinds of them professionally. So, here the lucky shape of FISH will be researched. The shape of fish is the first good shape created by the Chinese nation. It is about 6000 years. Its special shape and lucky meaning embody the peculiar inherent culture and intension of the Chinese nation. It's the important component of the Chinese traditional culture. The traditional shape of fish was focused on the continuation of history and the patterns recognition, etc. It seldom indicated the meaning of the shape into the using of the modern design. So by searching the lucky meaning & the way of fish shape, the purpose of the search is to explore the real analysis of value of the fish shape in the modern enterprise identity design. The way of search is through the development of the history, the evolvement and the meaning of lucky of the traditional fish shape to analyse the symbolic meaning and the cultural meaning from all levels in nation, culture, art and life, etc. And by using the huge living example of the enterprise identity design of the traditional shape of the fish to analyse that how it works in positive way by those enterprise which is based on the trust with good image. In the modern Chinese enterprise identity design, the lucky image will be reinterpreted in the modern way. It will be proofed by the national perceptual knowledge of the consumer and the way of enlarge the goodwill of corporate image. It will be the conclusion. The traditional fish shape is the important core of modern design.So this search is taken through the instance of the design of enterprise image of the traditional fish shape to analysis the idea of the majority Chinese people of the traditional luck and the influence of corporation which based on trust and credibility. In modern image design of Chinese corporation, the auspicious sign reappear. The question survey is taken by people through the perceptual knowledge of the consumer and the cognition the enterprise image. According the result, people can speculate the improvement of consumer's recognition and the possibility of development of traditional concept.

• Molecules and Cells
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• v.39 no.5
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• pp.426-438
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• 2016

Plant disease resistance occurs as a hypersensitive response (HR) at the site of attempted pathogen invasion. This specific event is initiated in response to recognition of pathogen-associated molecular pattern (PAMP) and subsequent PAMP-triggered immunity (PTI) and effector-triggered immunity (ETI). Both PTI and ETI mechanisms are tightly connected with reactive oxygen species (ROS) production and disease resistance that involves distinct biphasic ROS production as one of its pivotal plant immune responses. This unique oxidative burst is strongly dependent on the resistant cultivars because a monophasic ROS burst is a hallmark of the susceptible cultivars. However, the cause of the differential ROS burst remains unknown. In the study here, we revealed the plausible underlying mechanism of the differential ROS burst through functional understanding of the Magnaporthe oryzae (M. oryzae) AVR effector, AVR-Pii. We performed yeast two-hybrid (Y2H) screening using AVR-Pii as bait and isolated rice NADP-malic enzyme2 (Os-NADP-ME2) as the rice target protein. To our surprise, deletion of the rice Os-NADP-ME2 gene in a resistant rice cultivar disrupted innate immunity against the rice blast fungus. Malic enzyme activity and inhibition studies demonstrated that AVR-Pii proteins specifically inhibit in vitro NADP-ME activity. Overall, we demonstrate that rice blast fungus, M. oryzae attenuates the host ROS burst via AVR-Pii-mediated inhibition of Os-NADP-ME2, which is indispensable in ROS metabolism for the innate immunity of rice. This characterization of the regulation of the host oxidative burst will help to elucidate how the products of AVR genes function associated with virulence of the pathogen.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.21-26
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• 2011

Feature ranking is useful to gain knowledge of data and identify relevant features. In this study, we proposed a use of feature ranking for classification of neuro-degeneration and vascular dementia in micro-Raman spectra of platelet. The entire region of the spectrum is divided into local region including several peaks, followed by Gaussian curve fitting method in the region to be modeled. Local minima select from the subregion and then remove the background based on the position by using interpolation method. After preprocessing steps, significant features were selected by feature ranking method to improve the classification accuracy and the computational complexity of classification system. PCA (principal component analysis) transform the selected features and the overall features that is used classification with the number of principal components. These were classified as MAP (maximum a posteriori) and it compared with classification result using overall features. In all experiments, the computational complexity of the classification system was remarkably reduced and the classification accuracy was partially increased. Particularly, the proposed method increased the classification accuracy in the experiment classifying the Parkinson's disease and normal with the average 1.7 %. From the result, it confirmed that proposed method could be efficiently used in the classification system of the neuro-degenerative disease and vascular dementia of platelet.