• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.11
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• pp.19-24
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• 1992

In this paper, a high frequency method is developed which combines the uniform Geometrical Theory of Diffraction(GTD) and the Aperture Integration(AI) to analyze electromagnetic plane wave scattering by a perfectly-conducting, open-ended, semi-infinite parallel plate waveguide with a uniform layer of absorbing material on its inner wall, and with a slanted planar termination inside. In this method, first, the field of an arbitary point inside the paraller plate waveguide is computed by the GTD. Second, the field scattered into exterior region by the waveguide is found using the equivalent current, which can be obtaind from the aperture field of the waveguide and using the AI. Numerical results based on this GTD method are presented and compared with those based on the mode matching method.

• Ocean Systems Engineering
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• v.10 no.2
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• pp.227-241
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• 2020

This paper deals with the problem of the global stabilization for a class of tension leg platform (TLP) nonlinear control systems. Problem and objective: Based on the relaxed method, the chaotic system can be stabilized by regulating appropriately the parameters of dither. Scope and method: If the frequency of dither is high enough, the trajectory of the closed-loop dithered chaotic system and that of its corresponding model-the closed-loop fuzzy relaxed system can be made as close as desired. Results and conclusion: The behavior of the closed-loop dithered chaotic system can be rigorously predicted by establishing that of the closed-loop fuzzy relaxed system.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.10a
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• pp.221-225
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• 1998

본 논문에서는 연속분포(Continuous) HMM(hidden Markov model)을 기반으로 하여 한국어 고립단어인식 시스템을 설계, 구현하였다. 시스템의 학습과 평가를 위해 자동차 항법용 음성 명령어 도메인에서 추출한 10개의 고립단어를 대상으로 음성 데이터 베이스를 구축하였다. 음성 특징 파라미터로는 MFCCs(Mel Frequency Cepstral Coefficients)와 차분(delta) MFCC 그리고 에너지(energy)를 사용하였다. 학습 데이터로부터 추출한 18개의 유사 음소(phoneme-like unit : PLU)를 인식단위로 HMM 모델을 만들었고 조음 결합 현상(채-articulation)을 모델링 하기 위해 트라이폰(triphone) 모델로 확장하였다. 인식기 평가는 학습에 참여한 음성 데이터와 학습에 참여하지 않은 화자가 발성한 음성 데이터를 이용해 수행하였으며 평균적으로 97.5%의 인식성능을 얻었다.

• Asia Pacific Journal of Corpus Research
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• v.1 no.1
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• pp.95-125
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• 2020

This paper aims to inform people how to support each other on social media. It alludes to an architecture for social media discourse and proposes a novel theory of support in social media discourse. It makes a methodological contribution. It combines predominately artificial intelligence with corpus linguistics analysis. It is on a large-scale dataset of anonymised diabetes-related user's posts from the Facebook platform. Log-likelihood and precision measures help with validation. A multi-method approach with Discourse Analysis helps in understanding any potential patterns. People living with Diabetes are found to employ sophisticated high-frequency patterns of device-enabled categories of purpose and content. It is with, for example, linguistic forms of Advice with stance-taking and targets such as Diabetes amongst other interactional ways. There can be uncertainty and variation of effect displayed when sharing information for support. The implications of the new theory aim at healthcare communicators, corpus linguists and with preliminary work for AI support-bots. These bots may be programmed to utilise the language patterns to support people who need them automatically.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.6
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• pp.949-964
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• 2021

Accumulation of high-quality data is crucial for AI learning. The goal of using AI in fashion service is to propose of a creative, personalized solution that is close to the know-how of a human operator. These customized solutions require an understanding of fashion products and emotions. Therefore, it is necessary to accumulate data on the attributes of fashion products and fashion emotion. The first step for accumulating fashion data is to standardize the attribute with coherent system. The purpose of this study is to propose a fashion emotional classification system. For this, images of fashion products were collected, and metadata was obtained by allowing consumers to describe their emotions about fashion images freely. An emotional classification system with a hierarchical structure, was then constructed by performing frequency and CONCOR analyses on metadata. A final classification system was proposed by supplementing attribute values with reference to findings from previous studies and SNS data.

• Journal of the Korean Society of Safety
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• v.38 no.1
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• pp.1-8
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• 2023

It is extremely important to design safety-guaranteed industrial processes because such process determine the ultimate outcomes of industrial activities, including worker safety. Application of artificial intelligence (AI) in industrial safety involves modeling industrial safety systems by using vast amounts of safety-related data, accident prediction, and accident prevention based on predictions. As a preliminary step toward realizing AI-based industrial safety in Korea, this study discusses neural network-based modeling of industrial safety systems. The input variables that are the most discriminatory relative to the output variables of industrial safety processes are selected using two information-theoretic measures, namely entropy and cross entropy. Normalized frequency and severity of industrial accidents are selected as the output variables. Our simulation results confirm the effectiveness of the proposed neural network model and, therefore, the feasibility of extending the model to include more input and output variables.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.567-569
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• 2023

GAN은 이미지 생성모델로서 이미지 공간에서 좋은 결과를 보여왔다. 우리는 이러한 GAN의 능력을 더욱 향상하기 위하여 본 연구에서 주파수 영역에서 이미지를 학습하고 생성하는 새로운 방법을 제안한다. 이를 위하여 먼저 학습데이터를 2D FFT로 주파수 영역으로 변환한 후 변환된 학습데이터를 GAN이 학습하게 한다. 학습 후에 GAN은 새로운 이미지를 생성하며 생성된 이미지를 2D IFFT하여 이미지 공간으로 변환한다. 이렇게 주파수 영역에서 이미지를 생성하는 방법은 이미지 공간에서 생성하는 방법보다 다양한 장점이 있다. 생성된 이미지의 품질을 평가하기 위하여 4개 데이터 셋에 4개의 평가지표를 사용하여 평가한 결과 주파수 영역에서 생성한 이미지가 IS, P&R, D&C 측면에서 더 좋은 것으로 평가되었다.

• Journal of the East Asian Society of Dietary Life
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• v.21 no.3
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• pp.311-324
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• 2011

This study was performed to assess the nutritional status of low income elderly women aged ${\geq}$65 years residing in Gyeongnam Masan (n=124). Nutrition intakes, food intake frequency, and health-related behaviors including smoking, drinking, and exercise were investigated. Nutrition intake was calculated by the 24-hour recall method using CAN-pro (ver. 3.0). Average daily intakes of energy were $1,142.3{\pm}39$ kcal (71.4% of EER) in subjects aged 65~74 years and $1,071.0{\pm}41.7$ kcal (66.9% of EER) in subjects aged ${\geq}$75 years and the subjects consumed energy less than both 75% of estimated energy requirement (EER). The proportions of energy derived from protein, fat, and carbohydrate were 15.4:15.5:70.6 (aged 65~74 years), and 15.3:13.4:70.8 (aged ${\geq}$75). Nutrients consumed at less than estimated average requirements (EARs) were Ca (60.4%), P (98.4%), Zn (91%), vitamin E (48% of adequate intake, AI), vitamin $B_1$ (63.3%), vitamin $B_2$ (54%), niacin (87.7%), vitamin C (62.5%), and folate (50.5%). Especially, the intakes of Ca (58%), vitamin E (41% of AI), vitamin $B_1$ (60%), vitamin $B_2$ (50%), folate (46.5%), and vitamin C (54%) were 75% less than the EAR for people aged ${\geq}$75 years. According to the food intake frequency survey, the intakes of calcium, milk, fruits, and vegetables were very poor. In conclusion, this study suggests that a nutritional support program for elderly women of low socioeconomic class must be provided by the government to improve the quality of remaining life.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.207-213
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• 2022

Recently, with the improvement of the performance of IoT technology and AI, automation and unmanned work are progressing in a wide range of fields, and interest in image processing, which is the basis of automation such as object recognition and object classification, is increasing. Image noise removal is an important process used as a preprocessing step in an image processing system, and various studies have been conducted. However, in most cases, it is difficult to preserve detailed information due to the smoothing effect in high-frequency components such as edges. In this paper, we propose an algorithm to restore damaged images in AWGN(additive white Gaussian noise) using fuzzy weights based on Gaussian distribution. The proposed algorithm switched the filtering process by comparing the filtering mask and the noise estimate with each other, and reconstructed the image by calculating the fuzzy weights according to the low-frequency and high-frequency components of the image.

• Journal of Korean Society of Disaster and Security
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• v.15 no.4
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• pp.57-69
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• 2022

During the 10 years from 2011 to 2021, a whopping 2,800 people were killed or injured during port work. Among them, the frequency of occurrence at the port loading and unloading business is high. Container terminal operators must conduct risk assessments and establish reasonable safety measures in accordance with laws and regulations. As a research method, the contents of risk assessment presented in the Industrial Safety and Health Act, the Serious Accident Punishment Act, and the Special Act on Port Safety are presented through literature analysis. In this study, previous studies were analyzed to examine the risk assessment method and risk factors of container terminals. The purpose is to present 'industrial safety AI chatbot technology' that can improve the risk of safety accidents.