• International Journal of Computer Science & Network Security
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• 제21권12spc호
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• pp.526-538
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• 2021

Machine and deep learning-based models are emerging techniques that are being used to address prediction problems in biomedical data analysis. DNA sequence prediction is a critical problem that has attracted a great deal of attention in the biomedical domain. Machine and deep learning-based models have been shown to provide more accurate results when compared to conventional regression-based models. The prediction of the gene sequence that leads to cancerous diseases, such as prostate cancer, is crucial. Identifying the most important features in a gene sequence is a challenging task. Extracting the components of the gene sequence that can provide an insight into the types of mutation in the gene is of great importance as it will lead to effective drug design and the promotion of the new concept of personalised medicine. In this work, we extracted the exons in the prostate gene sequences that were used in the experiment. We built a Deep Neural Network (DNN) and Bi-directional Long-Short Term Memory (Bi-LSTM) model using a k-mer encoding for the DNA sequence and one-hot encoding for the class label. The models were evaluated using different classification metrics. Our experimental results show that DNN model prediction offers a training accuracy of 99 percent and validation accuracy of 96 percent. The bi-LSTM model also has a training accuracy of 95 percent and validation accuracy of 91 percent.

• 문화기술의 융합
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• 제8권4호
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• pp.263-270
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• 2022

이 연구의 목적은 한류의 전개 과정을 살펴보고 학생들과 토의를 통해 한류 발전 방안을 모색하고자 한다. 한류는 1990년대 이후 한국 문화의 세계적 인기를 얻고 유행하는 현상으로 시작하여 상호 문화교류를 지향하는 신한류로 변화하였다. 구체적으로 한류의 구분을 1기에서 4기로 나누어 전개 과정을 살펴보았다. 이 연구는 2022년 1학기 문학과 대중문화 수업 시간에 다룬 주제 중 하나인 한류 주제를 활용하였다. 왜냐하면 한류는 한국 대중문화를 전 세계적으로 확산하였기 때문이다. 이 연구는 한류에 대한 토의를 활용하여 학생들과 연구자의 한류 발전 방안을 제시하였다.

• 대한안전경영과학회지
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• 제25권3호
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• pp.9-15
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• 2023

As the first step of risk management, risk identification is inevitable to understand the degree of work safety. However, the safety requirements can be divided in necessary factors and additional factors. Thus, we propose a safety requirements assessment model using Kano model derived from Herzberg's two-factor theory, classifying safety requirements into ideal elements and must-be elements. The Kano model is usually applied to evaluate customer satisfaction divided into three major requirements in the fields of product development and marketing: attractive, must-be, and one-dimensional requirements. Among them, attractive requirement and must-be requirement are matched with ideal element and must-be element for safety requirement classification, respectively. The ideal element is defined as preventive safety elements to make systems more safe and the must-be element is referred to as fatal elements to be essentially eliminated in systems. Also, coefficients of safety measurement and safety prevention are developed to classify different class of safety requirements. The positioning map is finally visualized in terms of both coefficients to compare the different features. Consequently, the proposed model enables safety managers to make a decision between safety measurement and prevention.

• 한국소음진동공학회논문집
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• 제21권11호
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• pp.997-1004
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• 2011

A fault detection algorithm of a charge and discharge system to ensure the safe use of hybrid electric vehicle is proposed in this paper. This algorithm can be used as a complementary way to existing fault detection technique for a charge and discharge system. The proposed algorithm uses a SVDD technique, which additionally utilizes two methods for learning a large amount of data; one is to incrementally learn a large amount of data, the other one is to remove the data that does not affect the next learning using a new data reduction technique. Removal of data is selected by using lines connecting support vectors. In the proposed method, the data processing speed is drastically improved and the storage space used is remarkably reduced than the conventional methods using the SVDD technique only. A battery data and speed data of a commercial hybrid electrical vehicle are utilized in this study. A fault boundary is produced via SVDD techniques using the input and output in normal operation of the system without using mathematical modeling. A fault detection simulation is performed using both an artificial fault data and the obtained fault boundary via SVDD techniques. In the fault detection simulation, fault detection time via proposed algorithm is compared with that of the peak-peak method. Also the proposed algorithm is revealed to detect fault in the region where conventional peak-peak method is never able to do.

• 한국정보시스템학회지:정보시스템연구
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• 제29권3호
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• pp.145-157
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• 2020

Purpose This study proposed an approach for predicting the efficiency rating of the cultural tourism festivals using DEA and machine learning techniques. The cultural tourism festivals are selected for the best festivals through peer reviews by tourism experts. However, only 10% of the festivals which are held in a year could be evaluated in the view of effectiveness without considering the efficiency of festivals. Design/methodology/approach Efficiency scores were derived from the results of DEA for the prediction of efficiency ratings. This study utilized BCC models to reflect the size effect of festivals and classified the festivals into four ratings according the efficiency scores. Multi-classification method were considered to build the prediction of four ratings for the festivals in this study. We utilized neural networks and SVMs with OAO(one-against-one), OAR(one-against-rest), C&S(crammer & singer) with Korea festival data from 2013 to 2018. Findings The number of total visitors in low efficient rating of DEA is more larger than the number of total visitors in high efficient ratings although the total expenditure of visitors is the highest in the most efficient rating when we analyzed the results of DEA for the characteristics of four ratings. SVM with OAO model showed the most superior performance in accuracy as SVM with OAR model was not trained well because of the imbalanced distribution between efficient rating and the other ratings. Our approach could predict the efficiency of festivals which were not included in the review process of culture tourism festivals without rebuilding DEA models each time. This enables us to manage the festivals efficiently with the proposed machine learning models.

• 한국유체기계학회 논문집
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• 제19권4호
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• pp.48-53
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• 2016

The centrifugal separator which uses gravity separation method for oil-water separation, rotating at high-speed, is one of the most commonly used device for controlling the amount of the oil in waste water collected in bilge. The IMO (International Maritime Organization) has set regulations, also known as MARPOL 73/78, for the prevention of marine pollution. In addition, DET NORSKE VERITAS (DNV) has set standards regarding the assignment of Environmental Class Notation, CLEAN or CLEAN DESIGN, of ships. One of the requirements for classification is that in addition to conforming to MARPOL 73/78, more stringent measures must be taken as well. One of these measures is to limit the oil concentration in bilge water to less than 5ppm. So in this study, an Oil-Water Separator (OWS) is used together with multiple separating plates as a filtration system to be used as an oil-water separation device. The OWS operates using centrifugal separation in which the mixture is separated by centrifugal forces. The main purpose of this paper is to present the OWS separation efficiency according to the rotation speed, mass-flow rate, the angle and the number of stacked layers of the laminated plate using Computational Fluid Dynamics (CFD). Improvements to the device will be investigated from these results.

• Archives of Plastic Surgery
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• 제50권6호
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• pp.550-556
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• 2023

Blunt breast trauma occurs in 2% of blunt chest injuries. This study aimed to evaluate the evidence on breast reconstruction after blunt trauma associated with the use of a seat belt. Also, we describe the first case of breast reconstruction using the Ribeiro technique. In November 2022, a systematic search of MEDLINE, EMBASE, and Google Scholar databases was conducted. The literature was screened independently by two reviewers, and the data was extracted. Our search terms included breast, mammoplasty, blunt injury, and seat belts. In addition, we present the case of a woman with a left breast deformity and her reconstruction using the inferior Ribeiro flap technique. Six articles were included. All included studies were published between 2010 and 2021. The studies recruited seven patients. According to the Teo and Song classification, seven class 2b cases were reported. In five cases a breast reduction was performed in the deformed breast with different types of pedicles (three superomedial flaps, one lower flap, one superior flap). Only one case presented complications. The case here presented was a type 2b breast deformity in which the lower Ribeiro pedicle was used successfully without complications during follow-up. Until now there has been no consensus on reconstructive treatment due to the rarity of this entity. However, we must consider surgical treatment individually for each patient. We believe that the Ribeiro technique is a feasible and safe alternative in the treatment of posttraumatic breast deformities, offering very good long-term results.

• Journal of Preventive Medicine and Public Health
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• 제7권1호
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• pp.131-138
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• 1974

The author has conducted survey on the status of physical growth and morbidity of the children for christian children's fund programme, as a means of collecting basic data for the anticipated establishment of a health planning. A total 345 children aged 9 to 16 underwent C.C.F. programme while as a control, a total of 480 children of same ages from the middle-class school children in Jeonju area was also studied. As results of survey conducted for a period of one month (form July 1 to 31, 1974) on a total 429 children in 347 households living in Jeonju area. I. Socio-economic background 1. By educational status of the children, 39.9 per cent of the total children was attending at primary school, 33.8 per cent in middle school and 15.6 per cent in high school. 2. The greatest proportion or 28.8 per cent of the household head were engaged in labor, 17.9 per cent in peddler and 13.2 per cent in retail. 3. As for the living standard of the households, low class constitued 90.1 per cent, middle and high classes only 9.9 per cent. 4. 39.5 per cent of the households had their own house, 39.1 per cent lived in rent deposit house or rooms and 14.6 per cent in monthly rented house and rooms. II. Physical growth and nutritional status 1. The growth of children for C.C.F. programme in terms of height was found to be slightly smaller than the school children. The ages frm 9 to 16 corespond to the 'secondary growth and replenishment period and this period was regarded to be the one most affected by environmental and nutritional factors of all the other periods of growth and developmet. 2. The body weight of the children for C.C.F. presented a quite different pattern from that of the school children. The above findings appeared thin-and-long stature from the famillies with higher living standard while those from the household with low standard of living had a short-and-plump one. 3. According to the values of Rohrer's index, the children of C.C.F carried a higher degree of 'replenishment' than the children in Jeonju area and adolesecence comes later for the girls under C.C.F. programme. III. Morbidity 1. The monthly prevalence rate was 110.0 per thousand persons for the children under C.C.F. programme. 2. The total number of case was classified by timing of the incidence as follws. 40.0 per cent was constituted by diseases carried over from tile previous month and 60.0 per cent by new incidences. 3. The diseases were broken down by W.H.O. disease classification into the greatest proportion or 39.1 per thousand person constituted by disease of the digestive system.

• 지능정보연구
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• 제23권4호
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• pp.147-168
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• 2017

오래 전부터 학계에서는 정확한 주식 시장의 예측에 대한 많은 연구가 진행되어 왔고 현재에도 다양한 기법을 응용한 예측모형들이 연구되고 있다. 특히 최근에는 딥러닝(Deep-Learning)을 포함한 다양한 기계학습기법(Machine Learning Methods)을 이용해 주가지수를 예측하려는 많은 시도들이 진행되고 있다. 전통적인 주식투자거래의 분석기법으로는 기본적 분석과 기술적 분석방법이 사용되지만 보다 단기적인 거래예측이나 통계학적, 수리적 기법을 응용하기에는 기술적 분석 방법이 보다 유용한 측면이 있다. 이러한 기술적 지표들을 이용하여 진행된 대부분의 연구는 미래시장의 (보통은 다음 거래일) 주가 등락을 이진분류-상승 또는 하락-하여 주가를 예측하는 모형을 연구한 것이다. 하지만 이러한 이진분류로는 추세를 예측하여 매매시그널을 파악하거나, 포트폴리오 리밸런싱(Portfolio Rebalancing)의 신호로 삼기에는 적합치 않은 측면이 많은 것 또한 사실이다. 이에 본 연구에서는 기존의 주가지수 예측방법인 이진 분류 (binary classification) 방법에서 주가지수 추세를 (상승추세, 박스권, 하락추세) 다분류 (multiple classification) 체계로 확장하여 주가지수 추세를 예측하고자 한다. 이러한 다 분류 문제 해결을 위해 기존에 사용하던 통계적 방법인 다항로지스틱 회귀분석(Multinomial Logistic Regression Analysis, MLOGIT)이나 다중판별분석(Multiple Discriminant Analysis, MDA) 또는 인공신경망(Artificial Neural Networks, ANN)과 같은 기법보다는 예측성과의 우수성이 입증된 다분류 Support Vector Machines(Multiclass SVM, MSVM)을 사용하고, 이 모델의 성능을 향상시키기 위한 래퍼(wrapper)로서 유전자 알고리즘(Genetic Algorithm)을 이용한 최적화 모델을 제안한다. 특히 GA-MSVM으로 명명된 본 연구의 제안 모형에서는 MSVM의 커널함수 매개변수, 그리고 최적의 입력변수 선택(feature selection) 뿐만이 아니라 학습사례 선택(instance selection)까지 최적화하여 모델의 성능을 극대화 하도록 설계하였다. 제안 모형의 성능을 검증하기 위해 국내주식시장의 실제 데이터를 적용해본 결과 ANN이나 CBR, MLOGIT, MDA와 같은 기존 데이터마이닝 기법들이나 인공지능 알고리즘은 물론 현재까지 가장 우수한 예측 성과를 나타내는 것으로 알려져 있던 전통적인 다분류 SVM 보다도 제안 모형이 보다 우수한 예측성과를 보임을 확인할 수 있었다. 특히 주가지수 추세 예측에 있어서 학습사례의 선택이 매우 중요한 역할을 하는 것으로 확인 되었으며, 모델의 성능의 개선효과에 다른 요인보다 중요한 요소임을 확인할 수 있었다.

• Childhood Kidney Diseases
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• 제6권2호
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• pp.155-168
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• 2002

목적 : 전신성 홍반성 낭창(Systemic lupus erythematosus, SLE)은 여러장기를 침범하는 자가면역성 질환으로 신장의 손상이 본 질환의 예후를 좌우하는 주요원인이다. 특히 소아에서 루프스 신염은 성인보다 그 빈도가 높고, 증상이 심하므로, 신생검은 효과적인 치료의 계획을 위해서 중요한 수기이다. 이에 저자는 소아연령에서 루프스 신염의 임상적 병리학적 특성 및 치료방법에 대해 전반적으로 고찰하여 예후의 향상을 기대하고자 한다. 방법 : 1990년 1월부터 2002년 9월까지 소아과에서 전신성 홍반성 낭창으로 진단받은 63례의 환아중 신생검을 시행하여 루프스 신염으로 진단되었던 40례를 대상으로 의무 기록을 후향적으로 고찰하였다. 결과 : 환아의 남녀비는 1:3이었고 진단당시 평균발병 연령은 12.1(2-18)세였다. ARA 기준중에서는 형광 항핵항체(95.0%), 항dsDNA항체(87.5%), 나비모양 홍반(80.0%)의 순이었다. 가장 흔한 신장증상은 단백뇨와 현미경적 혈뇨(75.0%), 신증후군(55.0%), 현미경적 혈뇨 단독(15.0%)의 순이었고, 신생검상 27례(67.5%)에서 WHO Class IV 병변이 관찰되었고 3례에서 추적 관찰 신생검에서 조직소견이 바뀌었다. 치료는 prednisolone 단독 5례, prednisolone+azathioprine 9례, prednisolone+azathioprine+정맥cyclophosphamide 14례, prednisolone+cyclosporineA+정맥 cyclophosphamide 12례였고, 9례에서 혈장 교환술을 시행하였다. 환아들의 평균 추적관찰은 $51.8{\pm}40.5$개월이었고 사망은 4례에서 있었다. 사망과 관련된 위험인자로는 진단당시 성별이 남아일 때, WHO class IV의 조직소견, 급성 신부전을 동반할 때 의미있는 것으로 나타났다. 결론 : SLE 환아 중 루프스 신염의 빈도는 63.5%였으며 그중 67.5%가 예후가 불량한 WHO Class IV로 확인되었다. 따라서 신염의 초기에 적극적인 면역억제제 사용이 장기 예후 향상에 도움을 주리라고 생각된다. 하지만 소아기에 성장, 정신 사회적 발달, 생식기의 독성 등도 중요한 문제이므로 항상 적절한 치료를 위해 세심한 관심을 쏟아야 할 것이다.