• 제목/요약/키워드: Recognition of Support System

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상시학습체제에서 사이버교육 요인이 공무원의 사이버교육 선호도에 미치는 영향 -부산광역시를 중심으로- (The Research of Effect of Cyber Education at Always Learning System in Affinity of Cyber Education for Officials: Focusing on Busan Metropolitan City)

  • 박명규;심선희;김하균
    • 수산해양교육연구
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    • 제23권1호
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    • pp.116-125
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    • 2011
  • In this study, a survey research was conducted on government employees in Busan Metropolitan City to identify the influence of cyber education factors (learning factor, learner factor, and learning system factor) on the preference for government employee cyber education offered by the government always learning system. Analyzed results, recognition of learning factor, learner factor, and always learning system were shown to have significant influence on the preference for cyber education, but no indication of influence by always learning support. This study intends to assist stimulating voluntary participation in cyber education and active commitment in learning activities through improving learning effect and fortifying convenient informatization education, with regard to activation of cyber education and improved preference for cyber education.

Emotion Recognition in Arabic Speech from Saudi Dialect Corpus Using Machine Learning and Deep Learning Algorithms

  • Hanaa Alamri;Hanan S. Alshanbari
    • International Journal of Computer Science & Network Security
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    • 제23권8호
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    • pp.9-16
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    • 2023
  • Speech can actively elicit feelings and attitudes by using words. It is important for researchers to identify the emotional content contained in speech signals as well as the sort of emotion that resulted from the speech that was made. In this study, we studied the emotion recognition system using a database in Arabic, especially in the Saudi dialect, the database is from a YouTube channel called Telfaz11, The four emotions that were examined were anger, happiness, sadness, and neutral. In our experiments, we extracted features from audio signals, such as Mel Frequency Cepstral Coefficient (MFCC) and Zero-Crossing Rate (ZCR), then we classified emotions using many classification algorithms such as machine learning algorithms (Support Vector Machine (SVM) and K-Nearest Neighbor (KNN)) and deep learning algorithms such as (Convolution Neural Network (CNN) and Long Short-Term Memory (LSTM)). Our Experiments showed that the MFCC feature extraction method and CNN model obtained the best accuracy result with 95%, proving the effectiveness of this classification system in recognizing Arabic spoken emotions.

다중 바이오 인식을 위한 임베디드 시스템 구현 (Implementation of Multimodal Biometric Embedded System)

  • 김기현;유장희
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2006년도 하계종합학술대회
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    • pp.875-876
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    • 2006
  • In this paper, we propose a multimodal biometric embedded system. It is designed to support face, iris, fingerprint and vascular pattern recognition. We use a S3C2440A based on ARM926T core processor that is made in Samsung. The system has support various external device interfaces for multi biometric sensors, and RFID/Smart Card reader/writer. Additionally, it has a 6" LCD panel and numeric keypad for easy GUI. The embedded system offers useful environments to develop better biometric algorithms for stand alone biometric system and accelerator hardware modules for real time operation.

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Recognition and Intent-to-Participate of Rural Migrants on Urban and Rural Exchange Business in Namhae County, South Korea

  • Park, Myeong Sik;Kim, Inhea;Huh, Keun Young;Bui, Hai Dang
    • 인간식물환경학회지
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    • 제24권3호
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    • pp.285-300
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    • 2021
  • Background and objective: Rural migrants are an important human resource in urban and rural exchange (URE) business, therefore it is necessary to enhance their awareness and intent-to-participate. This study was to analyze the rural migrants' recognition and intent-to-participate of URE business and to propose the enhancement of them both. Methods: The questionnaire was designed to analyze the socio-demographic background, motivations, satisfaction with settlement, intent-to-persist, and intent-to-participate of URE business including tourism. The data of 144 respondents was subject to the statistical analysis. Results: The motives of migration were to enjoy leisure life after retirement, increased tiredness of city life, health problems, etc. The satisfaction with settlement was 3.67 at 5-point Likert scale. The intent-to-recommend and intent-to-publicize were 3.40 and 3.46, respectively. The intent-to-participate was 3.45, which was affected by the necessity of URE business and the support of central/local governments, and also showed a significant correlation with the satisfaction with settlement, intent-to-recommend, intent-to-publicize, tourism resources for green tourism or rural tourism, driving a car in Namhae county, and the service and price of meals. They thought the missions that the Namhae county office must focus on were to establish an internal/external public relations systems, establish a support system of central/local governments, and foster/support local leaders. Conclusion: It is necessary to improve the satisfaction with settlement and intent-to-persist, expand exchanges with local people, improve internal/external public relations systems, foster/support leaders, improve transportation in the county, enhance the service and price of meals, and develop/operate URE programs including tourism.

Efficient Sign Language Recognition and Classification Using African Buffalo Optimization Using Support Vector Machine System

  • Karthikeyan M. P.;Vu Cao Lam;Dac-Nhuong Le
    • International Journal of Computer Science & Network Security
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    • 제24권6호
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    • pp.8-16
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    • 2024
  • Communication with the deaf has always been crucial. Deaf and hard-of-hearing persons can now express their thoughts and opinions to teachers through sign language, which has become a universal language and a very effective tool. This helps to improve their education. This facilitates and simplifies the referral procedure between them and the teachers. There are various bodily movements used in sign language, including those of arms, legs, and face. Pure expressiveness, proximity, and shared interests are examples of nonverbal physical communication that is distinct from gestures that convey a particular message. The meanings of gestures vary depending on your social or cultural background and are quite unique. Sign language prediction recognition is a highly popular and Research is ongoing in this area, and the SVM has shown value. Research in a number of fields where SVMs struggle has encouraged the development of numerous applications, such as SVM for enormous data sets, SVM for multi-classification, and SVM for unbalanced data sets.Without a precise diagnosis of the signs, right control measures cannot be applied when they are needed. One of the methods that is frequently utilized for the identification and categorization of sign languages is image processing. African Buffalo Optimization using Support Vector Machine (ABO+SVM) classification technology is used in this work to help identify and categorize peoples' sign languages. Segmentation by K-means clustering is used to first identify the sign region, after which color and texture features are extracted. The accuracy, sensitivity, Precision, specificity, and F1-score of the proposed system African Buffalo Optimization using Support Vector Machine (ABOSVM) are validated against the existing classifiers SVM, CNN, and PSO+ANN.

Time-multiplexing과 바이오 피드백을 이용한 EEG기반 뇌-컴퓨터 인터페이스 시스템 (EEG Based Brain-Computer Interface System Using Time-multiplexing and Bio-Feedback)

  • 배일한;반상우;이민호
    • 센서학회지
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    • 제13권3호
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    • pp.236-243
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    • 2004
  • In this paper, we proposed a brain-computer interface system using EEG signals. It can generate 4 direction command signal from EEG signals captured during imagination of subjects. Bandpass filter used for preprocessing to detect the brain signal, and the power spectrum at a specific frequency domain of the EEG signals for concentration status and non-concentration one is used for feature. In order to generate an adequate signal for controlling the 4 direction movement, we propose a new interface system implemented by using a support vector machine and a time-multiplexing method. Moreover, bio-feed back process and on-line adaptive pattern recognition mechanism are also considered in the proposed system. Computer experimental results show that the proposed method is effective to recognize the non-stational brain wave signal.

PARAMETRIC DESIGN을 위한 자동설계모듈 생성 (Automated design module generation system for parametric design)

  • 이석희;반갑수
    • 한국정밀공학회지
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    • 제10권4호
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    • pp.236-247
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    • 1993
  • An davanced method for the automatic generation of parametric models in computer- aided design systems is required for most of two-dimensional model which is represented as a set of geometric elements, and constraining scheme formulas. The development system uses geometric constraints and support of topology parameters from feature recognition and grouping the design entities into optimal ones from pre-designed drawings. The aim of this paper is to present guidelines for the application and development of parametric design modules for the standard parts in mechanical system, the basic constitutional part of mold base, and other 2D features.

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대규모 시스템의 실시간 컴퓨터 제어를 위한 전문가 시스템 (An Expert System for the Real-Time Computer Control of the Large-Scale System)

  • 고윤석
    • 대한전기학회논문지:전력기술부문A
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    • 제48권6호
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    • pp.781-788
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    • 1999
  • In this paper, an expert system is proposed, which can be effectively applied to the large-scale systems with the diversity time constraints, the objectives and the unfixed system structure. The inference scheme of the expert system have the integrated structure composed of the intuitive inference module and logical inference module in order to support effectively the operating constraints of system. The intuitive inference module is designed using the pattern matching or pattern recognition method in order to search a same or similar pattern under the fixed system structure. On the other hand, the logical inference module is designed as the structure with the multiple inference mode based on the heuristic search method in order to determine the optimal or near optimal control strategies satisfing the time constraints for system events under the unfixed system structure, and in order to use as knowledge generator. Here, inference mode consists of the best-first, the local-minimum tree, the breadth-iterative, the limited search width/time method. Finally, the application results for large-scale distribution SCADA system proves that the inference scheme of the expert system is very effective for the large-scale system. The expert system is implemented in C language for the dynamic mamory allocation method, database interface, compatability.

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항적 데이터 학습을 통한 추천 항로 구성에 관한 연구 (Composing Recommended Route through Machine Learning of Navigational Data)

  • 김주성;정중식;이성용;이은석
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2016년도 춘계학술대회
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    • pp.285-286
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    • 2016
  • 해상교통관제센터에 의해 실시간으로 수집되는 선박의 항해 데이터를 바탕으로 선박 항적 패턴 인식을 수행하고 이를 바탕으로 항적 모델을 추출하여 사전에 선위를 예측하는 기법을 제안한다. 항적 데이터의 처리와 가공, 항적 모델링을 위하여 Support Vector Regression 알고리즘이 사용되었으며, 적정 파라미터 선정을 위하여 k-fold cross validation과 grid search가 사용되었다. 제안된 항적 데이터 모델링 기법을 통하여 사전에 선박의 선위를 예측하여 해상교통과제사의 의사결정을 지원하고자 한다.

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지문인식시스템의 신뢰성 품질 성능 평가모델 개발 (Development for Reliability Quality and Performance Evaluate Model of Fingerprint Recognition System)

  • 엄우식;전인오
    • 한국콘텐츠학회논문지
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    • 제11권2호
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    • pp.79-87
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    • 2011
  • 현재 지문인식시스템 제품은 양적으로 빠른 성장세를 보이고 있으나 그 동안 질적인 품질을 고려하는 노력이 미흡한 것이 사실이었다. 따라서, 본 논문에서는 지식정보보안 제품의 질적인 면을 평가하여 품질 수준을 파악하여 개선방향을 도출함으로써 품질향상을 지원할 수 있는 평가모델을 개발하기 위해 지문인식시스템 제품의 국내외 시장현황과 기술적인 요소들을 분석하였다. 제품의 특성을 고려하여 보안성, 성능, 신뢰성 요구사항을 분석하여 기존 보안기능 중심의 평가에서는 다루지 못했던 비 기능 요소를 포괄적으로 적용할 수 있는 신뢰성 품질평가 모델을 구축하였다. 본 논문을 통해 지문인식 제품 특성과 동향을 반영하고 제품별 평가를 수행할 수 있는 신뢰성 평가모델을 구축함으로써 지식정보보안 제품의 전반적인 품질향상에 기여할 수 있을 것이다.