• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.357-366
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• 2022

Artificial intelligence (AI) is the replication of human intelligence by computer systems and machines using tools like machine learning, deep learning, expert systems, and natural language processing. AI can be applied in administrative settings to automate repetitive processes, analyze and forecast data, foster social communication skills among staff, reduce costs, and boost overall operational effectiveness. In order to understand how AI is being used for administrative duties in various organizations, this paper gives a critical dialogue on the topic and proposed a framework for using artificial intelligence in organizations. Additionally, it offers a list of specifications, attributes, and requirements that organizations planning to use AI should consider.

• 디지털산업정보학회논문지
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• 제8권1호
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• pp.29-40
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• 2012

A challenging research issue that has been one of growing importance to those working in human-computer interaction are to endow a machine with an emotional intelligence. Thus, emotion recognition technology plays an important role in the research area of human-computer interaction, and it allows a more natural and more human-like communication between human and computer. In this paper, we propose the multimodal emotion recognition system using face and speech to improve recognition performance. The distance measurement of the face-based emotion recognition is calculated by 2D-PCA of MCS-LBP image and nearest neighbor classifier, and also the likelihood measurement is obtained by Gaussian mixture model algorithm based on pitch and mel-frequency cepstral coefficient features in speech-based emotion recognition. The individual matching scores obtained from face and speech are combined using a weighted-summation operation, and the fused-score is utilized to classify the human emotion. Through experimental results, the proposed method exhibits improved recognition accuracy of about 11.25% to 19.75% when compared to the most uni-modal approach. From these results, we confirmed that the proposed approach achieved a significant performance improvement and the proposed method was very effective.

• 디지털콘텐츠학회 논문지
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• 제19권4호
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• pp.821-827
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• 2018

Affective Computing은 HCI (Human Computer Interaction) 및 건강 관리 분야에서 다양한 애플리케이션이 개발됨에 따라 최근 몇 년 동안 관심이 높아지고 있다. 이에 필수적으로 필요한 인간의 감정 인식에 대한 중요한 연구가 있었지만, 언어 및 표정과 비교하여 심전도 (ECG) 또는 뇌파계 (EEG) 신호와 같은 생리적 신호 분석에 따른 감정 분석에 대한 관심은 적었다. 본 논문에서는 이산 웨이블릿 변환을 이용한 EEG 기반 감정 인식 시스템을 제안하고 감정 관련 정보를 얻기 위해 다른 뇌파와 뇌 영역을 연구 하였으며, 웨이블릿 계수에 기초한 특징 세트가 웨이블릿 에너지 특징과 함께 추출되었다. 중복성을 최소화하고 피처 간의 관련성을 극대화하기 위해 mRMR 알고리즘이 피쳐 선택에 적용된다. 다중클래스 Support Vector Machine을 사용하여 4 가지 종류의 인간 감정을 크게 분류하였으며 공개적으로 이용 가능한 "DEAP"데이터베이스의 뇌파 기록이 실험에서 사용되었다. 제안 된 접근법은 기존의 알고리즘에 비해 향상된 성능을 보여준다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 춘계학술대회 논문집
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• pp.1408-1415
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• 2007

To operate Platform Screen Door (PSD) automatically, the operational data of PSD and the train must be interfaced properly. PSD and train are operated together by the signaling system in Automatic Train Operation (ATO) signaling system zone where interfaces are provided between PSD and train. However, the additional PSD interface system with train is required in train operating zone without the interface between PSD and train. For the PSD interface, the wireless communication system or the train status (train correct stop status / train door status) detection system has been used. Seoul Metro line No.2. has the PSD wireless communication system using 447MHz band RF. For the safety of PSD operation, it is required to prevent RF interference in the subway environment where many frequencies exist. In this paper, the PSD wireless communication system is developed using 2.4GHz band RF to prevent the interference of the wireless communication and increase the traffic of the PSD interface. Furthermore, the improved system can store, manage and display the PSD and train operational data using Human Machine Interface (HMI) in the train's driver cab.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1229-1234
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• 2004

Face robots capable of expressing their emotional status, can be adopted as an e cient tool for friendly communication between the human and the machine. In this paper, we present a face robot actuated with arti cial muscle based on dielectric elastomer. By exploiting the properties of polymers, it is possible to actuate the covering skin, and provide human-like expressivity without employing complicated mechanisms. The robot is driven by seven types of actuator modules such as eye, eyebrow, eyelid, brow, cheek, jaw and neck module corresponding to movements of facial muscles. Although they are only part of the whole set of facial motions, our approach is su cient to generate six fundamental facial expressions such as surprise, fear, angry, disgust, sadness, and happiness. Each module communicates with the others via CAN communication protocol and according to the desired emotional expressions, the facial motions are generated by combining the motions of each actuator module. A prototype of the robot has been developed and several experiments have been conducted to validate its feasibility.

• 한국전자통신학회논문지
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• 제9권11호
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• pp.1249-1254
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• 2014

사람에 의해 만들어진 수많은 데이터를 기반으로 하는 빅 데이터는 유용한 정보를 얻기 위해 사용된다. 컴퓨터 프로그램의 특징에 인간 메모리의 변형성을 추가 한 기계 학습 기법을 적용 할 경우 보다 유용한 정보를 얻을 수 있다. 그리고 빅 데이터는 이러한 결론을 사용하여 예측된다. 인간은 원래의 데이터와 유사한 데이터를 기억하는 경향이 있다. 그래서 빅 데이터 처리 기술은 인간의 이러한 특성을 반영해야 한다. 본 연구에서는 정보의 선택성을 제공하는 알고리즘을 제안한다. 이 알고리즘은 위 요인들을 반영한 기술이다. 이 알고리즘은 데이터의 변형 특성에 기초하여 유사한 데이터를 결정하는 데 높은 선택성을 가진 데이터를 선택한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 춘계학술발표대회
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• pp.604-607
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• 2018

From the last past decade, the Internet of Thing (IoT) area has attracted a lot of attention from researchers. It is said to be a promising technology with great impact in people life, since it redefines the relationship objects have with Human and between themselves. It allows objects to gather data from the real world and communicate with others through the internet. This enabled many opportunities for service providers, companies, factories, environmental monitoring, healthcare, smart cities, and soon. Therefore, today, IoT is densely used in various domains of life, and knows an exponential growth. However, although many advancements have been achieved, several challenges keep causing issues and still need to be overcome. This paper gives an overview on the current trend issues in IoT on which researchers are focusing. It's also explores different proposed frameworks to allow the application of cognitive computing as an integrated process of an Internet of things (IoT) systems, to bring a great advanced in the way machine may communicate with human and their surroundings. This is known as cognitive IoT (CIoT), which allows machines to produce a human-like behavior, then providing enhanced level of capabilities to IoT.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2005년도 춘계학술대회 논문집
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• pp.48-53
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• 2005

The world, coming into the 21st century, is preparing a new revolution called a knowledge-based society after the industrial society. The interest of the world is concentrated on information technology, nano-technology and biotechnology. In particular, the nano-technology of which study was originally started from an alternative for overcoming semiconductor micro-technology. It can be applied to most industry subject such as electronics, information and communication, machinery, chemistry, bioengineering, energy, etc. They are emerging into the technology that can change civilization of human beings. Specially, ultra precision machining is quickly applied to nano-technology in the field of machinery. Lately, with rapid development of electronics industry and optic industry, there are needs for super precision finishing of various core parts required in such related apparatuses. This paper handles stability of a super precision micro cutting machine that is a core unit of such a super precision finisher, and analyzes the results depending on the hinge type and material change, using FEM analysis. By reviewing the stability, it is possible to achieve the effect of basic data collection for unit control and to reduce trials and errors in unit design and manufacturing.

• 한국정보통신학회논문지
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• 제8권2호
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• pp.456-463
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• 2004

본 논문에서는 다양한 조명하에서 실시간으로 눈을 검출하고 추적하는 새로운 방법을 제안하고자 한다. 기존의 능동적 적외선을 이용한 눈 검출 및 추적 방법은 외부의 조명에 매우 민감하게 반응하는 문제점을 가지고 있으므로, 본 논문에서는 적외선 조명을 이용한 밝은 동공 효과와 전형적인 외형을 기반으로 한 사물 인식 기술을 결합하여 외부 조명의 간섭으로 밝은 동공 효과가 나타나지 않는 경우에도 견실하게 눈을 검출하고 추적 할 수 있는 방법을 제안한다. 눈 검출과 추적을 위해 SVM과 평균 이동 추적방법을 사용하였고, 적외선 조명과 카메라를 포함한 영상 획득 장치를 구성하여 제안된 방법이 효율적으로 다양한 조명하에서 눈 검출과 추적을 할 수 있음을 보여 주었다.

• Geomechanics and Engineering
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• 제31권3호
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• pp.265-279
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• 2022

Tunnel convergence prediction is essential for the safe construction and design of tunnels. This study proposes five machine learning models of deep neural network (DNN), K-nearest neighbors (KNN), Gaussian process regression (GPR), support vector regression (SVR), and decision trees (DT) to predict the convergence phenomenon during or shortly after the excavation of tunnels. In this respect, a database including 650 datasets (440 for training, 110 for validation, and 100 for test) was gathered from the previously constructed tunnels. In the database, 12 effective parameters on the tunnel convergence and a target of tunnel wall convergence were considered. Both 5-fold and hold-out cross validation methods were used to analyze the predicted outcomes in the ML models. Finally, the DNN method was proposed as the most robust model. Also, to assess each parameter's contribution to the prediction problem, the backward selection method was used. The results showed that the highest and lowest impact parameters for tunnel convergence are tunnel depth and tunnel width, respectively.