• International journal of advanced smart convergence
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• 제10권2호
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• pp.86-96
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• 2021

This cross-sectional survey research carried out with the inquisitive agenda on satisfaction of the translation outcomes as performed by human translation and (machine translation) post-editing. The survey group consisted of 166 Korean translators primarily working with the English, Chinese, and Japanese languages. They were asked to rate the satisfactory level with accuracy, fluency, idiomatic expression, and terminology in the Richter's scale of four. The result reveals that human translation is more satisfactory than post-editing with respect to accuracy, but it is uneasy to assert that accuracy is unsatisfactory in post-editing. On the other hand, the Korean translators are less satisfied with fluency, idiomatic expression, and terminology than accuracy. It can be assumed that although human translation is more satisfactory than post-editing, the accuracy of post-editing seems to be more acknowledged than fluency, idiomatic expression, and terminology, which lead the translators to take the accuracy of raw machine-translation products and to go on to improve the fluency, idiomatic expression, and terminology. Nevertheless, Korean translators believe Korean idiomatic expressions cannot be satisfactorily produced in post-editing, while fluency and terminology can be improved in post-editing.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.146-149
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• 2003

This paper proposes the concept of “Artificial Emotion”(AE). The goal of AE is simulation, extension and expansion of natural emotion, especially human emotion. The object of AE is machine emotion and emotion machine. The contents of AE are emotion recognition, emotion measurement, emotion understanding emotion representation emotion generation, emotion processing, emotion control and emotion communication. The methodology, technology, scientific significance and application value of artificial emotion are discussed

• 디지털융복합연구
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• 제12권9호
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• pp.219-223
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• 2014

최근 무선통신 시스템의 기술이 발전함으로 M2M(Machine-to-Machine)이 산업분야에서 관심이 되고 있다. 기기간 통신인 M2M은 재난, 안전, 건설, 보건복지, 기상, 환경, 물류, 문화, 국방, 의료, 농.축산 등 사람의 접근이 어려운 공간 등에 설치되어 운용된다. 이는 사람을 대신해 장비들이 자동으로 상황에 맞추어 통신을 하고 어느 정도의 조치는 자동으로 취해지도록 함으로써 사람을 대신한 정보 관리 및 장비 운영을 할 수 있다. M2M이 디바이스간 통신이 무선으로 이루어지는 경우 공격자의 공격에 노출되어 운영되는 보안적 문제로 정당한 장치인지 상호인증 등 적절한 보안이 필요하다. 관련하여 최근 보안적으로 안전한 많은 프로토콜이 연구 되고 있으며 본 논문에서는 M2M 보안문제를 해결하기 위하여 SessionKey, HashFunction, 및 Nonce 를 적용하였으며 보안취약성을 보완한 안전한 프로토콜을 제안한다. 제안프로토콜을 기존의 대부분의 연구처럼 수학적 정리증명으로 안전함을 주장하지 않고 Casper/FDR을 이용하여 정형검증 하였으며 실험결과 제안프로토콜이 안전함이 확인되었다.

• 디지털산업정보학회논문지
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• 제10권4호
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• pp.11-18
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• 2014

Recently, ICT technology has been evolving towards an M2M (Machine to Machine) environment that allows communication between machine and machine from the communication between person and person, and now the IoT (Internet of Things) technology that connects all things without human intervention is receiving great attention. In such a network environment, the communication network between object and object as well as between person and person, and person and object is available which leads to the sharing of information between all objects, which is the essential technical element for us to move forward to the information service society of the era of future ubiquitous computing. On this paper, the protocol related to DTMNs in a Sparse M2M environment was applied and the improved routing protocol was applied by using the azimuth and density of the moving node in order to support a more efficient network environment to deliver the message between nodes in an M2M environment. This paper intends to verify the continuity of the study related to efficient routing protocols to provide an efficient network environment in the IoT and IoE (Internet of Everything) environment which is as of recently in the spotlight.

• 디지털융복합연구
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• 제11권2호
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• pp.309-316
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• 2013

사물지능통신(Machine to Machine) 은 사람의 도움없이 언제, 어디서나 독립적으로 기기간 통신을 가능하게 한다. M2M통신은 보통 무선구간의 통신을 포함하므로 도청, 가로채기, 변조, 프라버시 침해 등의 보안문제가 많이 발생할 수 있다. 따라서 무엇보다 기기들간의 안전한 통신을 이루는 것이 가장 중요한 문제 중 하나이다. 본 논문에서는 M2M 아키텍쳐에서 M2M 도메인과 네트워크 도메인간에 인증을 통해 데이터 노출을 피하고 안전한 통신을 제공하기위해 동적 ID기반의 원격 인증 기법을 제안한다. 제안된 기법은 로직기반의 정형검증을 통해서 우수한 보안성과 안전성이 증명되었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.36.3-36
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• 2002

$\textbullet$ Motion capture system $\textbullet$ Exoskeleton mechanism $\textbullet$ Kinematics analysis $\textbullet$ Man-machine Interface $\textbullet$ Wireless communication $\textbullet$ Control algorithm

• ETRI Journal
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• 제43권5호
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• pp.787-798
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• 2021

This paper applies learning automata to improve the performance of a Q-learning based random access channel (QL-RACH) scheme in a cellular machine-to-machine (M2M) communication system. A prioritized learning automata QL-RACH (PLA-QL-RACH) access scheme is proposed. The scheme employs a prioritized learning automata technique to improve the throughput performance by minimizing the level of interaction and collision of M2M devices with human-to-human devices sharing the RACH of a cellular system. In addition, this scheme eliminates the excessive punishment suffered by the M2M devices by controlling the administration of a penalty. Simulation results show that the proposed PLA-QL-RACH scheme improves the RACH throughput by approximately 82% and reduces access delay by 79% with faster learning convergence when compared with QL-RACH.

• 전기학회논문지
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• 제67권11호
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• pp.1496-1505
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• 2018

The technology of emotion recognition is necessary for human computer interaction communication. There are many cases where one cannot communicate without considering one's emotion. As such, emotional recognition technology is an essential element in the field of communication. n this regard, it is highly utilized in various fields. Various bio-sensor sensors are used for human emotional recognition and can be used to measure emotions. This paper proposes a system for recognizing human emotions using two physiological sensors. For emotional classification, two-dimensional Russell's emotional model was used, and a method of classification based on personality was proposed by extracting sensor-specific characteristics. In addition, the emotional model was divided into four emotions using the Support Vector Machine classification algorithm. Finally, the proposed emotional recognition system was evaluated through a practical experiment.

• 한국자동차공학회논문집
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• 제17권4호
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• pp.16-23
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• 2009

Driving simulators are useful tools not only to test the components of future cars but also to evaluate the telematics service and HMI (Human-Machine Interface). However driving simulators cannot be implemented to test and evaluate the telematics service system because the GPS (Global Positioning System) which contains basic functional support for the telematics module do not work in the VR (virtual reality) environment. This paper presents a method to implement telematics service to a driving simulator by developing the GPS simulator which is able to emulate GPS satellite signals consist of NMEA-0183 protocol and RS232C communication standards. It is expected that the driving simulator with the GPS simulator can be used to study HMI and human-factor evaluations of the commercial telematics system to realize the HiLES (Human-in-the-Loop Evaluation System).

• 한국멀티미디어학회논문지
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• 제21권4호
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• pp.478-484
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• 2018

The choice of the motion features influences the result of the human action recognition method directly. Many factors often influence the single feature differently, such as appearance of the human body, environment and video camera. So the accuracy of action recognition is restricted. On the bases of studying the representation and recognition of human actions, and giving fully consideration to the advantages and disadvantages of different features, the Dense Trajectories(DT) algorithm is a very classic algorithm in the field of behavior recognition feature extraction, but there are some defects in the use of optical flow images. In this paper, we will use the improved Dense Trajectories(iDT) algorithm to optimize and extract the optical flow features in the movement of human action, then we will combined with Support Vector Machine methods to identify human behavior, and use the image in the KTH database for training and testing.