• 영어어문교육
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• 제3호
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• pp.43-54
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• 1997

According to Asher(1972) listening skill must be taught before any other skills. Despite such an importance of listening skill, listening tests taken at the secondary schools depend on simple multiple choice method. So more various method such as Task-Based Listening Test need suggesting. This study aims at (1) three step listening material development (2) and advancement of listening ability through the materials.

• The Journal of Korean Physical Therapy
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• 제18권4호
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• pp.1-9
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• 2006

Recently, several investigations revealed that after unilateral brain damage, movement abnormalities were exposed on the ipsilateral side as well as the upper extremity contralateral to the damaged hemisphere. Even the motor abilities had significantly recovered from ipsilateral motor deficits on not only simple sensoriomotor function, also clinical assessments since subacute stage, although could not completely returned. Such motor deficits were detected in a diversity of motor tasks depending on the interhemispheric specialization, further in clinical evaluation and a daily of activities. In the clinical features, muscular weakness, sensory loss and impaired manual dexterity were observed. In a laboratory experiment, there were increasing evidences that the kinematic processing deficits was founded in various-specific motor tasks, which ranged from simple basic element to complex tasks, such as tapping task, step-tracking, goal directional aiming task, and iso(and non-)directional interlimb coordination. In the point of view, the manifest understanding in related to ipsilateral deficits provide the clinicians with an important information for scientific management about brain injured patient's prognosis and therapeutic guidelines.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.8-8
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• 2000

PICARD (Port-Interface Component Architecture for Real-time system Design) is a software architecture and environment, which is aimed to reduce development time and cost of real-time, control system. With PICARD, a control engineer can construct a control system software by assembling pre-built software components us ing interact ive graphical development environment. PICARD consists of PVM(Picard Virtual Machine) , a component library, and PICE(PIcard Configuration Editor). PVM is a real-time engine of the PICARD system which runs control tasks on a real-time operating system. The component library is composed of components which are called task blocks. PICE is a visual editor which can configure control tasks by creating data-flow diagrams of task blocks or Ladder diagrams for sequential logics. For the communication between PVM on a target system and PICE on a host computer, a simple protocol and tools for stub generation was dove]oped because RPC or CORBA is difficult to be applied for the embedded system. New features such as a byte-code based run time system and a simple and easy MMI builder are also introduced.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.751-770
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• 2019

Action recognition is an essential task in computer vision due to the variety of prospective applications, such as security surveillance, machine learning, and human-computer interaction. The availability of more video data than ever before and the lofty performance of deep convolutional neural networks also make it essential for action recognition in video. Unfortunately, limited crafted video features and the scarcity of benchmark datasets make it challenging to address the multi-person action recognition task in video data. In this work, we propose a deep convolutional neural network-based Effective Hybrid Learning (EHL) framework for two-person interaction classification in video data. Our approach exploits a pre-trained network model (the VGG16 from the University of Oxford Visual Geometry Group) and extends the Faster R-CNN (region-based convolutional neural network a state-of-the-art detector for image classification). We broaden a semi-supervised learning method combined with an active learning method to improve overall performance. Numerous types of two-person interactions exist in the real world, which makes this a challenging task. In our experiment, we consider a limited number of actions, such as hugging, fighting, linking arms, talking, and kidnapping in two environment such simple and complex. We show that our trained model with an active semi-supervised learning architecture gradually improves the performance. In a simple environment using an Intelligent Technology Laboratory (ITLab) dataset from Inha University, performance increased to 95.6% accuracy, and in a complex environment, performance reached 81% accuracy. Our method reduces data-labeling time, compared to supervised learning methods, for the ITLab dataset. We also conduct extensive experiment on Human Action Recognition benchmarks such as UT-Interaction dataset, HMDB51 dataset and obtain better performance than state-of-the-art approaches.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1992년도 춘계학술대회 논문집
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• pp.127-132
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• 1992

To relize the future intelligent robot the development of a special-purpose processor for a coordinate transformation is evidently challenging task. In this case the complexity of a hardware architecture strongly depends on the adopted algorithm. In this paper we have used an inverse kinemetics algorithm based on incremental unit computation method. This method considers the 3-axis articulated robot as the combination of two types of a 2-axis robot: polar robot and 2-axis planar articulated one. For each robot incremental units in the joint and Cartesian spaces are defined. With this approach the calculation of the inverse Jacobian matrix can be realized through a simple combinational logic gate. Futhermore, the incremental computation of the DDA integrator can be used to solve the direct kinematics. We have also designed a hardware architecture to implement the proposed algorithm. The architecture consists of serveral simple unitsl. The operative unit comprises several basic operators and simple data path with a small bit-length. The hardware architecture is realized byusing the EPLD. For the straight-line motion of the KAIST arm we have obtained maximum end effector's speed of 12.6 m/sec by adopting system clock of 8 MHz.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.502-507
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• 1990

The robot operation by teach playback is easy and was widely used for simple jobs performed by a simple robot manipulator. However, as robots and their control systems and tasks become more and more sophisticated, such a simple robot operation is no longer adequate and programming languages capable for the complicated systems and tasks are greatly needed. In this paper, a high-level robot-specific programming language, SAITEL, is presented. It is an interpreter, based on Assembly, and has form similar to BASIC. SAITEL is easy to use for people who are not skilled programmers, and provides the capability to define robot task very conveniently. SAITEL was implemented on a direct drive SCARA robot developed in the Samsung Advanced Institute of Technology, and proved to be very useful for the operation of SCARA-type robots. It can be used also for other types of robots by slight modification.

• 한국멀티미디어학회논문지
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• 제8권4호
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• pp.566-574
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• 2005

최근에 웹이나 가상환경에서 아바타의 활용이 점차 증가하고 있으나, 아바타의 행위를 사용자가 직접 제어하는 수준의 서비스는 이루어지지 못하고 있다. 또한 아바타의 동작 제어를 위해 제공되었던 기존의 언어들에는 일반 사용자가 언어를 작성하는데 까다로움이 많다. 따라서 본 연구에서는 아바타의 행위언어를, 작업도메인별 아바타의 행위를 작성 할 수 있는 작업 수준의 행위 표현 언어(Task-Level Behavior Description Language)와 동작과 관련된 복잡한 데이터를 포함할 수 있는 동작 표현 언어(Motion Representation Language)로 각각 정의하였고, 시스템 내에 행위표현 언어를 동작 표현 언어로 자동변환 시킬 수 있는 인터프리터를 두어 사용자가 행위 표현 언어만으로 아바타의 행위를 쉽게 제어 할 수 있는 시스템을 구성하였다. 이러한 정의를 이용하여 쇼핑몰의 작업 수준 행위 표현 언어와 동작 표현 언어를 정의하였으며, 이때 정의한 행위 표현 언어와 기존의 언어들과 비교해 보고, 본 연구에서 정의한 작업 수준의 행위 표현 언어가 아바타의 행위를 얼마나 간단히 표현할 수 있는지 검토하였다.

• 한국지구과학회지
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• 제24권6호
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• pp.495-507
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• 2003

본 연구는 정교화이론을 기초로 개발된 단순화 조건법을 적용하여 지구과학 교과의 지질연대 단원에서 지질 단면도 해석에 대한 학습자료를 개발하고 개발된 자료의 수업에서의 효과를 알아보는 것이다. 이를 위하여 고등학교 1학년 학생들을 대상으로, 단순화 조건법을 적용한 수업과 체제적 과제분석 결과를 바탕으로 개발된 자료를 적용한 수업과의 비교 실험을 실시하고 학습자의 자기주도적 학습특성과 과학성취도에 미치는 영향을 분석하였다 연구의 결과를 바탕으로 얻어진 결론으로는, 단순화 조건법을 이용한 수업은 다른 자료를 활용한 수업에 비하여 학생의 자기주도적 학습특성과 학업성취도에서 모두 긍정적인 영향을 미친 것으로 나타났다 이러한 연구의 결과는 단순화 조건법에 따라 개발된 자료를 활용한 수업에서 핵심과제(epitome)의 제시는 학생들에게 새롭고 복잡한 학습과제를 간단하고 의미 있게 하며 이를 기존의 지식들과 연결시켜주는 역할을 한 결과로 생각된다.

• 대한물리의학회지
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• 제8권2호
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• pp.281-287
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• 2013

PURPOSE: The study was designed to investigate the effects of visual, auditory, and visuoauditory cues on simple Serial Task Performance in heaithy adults. METHODS: Sixty-three right-handed heaithy adults without history of neurological dysfunction were participated. A modified version of the Serial Reaction Time Task (SRTT) using five blocks of perceptual motor sequences was administered. The blocked paradigm consisted of the five blocks with randomly repeated 8 digit sequences with 5 repetition. Three types of sensory cue were employed: visual cue, auditory cue and visuoauditory cue. All subjects were assigned to press the matched botton as quickly and accurately as possible, when one of 8 stimulations was presented(one, two, three, four, five, six, seven, eight). The reaction time, accuracy, and P300 latency were measured during serial task performance. The mean reaction time(ms), accuracy(%), and P300 latency(ms) were compared between three types of cue using ANOVA. RESULTS: The reaction time to auditory cue was significantly longer than visual and visuoauditory cues(p<.001). And accuracy to auditory cue was significantly lower than visual and visuoauditory cues(p<.001). All P300 latency(at Fz, Cz, Pz) were significantly longer than to visual and visuoauditory cues(p<.05). CONCLUSION: It is suggested that type of cues influence in choice reaction. These data may helpful in designing not only effective motor learning training programs for healthy persons but also reeducation programs for patients with neurological dysfunction.

• 정보처리학회논문지A
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• 제10A권3호
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• pp.181-188
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• 2003

본 논문에서는 IRIS(Increasing Reward with Increasing Service) 태스크들을 위한 기존 온-라인 최적 알고리즘에 근접한 총가치(total reward)를 생성하면서 보다 낮은 스케줄링 복잡도를 가진 휴리스틱(heuristic) 온-라인 스케줄링 알고리즘을 제안한다. 기존 알고리즘들은 총가치를 최대화하기 위해 시스템 내의 모든 태스크들을 스케줄링 대상으로 고려한다. 따라서 이들 알고리즘들은 많은 태스크들을 가진 실제 시스템에 적용하기에는 매우 놀은 시간 복잡도를 가진다. 제안 알고리즘은 시스템 내의 모든 태스크들을 대상으로 스케줄링하는 것이 아니라, 상수 W개의 태스크들을 선택하여 이들을 대상으로 스케줄링 한다. 제안 알고리즘은 W개의 태스크를 어떤 기준에 의해 선택할 것인가를 규정하는 테스크 선택정책에 기반을 두고 있으며, 간단하면서도 직관적인 두 가지 선택정책과 이 둘을 통합한 보다 일반화된 선택정책을 제안한다. 스케줄링 대상을 축소함으로써 제안 알고리즘의 복잡도를 O(Wn)로 줄일 수 있었다. 다양한 성능실험 결과 알고리즘 평균 계산 빈도는 O(W)에 더 가깝다는 것을 확인할 수 있었다.