• 전자통신동향분석
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• 제32권5호
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• pp.117-126
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• 2017

With the advances of high-performance, lightweight hardware components and control software, unmanned aerial vehicles (UAVs) have expanded in terms of use, not only for military applications but also for civilian applications. To complete their task at a remote location, UAVs are generally equipped with a camera, and various sensors and types of hardware devices can be attached according to the particular task. When UAVs capture video images and transmit them into the user's interface, augmented reality (AR) and virtual reality (VR) technologies as a user interface may have advantages in controlling the UAV. In this paper, we review AR and VR applications for UAVs and discuss their future directions.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1995년도 춘계공동학술대회논문집; 전남대학교; 28-29 Apr. 1995
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• pp.79-90
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• 1995

The material handling equipment selection, that is a key task in the material handling system design, is a complex, difficult task, and requires a massive technical knowledge and systematic analysis. It is invaluable to justify the selected equipment model by the performance evaluation before its actual implementation. This paper presents an intelligent knowledge-based expert system called "IMESE" created by authors, for the selection and evaluation of material handling equipment model suitable for movement and storage of materials in a manufacturing facility. The IMESE is consisted of four modules: a knowledge base to select an appropriate equipment type, a multiple criteria decision making procedure to choose the most favorable commercial model of the selected equipment type, a database to store the list of commercial models of equipment types with their specifications, and simulators to evaluate the performance of the equipment model. The whole process of IMESE is executed under VP-Expert expert system environment.vironment.

• 산업경영시스템학회지
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• 제13권22호
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• pp.71-78
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• 1990

Some problems to assess the safety of automated man-machine system are studied in many ways. The difficulty occurred in this system is the vagueness of human behavior. Fuzzy set theory is used to assess the human behavior in safety analysis. The unsafe behavior listed top 10 in accident statistics would be explained as the factors of human vagueness. Three cases are considered, which consist of man-machine system as man-man, man-machine, machine-machine types. For the design of safe task, using characteristics of work performance, each motion cycle time is required to know the rate of learning. Approach of human behavior to the standard motion means more safe motion. It is important to design the works as to minimize the time performance to the standard motion's, which utilize the control of risk potential with easy. In that process, use of fuzzy set theory is appropriate to analyze the human behavior to identify its vagueness.

• 아동학회지
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• 제22권2호
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• pp.375-390
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• 2001

본 연구는 혼잣말이 유아들의 인지적 과정에 중요한 역할을 한다는 비고츠키의 이론을 검증하는데 그 목적이 있다. 비고츠키의 혼잣말에 관한 이론을 확인하고자 하는 선행연구들은 일관된 결과를 보이지 못해 왔다. 이에 본 연구에서는 두 가지 과제해결조건, 즉 혼잣말을 억제하는 경우와 혼잣말을 격려하는 조건하에서 두 종류의 과제를 수행할 경우, 유아들의 혼잣말의 발생 빈도와 과제수행력은 어떠한 양상으로 나타나는지를 알아봄으로써 혼잣말의 인지적 기능을 확인하고자 한다. 30명의 5세 유아들을 대상으로 하여 이루어진 본 연구의 결과는 다음과 같았다. 유아들이 자발적으로 사용하는 혼잣말은 혼잣말이 적극 격려되는 조건일 때 그리고 언어적 과제유형보다는 공간-지각적 과제유형에서 더 높은 빈도로 관찰되었으며 높게 나타난 혼잣말은 공간-지각적 과제의 수행력에 긍정적인 영향을 보였다. 이는 비고츠키의 주장대로, 유아들의 혼잣말에 인지적 자기조절 기능이 있음을 지지하는 결과로 해석된다.

• 영재교육연구
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• 제5권2호
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• pp.17-36
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• 1995

The present study examined preschooler's (3-5yrs) representation and evaluation skills in a puzzle completion task. The puzzle contained panels of four children dressed for each seacon and the key to success was using a body scheme to reconstruct the panels (head, torso, legs, feet and sky on top). Baseline data (Study 1) revealed a developmental pattern of increasing bydy scheme representation along with more careful attention to season consitent construction. Spontaneous verbalization also shifted from more guiding statements (where'the head?) to move evaluative statements (this isn't right). Study 2 examined different intervention techniques for increasing representation (verbal laveling) and evaluative processes (error detection practice), along with a control group that had unassisted practice. Three year olds benefited from verbal labeling, four year olds from both types of training. Verbalizations also showed appropriated shifts toward increasing evaluation, particularly for the older children. These findings are discussed in terms of a developmental hypothesis that representation precedes evaluation skills and that training techniques should take into account the relative balance between representation and evaluation skills in the individual for the task at hand.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1993년도 춘계학술대회논문집
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• pp.41-48
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• 1993

In order to provide design concept and guidelines for the user interface of MIDAS$^{TM}$(Medical Image Display and Archiving System), a questionnire survey and empirical study were conducted. User and task requirements were analyzed based upon usrvey results. The empirical study was done on the 1.0 version of MIDAS to find out the influence of user charactenistics (i.e.job, experiences, etc.) and UI design factors(i.e. layout, wording, procedures) on various usability measures(i.e. performance, satisfaction). To perform empinical tests, eight task scenarios were selected and user interactions were recorderded using an auto-logging software. The results show that the doctor group requires more learning time. Also, eight types of user errors such as commision, omission, repeat were identified and the causes of the errors were analyzed related to UI design factors. UI design guidelines were suggested for a new version of medical image filing system.m.

• Educational Technology International
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• 제20권1호
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• pp.57-81
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• 2019

This study aimed to investigate effects of peer feedback types and feedback acceptance levels on academic achievement in project-based learning. The participants were 70 middle-school students taking an English course. They were divided into corrective and suggestive feedback groups. These participants were asked to create user-created content (UCC) as an individual task and provide peer feedback on a peer's UCC in the same type of feedback group. Results showed that there were significant differences in academic achievement according to peer feedback types (corrective vs. suggestive) and feedback acceptance levels (high vs. low). In particular, the suggestive peer feedback group had higher academic achievement than the corrective peer feedback group. Moreover, the group with a high level of feedback acceptance gained higher academic achievement than the group with a low level of feedback acceptance. Moreover, there was an interaction effect between peer feedback types and feedback acceptance on academic achievement. These results indicate that peer feedback types and feedback acceptance should be considered for effective peer feedback activity. These findings provide practical implications for the design and implementation of peer feedback activity in project-based learning.

• 한국콘텐츠학회논문지
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• 제19권11호
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• pp.1-11
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• 2019

현대 경영환경에서 팀 과업의 증가에 따른 집단성과급의 도입이 일반화되는 추세이다. 선행연구에서 집단성과급의 효과는 과업의 상호의존성에 따라 달라질 수 있다는 논의가 진행되어 왔는데, 이를 실증적으로 분석한 연구는 드물고 결과가 일관적이지 않았다. 또한, 선행연구의 과업구조가 모두 상이했다. 본 연구의 목적은 과업의 상호의존성에 따라 집단 성과급 분배 방식이 수행에 미치는 효과를 검증하는 것이었다. 이를 위해 서울소재 대학 교내 게시판 및 홈페이지를 통하여 대학생 및 대학원생, 교직원 120명을 모집하였고, 120명을 대상으로 실험을 실시하였다. 본 연구에서 사용된 실험 과제는 정해진 양식에 따라 글자, 숫자 그리고 기호를 입력하는 것이었다. 본 연구의 독립변인은 과업의 상호의존성 정도(개인과업과 상호의존과업)와 성과급 분배방식(동등분배 집단 성과급과 차등분배 집단 성과급)이었으며, 종속변인은 정확하게 입력한 문자의 수였다. 실험 설계는 2 × 2 요인설계였으며, 각 집단에 30명씩 무작위로 할당되었다. 분석은 개인차의 영향력을 최소화하기 위해 공변량 분석을 실시하였으며, 전체 회기는 공변량 분석을 위한 사전회기 1회기, 실험회기 4회기 총 5회기였으며, 각 회기는 20분으로 구성되었다. 연구 결과, 개인과업에서 차등분배 성과급과 동등분배 성과급이 수행에 미치는 효과는 거의 동일하게 나타났으나, 상호의존 과업에서는 동등분배 성과급이 차등분배 성과급보다 더 효과적으로 수행을 향상시키는 것으로 나타났다. 이는 과업의 상호의존성에 따라 집단 성과급 효과가 달라 질 수 있음을 시사하는 결과이다.

• 정보교육학회논문지
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• 제20권6호
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• pp.655-672
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• 2016

본 연구는 4C/ID 모형(Four-Components Instructional Design model)을 적용한 웹기반 학습에서 학습자의 배경지식 수준과 지원정보 제시 유형이 인지부하와 쉐마획득에 미치는 영향을 규명하는 데 있다. 이를 위하여 웹기반 수업을 설계하고 대학수업 4주 동안 166명의 대학생들을 대상으로 수업을 진행하였다. 수업 후 인지부하 자가보고식 설문지와 쉐마획득 측정을 위한 개념도를 수집하여 이원변량 분석하였다. 연구결과는 다음과 같다. 첫째, 학습자의 배경지식 수준에 따라 인지부하 점수는 유의한 차이가 있었고, 지원정보 제시 유형에서 질문 집단과 진술문 집단은 인지부하 점수가 유의한 차이가 없었다. 둘째, 학습자의 배경지식 수준에 따른 쉐마획득이 유의한 차이를 나타냈고, 질문 집단이 진술문 집단보다 쉐마획득이 유의하게 높았다. 또한 쉐마획득에서 학습자의 배경지식 수준과 지원정보 제시 유형 간 상호작용효과가 나타났다. 본 연구는 실제적 과제에서 초보 학습자의 수업 설계 및 적용에 고려할 수 있는 조건을 제시했다는 점에서 의의가 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권2호
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• pp.483-503
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• 2014

In this paper, human action recognition using pyramid histograms of oriented gradients and collaborative multi-task learning is proposed. First, we accumulate global activities and construct motion history image (MHI) for both RGB and depth channels respectively to encode the dynamics of one action in different modalities, and then different action descriptors are extracted from depth and RGB MHI to represent global textual and structural characteristics of these actions. Specially, average value in hierarchical block, GIST and pyramid histograms of oriented gradients descriptors are employed to represent human motion. To demonstrate the superiority of the proposed method, we evaluate them by KNN, SVM with linear and RBF kernels, SRC and CRC models on DHA dataset, the well-known dataset for human action recognition. Large scale experimental results show our descriptors are robust, stable and efficient, and outperform the state-of-the-art methods. In addition, we investigate the performance of our descriptors further by combining these descriptors on DHA dataset, and observe that the performances of combined descriptors are much better than just using only sole descriptor. With multimodal features, we also propose a collaborative multi-task learning method for model learning and inference based on transfer learning theory. The main contributions lie in four aspects: 1) the proposed encoding the scheme can filter the stationary part of human body and reduce noise interference; 2) different kind of features and models are assessed, and the neighbor gradients information and pyramid layers are very helpful for representing these actions; 3) The proposed model can fuse the features from different modalities regardless of the sensor types, the ranges of the value, and the dimensions of different features; 4) The latent common knowledge among different modalities can be discovered by transfer learning to boost the performance.