• 한국컴퓨터정보학회논문지
• /
• 제27권11호
• /
• pp.165-172
• /
• 2022

본 논문에서는 발달 장애 학생이 가상현실 콘텐츠로 직업 훈련을 수행하는 중에 콘텐츠가 부여한 과제를 이해하지 못하여 더 이상의 훈련을 진행하지 못하고 현재의 상태에 머물러 있는 상황이 발생했을 때 문제의 상태에서 스스로 벗어나서 훈련을 진행할 수 있도록 도움을 주는 행위, 즉 중재의 제공이 필요한 시점을 파악하는 방안을 연구하였다. 이를 위해, 선행 연구의 결과를 토대로 가상현실 기반의 바리스타 훈련을 수행할 수 있는 콘텐츠를 이용하여 커피 제조를 교육하는 과정에서 주어진 과제를 성공적으로 완수하기 위해 발달 장애 학생이 반드시 조작하여야 하는 바리스타 도구를 선정하고, 해당 도구와 발달 장애 학생의 왼손과 오른손과의 거리를 측정하여 통계적 분석을 통해 가설을 검증하였다. 손으로부터 관심 바리스타 도구 및 인접 도구들까지의 누적거리가 다른 바리스타 도구까지의 누적거리보다 상대적으로 긴 것으로 분석된 연구 대상자는 관심 바리스타 도구를 사용하고 있지 않을 확률이 크므로 해당 과제를 제대로 수행하고 있지 않다고 인식하고 중재를 제공할 시점이라고 판단할 수 있기 때문이다. 검증 결과, 왼손의 경우는 학생들의 훈련 수행의 성공 또는 실패 여부와 손과 바리스타 도구와의 거리간의 관계는 통계적으로 유의미하지 않은 것으로 분석되었으나, 오른손의 경우는 유의미하였다.

• 한국산학기술학회논문지
• /
• 제11권4호
• /
• pp.1411-1418
• /
• 2010

이러닝을 활용한 원격교육은 평생교육의 측면에서 교육의 내용과 방법에 대한 선택의 다양성을 제공하고 있다. 양질의 콘텐츠와 이를 운영하는 학습관리시스템의 효과적 운영은 원격교육의 효과성을 높이는 중요한 요인이라 할 수 있다. 이에 본 연구는 원격교육의 질을 높이는 데 필요한 학습관리시스템의 현황을 분석하였다. 현황 분석과 함께 원격교육의 학습관리시스템 기능에 대해 델파이를 통해 전문가의 의견을 수렴하였다. 전문가 의견 수렴을 토대로 본 연구는 원격교육의 효과성을 높일 수 있는 학습관리시스템에 필요한 기능을 제안하였다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.2037-2040
• /
• 2004

In this paper we introduce a new prototype based classifiers for overlapping data, where training pattern can be overlap on the feature space. The proposed classifier is based on the prototype from neural network classifier (NNC)[1] for overlap data. The method automatically chooses the initial center and two radiuses for each class. The center is used as a mean representative of training data for each class. The unclassified pattern is classified by measure distance from the class center. If the distance is in the lower (shorter radius) the unknown pattern has the high percentage of being in this class. If the distance is between the lower and upper (further radius), the pattern has the probability of being in this class or others. But if the distance is outside the upper, the pattern is not in this class. We borrow the words upper and lower from the rough set to represent the region of certainty [3]. The training algorithm to find number of cluster and their parameters (center, lower, upper) is presented. The clustering result is tested using patterns from Thai handwritten letter and the clustering result is very similar to human eyes clustering.

• 한국음향학회지
• /
• 제14권1호
• /
• pp.5-12
• /
• 1995

Training 벡터 집합이 Cluster를 이루는 경우, 벡터 양자화에서 영상과 음성의 압축에 사용되는 코드북의 코드벡터는 Cluster의 중심벡터로 간주된다. 본 연구에서는 Training 벡터 간의 Euclidean 거리가 최소가 되는 벡터를 찾는 과정에서 얻어지는 Euclidean 거리분포를 관찰하여 적절한 Cluster수와 그 중심벡터를 결정할 수 있는 방법을 제시하고, 제안된 방법이 기존의 LBG 알고리즘이나 Competitive 학습 알고리즘에 의한 영상 압축보다 약 4[dB] 이상 향상된 SNR을 얻을 수 있음을 보인다.

• 국제물리치료학회지
• /
• 제7권1호
• /
• pp.965-971
• /
• 2016

The purpose of this study was to investigate the effects of core strengthening training on baseball throwing. A total of 14 subjects were recruited from among middle school baseball players. The main outcome measures were as follows: speed guns were used to measure the velocity of baseballs thrown; scored targets were used to measure throwing accuracy; and 50m measuring tapes were used to measure throwing distances. It was found that core strengthening training improved the velocity of baseballs thrown and throwing accuracy and distance. Thus, core strengthening training is effective for improving the throwing ability of baseball players.

• 대한임베디드공학회논문지
• /
• 제17권5호
• /
• pp.289-296
• /
• 2022

In this paper, we developed a deep learning-based recyclable object detection model. The model is developed based on YOLOv5 that is a one-stage detector. The deep learning model detects and classifies the recyclable object into 7 categories: paper, carton, can, glass, pet, plastic, and vinyl. We propose two methods for recyclable object detection models to solve problems during training. Bounding Box CutMix solved the no-objects training images problem of Mosaic, a data augmentation used in YOLOv5. Standardized Distance-based IoU replaced DIoU using a normalization factor that is not affected by the center point distance of the bounding boxes. The recyclable object detection model showed a final mAP performance of 0.91978 with Bounding Box CutMix and 0.91149 with Standardized Distance-based IoU.

• International Journal of Computer Science & Network Security
• /
• 제23권2호
• /
• pp.152-163
• /
• 2023

This research aimed at investigating Islamic Studies teachers' attitudes towards utilizing virtual learning environment in distance teaching among primary stage pupils. It also aimed at determining the statistical differences among variables due to sex, educational qualification, number of years of experience, and training sessions. This research adopted the descriptive approach. The sample consisted of male and female primary teachers of Islamic Studies (N=250) in governmental schools in Taif. The questionnaire was used as a main research tool. It included (20) items. Results showed that Islamic Studies teachers' attitudes towards utilizing virtual learning environment in distance teaching among primary stage pupils were ranked to a medium degree. There was a statistically significant difference among primary Islamic Studies teachers' attitudes due to sex variable. It was recommended to adopt more training sessions and seminars for adopting the idea of utilizing virtual learning environments among Islamic Studies teachers at boys' and girls' school in Mecca through emphasizing its significance and benefits in Teaching.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.154.2-154
• /
• 2001

This paper presented a adaptation approach based on maximum model distance (MMD) method. This method shares the same framework as they are used for training speech recognizers with abundant training data. The MMD method could adapt to all the models with or without adaptation data. If large amount of adaptation data is available, these methods could gradually approximate the speaker-dependent ones. The approach is evaluated through the phoneme recognition task on the TIMIT corpus. On the speaker adaptation experiments, up to 65.55% phoneme error reduction is achieved. The MMD could reduce phoneme error by 16.91% even when ...

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.99.1-99
• /
• 2001

This paper presented an adaptation approach based on maximum model distance (MMD) method. This method shares the same framework as they are used for training speech recognizers with abundant training data. The MMD method could adapt to all the models with or without adaptation data. If large amount of adaptation data is available, these methods could gradually approximate the speaker-dependent ones. The approach is evaluated through the phoneme recognition task on the TIMIT corpus. On the speaker adaptation experiments, up to 65.55% phoneme error reduction is achieved. The MMD could reduce phoneme error by 16.91% even when only one adaptation utterance is used.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
• /
• pp.325-328
• /
• 2003

In this paper, we tried to develop a vowel training assistant method using vowel formant statistics. Formant statistics were obtained from PBW set consists of 452 words from 8 persons. Then, we calculated distance from input formants to each center of vowel formant space. Based on the distance, directions to correct the speaker's manner of articulation, i.e. position of jaw and tongue.