• 한국항해항만학회지
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• 제45권3호
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• pp.148-154
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• 2021

컨테이너터미널 운영에서 안벽영역의 장비와 기술이 발전함에 따라 항만운영의 정체가 장치장으로 이전되었다. 따라서 장치장 관리가 터미널 운영 전반에 미치는 영향이 매우 커졌다. 이에 따라 컨테이너터미널 장치장 운영의 최적화를 위한 연구가 많이 수행되었으나 장래 장치장 점유율 변화 자체를 추정한 연구는 없는 실정이다. 본 연구는 부산항 신항을 대상으로 시간의 경과에 따른 확률의 변화를 설명하는 마코프 체인을 적용하여 부산항 신항 컨테이너 터미널의 장치장 점유율 수준에 대한 확률을 분석하였다. 분석결과 부산항 신항의 장치장 점유율은 향후에도 높은 수준을 유지할 확률이 큰 것으로 나타났다.

• Journal of Animal Science and Technology
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• 제65권6호
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• pp.1254-1269
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• 2023

This study aims to predict the change in corn share according to the grazing of 20 gestational sows in a mature corn field by taking images with a camera-equipped unmanned air vehicle (UAV). Deep learning based on convolutional neural networks (CNNs) has been verified for its performance in various areas. It has also demonstrated high recognition accuracy and detection time in agricultural applications such as pest and disease diagnosis and prediction. A large amount of data is required to train CNNs effectively. Still, since UAVs capture only a limited number of images, we propose a data augmentation method that can effectively increase data. And most occupancy prediction predicts occupancy by designing a CNN-based object detector for an image and counting the number of recognized objects or calculating the number of pixels occupied by an object. These methods require complex occupancy rate calculations; the accuracy depends on whether the object features of interest are visible in the image. However, in this study, CNN is not approached as a corn object detection and classification problem but as a function approximation and regression problem so that the occupancy rate of corn objects in an image can be represented as the CNN output. The proposed method effectively estimates occupancy for a limited number of cornfield photos, shows excellent prediction accuracy, and confirms the potential and scalability of deep learning.

• Journal of applied mathematics & informatics
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• 제32권1_2호
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• pp.129-136
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• 2014

One of the fundamental issues in the design of dynamic spectrum access policy is the modeling of the dynamic behavior of channel occupancy by primary users. Under a Markovian modeling of channel occupancy, a periodic sensing and greedy access policy is known as one of the simple and practical dynamic spectrum access policies in cognitive radio networks. In this paper, the primary occupancy of each channel is modeled as a discrete-time alternating renewal process with generally distributed on- and off-periods. A periodic sensing and greedy access policy is constructed based on the general channel occupancy model. Simulation results show that the proposed policy has better throughput than the policies using channel models with exponentially distributed on- or off-periods.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.900-903
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• 1996

The objective of this paper is to make the weighted graph map for path planning using the ultrasonic sensor measurements that are acquired when an A.M.R (autonomous mobile robot) explores the unknown circumstance. First, The A.M.R navigates on unknown space with wall-following and gathers the sensor data from the environments. After this, we constructs the occupancy grid map by interpreting the gathered sensor data to occupancy probability. For the path planning of roadmap method, the weighted graph map is extracted from the occupancy grid map using morphological image processing and thinning algorithm. This methods is implemented on an A.M.R having a ultrasonic sensor.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.138.4-138
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• 2001

The purpose of this research is to build a quality-improved occupancy grid map for path-planning of an autonomous mobile robot(AMR) based on the measurements from a single ultrasonic sensor, which are acquired when the autonomous mobile robot explores unknown indoor environment. The AMR navigates in the unknown space by following the wall and gathers the range data using the ultrasonic sensor, from which the occupancy grid map is constructed by associating the range data with occupancy certainties. In order to increase the quality of the map we modify the Bayesian probability updating rule, reject non-systematic measurement errors and correct the predictable error of the AMR itself. These procedures are implemented and tested using an AMR, and primary results are presented in this paper.

• 가족자원경영과 정책
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• 제9권4호
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• pp.21-40
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• 2005

The purpose of this study was to exam the activities by the distribution of time and space occupancy on their weekday and weekend. to study the space and labor segregation by sex. The sample population included 23 wives and their husbands(30-40 years old). The major findings of the research are as follows: First, it shows that wives' time use by activity was consistent with the space occupancy on weekday. Second, on weekend, wives was used to stay in living room most of time. Thirdly, husbands show the stereotype of time use on weekday, and substitute leisure time for labor time. Finally, on weekend, the wives and husbands have the joint time in the household labor or leisure activities.

• 대한안전경영과학회지
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• 제13권2호
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• pp.147-155
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• 2011

For an effective energy management in intelligent buildings it is necessary to gather information about position/absence of people and the level of population. In this paper the smart occupancy detection system based on the active RFID is developed to satisfy such a demand. The performance of the developed system is tested and verified through various experiments. Furthermore the feasibility test of the active RFID tag is performed to verify whether it can be used as a location-based occupancy sensor. The developed core technology can be also applied to other fields such as security, healthcare, smart home, etc.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.3156-3158
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• 1999

Occupancy sensor is a efficient light control system which light on/off automatically and reduces the unnecessary power waste. From now the research on occupancy sensor is restricted to the selection of the appropriate place or sensor. Exist occupancy sensor changes the delay time by manually to the place or situation, so it is unreliable. The delay time can been changed by the average time of the occupied and the preset time, but it is not enough to reliable. In this paper, so to acquire the reliance the average and the standard deviation of the occupied time change the delay time automatically and protect the malfunction from the detector. And to embody it, AT89C52 microcontroller is adopted to the control circuit. It is verified by simulation and experiment results of output characteristic for randomized input.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2021년도 하계학술대회
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• pp.151-153
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• 2021

포인트 클라우드는 특정 개체 혹은 장면을 다수의 3 차원 포인터를 사용하여 표현하는 데이터의 표현 방식 중 하나로 3D 데이터를 정밀하게 수집하고 표현할 수 있는 방법이다. 하지만 방대한 양의 데이터를 필요로 하기 때문에 효율적인 압축이 필수적이다. 이에 따라 국제 표준화 단체인 Moving Picture Experts Group 에서는 포인트 클라우드 데이터의 효율적인 압축 방법 중 하나로 Video based Point Cloud Compression(V-PCC)에 대한 표준을 제정하였다. V-PCC 는 포인트 클라우드 정보를 Occupancy, Geometry, Texture 와 같은 다수의 2D 영상으로 변환하고 각 2D 영상을 전통적인 2D 비디오 코덱을 활용하여 압축하는 방법이다. 본 논문에서는 V-PCC 에서 변환하는 Occupancy 의 정보를 활용하여 효율적으로 Texture 영상을 압축할 수 있은 방법을 소개한다. 또한 제안방법이 V-PCC 에서 약 1%의 부호화 효율을 얻을 수 있음을 보인다.

• 한국항만학회지
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• 제14권1호
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• pp.66-75
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• 2000

From the traffic analysis, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results were obtained : ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy. ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period showed 10mph decrease when compared with the 24hours'average speed, but the speed did not show a big difference in the afternoon peak period. ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge section. ⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.