• 대한안전경영과학회지
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• 제19권3호
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• pp.89-95
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• 2017

This paper presents another maintenance policy for a group of units under finite operating horizon. A group of identical units are subject to random failures. Group maintenances are performed to all units together at specified intervals, and the failed units during operation are remained idle until the next group maintenance set-up. Unlike the traditional assumption of infinite operating horizon, we adopt the assumption of the finite operating horizon which reflect the rapid industrial advance and short life cycle of modern times. The units are under operation until the end of the operating horizon. Further, the operation of units are extended to the first group maintenance time after the end of the horizon. The total cost under the proposed maintenance policy is derived. The optimal group maintenance interval and the expected number of group maintenances during the horizon are found. It is shown that the proposed policy is better than the classical group maintenance policy in terms of total cost over the operating horizon. Numerical examples are presented for illustrations.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.55-62
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• 2023

Slotted-Aloha (S-Aloha) has been widely employed in random access networks owing to its simple implementation in a distributed manner. To enhance the throughput performance of the S-Aloha, connection-based slotted-Aloha (CS-Aloha) has been proposed in recent years. The fundamental principle of the CS-Aloha is to establish a connection with a short-sized request packet before transmitting data packets. Subsequently, the connected node transmits long-sized data packets in a batch of size M. This approach efficiently reduces collisions, resulting in improved throughput compared to the S-Aloha, particularly for a large M. In this paper, we address the short-term fairness of the CS-Aloha, as quantified by Jain's fairness index. Specifically, we evaluate how equitably the CS-Aloha allocatestime slots to all nodes in the network within a finite time interval. Through simulation studies, we identify the impact of system parameters on the short-term fairness of the CS-Aloha and propose an optimal transmission probability to support short-term fairness.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제12권3호
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• pp.125-132
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• 2023

본 연구에서는 식물의 영양분 흡수에 따른 식물 성장뿐만 아니라 기공 기능 및 광합성에도 영향을 끼치는 온실의 수증기압차(VPD, Vapor Pressure Deficit)예측을 위한 머신러닝 모델들의 성능을 비교해보았다. VPD 예측을 위해 온실 내·외부 환경요소 및 시계열 데이터의 시간적 요소들과의 상관관계를 확인하고 상관관계가 높은 요소들이 VPD에 어떤 영향을 미치는지 확인하였다. 예측 모델의 성능을 분석하기 전 분석 시계열 데이터의 양(1일, 3일, 7일), 간격(20분, 1시간)이 예측 성능에 미치는 영향을 확인하여 데이터의 양과 간격을 조절하였다. 마지막으로 4개의 머신러닝 예측 모델(XGB Regressor, LGBM Regressor, Random Forest Regressor 등)을 적용하여 모델별 예측 성능을 비교했다. 모델의 예측 결과로 20분 간격의 1일의 데이터를 사용했을 때 LGBM에서 MAE는 0.008, RMSE는 0.011의 가장 높은 예측 성능을 보였다. 또한 20분 후 VPD 예측에 가장 큰 영향을 미치는 요소는 환경적 요인보다는 과거 20분 전의 VPD(VPD_y__71)임을 확인하였다. 본 연구의 결과를 활용하여 VPD 예측을 통해 작물의 생산성을 높이고, 온실의 결로, 병 발생 예방 등이 가능하다. 향후 온실의 환경 데이터 예측뿐만 아니라 더 나아가 생산량 예측, 스마트팜 제어 모델 등 다양한 분야에 활용할 수 있을 것이다.

• 한국국방경영분석학회지
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• 제18권2호
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• pp.181-191
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• 1992

In this paper in order to prevent break of operation of equipments resulted from the delay of parts supply, the continuous review(Q, r) inventory model with probabilistic lead time is developed. If the lead tire is random varivable, the cycle also is stochastic. Then it is not easy to obtain the total cost equation of this inventory model. Therefore it is assumed that one cycle is the interval of reorder points. When the lead time is assumed to have exponential probability distribution, the lot-size and reorder point which minimize total cost are obtained. And as the lead time increases, the order quantity and the total cost are greater, but the reorder point increases by a certain point of time and then decreases.

• 산업경영시스템학회지
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• 제28권2호
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• pp.146-151
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• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• 산업경영시스템학회지
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• 제28권4호
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• pp.79-84
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• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• Journal of Computing Science and Engineering
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• 제5권4호
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• pp.294-304
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• 2011

Enhancing continuous queries over data streams with temporal functions and predicates enriches the expressive power of those queries. While traditional continuous queries retrieve only the values of attributes, temporal continuous queries retrieve the valid time intervals of those values as well. Correctly evaluating such queries requires the coalescing of adjacent timestamps for value-equivalent tuples prior to evaluating temporal functions and predicates. For many stream applications, the available computing resources may be too limited to produce exact query results. These limitations are commonly addressed through load shedding and produce approximated query results. There have been many load shedding mechanisms proposed so far, but for temporal continuous queries, the presence of coalescing makes theses existing methods unsuitable. In this paper, we propose a new accuracy metric and load shedding algorithm that are suitable for temporal query processing when memory is insufficient. The accuracy metric uses a combination of the Jaccard coefficient to measure the accuracy of attribute values and $\mathcal{PQI}$ interval orders to measure the accuracy of the valid time intervals in the approximate query result. The algorithm employs a greedy strategy combining two objectives reflecting the two accuracy metrics (i.e., value and interval). In the performance study, the proposed greedy algorithm outperforms a conventional random load shedding algorithm by up to an order of magnitude in its achieved accuracy.

• 대한전자공학회논문지
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• 제16권1호
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• pp.1-8
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• 1979

비동기 디지탈 변조 시스템은 일반적으로 아날로그(analog) 신호를 시간축상에 샘플링(sampling)하지 않고 진폭축상에서 양자화하기 때문에 그 출력펄스는 보통 랜덤(random)하여 재래의 동기식 시분할 다중방식은 적용하지 못한다. 아날로그 신호를 터지탈 코오드화하게 되면 전송회로의 비직선성이나 중계기의 잡음 누적 등의 문제점이 어느 정도 해소되므로 여기에 Pierce의 다중통신 방식(1)을 적용하기로 하고 이를 실현시키는데 알맞는 디지탈 변조방식에 대해서 고찰하였다.

• 한국경영과학회지
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• 제16권1호
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• pp.13-34
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• 1991

A production/inventory system is considered in which a production facility produces one type of product. The demand for the product is given by a compound Poison process and is supplied directly from inventory when inventory is available and is lost when inventory is out of stock. The processing time to produce one item is assumes to follow a general distribution. An (s, S) policy is considered in which production stops at the instant the stock on hand reachs S and the setup of the production facility begins at an inspection point when the stock on hand drops to or below s for the first time. The time interval between two successive inspection points during a non-production period is a random variable which follows a general distribution.

• 전기전자학회논문지
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• 제26권4호
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• pp.614-621
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• 2022

본 논문은 CAN(Controller Area Network) 버스에서 해킹에 의한 공격을 탐지하기 위한 랜덤 포레스트 기반 칩입 감지 시스템(RIDS: Random Forest-Based Intrusion Detection)을 제안한다. RIDS는 CAN 버스에서 나타날 수 있는 전형적인 세 가지 공격, 즉 DoS(Denial of Service) 공격, Fuzzing 공격, Spoofing 공격을 탐지하며, 데이터 프레임 사이의 시간 간격과 그 편차, 페이로드끼리의 해밍 거리와 그 편차의 네 가지 파라미터를 사용하여 공격을 판단한다. RIDS는 메모리 중심 방식의 아키텍쳐를 가지며 노드의 정보를 메모리에 저장하여 사용하며 트리의 개수와 깊이만 조절하면 DoS 공격, Fuzzing 공격, Spoofing 공격을 모두 탐지할 수 있도록 확장이 용이한 구조로 설계되었다. 시뮬레이션 결과 RIDS는 정확도 0.9835, F1 점수 0.9545로 세 가지 공격을 효과적으로 탐지할 수 있었다.