• 교육시설 논문지
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• 제25권4호
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• pp.19-30
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• 2018

The school classroom is a common living place where students spend 7 to 14 hours a day to prepare for their careers. Therefore, if the ventilation of the classroom is not properly performed, it may lead to the deterioration of learning ability due to the unclear air. The concentration of carbon dioxide in the classroom is reported to be high, and the increase in carbon dioxide concentration has a negative effect on the learner's academic performance. In this context, the purpose of this study is to propose a methodology for intelligent and responsive window opening-closing operation process that can reduce the concentration of $CO_2$ in the classroom in order to build a support space that can create an effective teaching-learning environment for adolescents. The specific objectives are as follows. First of all, we define the concept of window opening-closing operation. Secondly, twe develop the operation process of window opening-closing. Thirdly, we develop an algorithm for real-time window opening and closing (process) (Window Opening-Closing Operation Process). Finally, we verify the intelligent responsive window opening-closing operation process through developing examples of window opening-closing operation process using the parametric design program. This study is a preliminary study to develop algorithms necessary for window opening-closing operation. Based on the first-order algorithm, We simulated window opening-closing operations according to a hypothetical scenario. As a result, This study can show that the window is open and close depending on the $CO_2$ concentration, but the $CO_2$ concentration in the room is higher than outdoors. Consequentially, we suggest that it is necessary to develop an algorithm to supplement these results because window is often not working when the temperature difference between indoor and outdoor in winter is large.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1989년도 하계종합학술대회 논문집
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• pp.258-261
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• 1989

This paper presents a new algorithm of the operation on power distribution system by automated distribution system (ADS). A performance of this automated algorithm is established to operate the distribution system faster than earlier. We reduced the time and area of power failure by using automation algorithm on ADS.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제55권5호
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• pp.280-286
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• 2006

The paper proposes a new protection algorithm for reliable operation of grid-interfaced PV system, which can flexibly interact with conventional protective schemes of power utility grid not only to prevent damages to utility or public persons and utility apparatus caused by malfunction or failure in distribution network protection system, but also to protect a PV system itself from faults or abnormal conditions of the network. The proposed algorithm is based on reclosing characteristics of the distribution system. As a network fault occurs, the new scheme determines whether it is momentary or permanent and responds in a pre-programmed way to the fault. For permanent outage, the proposed algorithm shuts down inverter's operations but monitoring system voltage and frequency at the point of common coupling with grid. When it comes to the momentary outage, Inverter starts stand-by operation mode so that it can be automatically connected to the grid without start-up procedures as soon as the system voltage and frequency returns into the normal operation range. In order to investigate' and evaluate the PV system operation, simulation study based on PSCAD/EMTDC has been carried out to verify the performance of the proposed protection scheme.

• 대한산업공학회지
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• 제21권1호
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• pp.85-101
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• 1995

Automated Guided Vehicles(AGVs) are widely used in computer integrated manufacturing(CIM) systems for material handling purposes. Although automated guided vehicles provide higher levels of flexibility and computer integrability, the installations are limited in number and one of the critical reasons lies in the complexity involved in the operation. The main objective of this research is to alleviate this problem by proposing efficient integrated operational control methods for AGV-based CIM systems. Particularly, this research is concerned with the mixed problem of dispatching automated guided vehicles and scheduling machines operation. The proposed dynamic heuristic algorithm uses various priority schemes and relevant information concerning the load of the system, the status of queues, and the position of AGVs in the scheduling process. The scheduling decision process is hierarchical in the sense that different decision criteria are applied sequentially to identify the most appropriate part to be served. This algorithm consists of two sections, the section of part selection by AGVs for the next service whenever an AGV completes the current assignment, and the section of part selection by machines for next service whenever a machine completes the current operation. The proposed algorithm has been compared with other scheduling schemes using the performance measure of mean flow-time and mean tardiness. Simulation results indicate that the proposed algorithm can reduce the mean flow-time and mean tardiness significantly.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1416-1418
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• 1999

This paper presents a restoration method by using Dijkstra algorithm for outage restoration problems in distribution system that considering load capacity constraints and operation constraints. Restoration problem in distribution system is difficult to solve problem in a short times, because of a distribution system that supplies power for customers combined with many tie-line switches and sectionalizing switches and have to satisfy plenty of operation conditions. Therefore, this paper applied Dijkstra algorithm which is satisfy radial operation conditions in distribution system. This proposed method used Kruskal algorithm include to Dijkstra algorithm Therefore, proposed method is restored to a outage sections in a short times and just then to satisfied with a operation conditions in distribution system. A 26-bus, 31-branch model system is used to demonstrate the effectiveness of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.413-435
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• 2018

Although the accuracy of handwritten character recognition based on deep networks has been shown to be superior to that of the traditional method, the use of an overly deep network significantly increases time consumption during parameter training. For this reason, this paper took the training time and recognition accuracy into consideration and proposed a novel handwritten character recognition algorithm with newly designed network structure, which is based on an extended nonlinear kernel residual network. This network is a non-extremely deep network, and its main design is as follows:(1) Design of an unsupervised apriori algorithm for intra-class clustering, making the subsequent network training more pertinent; (2) presentation of an intermediate convolution model with a pre-processed width level of 2;(3) presentation of a composite residual structure that designs a multi-level quick link; and (4) addition of a Dropout layer after the parameter optimization. The algorithm shows superior results on MNIST and SVHN dataset, which are two character benchmark recognition datasets, and achieves better recognition accuracy and higher recognition efficiency than other deep structures with the same number of layers.

• 한국산학기술학회논문지
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• 제16권5호
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• pp.3391-3398
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• 2015

현재 대부분의 도서지역에서는 태양광발전을 효율적으로 운용하기 위하여 대용량 연축전지가 많이 사용되고 있지만, 풍력발전의 도입, 축전지 교체로 인하여 리튬이온전지의 도입이 증가하고 있다. 따라서 본 논문에서는 기존에 많이 보급되어 사용되고 있는 연축전지와 리튬이온전지의 장점을 최대한 활용하기 위하여, 연축전지와 리튬이온전지용 하이브리드 BMS 알고리즘을 제시하였다. 즉, 각 전지의 충전상태(state of charge, SOC)를 평가하는 알고리즘과 각 전지의 도입비용과 운용비용에 따른 최적 구성비를 산출하는 하이브리드 운용 알고리즘을 제안하였다. 상기의 알고리즘을 이용하여 다양한 시뮬레이션을 수행한 결과, 기존의 충전상태 평가 방법보다 오차율이 개선되어 정확한 충전상태에 대한 결과가 산출되었고, 각 전지의 도입비용과 운용비용이 최소화되는 조건에서 최적구성비를 구하여, 본 논문에서 제안한 하이브리드 BMS 알고리즘의 유용성을 확인하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.246-246
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• 2023

Multi-purpose dams are operated accounting for both physical and socioeconomic factors. This study aims to evaluate the utility of a deep learning algorithm-based model for three multi-purpose dam operation (Seomjin River dam, Juam dam, and Juam Control dam) in Seomjin River. In this study, the Gated Recurrent Unit (GRU) algorithm is applied to predict hourly water level of the dam reservoirs over 2002-2021. The hyper-parameters are optimized by the Bayesian optimization algorithm to enhance the prediction skill of the GRU model. The GRU models are set by the following cases: single dam input - single dam output (S-S), multi-dam input - single dam output (M-S), and multi-dam input - multi-dam output (M-M). Results show that the S-S cases with the local dam information have the highest accuracy above 0.8 of NSE. Results from the M-S and M-M model cases confirm that upstream dam information can bring important information for downstream dam operation prediction. The S-S models are simulated with altered outflows (-40% to +40%) to generate the simulated water level of the dam reservoir as alternative dam operational scenarios. The alternative S-S model simulations show physically inconsistent results, indicating that our deep learning algorithm-based model is not explainable for multi-purpose dam operation patterns. To better understand this limitation, we further analyze the relationship between observed water level and outflow of each dam. Results show that complexity in outflow-water level relationship causes the limited predictability of the GRU algorithm-based model. This study highlights the importance of socioeconomic factors from hidden multi-purpose dam operation processes on not only physical processes-based modeling but also aritificial intelligence modeling.

• 한국통신학회논문지
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• 제35권4A호
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• pp.315-321
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• 2010

Ad-hoc 네트워크에서는 전력을 제어할 기지국의 부재로 시스템의 성능을 최적화 시키는 중앙 전력 제어가 불가능하여, 각 노드들은 독립적이고 자동적인 방식으로 분산형 전력 제어 알고리즘을 수행해야 한다. 기존의 분산형 전력 제어 알고리즘은 수신 신호의 SINR (signal to interference and noise ratio)에 따라 MCS (modulation and coding scheme) 레벨을 변화 시키는 adaptive bit loading operation을 고려하지 않기 때문에, 전체 throughput 향상에 제한이 있다. 본 논문에서는 Ad-hoc 환경에서 전체 throughput 을 향상시키고, outage 확률을 낮추기 위해 MCS 레벨에 따라 adaptive bit loading operation을 고려한 분산형 전력 제어 알고리즘을 제안한다. 컴퓨터 모의실험 결과 매우 큰 throughput 향상과 outage 확률 감소의 성능 향상을 확인할 수 있다.

• Journal of Electrical Engineering and Technology
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• 제11권3호
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• pp.585-591
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• 2016

DOCR can be used to efficiently increase the reliability and to protect the bi-directional D/L(Distribution Lines). As more DG(Distributed Generation)s attempt to connect the bi-directional D/L, there is an increasing need for studies of how to use DOCR installed in the D/L. This paper investigates the operating principles of DOCR and presents the results an effect of sequence and fault impedance in L-L(Line to Line) fault. An advanced DOCR operating algorithm is proposed to reduce the mal-operation of conventional DOCR. The proposed algorithm is applied to the bi-directional power flow system and shows that it decreases the mal-operation of DOCR through the computer simulation.