• The Journal of Bigdata
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• v.9 no.1
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• pp.153-168
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• 2024

In summer, as chillers are considered the main energy consumer of building, the efficient chiller operation is considered important. However, it is difficult to operate chillers to meet the cooling demand of the building as the demand fluctuates with various factors like the internal, external environment and behavior of the occupants and as chiller's constraint cause the current operation constrains operation in future. To address these problems, this study proposes a multi-chiller operation model based on deep reinforcement learning considering the minimum up-time of the chiller. The proposed model learns the value of the chiller operations according to the state composed of metrological and cooling system information and determines operation that minimizes the difference between the supply load and the cooling demand among feasible operations. The practical applicability was improved by applying the training algorithm considering the minimum up-time constraint and Experiments results using the actual data from a Korean university confirmed that the proposed model complies with the chiller constraints and outperforms the existing chiller operation logic of the university in terms of differences from the building cooling demand.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.5
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• pp.285-294
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• 2024

Seismic fragility curves present the conditional probability of damage to target structures due to external seismic load and are widely used in various ways. When constructing such a seismic fragility curve, it is essential to consider various types and numbers of ground motions. In general, the earthquake occurrence characteristics of an area where the target structure of the seismic fragility curve exists are analyzed, and based on this, appropriate ground motions are selected to derive the seismic fragility curve. If the number of selected ground motions is large, the diversity of ground motions is considered, but a large amount of computational time is required. Conversely, if the number of ground motions is too small, the diversity of ground motions cannot be considered, which may distort the seismic fragility curve. Therefore, this study analyzed the relationship between the number of ground motions considered when deriving the seismic fragility curve and the parameters of the seismic fragility curve. Using two example structures, numerical analysis was performed by selecting a random number of ground motions from a total of two hundred, and a seismic fragility curve was derived based on the results. Analysis of the relationship of the parameter of the seismic fragility curve and the number of selected ground motions was performed. As the number of ground motions considered increases, uncertainty in ground motion selection decreases, and when deriving seismic fragility curves considering the same number of ground motions, uncertainty increases relatively as the degree of freedom of the target structure increases. However, considering a relatively large number of ground motions, uncertainty appeared insignificant regardless of increased degrees of freedom. Finally, it is possible that the increase in the number of ground motions could lower the epistemic uncertainty and thus improve the reliability of the results.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.213-226
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• 2011

In global supply chain, the scheduling problems of large products such as ships, airplanes, space shuttles, assembled constructions, and/or automobiles are complicated by nature. New scheduling systems are often developed in order to reduce inherent computational complexity. As a result, a problem can be decomposed into small sub-problems, problems that contain independently small scheduling systems integrating into the initial problem. As one of the authors experienced, DAS (Daewoo Shipbuilding Scheduling System) has adopted a two-layered hierarchical architecture. In the hierarchical architecture, individual scheduling systems composed of a high-level dock scheduler, DAS-ERECT and low-level assembly plant schedulers, DAS-PBS, DAS-3DS, DAS-NPS, and DAS-A7 try to search the best schedules under their own constraints. Moreover, the steep growth of communication technology and logistics enables it to introduce distributed multi-nation production plants by which different parts are produced by designated plants. Therefore vertical and lateral coordination among decomposed scheduling systems is necessary. No standard coordination mechanism of multiple scheduling systems exists, even though there are various scheduling systems existing in the area of scheduling research. Previous research regarding the coordination mechanism has mainly focused on external conversation without capacity model. Prior research has heavily focuses on agent-based coordination in the area of agent research. Yet, no scheduling domain has been developed. Previous research regarding the agent-based scheduling has paid its ample attention to internal coordination of scheduling process, a process that has not been efficient. In this study, we suggest a general framework for agent-based coordination of multiple scheduling systems in global supply chain. The purpose of this study was to design a standard coordination mechanism. To do so, we first define an individual scheduling agent responsible for their own plants and a meta-level coordination agent involved with each individual scheduling agent. We then suggest variables and values describing the individual scheduling agent and meta-level coordination agent. These variables and values are represented by Backus-Naur Form. Second, we suggest scheduling agent communication protocols for each scheduling agent topology classified into the system architectures, existence or nonexistence of coordinator, and directions of coordination. If there was a coordinating agent, an individual scheduling agent could communicate with another individual agent indirectly through the coordinator. On the other hand, if there was not any coordinating agent existing, an individual scheduling agent should communicate with another individual agent directly. To apply agent communication language specifically to the scheduling coordination domain, we had to additionally define an inner language, a language that suitably expresses scheduling coordination. A scheduling agent communication language is devised for the communication among agents independent of domain. We adopt three message layers which are ACL layer, scheduling coordination layer, and industry-specific layer. The ACL layer is a domain independent outer language layer. The scheduling coordination layer has terms necessary for scheduling coordination. The industry-specific layer expresses the industry specification. Third, in order to improve the efficiency of communication among scheduling agents and avoid possible infinite loops, we suggest a look-ahead load balancing model which supports to monitor participating agents and to analyze the status of the agents. To build the look-ahead load balancing model, the status of participating agents should be monitored. Most of all, the amount of sharing information should be considered. If complete information is collected, updating and maintenance cost of sharing information will be increasing although the frequency of communication will be decreasing. Therefore the level of detail and updating period of sharing information should be decided contingently. By means of this standard coordination mechanism, we can easily model coordination processes of multiple scheduling systems into supply chain. Finally, we apply this mechanism to shipbuilding domain and develop a prototype system which consists of a dock-scheduling agent, four assembly- plant-scheduling agents, and a meta-level coordination agent. A series of experiments using the real world data are used to empirically examine this mechanism. The results of this study show that the effect of agent-based platform on coordinated scheduling is evident in terms of the number of tardy jobs, tardiness, and makespan.

• Journal of agriculture & life science
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• v.45 no.5
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• pp.105-113
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• 2011

This study was carried out to develop an automatic loading equipment that can load seedling trays on loading position of the seedling bed driving on enclosed-type rail installed for interconnecting each process of raising seedlings in plant factory. The experiment of transferring the seedling tray by monorail pusher was carried out to figure out the required transfer force and problems during push type device of transporting the plastic seedling trays, that has completed its sowing process, which are installed onto the board of different materials. From the results of this experiment, the loading equipment which can exactly load three of the seedling trays orderly on the loading position of the seedling bed was designed and made. When three sowed trays on every board are transferred by pusher with the speed is at 30 cm/s, the maximum peak transfer force with maximum overshooting at initial transient state and the maximum transfer force at stead state are were respectively 32.8 N, 29.4 N on rubber board, 29.7 N, 22.5 N on a wooden board, 26.9 N, 19.6 N on a acrylic board, and 27.6 N, 19.1 N on an iron board. Changes in the transfer force occurred its maximum at the moment when the pusher collided with the tray, after the collision gradually decreased until it became stable. When two or three trays placed it in order of widthwise are transferred, it is occurred the overlapping of the tray's external bracket. The developed automatic loading equipment with PLC controller did not make any operation error through 100 times of tests, its maximum seedling tray loading speed was 2 sec/tray and its maximum error of transferred location of the tray was 0.5 cm.

• Membrane Journal
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• v.22 no.2
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• pp.95-103
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• 2012

To treat nitrate and non-biodegradable organics effectively in sewage, industrial wastewater and livestock wastewater, the activated sludge process integrated by a membrane separation and a porous electrode- electrolysis was proposed and its efficiency was investigated. The proposed system was consisted of 3 processes; activated sludge, membrane filtration and electrolysis. In the study, the membrane filtration played a role in reducing the load of the electrolysis to operate the proposed process stably. The electrolysis consisted of a porous electrode to increase the efficiency due to the extension of the specific surface area. Additionally, redox reaction in the electrolysis was induced by decomposing influent water as current was applied. As a result, hydrogen free radicals and oxygen radicals as intermediates were produced and they acted as oxidants to play a role in decomposing non-degradable organics. It was environmentally-friendly process because intermediates produced by porous electrode were used to treat waste matters without supplying external reagent. Experimental data showed that the proposed process was more excellent than activated sludge process. SS removal efficiencies of the proposed process, membrane filtration and activated sludge process were about 100%, about 100% and about 90%, respectively. COD removal efficiencies of the proposed system, membrane filtration and activated sludge process were about 92%, about 84% and about 78%, respectively. T-N removal efficiencies of the proposed system, membrane filtration and activated sludge process were about 88%, about 67%, and about 58%, respectively. The SS data showed that SS was efficiently removed in the single of the membrane filtration. The COD/T-N data showed that COD/T-N of membrane hybrid process was treated by removing a little soluble organics and SS, and that COD/T-N of electrolysis hybrid process was treated by oxidize organics with high removal rate.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Journal of Environmental Impact Assessment
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• v.26 no.6
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• pp.553-562
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• 2017

In these days, agricultural reservoirs are considered as a useful resource for recreational purposes, tour and cultural amenity for vicinity communities as well as irrigation water supply. However, many of the agricultural reservoirs are showing a eutrophic or hyper-eutrophic state and high level of organic contamination. In particular, about 44.7% of the aged agricultural reservoirs that constructed before 1945 exceed the water quality criteria for irrigational water use. In addition to external loading, internal nutrient loading from bottom sediment may play an important role in the nutrient budget of the aged reservoirs. The objectives of this study were to characterize variations of thermal structure of a shallow M reservoir (mean depth 1.7 m) and examine the potential of internal nutrient loading by continuous monitoring of vertical water temperature and dissolved oxygen (DO) concentration profiles in 2015 and 2016. The effect of internal loading on the total loading of the reservoir was evaluated by mass balance analysis. Results showed that a weak thermal stratification and a strong DO stratification were developed in the shallow M Reservoir. And, dynamic temporal variation in DO was observed at the bottom of the reservoir. Persistent hypoxic conditions (DO concentrations less than 2 mg/L) were established for 87 days and 98 days in 2015 and 2016, respectively, during the no-rainy summer periods. The DO concentrations intermittently increased during several events of atmospheric temperature drop and rainfall. According to the mass balance analysis, the amount of internal $PO_4-P$ loading from sediment to the overlying water were 37.9% and 39.7% of total loading during no-rainy season in 2015 and 2016, respectively on August when algae growth is enhanced with increasing water temperature. Consequently, supply of DO to the lower layer of the reservoir could be effective countermeasure to reduce nutrient release under the condition of persistent DO depletion in the bottom of the reservoir.

• The Journal of Korean Academy of Prosthodontics
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• v.53 no.4
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• pp.345-351
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• 2015

Purpose: The purpose of this study was to evaluate the proper axial thickness of zirconia abutment applied to implant in the anterior region. Materials and methods: Zirconia abutments were prepared at different axial wall thickness by processing pre-sintered zirconia blocks via CAD/CAM to obtain equal specimens. The abutments were each produced with a thickness of 0.5 mm (Group 1), 0.8 mm (Group 2), 1.2 mm (Group 3), or 1.5 mm (Group 4). The implant used in this study was a external connection type one (US, Osstem, Pussan, Korea) product and the zirconia abutment was prepared via replication of a cemented abutment. The crowns were prepared via CAM/CAM with a thickness of 1.5 mm and were cemented to the abutments using $RelyX^{TM}$ UniCem cement. A universal testing machine was used to apply load at 30 degrees and measure fracture strength of the zirconia abutment. Results: Fracture strength of the abutments for Group 1, Group 2, Group 3, and Group 4 were $236.00{\pm}67.55N$, $599.00{\pm}15.80N$, $588.20{\pm}33.18N$, and $97.83{\pm}98.13N$, respectively. Group 1 showed a significantly lower value, as compared to the other groups (independent Mann-Whitney U-test. P<.05). No significant differences were detected among Group 2, Group 3, and Group 4 (independent Mann-Whitney U-test. P>.05). Conclusion: Zirconia abutment requires optimal thickness for fracture resistance. Within the limitation of this study, > 0.8 mm thickness is recommended for zirconia abutment in anterior implants.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.485-496
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• 2022

Modern agriculture is being transformed into smart agriculture to maximize production efficiency along with changes in the 4th industrial revolution. However, rural areas in Korea are facing challenges of aging, low fertility, and population outflow, making it difficult to transition to smart agriculture. Among ICT technologies, simulation allows users to observe or experience the results of their choices through imitation or reproduction of reality. The combination of the three-dimension (3D) model and the greenhouse simulator enable a 3D experience by virtual greenhouse for fruits and vegetable cultivation. At the same time, it is possible to visualize the greenhouse under various cultivation or climate conditions. The objective of this study is to apply the greenhouse climate management model for simulation development that can visually see the state of the greenhouse environment under various micrometeorological properties. The numerical solution with the mathematical model provided a dynamic change in the greenhouse environment for a particular greenhouse design. Light intensity, crop transpiration, heating load, ventilation rate, the optimal amount of CO₂ enrichment, and daily light integral were calculated with the simulation. The results of this study are being built so that users can be linked through a web page, and software will be designed to reflect the characteristics of cladding materials and greenhouses, cultivation types, and the condition of environmental control facilities for customized environmental control. In addition, environmental information obtained from external meteorological data, as well as recommended standards and set points for each growth stage based on experiments and research, will be provided as optimal environmental factors. This simulation can help growers, students, and researchers to understand the ICT technologies and the changes in the greenhouse microclimate according to the growing conditions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5A
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• pp.557-564
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• 2009

In recent years, there have been numerous explosion-related accidents due to military and terrorist activities. Such incidents caused not only damages to structures but also human casualties, especially in urban areas. To protect structures and save human lives against explosion accidents, better understanding of the explosion effect on structures is needed. In an explosion, the blast overpressure is applied to concrete structures as an impulsive load of extremely short duration with very high pressure and heat. Generally, concrete is known to have a relatively high blast resistance compared to other construction materials. However, information and test results related to the blast experiment of internal and external have been limited due to military and national security reasons. Therefore, in this paper, to evaluate blast effect on reinforced have concrete structure and its protective performance, blast tests are carried out with $1.0m{\times}1.0m{\times}150mm$ reinforce concrete slab structure at the Agency for Defence Development. The standoff blast distance is 1.5 m and the preliminary tests consists with TNT 9 lbs and TNT 35 lbs and the main tests used ANFO 35 lbs. It is the first ever blast experiment for nonmilitary purposes domestically. In this paper, based on the basic experiment procedure and measurement details for acquiring structural behavior data, the blast experimental measurement system and procedure are established details. The procedure of blast experiments are based on the established measurement system which consists of sensor, signal conditioner, DAQ system, software. It can be used as basic research references for related research areas, which include protective design and effective behavior measurements of structure under blast loading.