• Aerospace Engineering and Technology
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• v.7 no.1
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• pp.161-169
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• 2008

This paper introduces test configuration and operation method for the GPS receiver system under electromagnetic test of KSLV-I upper-stage as a system qualification level and describes performance analysis of the test results. The GPS receiver system has clearly passed the electromagnetic test specifications of component level which is based on MIL-STD-461E through several design changes. Under electromagnetic test as a system qualification level, the GPS receiver system normally operates in spite of electromagnetic interferences with other systems. Performance of the GPS receiver system is also, not degraded on the condition of electromagnetic field incidence and electrostatic discharge. The KSLV-I GPS receiver system, as a result, is verified on the electromagnetic condition of the KSLV-I upper-stage.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.645-652
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• 2024

Building Information Modeling (BIM) involves the integration of equipment information and component parameters across various engineering disciplines. The complex processes during model construction can lead to human errors. Furthermore, design changes often occur at various stages of the building's lifecycle, requiring designers and modelers to make timely modifications, resulting in significant costs and time consumption. Mechanical, electrical, and plumbing (MEP) design is considerably more complex than architectural design. Therefore, this study focuses on the automatic generation of a heating, ventilation, and air conditioning (HVAC) ductwork model with MEP design through BIM. Dynamo, a visual programming language (VPL), offers features such as arrangement, connectivity, and scalability. Thus, this research applied Dynamo to develop the Automatic Ductwork BIM Model Generation System. The BIM model generated by the system facilitates collaborative efforts and enables the analysis of HVAC System Conflicts. The system extracts coordinates for air handling units, supply air, and exhaust air outlets. The equipment is automatically positioned based on these coordinates, and the corresponding duct paths are generated by reading CAD files. At each duct connection point, appropriate fittings are fabricated according to specifications and dimensions. The duct system is configured with distinct colors, and the results are visualized in Revit, facilitating HVAC system clash detection in the future. This study undertakes a real project to validate the proposed system and processes and assesses its impact on modeling efficiency, real-time responsiveness, and accuracy, realizing automated ductwork generation.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.153-169
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• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2B
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• pp.117-128
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• 2003

The network management becomes more complicated due to the growth of network technology and introduction of a large number of new multimedia services. TINA has appeared as a concept for the advanced network management system platform using the information technology such as distributed processing and object oriented modeling. Since TINA is on the basis of DPE (Distributed Processing Environment), it can manage networks and services for open telecommunications. In this paper, we propose an implementation strategy of the MIB/MIT to federate various CORBA objects in CORBA based network management system implementing TINA DPE. The proposed strategy is novel in the sense that it can support the distribution of MIB/MIT that is well matched with the distributed component architecture of TINA DPE, and it can also support the scoping and filtering services on the MIT using CORBA Naming Service.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.56.2-56.2
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• 2015

The KMTNet Supernovae Project utilizes the large $2^{\circ}{\times}2^{\circ}$ field of view of the three KMTNet telescopes to search and monitor supernovae, especially early ones, and other optical transients. A key component of the project is to build a data pipeline with a descent latency and an early alerting system that can handle the large volume of the data in an efficient and a prompt way, while minimizing false alarms, which casts a significant challenge to the software development. Here we present the current status of their development. The pipeline utilizes a difference image analysis technique to discover candidate transient sources after making correction of image distortion. In the early phase of the program, final selection of transient sources from candidates will mainly rely on multi-filter, multi-epoch and multi-site screening as well as human inspection, and an interactive web-based system is being developed for this purpose. Eventually, machine learning algorithms, based on the training set collected in the early phase, will be used to select true transient sources from candidates.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.538-561
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• 2020

Recommender Systems (RecSys) have a major role in e-commerce for recommending products, which they may like for every user and thus improve their business aspects. Although many types of RecSyss are there in the research field, the state of the art RecSys has focused on finding the user similarity based on sequence (e.g. purchase history, movie-watching history) analyzing and prediction techniques like Recurrent Neural Network in Deep learning. That is RecSys has considered as a sequence prediction problem. However, evaluation of similarities among the customers is challenging while considering temporal aspects, context and multi-component ratings of the item-records in the customer sequences. For addressing this issue, we are proposing a Deep Learning based model which learns customer similarity directly from the sequence to sequence similarity as well as item to item similarity by considering all features of the item, contexts, and rating components using Dynamic Temporal Warping(DTW) distance measure for dynamic temporal matching and 2D-GRU (Two Dimensional-Gated Recurrent Unit) architecture. This will overcome the limitation of non-linearity in the time dimension while measuring the similarity, and the find patterns more accurately and speedily from temporal and spatial contexts. Experiment on the real world movie data set LDOS-CoMoDa demonstrates the efficacy and promising utility of the proposed personalized RecSys architecture.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.10a
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• pp.24-29
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• 2003

Deep sea water has cold temperature, abundant nutrients and minerals, and good water quality that is pathogen-free and stable. Compared with surface water, deep sea water contains more nutrition salt, such as nitrogen and phosphor. Moreover, if has the good balance of minerals. Because of the ability of the spray drying process to produce a free-flowing power considering of spherical particles with a well-defined size distribution and the rapid drying times for heat-sensitive material, spray drying is attractive for a wide range of applications spray drying is a unique unit operation in which powders are produced from a liquid feed in a single processing step. Key component of the process are atomizer, spray chamber. Design of spray chamber should be based on the atomizer type, the production rate, and the particle size required. Because of the complex processes taking place during spray drying, traditional design method are based on pilot-plant tests and empirical scale-up rules. Modern technique such as CFD have a role to play in design and troubleshooting.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.9
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• pp.1531-1540
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• 2016

In this paper, we propose vehicle license plate recognition system based on Radial Basis Function Neural Networks (RBFNNs) with the use of local binarization functions and canny edge algorithm. In order to detect the area of license plate and also recognize license plate numbers, binary images are generated by using local binarization methods, which consider local brightness, and canny edge detection. The generated binary images provide information related to the size and the position of license plate. Additionally, image warping is used to compensate the distortion of images obtained from the side. After extracting license plate numbers, the dimensionality of number images is reduced through Principal Component Analysis (PCA) and is used as input variables to RBFNNs. Particle Swarm Optimization (PSO) algorithm is used to optimize a number of essential parameters needed to improve the accuracy of RBFNNs. Those optimized parameters include the number of clusters and the fuzzification coefficient used in the FCM algorithm, and the orders of polynomial of networks. Image data sets are obtained by changing the distance between stationary vehicle and camera and then used to evaluate the performance of the proposed system.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1432-1440
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• 2015

A dynamic economic dispatch and control method is proposed to minimize the overall generating cost for a stand-alone microgrid in DongAo Island, which is integrated with wind turbine generator, solar PV, diesel generator, battery storage, the seawater desalination system and the conventional loads. A new dispatching strategy is presented based on the ranking of component generation costs and two different control modes, in which diesel generator and battery storage alternate to act as the master power source to follow system power fluctuation. The optimal models and GA-based optimization process are given to minimize the overall system generating cost subject to the corresponding constraints and the proposed dispatch strategy. The effectiveness of the proposed method is verified in the stand-alone microgrid in DongAo Island, and the results provide a feasible theoretical and technical basis for optimal energy management and operation control of stand-alone microgrid.