• Steel and Composite Structures
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• v.52 no.6
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• pp.647-656
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• 2024

This paper discusses the study of concrete composite walls of algorithmic modeling, in which steel tubes are embedded. The load-bearing capacity of STHC composite walls increases with the increase of axial load coefficient, but its ductility decreases. The load-bearing capacity can be improved by increasing the strength of the steel pipes; however, the elasticity of STHC composite walls was found to be slightly reduced. As the shear stress coefficient increases, the load-bearing capacity of STHC composite walls decreases significantly, while the deformation resistance increases. By analyzing actual cases, we demonstrate the effectiveness of the research results in real situations and enhance the persuasiveness of the conclusions. The research results can provide a basis for future research, inspire more explorations on seismic design and construction, and further advance the development of this field. Emphasize the importance of research results, promote interdisciplinary cooperation in the fields of structural engineering, earthquake engineering, and materials science, and improve overall seismic resistance. The emphasis on these aspects will help highlight the practical impact of the research results, further strengthen the conclusions, and promote progress in the design and construction of earthquake-resistant structures. The goals of this work are access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient architecture, sustainable planning and management of human settlements. Simulation results of linear and nonlinear structures show that this method can detect structural parameters and their changes due to damage and unknown disturbances. Therefore, it is believed that with the further development of fuzzy neural network artificial intelligence theory, this goal will be achieved in the near future.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.5
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• pp.44-58
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• 2018

Cities face new challenges not only in natural disasters by climate change but also in social and economic fluctuations. With the existing simple reconstruction method, it is difficult to solve the overall problems that a city or region may face. As a new approach to cope with various changes, the concept of resilience is emerging. Resilience is also one of the themes of recent major urban design projects. Design with the concept of resilience is a new strategy that can deal with various changes of urban space, rather than a temporary trend. The purpose of this paper is to explore the design method by analyzing cases where the concept of resilience is employed. We aim to examine what kind of design strategies are needed for the resilience design and how this design process differ in character, as compared to general design projects. Cases for this study include the "Rebuild by Design" competition held in 2013 and the "Resilient by Design/Bay Area Challenge" competition held in 2017. This paper consists of literature reviews and case studies. The latter is divided into two aspects: content analysis based on the theory of resilience and characteristics of the design process. Cases are analyzed through literature reviews and process characteristics of resilience design in response to the general design process. The main categories for urban resilience used as the framework for analysis include: Urban Infrastructure, Social Dynamics, Economic Dynamics, Health and Wellbeing, Governance Networks, and Planning and Institutions. As a result, the aspects of resilience concepts considered and design strategies undertaken by each team were identified. Each team tried to connect all 6 categories to their design strategies, placing special value on the role of governance, a system that enables collaborative design and project persistency. In terms of the design process, the following characteristics were found: planning the whole project process in the pre-project phase, analyzing predictable socioeconomic risk factors in addition to physical vulnerabilities, aiming for landscape-oriented integrated design, and sustainable implementation strategies with specific operations and budget plans. This paper is meaningful to connect the concept of resilience, which has been discussed in various articles, to design strategy, and to explore the possibility of constructing a practical methodology by deriving the characteristics of the resilience design process. It remains a future task to research design strategies that apply the concept of resilience to various types of urban spaces, in addition to areas that are vulnerable to disasters.

• The Journal of Society for e-Business Studies
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• v.25 no.2
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• pp.15-27
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• 2020

This study starts with the idea that the process of creating a Gantt Chart for schedule planning is similar to Tetris game with only a straight line. In Tetris games, the X axis is M machines and the Y axis is time. It is assumed that all types of orders can be worked without separation in all machines, but if the types of orders are different, setup cost will be incurred without delay. In this study, the game described above was named Gantris and the game environment was implemented. The AI-scheduling table through in-depth reinforcement learning compares the real-time scheduling table with the human-made game schedule. In the comparative study, the learning environment was studied in single order list learning environment and random order list learning environment. The two systems to be compared in this study are four machines (Machine)-two types of system (4M2T) and ten machines-six types of system (10M6T). As a performance indicator of the generated schedule, a weighted sum of setup cost, makespan and idle time in processing 100 orders were scheduled. As a result of the comparative study, in 4M2T system, regardless of the learning environment, the learned system generated schedule plan with better performance index than the experimenter. In the case of 10M6T system, the AI system generated a schedule of better performance indicators than the experimenter in a single learning environment, but showed a bad performance index than the experimenter in random learning environment. However, in comparing the number of job changes, the learning system showed better results than those of the 4M2T and 10M6T, showing excellent scheduling performance.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2280-2288
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• 1997

An agent is a software element that, by making use of knowledge and inference, performs tasks on behalf of the user. In general, an agent has the properties of autonomy, social ability, reactivity, and durability. Many researches on agents are more and more aiming at the multiagent systems since it is not sufficient to let a single agent do the whole things, especially in a real world where tasks require many diverse activities. However, the multiagent frameworks still have some limitations in the processing of user queries that are often ambiguous and goal-oriented. Also, a series of procedures or plans could not be generated from a single query directly. In order to give more intelligence to the multiagent framework, we propose a method of extending the framework with a plan generation module. The open agent architecture (OAA), which is a multiagent framework that we developed, is integrated with UCPOP, which is a AI planner. A travel schedule management agent (TSMA) system is implemented to explore the effects of the method. The extended system enables the user to only specify goal-oriented queries, and the plans and procedures to satisfy these goals are generated automatically. Also, this system provides a cooperative and knowledge-sharing environment that integrates several knowledge-based systems and planning systems that are distributed and used independently.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2243-2248
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• 2013

Background: To compare the dosimetric coverage of target volumes and organs at risk in the radical treatment of nasopharyngeal carcinoma (NPC) between intensity-modulated radiotherapy (IMRT) and three-dimensional conformal radiotherapy (3DCRT). Materials and Methods: Data from 10 consecutive patients treated with IMRT from June-October 2011 in Penang General Hospital were collected retrospectively for analysis. For each patient, dose volume histograms were generated for both the IMRT and 3DCRT plans using a total dose of 70Gy. Comparison of the plans was accomplished by comparing the target volume coverage (5 measures) and sparing of organs at risk (17 organs) for each patient using both IMRT and 3DCRT. The means of each comparison target volume coverage measures and organs at risk measures were obtained and tested for statistical significance using the paired Student t-test. Results: All 5 measures for target volume coverage showed marked dosimetric superiority of IMRT over 3DCRT. V70 and V66.5 for PTV70 showed an absolute improvement of 39.3% and 24.1% respectively. V59.4 and V56.4 for PTV59.4 showed advantages of 18.4% and 16.4%. Moreover, the mean PTV70 dose revealed a 5.1 Gy higher dose with IMRT. Only 4 out of 17 organs at risk showed statistically significant difference in their means which were clinically meaningful between the IMRT and 3DCRT techniques. IMRT was superior in sparing the spinal cord (less 5.8Gy), V30 of right parotid (less 14.3%) and V30 of the left parotid (less 13.1%). The V55 of the left cochlea was lower with 3DCRT (less 44.3%). Conclusions: IMRT is superior to 3DCRT due to its dosimetric advantage in target volume coverage while delivering acceptable doses to organs at risk. A total dose of 70Gy with IMRT should be considered as a standard of care for radical treatment of NPC.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.323-330
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• 2016

Communication, Ocean and Meteorological Satellite (COMS) was launched in 2010 with three payloads that include Ka-band communication payload developed by Ministry of Science, ICT and Future Planning (MSIP) and Electronics and Telecommunications Research Institute (ETRI). This study introduces a real-time remote vessel monitoring system built in the Socheongcho Ocean Research Station using the Ka-band communication satellite. The system is composed of three steps; real-time data collection, transmission, and processing/visualization. We describe hardware (H/W) and software systems (S/W) installed to perform each step and the whole procedure that made the raw data become vessel information for a real-time ocean surveillance. In addition, we address functional requirements of H/W and S/W and the important considerations for successful operation of the system. The system is now successfully providing, in near real-time, ship information over a VHF range using AIS data collected in the station. The system is expected to support a rapid and effective surveillance over a huge oceanic area. We hope that the concept of the system can be fully used for real-time maritime surveillance using communication satellite in future.

• Ecology and Resilient Infrastructure
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• v.2 no.1
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• pp.12-21
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• 2015

Social demand for ecological engineering and technology has increased in tandem with national economic growth in order to improve the environmental capacity of civil infrastructures. To meet this demand, the Korean Society of Ecology and Infrastructure Engineering (KSEIE) was established in January 2013 and has contributed to the development of ecological engineering technologies. However, the establishment of an educational system for human resources training in ecological engineering is still at an early stage, and it is imperative to develop a curriculum for producing the human resources that can understand and apply ecological principles and functions and that is equipped with the abilities required for ecological conservation, restoration, and creation. As part effort, the KSEIE held a forum, entitled Founding the Education for Ecological Engineering, to discuss the establishment of the education system for ecological engineering in Korea. In this paper, based on the discussions and suggestions made during the forum, we analyzed the current status of ecological engineering education in various disciplines - civil and construction engineering, biology and environment, and landscape planning - in domestic universities, and attempted to seek possible solutions based on the cases of foreign universities. Generally, ecology and other application curricula are taught as fragmented subjects and fields in domestic universities. The development of new education strategies and systematic curricula for multidisciplinary education, ecological response to climate change, and the expansion of research fields is required.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.1-13
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• 2021

This study tried to suggest ways to improve the indicator system to strengthen the personal information protection. For this purpose, the components of indicator system are derived through domestic and foreign literature, and it was selected as main the diagnostic indicators through FGI/Delphi analysis for personal information protection experts and a survey for personal information protection officers of public institutions. As like this, this study was intended to derive an inspection standard that can be reflected as a separate index system for personal information protection, by classifying the specific IT technologies of the 4th industrial revolution, such as big data, cloud, Internet of Things, and artificial intelligence. As a result, from the planning and design stage of specific technologies, the check items for applying the PbD principle, pseudonymous information processing and de-identification measures were selected as 2 common indicators. And the checklists were consisted 2 items related Big data, 5 items related Cloud service, 5 items related IoT, and 4 items related AI. Accordingly, this study expects to be an institutional device to respond to new technological changes for the continuous development of the personal information management level diagnosis system in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.43-50
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• 2019

Block-chain enjoys technical advantages such as "robust security," owing to the structural characteristic that forgery is impossible, decentralization through sharing the ledger between participants, and the hyper-connectivity connecting Internet of Things, robots, and Artificial Intelligence. As a result, public organizations have highly positive attitudes toward the adoption of technology using block-chain, and the design of university information services is no exception. Universities are also considering the application of block-chain technology to foundations that implement various information services within a university. Through case studies of block-chain applications across various industries, this study designs an empirical model of an integrated information service platform that integrates information systems in a university. A basic road map of university information services is constructed based on block-chain technology, from planning to the actual service design stage. Furthermore, an actual empirical model of an integrated information service in a university is designed based on block-chain by applying this framework.

• Advanced Industrial SCIence
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• v.1 no.1
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• pp.7-15
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• 2022

To adopt the development in the medical scenario IoT developed towards the advancement with the processing of a large amount of medical data defined as an Internet of Medical Things (IoMT). The vast range of collected medical data is stored in the cloud in the structured manner to process the collected healthcare data. However, it is difficult to handle the huge volume of the healthcare data so it is necessary to develop an appropriate scheme for the healthcare structured data. In this paper, a machine learning mode for processing the structured heath care data collected from the IoMT is suggested. To process the vast range of healthcare data, this paper proposed an MTGPLSTM model for the processing of the medical data. The proposed model integrates the linear regression model for the processing of healthcare information. With the developed model outlier model is implemented based on the FinTech model for the evaluation and prediction of the COVID-19 healthcare dataset collected from the IoMT. The proposed MTGPLSTM model comprises of the regression model to predict and evaluate the planning scheme for the prevention of the infection spreading. The developed model performance is evaluated based on the consideration of the different classifiers such as LR, SVR, RFR, LSTM and the proposed MTGPLSTM model and the different size of data as 1GB, 2GB and 3GB is mainly concerned. The comparative analysis expressed that the proposed MTGPLSTM model achieves ~4% reduced MAPE and RMSE value for the worldwide data; in case of china minimal MAPE value of 0.97 is achieved which is ~ 6% minimal than the existing classifier leads.