• Journal of Soil and Groundwater Environment
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• v.28 no.spc
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• pp.18-39
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• 2023

Rapid development of geophysical exploration and hydrogeologic monitoring techniques has yielded remarkable increase of datasets related to groundwater systems. Increased number of datasets contribute to understanding of general aquifer characteristics such as groundwater yield and flow, but understanding of complex heterogenous aquifers system is still a challenging task. Recently, applications of data science technique have become popular in the fields of geophysical explorations and monitoring, and such attempts are also extended in the groundwater field. This work reviewed current status and advancement in utilization of data science in groundwater field. The application of data science techniques facilitates effective and realistic analyses of aquifer system, and allows accurate prediction of aquifer system change in response to extreme climate events. Due to such benefits, data science techniques have become an effective tool to establish more sustainable groundwater management systems. It is expected that the techniques will further strengthen the theoretical framework in groundwater management to cope with upcoming challenges and limitations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.904-913
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• 2020

As the data volumes and complexity rapidly increase, data-intensive science handling large-scale scientific data needs to investigate new techniques for intelligent storage and data distribution over networks. Recently, Named Data Networking (NDN) and data-intensive science communities have inspired innovative changes in distribution and management for large-scale experimental data. In this article, analysis on NDN testbeds for large-scale scientific data such as climate science data and High Energy Physics (HEP) data is presented. This article is the first attempt to analyze existing NDN testbeds for large-scale scientific data. NDN testbeds for large-scale scientific data are described and discussed in terms of status, NDN-based application, and features, which are NDN testbed instance for climate science, NDN testbed instance for both climate science and HEP, and the NDN testbed in SANDIE project. Finally various issues to prevent pitfalls in NDN testbed establishment for large-scale scientific data are analyzed and discussed, which are drawn from the descriptions of NDN testbeds and features on them.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.8
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• pp.426-432
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• 2004

This paper presents a systematic approach of measurement, modeling and analysis of grounding system impedance in the field of lightning protection system and intelligent power equipments. The measurement and analysis system of ground impedance is based on a computer aided technique. The magnitude and phase of ground impedance were determined by the novel measurement and analysis using the revised fall-of-potential method. The ground impedances of the ground rod of 50 m long are considerably dependent on the frequency. The ground impedance is mainly resistive in the frequency range of 3-20 kHz. At higher frequencies, the reactive components of the ground impedances are no longer negligible and the inductance of the ground rod was found to be the core factor deciding the ground impedance. Although the steady-state ground resistance of the ground rod of 50 m was less than that of the ground rod of 10 m, the ground impedances of the ground rod of 50 m over the frequency range of more than 60 kHz were much greater than those of the ground rod of 10 m. Furthermore, the equivalent circuit model based on the measured data was proposed. and the calculated results were in approximately agreement with the measured data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.88-103
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• 2023

With the recent advancement of 4th Industrial Revolution technology, transportation systems are generating large amounts of mobility data related to the individual movement trajectories of vehicles and people. There are many constraints on utilizing mobility data containing personal information. Thus, in South Korea, the processing and generation of pseudonymized information and the analysis and utilization of this information have been managed in a dual manner by applying separate agencies and technologies through the revision of the Data 3 Act and the enactment of the Data Basic Act. However, this dual approach fails to securely support the entire data lifecycle and suffers from inefficiencies in terms of processing time and cost. Therefore, to compensate for the problems of the existing Expert Data Combination System and Data Safety Zone, this study proposes an Integrated Data Safety Zone Framework that integrates and unifies the process of generating, processing, analyzing, and utilizing mobility data. The integrated process for data processing was redesigned, and common requirements and core technologies were derived. The result is an architecture for a next-generation Integrated Data Safety Zone system that can manage and utilize the entire life cycle of mobility data at one stop.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.545-550
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• 2013

In pattern recognition field, data classification is an essential process for extracting meaningful information from data. Adaptive boosting algorithm, known as AdaBoost algorithm, is a kind of improved boosting algorithm for applying to real data analysis. It consists of weak classifiers, such as random guessing or random forest, which performance is slightly more than 50% and weights for combining the classifiers. And a strong classifier is created with the weak classifiers and the weights. In this paper, a research is performed using AdaBoost algorithm for detecting chaff echo which has similar characteristics to precipitation echo and interrupts weather forecasting. The entire process for implementing chaff echo classifier starts spatial and temporal clustering based on similarity with weather radar data. With them, learning data set is prepared that separated chaff echo and non-chaff echo, and the AdaBoost classifier is generated as a result. For verifying the classifier, actual chaff echo appearance case is applied, and it is confirmed that the classifier can distinguish chaff echo efficiently.

• Journal of Wetlands Research
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• v.24 no.1
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• pp.38-43
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• 2022

Smart sewage treatment plant means creating a safe and clean water environment by establishing an ICT-based real-time monitoring, remote control management and intelligent system for the entire sewage treatment process. The core technology of such a smart sewage treatment plant can be operation control technology using measuring instruments. This research team analyzed and suggested the operation control technologies necessary for the establishment of the intelligent business by referring to the intelligent research projects of the sewage treatment plant in progress in Korea. As a result of the analysis, a total of six removal technologies were presented, including control by scale, reflow water control, linked treated water control, chemical quantity control, winter operation control, and total organic carbon control. By size, standards that can be classified into small and medium-sized large-scale are presented, and in the case of reflow water control, the location of water quality and flow sensors capable of managing reflow water is suggested. In the case of the linked treated water control, the influence and control points of the linked treated water on the sewage treatment plant were presented, and in the case of the chemical injection volume control, a system capable of optimizing the amount of chemical injection according to the introduction of an intelligent sewage treatment plant was presented. In the case of winter operation, the sensors and pumps to be controlled are suggested when considering the decrease in nitrification due to the decrease in water temperature. In the case of total organic carbon control, an interlocking system considering the total amount of pollution in the future was proposed. These operation control scenarios are expected to be used as basic data to be used in intelligent sewage treatment algorithms and scenarios in the future.

• International Journal of High-Rise Buildings
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• v.12 no.3
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• pp.225-234
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• 2023

Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.1
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• pp.31-41
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• 2018

This study aims to analyze region-based pedestrian evacuation behaviors and information offering effect using Social Force Model, which is micro simulation. All pedestrians were assumed to move to shelters through pedestrian roads according to guidance information at emergency situations, and the pedestrians were classified into adults and the handicapped. According to the results of the road network analysis and simulation analysis, the shelters to which pedestrians can move within the shortest time from each zone were selected as optimum shelters. From this study, the analysis showed that the information provision effects are informative even though total evacuation time increases due to the increase of pedestrian conflict. This study can be used as baseline data for urban area's pedestrian disaster prevention plans.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.118-127
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• 2009

This study tries to develop model in order to assess personal factors of senior traffic accidents that are widely recognized as one of the social problems. For the current practice. it gathers data (Simulation & Questionnaire Survey) of KOTSA and conducts Poisson and Negative Binomial Regression Analysis to develop traffic accident severity model. The results show that elderly drivers' accidents are mainly affected by attentiveness selection, velocity prediction ability and attentiveness distribution ability in a positive(+) way. Second, non-senior drivers' accidents are also positively(+) influenced by attentiveness selection, velocity prediction, distance perception, attentiveness distribution ability and attentiveness diversion ability. Therefore, influencing factors of senior and non-senior drivers to vehicle accidents are different. This eventually poses a indication that preliminary education for car accident prevention should be implemented based up[n the distinction between senior drivers and non-senior drivers.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.489-494
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• 2015

The purpose of this paper is to analyse outcomes of Korean Pro-basketball games using regression models. Both Classic Fuzzy Regression Model and Fuzzy Regression Model applying linguistic variables were used to meet the purpose of the paper. In General Regression Analysis, in which the results of games are expressed and analyzed through score differences, a regression model is proposed considering influential variables for the score differences of the two teams. In Fuzzy Regression Analysis, the results are sorted into six different literal expressions, 'win with large margin, win with moderate margin, win with narrow margin, defeat with narrow margin, defeat with moderate margin, and defeat with large margin'. Athletic performances and team work of each teams were expressed in fuzzy number to analyse how much athletic performances and team work affect results of games. This paper referred back to 2013-2014 season data provided by KBL(Korean Basketball League) and professional columns on Korean basketball analysis.