• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.93-99
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• 2011

A PRT vehicle's control method is presented in this paper. In the asynchronous vehicle control system, vehicles follow their leading vehicles. Leading vehicles are defined differently among the different types of track. The main topic of this paper is to present a method to define the leading vehicle among different types of track and the calculation algorithm of the safety length the following vehicle must maintain. Simulation program is developed using the algorithm and the results of the test run are presented. An asynchronous PRT vehicle control algorithm was presented by Szillat in the paper "A low level PRT Microsimulation, Dissertation, University of Bristol, 2001". But it is different from the algorithm in this paper. In the algorithm proposed by Markus, vehicles in the merging track are controlled synchronously, and its safety distance between the leading and the following car is evaluated after the establishment of the complicated future time-location table instead of simple equations proposed in this paper.

• Journal of the Korea Safety Management & Science
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• v.13 no.3
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• pp.107-114
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• 2011

Traveling salesman problem is to minimize the total cost for a traveling salesman who wants to make a tour given finite number of cities along with the cost of travel between each pair them, visiting each cities exactly once before returning home. Traveling salesman problem is known to be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristics are more frequently developed than optimal algorithms. This study suggests a hybrid parallel genetic algorithm(HPGA) for traveling salesman problem The suggested algorithm combines parallel genetic algorithm, nearest neighbor search, and 2-opt. The suggested algorithm has been tested on 7 problems in TSPLIB and compared the results of existing methods(heuristics, meta-heuristics, hybrid, and parallel). Experimental results shows that HPGA could obtain good solution in total travel distance minimization.

• Journal of the Korean Society of Safety
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• v.25 no.6
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• pp.75-80
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• 2010

The present study presented the implementation of a remote control/supervision system for guard lamps used in public illumination with little endeavor by far for safe management, which makes possible to supervise the state and to control the functions remotely including electric safety elements. Especially, the developed system adopts the measurement algorithm for detecting resistive leakage current(Igr) flowing based on the phase difference checkable for sensing at a monitor, being allowable for monitoring at MMI and transmitter for data transmittance. To verify reliability about the algorithm to accurately detect Igr leakage current, the laboratory-based functional test was performed.

• Journal of Food Hygiene and Safety
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• v.26 no.4
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• pp.302-307
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• 2011

One of the most important objectives of post-marketing monitoring of dietary supplements is the early detection of unknown and unexpected adverse events (AEs). Several causality algorithms, such as the Naranjo scale, the RUCAM scale, and the M & V scale are available for the estimation of the likelihood of causation between a product and an AE. Based on the existing algorithms, the Korea Food & Drug Administration has developed a new algorithm tool to reflect the characteristics of dietary supplements in the causality analysis. However, additional work will be required to confirm if the newly developed algorithm tool has reasonable sensitivity and not to generate an unacceptable number of false positives signals.

• Journal of the Korea Safety Management & Science
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• v.21 no.4
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• pp.51-58
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• 2019

The LBS(Location Based Service) technology plays an important role in reducing wastes of time, losses of human lives and economic losses by detecting the user's location in order by suggesting the optimal evacuation route of the users in case of safety accidents. We developed an algorithm to estimate indoor location, movement path and indoor location changes of smart phone users based on the built-in sensors of smartphones and the dead-reckoning algorithm for pedestrians without a connection with smart devices such as Wi-Fi and Bluetooth. Furthermore, seven different indoor movement scenarios were selected to measure the performance of this algorithm and the accuracy of the indoor location estimation was measured by comparing the actual movement route and the algorithm results of the experimenter(pedestrian) who performed the indoor movement. The experimental result showed that this algorithm had an average accuracy of 95.0%.

• Journal of the Society of Naval Architects of Korea
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• v.58 no.2
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• pp.121-128
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• 2021

According to the increasing interest and demand for the Autonomous Surface Vessels (ASV), the autonomous navigation system is being developed such as obstacle detection, avoidance, and path planning. In general, autonomous navigation algorithm controls the ship by detecting the obstacles with various sensors and planning path for collision avoidance. This study aims to construct and prove autonomous algorithm with integrated various sensor using the Robot Operating System (ROS). In this study, the safety zone technique was used to avoid obstacles. The safety zone was selected by an algorithm to determine an obstacle-free area using 2D LiDAR. Then, drift angle of the ship was controlled by the propulsion difference of the port and starboard side that based on PID control. The algorithm performance was verified by participating in the 2020 Korea Autonomous BOAT (KABOAT).

• Journal of the Korean Society of Safety
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• v.38 no.2
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• pp.8-14
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• 2023

In various industrial sites, piping systems play an essential role in stable fluid supply and pressure maintenance. However, these systems are constantly exposed to risks of earthquakes, explosions, fires, and leaks, which can result in casualties or serious economic losses. With rapid advancements in the industry, different-sized piping systems have been launched; however, there are not enough maintenance personnel for troubleshooting and responding to situations where damages occur to piping systems. This increases the need for introducing autonomous damage management systems. In this study, a lab-based piping system was designed and manufactured by referring to the piping system of a naval ship to analyze the effectiveness of autonomous damage management systems. By using this testbed, a representative algorithm, the hydraulic resistance control algorithm, was realized and examinedIn addition, the difference between the averaged pressure and normalized pressure was introduced to improve the performance of the existing algorithm, which faces some limitations with regard to sensor noise and back pressure from the rupture-simulated pipeline part.

• Journal of the Korean Society of Safety
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• v.23 no.6
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• pp.51-56
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• 2008

As RFID/USN technology is used in the latest industry trend, the information analysis paradigm shifts to intelligence service environment. The intelligent service includes autonomic operation, which select activity by defining itself to the status of industry facilities. Furthermore, information analysis based on IT used to frequently data mining for detecting the meaning information and deriving new pattern. This paper suggest self-classifying of context-aware by applying data mining in gas facilities for serving the intelligent gas safety management. We modify data algorithm for fitting the domain of gas safety, construct context-aware model by using the proposed algorithm, and demonstrate our method. As the accuracy of our model is improved over 90%, the our approach can apply to intelligent gas safety management based on RFID/USN environments.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.56-63
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• 2021

The narrative texts of industrial accident reports help to identify accident risk factors. They relate the accident triggers to the sequence of events and the outcomes of an accident. Particularly, a set of related keywords in the context of the narrative can represent how the accident proceeded. Previous studies on text analytics for structuring accident reports have been limited to extracting individual keywords without context. We proposed a context-based analysis using a Natural Language Processing (NLP) algorithm to remedy this shortcoming. This study aims to apply Word2Vec of the NLP algorithm to extract adjacent keywords, known as word embedding, conducted by the neural network algorithm based on supervised learning. During processing, Word2Vec is conducted by adjacent keywords in narrative texts as inputs to achieve its supervised learning; keyword weights emerge as the vectors representing the degree of neighboring among keywords. Similar keyword weights mean that the keywords are closely arranged within sentences in the narrative text. Consequently, a set of keywords that have similar weights presents similar accidents. We extracted ten accident processes containing related keywords and used them to understand the risk factors determining how an accident proceeds. This information helps identify how a checklist for an accident report should be structured.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.644-654
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• 2024

After the Tohoku earthquake and tsunami (Japan, 2011), regulatory efforts to mitigate external hazards have increased both the safety requirements and the total capital cost of nuclear power plants (NPPs). In these circumstances, identifying not only disaster robustness but also cost-effective capacity setting of NPPs has become one of the most important tasks for the nuclear power industry. A few studies have been performed to relocate the seismic capacity of NPPs, yet the effects of multiple hazards have not been accounted for in NPP capacity optimization. The major challenges in extending this problem to the multihazard dimension are (1) the high computational costs for both multihazard risk quantification and system-level optimization and (2) the lack of capital cost databases of NPPs. To resolve these issues, this paper proposes an effective method that identifies the optimal multihazard capacity of NPPs using a multi-objective genetic algorithm and the two-stage direct quantification of fault trees using Monte Carlo simulation method, called the two-stage DQFM. Also, a capacity-based indirect capital cost measure is proposed. Such a proposed method enables NPP to achieve safety and cost-effectiveness against multi-hazard simultaneously within the computationally efficient platform. The proposed multihazard capacity optimization framework is demonstrated and tested with an earthquake-tsunami example.