• Journal of IKEEE
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• v.26 no.3
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• pp.510-514
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• 2022

In this paper, we propose the development of high-sensitivity low-end radiation measuring sensor module. The proposed measurement sensor module is a scintillator + photomultiplier(SiPM) sensor optimization structure design, amplification and filter and control circuit design for sensor driver, control circuit design including short-distance communication, sensor mechanism design and manufacturing, and GUI development applied to prototypes consists of, etc. The scintillator + photomultiplier(SiPM) sensor optimization structure design is designed by checking the characteristics of the scintillator and the photomultiplier (SiPM) for the sensor structure design. Amplification, filter and control circuit design for sensor driver is designed to process fine scintillation signal generated by radiation with a scintillator using SiPM. Control circuit design including short-distance communication is designed to enable data transmission through MCU design to support short-range wireless communication function and wired communication support. The sensor mechanism design and manufacture is designed so that the glare generated by wrapping a reflective paper (mirroring) on the outside of the plastic scintillator is reflected to increase the efficiency in order to transmit the fine scintillation signal generated from the plastic scintillator to the photomultiplier(SiPM). The GUI development applied to the prototype expresses the date and time at the top according to each screen and allows the measurement unit and time, seconds, alarm level, communication status, battery capacity, etc. to be expressed. In order to evaluate the performance of the proposed system, the results of experiments conducted by an authorized testing institute showed that the radiation dose measurement range was 30 𝜇Sv/h ~ 10 mSv/h, so the results are the same as the highest level among products sold commercially at domestic and foreign. In addition, it was confirmed that the measurement uncertainty of ±7.4% was measured, and normal operation was performed under the international standard ±15%.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.562-569
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• 2022

The alarm monitoring technology applied to existing operating ships manages data items such as temperature and pressure with AMS (Alarm Monitoring System) and provides an alarm to the crew should these sensing data exceed the normal level range. In addition, the maintenance of existing ships follows the Planned Maintenance System (PMS). whereby the sensing data measured from the equipment is monitored and if it surpasses the set range, maintenance is performed through an alarm, or the corresponding part is replaced in advance after being used for a certain period of time regardless of whether the target device has a malfunction or not. To secure the reliability and operational safety of ship engine operation, it is necessary to enable advanced diagnosis and prediction based on real-time condition monitoring data. To do so, comprehensive measurement of actual ship data, creation of a database, and implementation of a condition diagnosis monitoring system for condition-based predictive maintenance of auxiliary equipment and piping must take place. Furthermore, the system should enable management of auxiliary equipment and piping status information based on a responsive web, and be optimized for screen and resolution so that it can be accessed and used by various mobile devices such as smartphones as well as for viewing on a PC on board. This update cost is low, and the management method is easy. In this paper, we propose CBM (Condition Based Management) technology, for autonomous ships. This core technology is used to identify abnormal phenomena through state diagnosis and monitoring of pumps and purifiers among ship auxiliary equipment, and seawater and steam pipes among pipes. It is intended to provide performance diagnosis and failure prediction of ship auxiliary equipment and piping for convergence analysis, and to support preventive maintenance decision-making.

• Journal of the Korean Society of Propulsion Engineers
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• v.26 no.2
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• pp.12-19
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• 2022

Propellant grains with embedded metal wires have been used for enhancement of burning rate while maintaining high loading density. For the performance design of a solid rocket motor using propellant grain with embedded metal wires, burn-back analysis is required according to number, location, arrangement angle of metal wires, and augmentation ratio of the propellant burning rate near a wire region. In this study, a numerical method to quickly calculate a burning surface area was developed in response to the design change of the propellant grain with embedded metal wires. The burning surface area derived from the developed method was compared with the results of a CAD program. Error rate decreased as the radial size of the grid decreased. Analysis for characteristics of burning surface area was performed according to the number and location of metal wires, the initial and final phases were shortened and the steady-state phase was increased when the number of metal wires increased. When arranging the metal wires at different radii, the burning surface area rapidly increased in the initial phase and sharply decreased in the final phase compared to the case where the metal wires were disposed in the same radius.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.9-16
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• 2022

In this paper, we propose a plan to design and utilize the RDBS(Record Block Data file management System) so that data can be recovered when data files in the Combat Management System are mismatched. The CMS(Combat Management System) manages the same files in multiple IPN(Infomation Processing Node) repositories to support multiplexing. However, mismatches in data files can occur due to equipment maintenance or user immaturity. The existing CMS does not manage the history of changes in data files, and when a mismatch occurs, data file were synchronized based on the latest date. But, It is difficult to say that files with the latest date have the highest reliability, and once the file synchronization has progressed, it cannot be recovered with pre-synchronization data. To solve this problem, data was stored and synchronized in units of record blocks using RDBS proposed in this paper, and the Rsync algorithm was used to reduce the overhead of file synchronization due to units of record blocks. SW applied with RDBS was tested for performance in a simulated environment, and it was confirmed that it could be applied to CMS through normal operation confirmation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.57-66
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• 2022

The Road Management Administration is cracking down on overloaded vehicles by installing low-speed or high-speed WIMs at toll gates and main lines on expressways. However, in recent years, the act of intelligently evading the overloaded-vehicle control system of the Road Management Administration by illegally manipulating the variable axle of an overloaded truck is increasing. In this manipulation, when entering the overloaded-vehicle checkpoint, all axles of the vehicle are lowered to pass normally, and when driving on the main road, the variable axle of the vehicle is illegally lifted with the axle load exceeding 10 tons alarmingly. Therefore, this study developed a technology to detect the state of the variable axle of a truck driving on the road using roadside camera images. In particular, this technology formed the basis for cracking down on overloaded vehicles by lifting the variable axle after entering the checkpoint and linking the vehicle with the account information of the checkpoint. Fundamentally, in this study, the tires of the vehicle were recognized using the Mask RCNN algorithm, the recognized tires were virtually arranged before and after the checkpoint, and the height difference of the vehicle was measured from the arrangement to determine whether the variable axle was lifted after the vehicle left the checkpoint.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.44-59
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• 2023

Purpose: In the event of mass casualties, triage must be done promptly and accurately so that as many patients as possible can be recovered and returned to the battlefield. However, medical personnel have received many tasks with less manpower, and the battlefield for classifying patients is too complex and uncertain. Therefore, we studied an artificial intelligence model that can assist and replace medical personnel on the battlefield. Method: The triage model is presented using reinforcement learning, a field of artificial intelligence. The learning of the model is conducted to find a policy that allows as many patients as possible to be treated, taking into account the condition of randomly set patients and the medical capability of the military hospital. Result: Whether the reinforcement learning model progressed well was confirmed through statistical graphs such as cumulative reward values. In addition, it was confirmed through the number of survivors whether the triage of the learned model was accurate. As a result of comparing the performance with the rule-based model, the reinforcement learning model was able to rescue 10% more patients than the rule-based model. Conclusion: Through this study, it was found that the triage model using reinforcement learning can be used as an alternative to assisting and replacing triage decision-making of medical personnel in the case of mass casualties.

• Membrane Journal
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• v.33 no.4
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• pp.222-232
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• 2023

In this study, a hollow fiber support membrane was prepared by a non-solvent induced phase separation (NIPS) method using a polysulfone (PSf). The prepared hollow fiber support membrane was coated with PDMS and Pebax to prepare a hollow fiber composite membrane. The prepared composite membrane was measured for permeance and selectivity for pure CO₂, H₂, O₂ and N₂. Gas separation performance of the module having the highest selectivity (CO₂/H₂) among the prepared composite membrane modules was measured according to the change in stage cut using simulated gas. The composition of the simulated gas used at this time was 70% CO₂ and 30% H₂. In the 1 stage experiment, it was possible to obtain values of about 60% of H₂ concentration and 12% of H₂ recovery. In order to overcome the low H₂ concentration and recovery, 2 stage serial test was performed, and through this, it was possible to achieve 70% H₂ concentration and 70% recovery. Through this, it was possible to derive a separation process configuration for CO₂/H₂ separation.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1211-1222
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• 2022

Abnormal condition inevitably occurs during operation of water distribution system (WDS) and requires the isolation of certain areas using isolation valves. In general, the determination of the optimal location of isolation valves considered minimization of hydraulic failures as isolation of certain areas causes a change in hydraulic states (e.g., flow direction, velocity, pressure, etc.). Water quality failure can also be induced by changes in hydraulics, which have not been considered for isolation valve system design. Therefore, this study proposes a new isolation valve system design methodology to prevent unexpected water quality failure events. The new methodology considers flow direction change ratio (FDCR), which accounts for flow direction changes after isolation of the area, as a constraint while reliability is used as the objective function. The optimal design model has been applied to a synthetic grid network and the results are compared with the traditional design approach. Results show that considering FDCR can eliminate flow direction changes while average pressure and coefficient of variation of pressure, velocity, and hydraulic geodesic index (HGI) outperform compared to the traditional design approach. The proposed methodology is expected to be a useful approach to minimizing unexpected consequences by traditional design approaches.

• Journal of Korean Society on Water Environment
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• v.39 no.1
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• pp.61-75
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• 2023

Denitrifying bacteria convert nitrate to nitrogen gas using an external carbon source as an electron donor. The external carbon source affects the denitrification performance and bacterial community structure. Although methanol is a cheap and effective external carbon source, the addition of diverse carbon sources may improve the total nitrogen removal rate and biomass characteristics, such as settleability. In this study, denitrifying reactions were performed using solely methanol and mixed carbon sources of methanol, glucose, and acetate in a sequencing batch reactor. The denitrifying reactor using methanol resulted in a total nitrogen removal rate of 0.39 ± 0.025 kg-N/m³-day while the suspended biomass transformed into dark brown granules. Methyloversatilis discipulorum had the highest predominance at 43.84%. The individual denitrifying biomasses, which were separately enriched with methanol, glucose, and acetate, showed the same total nitrogen removal performance of 0.39 ± 0.016 kg-N/m³-day. However, the addition of mixed carbon sources showed an improved total nitrogen removal rate of 0.42 ± 0.043 kg-N/m³-day, with the domination of Candidatus Saccaribacteria at 25.61%. The denitrifying granules turned pale yellow color. Influent COD/NO₃^--N ratios of 3.5, 5, and 7.5 exhibited COD/NO₃^--N consumptions of 4.3 ± 0.4, 4.4 ± 0.8, and 5.2 ± 0.7, and the consistent predominance of Candidatus Saccharibacteria.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.119-125
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• 2023

IT infrastructure operation has advanced, and the methods for managing systems have become widely adopted. Recently, research has focused on improving system management using Syslog. However, utilizing log data collected through these methods presents challenges, as logs are extracted in various formats that require expert analysis. This paper proposes a system that utilizes edge computing to distribute the collection of Syslog data and preprocesses duplicate data before storing it in a central database. Additionally, the system constructs a data dictionary to classify and count data in real-time, with restrictions on transmitting registered data to the central database. This approach ensures the maintenance of predefined patterns in the data dictionary, controls duplicate data and temporal duplicates, and enables the storage of refined data in the central database, thereby securing fundamental data for big data analysis. The proposed algorithms and procedures are demonstrated through simulations and examples. Real syslog data, including extracted examples, is used to accurately extract necessary information from log data and verify the successful execution of the classification and storage processes. This system can serve as an efficient solution for collecting and managing log data in edge environments, offering potential benefits in terms of technology diffusion.