• Journal of the Ergonomics Society of Korea
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• v.28 no.4
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• pp.147-154
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• 2009

The tactical computer is currently being developed and installed in armored vehicles and tanks for reinforcement. With the tactical computer, Korea Army will be able to grasp the deployment status of our forces, enemy, and obstacles under varying situations. Furthermore, it makes the exchange of command and tactical intelligence possible. Recent studies showed that the task performance is greatly affected by the user interface. The U.S. Army is now conducting user-centered evaluation tests based on C2 (Command & Control) to develop tactical intelligence machinery and tools. This study aims to classify and regroup subordinate menu functions according to the user-centered task performance for the Korea Army's tactical computer. Also, the research suggests an ergonomically sound layout and size of main touch buttons by considering human factors guidelines for button design. To achieve this goal, eight hierarchical subordinate menu functions are initially drawn through clustering analysis and then each group of menu functions was renamed. Based on the suggested menu structure, new location and size of the buttons were tested in terms of response time, number of error, and subjective preference by comparing them to existing ones. The result showed that the best performance was obtained when the number of buttons or functions was eight to conduct tactical missions. Also, the improved button size and location were suggested through the experiment. It was found in addition that the location and size of the buttons had interactions regarding the user's preference.

• Journal of the Korea Institute of Building Construction
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• v.23 no.3
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• pp.273-284
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• 2023

This study is centered on the combined use of LiDAR(Light Detection and Ranging) and AR(Augmented Reality) technologies during vertical and horizontal frame measurements in construction projects. The intention is to enhance the quality control procedure, elevate accuracy, and curtail manual labor along with time expenditure. Present methods for accuracy inspection in frame construction often grapple with reliability concerns due to subjective interpretation and the scope for human error. This research recommends the application of LiDAR and AR technologies to counter these issues and augment the efficiency of the inspection process, along with facilitating the dissemination of results. The suggested technique involves the collection of 3D point cloud data of the frame utilizing LiDAR and leveraging this data for checks on construction accuracy. Furthermore, the inspection outcomes are fed into a BIM (Building Information Modeling) model, and the results are visualized via AR. Upon juxtaposing this methodology with the current approach, it is evident that it offers benefits in terms of objective inspection, speed, precise result sharing, and potential enhancements to the overall quality and productivity of construction projects.

• Journal of Mechanical Science and Technology
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• v.20 no.11
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• pp.1863-1872
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• 2006

In FMS (Flexible Manufacturing System) and CIM (Computer Integrated Manufacturing), machine-tools have been the target of integration in the last three decades. The conventional concept of integration is being changed into the autonomous manufacturing device based on the knowledge evolution by applying advanced information technology in which an open architecture controller, high-speed network and internet technology are included. In the advanced environment, the machine-tools is not the target of integration anymore, but has been the key subject of cooperation. In the near future, machine-tools will be more improved in the form of a knowledge-evolutionary intelligent device. The final goal of this study is to develop an intelligent machine having knowledge-evolution capability and a management system based on internet operability. The knowledge-evolutionary intelligent machine-tools is expected to gather knowledge autonomically, by producing knowledge, understanding knowledge, reasoning knowledge, making a new decision, dialoguing with other machines, etc. The concept of the knowledge-evolutionary intelligent machine is originated from the machine control being operated by human experts' sense, dialogue and decision. The structure of knowledge evolution in M2M (Machine to Machine) and the scheme for a dialogue agent among agent-based modules such as a sensory agent, a dialogue agent and an expert system (decision support agent) are presented in this paper, with intent to develop the knowledge-evolutionary machine-tools. The dialogue agent functions as an interface for inter-machine cooperation. To design the dialogue agent module in an M2M environment, FIPA (Foundation of Intelligent Physical Agent) standard platform and the ping agent based on FIPA are analyzed in this study. In addition, the dialogue agent is designed and applied to recommend cutting conditions and thermal error compensation in a tapping machine. The knowledge-evolutionary machine-tools are expected easily implemented on the basis of this study and shows a good assistance to sensory and decision support agents.

• Journal of Biosystems Engineering
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• v.39 no.1
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• pp.21-33
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• 2014

Background: Significant technological development and changes happened in the tractor industries. Contrariwise, the test procedures of the major standard development organizations (SDO's) remained unchanged or with a little modification over the years, demanding new tractor test standards or improvement of existing ones for tractor performance, safety, and comfort. Purpose: This study focuses on reviewing the research trends regarding performance, safety and comfort evaluation of agricultural tractors. Based on this review, few recommendations were proposed to revise or improve the current test standards. Review: Tractor power take-off power test using the DC electric dynamometer reduced human error in the testing process and increased the accuracy of the test results. GPS signals were used to determine acceleration and converted into torque. High capacity double extended octagonal ring dynamometer has been designed to measure drawbar forces. Numerical optimization methodology has been used to design three-point hitch. Numerous technologies, driving strategies, and transmission characteristics are being considered for reducing emissions of gaseous and particulate pollutants. Engine emission control technology standards need to be revised to meet the exhaust regulations for agricultural tractors. Finite Element Analysis (FEA) program has been used to design Roll-Over Protective Structures (ROPS). Program and methodology has been presented for testing tractor brake systems. Whole-body vibration emission levels have been found to be very dependent upon the nature of field operation performed, and the test track techniques required development/adaptation to improve their suitability during standardized assessment. Emphasizes should be given to improve visibility and thermal environment inside the cab for tractor operator. Tractors need to be evaluated under electromagnetic compatibility test conditions due to large growing of electronic devices. Research trends reviewed in this paper can be considered for possible revision or improvement of tractor performance, safety, and comfort test standards.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.94-107
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• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.

• The Korean Journal of Cytopathology
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• v.9 no.2
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• pp.129-137
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• 1998

Although the success of the Papanicolaou test as a screening tool of cervical cancer is evident, there still exists $2{\sim}5%$ of discrepancy rate by both human and machine. To improve the qualilty of cervico-vaginal cytology, the authors compared cervicovaginal smear with cervical biopsy diagnoses, and analysed the causes of discrepancies. Among 30,922 cervicovaginal smears from June 1996 to April 1997 at our hospital, there were 271 cases of cervicovaginal smear with subsequent cervical punch or LEEP cone biopsies within several months. The biopsies and smears from a total of 98 discordant cases were reviewed. The discrepancy was attributed to sampling errors in 43 cases(43.9%), and to cytologic diagnosis in 49 cases(50.0%). Among these, 43 cases were interpretative errors(categories A;19, B;16 and C;8) whereas six cases were screening errors(categories B:2 and C:4). Among cervical biopsy cases, errors were present in four. As for 10% random rescreening, cytotechnologists reviewed 3,196 of 30,922 smears during the same period, There were 43 cases of screening error(categories A;27, B;16). Cytologic/histologic correlation was superior to 10% random rescreening of negative cases. The most effective method for quality improvement in cervicovaginal cytology was to implement both quality control(rescreening) and qualify assurance(cytologic/histologic correlation) programs.

• Journal of the Korean Society of Safety
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• v.28 no.4
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• pp.1-7
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• 2013

Train accidents can be directly connected to fatal accidents-collision, derailment, Fire, railway crossing accidents-resulting in tremendous human casualties. First of all, the railway derailment is not only related to most of railway accidents but also it can lead to much more catastrophic accompanying train overtured than other factors. Therefore, it is most important factor to ensure railway safety. some foreign countries have applied to the detector machines(e.g., ultrasonic detector car, sleep mode, current detector, optical sensing, optical fiber). Since it was developed in order to prevent train from being derailed. In korea, the existing track method has been used to monitor rail condition using track circuit. However, we found out it impossible for Communication Based Train Control system(CBTC), recent technology to detect rail condition using balise(data transmission devices) without no track circuit. For this reason, it is needed instantly to develop real-time monitoring system used to detect broken rails. Firstly, this paper presents domestic and international statues analysis of rail breaks technology. Secondly, the composition and the characteristics of the real-time monitoring system. Finally, the evidence that this system could assumed the location and type of broken rails was proved by the experiment of prototype and operation line tests. We concluded that this system can detect rail break section in which error span exist within${\pm}1m$.

• Journal of the Korean Institute of Gas
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• v.27 no.2
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• pp.49-56
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• 2023

As AI (Artificial Intelligence)-related technologies are highly developed due to the 4th industrial revolution, cases of applying AI in various fields are increasing. The main reason is that there are practical limits to direct processing and analysis of exponentially increasing data as information and communication technology develops, and the risk of human error can be reduced by applying new technologies. In this study, after collecting the data received from the 'remote potential measurement terminal (T/B, Test Box)' and the output of the 'remote rectifier' at that time, AI was trained. AI learning data was obtained through data augmentation through regression analysis of the initially collected data, and the learning model applied the value-based Q-Learning model among deep reinforcement learning (DRL) algorithms. did The AI that has completed data learning is put into the actual city gas supply area, and based on the received remote T/B data, it is verified that the AI responds appropriately, and through this, AI can be used as a suitable means for electricity management in the future. want to verify.

• Analytical Science and Technology
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• v.18 no.2
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• pp.163-167
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• 2005

In this study, a novel analytical method has been developed for the rapid determination of L-carnitine in human plasma using electrospray ionization tandem mass spectrometry. Free carnitine (FC) was analyzed after extraction with 80% methanol and total carnitine (TC) was analyzed after hydrolysis and extraction. Acyl carnitine (AC) was subtracted FC from TC. Analytical methods used multiple reaction monitoring (MRM) scan modes. A correlation coefficient of linear regression ($r^2$) was 0.9995, recovery was 97%, reproducibility was less than 10%, and limit of detection (LOD) was $0.0016{\mu}mol/L$. This method reduced sample preparation time and showed high resolution and good reproducibility compared to that with liquid chromatographic methods. Normal control showed AC was lower than FC. Clinical management of patients with inborn error of metabolism showed FC was lower than AC. Thus, carnitine fraction level was very important to monitoring patients with metabolic disorder.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2010.10a
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• pp.180-181
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• 2010

An estimation algorithm of collision risk among multiple ships has been developed in order to reduce human error and prevent collision accidents. The algorithm is designed to calculate the collision risk among ships based on Fuzzy theory by using AIS data as traffic information. In this paper, to validate the algorithm, the AIS data of actual collision accident, which occurred between a product carrier and a cargo carrier in Busan harbor in 2009 are collected. The replay simulation is carried out on the actual AIS data and the collision risk is calculated in real time. In this paper, the features of the estimation algorithm of collision risk and the results of replay simulation based on AIS data of actual collision accident are discussed.