• Proceedings of KOSOMES biannual meeting
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• 2003.11a
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• pp.45-51
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• 2003

The ship's signal sound dispersed by air, obstacles, and noises due to absorption, reflection, and disturbances, respectively. It is one of the factors of marine casualties by misjudgment if receiving direction The last target of this study is to prevent inherent marine casualty using the analysis-evaluation techniques if the interferences of ship's signal sound. In this work, three-dimensional sound field control model is proposed to simulate various sound transmitting characteristics according to sea environments at sea The efficiency test of the model was carried out using VR-based ship simulator.

• Journal of the Korean Institute of Gas
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• v.2 no.1
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• pp.14-22
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• 1998

In this work, in order to quantitatively predict the radiation flux and propose an idea about how to reduce the radiation damage, the radiation flux caused by pool fire of an LNG storage tank has been calculated using the RISC (Risk and Industrial Safety Consultant) proposed model under various conditions. Model predictions showed that the most important parameter affecting the radiation flux by the LNG pool fire is the wind speed. The extent of radiation damage to a target from fire flame was more significant with variation of wind speed at a low wind speed than with that at a high wind speed. It was found that the radiation damage by the former is substantially reduced with planting windbreak system around the plant. Since the windbreak is most economical than any other method, it is strongly suggested to plant a tree belt in the factory surroundings, especially near by the area of gas storage facilities, linking with water cooling and fire protection systems.

• Steel and Composite Structures
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• v.34 no.2
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• pp.189-213
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• 2020

Stainless-clad (SC) bimetallic steels that are manufactured by metallurgically bonding stainless steels as cladding metal and conventional mild steels as substrate metal, are kind of advanced steel plate products. Such advanced composite steels are gaining increasingly widespread usage in a range of engineering structures and have great potential to be used extensively for large civil and building infrastructures. Unfortunately, research work on the SC bimetallic steels from material level to structural design level for the applications in structural engineering field is very limited. Therefore, the aim of this paper is to investigate the material behaviour of the SC bimetallic steels under the cyclic loading which structural steels usually could encounter in seismic scenario. A number of SC bimetallic steel coupon specimens are tested under monotonic and cyclic loadings. The experimental monotonic and cyclic stress-strain curves of the SC bimetallic steels are obtained and analysed. The effects of the clad ratio that is defined as the ratio of the thickness of cladding layer to the total thickness of SC bimetallic steel plate on the monotonic and cyclic behaviour of the SC bimetallic steels are studied. Based on the experimental observations, a cyclic constitutive model with combined hardening criterion is recommended for numerical simulation of the cyclic behaviour of the SC bimetallic steels. The parameters of the constitutive model for the SC bimetallic steels with various clad ratios are calibrated. The research outcome presented in this paper may provide essential reference for further seismic analysis of structures fabricated from the SC bimetallic steels.

• Geomechanics and Engineering
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• v.27 no.6
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• pp.551-560
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• 2021

Due to the low strength and high compressibility characteristics, the loess deposits tunnels are prone to large deformations and collapse. An accurate stability evaluation for loess deposits is of considerable significance in deformation control and safety work during tunnel construction. 37 groups of representative data based on real loess deposits cases were adopted to establish the stability evaluation model for the tunnel project in Yan'an, China. Physical and mechanical indices, including water content, cohesion, internal friction angle, elastic modulus, and poisson ratio are selected as index system on the stability level of loess. The data set is randomly divided into 80% as the training set and 20% as the test set. Firstly, principal component analysis (PCA) is used to convert the five index system to three linearly independent principal components X1, X2 and X3. Then, the principal components were used as input vectors for probabilistic neural network (PNN) to map the nonlinear relationship between the index system and stability level of loess. Furthermore, Leave-One-Out cross validation was applied for the training set to find the suitable smoothing factor. At last, the established model with the target smoothing factor 0.04 was applied for the test set, and a 100% prediction accuracy rate was obtained. This intelligent classification method for loess deposits can be easily conducted, which has wide potential applications in evaluating loess deposits.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.741-747
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• 2022

Fatigue lowers an individual's ability and makes it difficult to perform work. As fatigue accumulates, concentration decreases and thus the possibility of causing a safety accident increases. Awareness of fatigue is subjective, but it is necessary to quantitatively measure the level of fatigue in the actual field. In previous studies, it was proposed to measure the level of fatigue by expert judgment by adding objective indicators such as bio-signal analysis to subjective evaluations such as multidisciplinary fatigue scales. However this method is difficult to evaluate fatigue in real time in daily life. This paper is a study on the fatigue classification model that determines the fatigue level of workers in real time using speech data recorded in the field. Machine learning models such as logistic classification, support vector machine, and random forest are trained using speech data collected in the field. The performance evaluation showed good performance with accuracy of 0.677 to 0.758, of which logistic classification showed the best performance. From the experimental results, it can be seen that it is possible to classify the fatigue level using speech signals.

• Convergence Security Journal
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• v.22 no.2
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• pp.27-42
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• 2022

In the era of the Fourth Industrial Revolution, digital transformation to increase the effectiveness of industry is becoming more important to achieving the goal of industrial innovation. The digital new deal and smart defense are required for digital transformation and utilize artificial intelligence, big data analysis technology, and the Internet of Things. These changes can innovate the industrial fields of national defense, society, and health with new intelligent services by continuously expanding cyberspace. As a result, work productivity, efficiency, convenience, and industrial safety will be strengthened. However, the threat of cyber-attack will also continue to increase due to expansion of the new domain of digital transformation. This paper presents the risk scenarios of cyber-attack threats in the Fourth Industrial Revolution. Further, we propose a preemptive intrusion response model to bolster the complex security environment of the future, which is one of the fundamental alternatives to solving problems relating to cyber-attack. The proposed model can be used as prior research on cyber security strategy and technology development for preemptive response to cyber threats in the future society.

• Journal of the Korean Society of Marine Environment & Safety
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• v.15 no.4
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• pp.369-374
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• 2009

It is difficult to improve maritime safety in the aspect of human elements without seafarers' job satisfaction. Therefore, through the career development for seafarers from their entries into the job to their retirements, longer and more stable seafarers' life on board ship could be achieved together with maritime safety. This study aims at the establishment of seafarers' career path model and the verification of six hypotheses by using the questionnaire data of 2,830 respondents of students, slip officers and shore-based ex-seafarers. The results of analyses of behavior factors on the career path are as follows; first, it is important to improve educational environment and to provide seafarers with detailed information on seafarer's life; second, economic factors such as income-level and etc. do not play a role in promoting motivation of going to sea; third, the guidance to shore jobs at proper time increases seafarers' job satisfaction and induces longer stay at sea; last, it is necessary to simplify the licence system for seafarers, to allow seafarers to acquire higher class certificates, and to work at higher rank on board ships as early as possible.

• Journal of the Korean Society of Marine Environment & Safety
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• v.10 no.2 s.21
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• pp.35-39
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• 2004

Ship structures are basically an assembly of plate elements and the load-carrying capacity or the ultimate strength is one of the most important criteria for safety assessment and economic design. Also, Structural elements making up ship plated structures do not work separately, resulting in high degree of redundancy and complexity, in contrast to those of steel framed structures. To enable the behavior of such structures to be analyzed simplifications or idealizations must essentially be made considering the accuracy needed and the degree of complexity of the analysis to be used On this study, to investigate effect of modeling range, the finite element method are used and their results are compared varying the analysis ranges. The model has been selected from bottom panels of merchant ship structures. For FHA, three types of structural modeling are adopted in terms of the extent of the analysis. The purpose of the present study is to numerically calculate the characteristics of ultimate strength behavior according to the analysis ranges of stiffened panels subject to uniaxial compressive loads.

• Safety and Health at Work
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• v.10 no.4
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• pp.452-460
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• 2019

Background: Monitoring and control of PM_2.5 are being recognized as key to address health issues attributed to PM_2.5. Availability of low-cost PM_2.5 sensors made it possible to introduce a number of portable PM_2.5 monitors based on light scattering to the consumer market at an affordable price. Accuracy of light scatteringe-based PM_2.5 monitors significantly depends on the method of calibration. Static calibration curve is used as the most popular calibration method for low-cost PM_2.5 sensors particularly because of ease of application. Drawback in this approach is, however, the lack of accuracy. Methods: This study discussed the calibration of a low-cost PM_2.5-monitoring device (PMD) to improve the accuracy and reliability for practical use. The proposed method is based on construction of the PM_2.5 sensor network using Message Queuing Telemetry Transport (MQTT) protocol and web query of reference measurement data available at government-authorized PM monitoring station (GAMS) in the republic of Korea. Four machine learning (ML) algorithms such as support vector machine, k-nearest neighbors, random forest, and extreme gradient boosting were used as regression models to calibrate the PMD measurements of PM_2.5. Performance of each ML algorithm was evaluated using stratified K-fold cross-validation, and a linear regression model was used as a reference. Results: Based on the performance of ML algorithms used, regression of the output of the PMD to PM_2.5 concentrations data available from the GAMS through web query was effective. The extreme gradient boosting algorithm showed the best performance with a mean coefficient of determination (R²) of 0.78 and standard error of 5.0 ㎍/㎥, corresponding to 8% increase in R² and 12% decrease in root mean square error in comparison with the linear regression model. Minimum 100 hours of calibration period was found required to calibrate the PMD to its full capacity. Calibration method proposed poses a limitation on the location of the PMD being in the vicinity of the GAMS. As the number of the PMD participating in the sensor network increases, however, calibrated PMDs can be used as reference devices to nearby PMDs that require calibration, forming a calibration chain through MQTT protocol. Conclusions: Calibration of a low-cost PMD, which is based on construction of PM_2.5 sensor network using MQTT protocol and web query of reference measurement data available at a GAMS, significantly improves the accuracy and reliability of a PMD, thereby making practical use of the low-cost PMD possible.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.24 no.1
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• pp.65-73
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• 2014

Objectives: The purposes of this study are to investigate workers' exposures to respirable particles generated in taconite mines and to compare two metric methods for mass concentrations using direct-reading instruments. Methods: Air monitorings were conducted at six mines where subjects have been exposed primarily to particulate matters in crushing, concentrating, and pelletizing processes. Air samples were collected during 4 hours of the entire work shift for similarly exposure groups(SEGs) of nine jobs(N=37). Following instruments were employed to evaluate the workplace: a nanoparticle aerosol monitor(particle size range; 10-1000 nm, unit: ${\mu}m^2/cc$, Model 9000, TSI Inc.); DustTrak air monitors($PM_{10}$, $PM_{2.5}$, unit: $mg/m^3$, Model 8520, TSI Inc.); a condensation particle counter(size range; 20-1000 nm, unit: #/cc, P-Trak 8525, TSI Inc.); and an optical particle counter(particle number by size range $0.3-25{\mu}m$, unit: #/cc, Aerotrak 9306, TSI Inc.). Results: The highest airborne concentration among SEGs was for furnace operator followed by pelletizing maintenance workers in number of particle and surface area, but not in mass concentrations. The geometric means of $PM_{2.5}$ by the DustTrak and the Ptrak/Aerotrak were $0.04{\mu}m$(GSD 2.52) and $0.07{\mu}m$(GSD 2.60), respectively. Also, the geometric means of RPM by the DustTrak and the Ptrak/Aerotrak were $0.16{\mu}m$(GSD 2.24) and $0.32{\mu}m$(GSD 3.24), respectively. The Pearson correlation coefficient for DustTrak $PM_{2.5}$ and Ptrak/Aerotrak $PM_{2.5}$ was 0.56, and that of DustTrak RPM and Ptrak/Aerotrak RPM was 0.65, indicating a moderate positive association between the two sampling methods. Surface area and number concentration were highly correlated($R^2$ = 0.80), while $PM_{2.5}$ and RPM were also statistically correlated each other($R^2$ = 0.79). Conclusions: The results suggest that it is possible to measure airborne particulates by mass concentrations or particle number concentrations using real-time instruments instead of using the DustTrak Aerosol monitor that monitor mass concentrations only.