• Journal of Navigation and Port Research
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• v.33 no.3
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• pp.181-191
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• 2009

In general, seafarer's human error is considered to be the preponderant muse for the majority of maritime transportation accidents in a merchant ship. The implementation techniques for Human Error Model (HEM) to assess possible accident risk by deck officers including captain, chief officer, second mate and third mate are described in this study. The scope of this work is focused to 642 deck officers in the ship management company with 130 vessels. At first, HEM can be constructed through the statistical analysis and expert's brainstorming process with human data to 642 deck officers. Then the variables $\upsilon$ for the human factors, the evaluation level EP($\upsilon$) for $\upsilon$, the weight $\alpha$ of $\upsilon$, and the title weight $\beta$ of each deck officers can be decided. In addition, through the analysis of ship's accident history, the accident causation ratios by human error ${\gamma}_H$ and by external error ${\gamma}_B$ can be found as 0.517(51.7%) and 0.483(48.3%), respectively. The correlation coefficients to $\upsilon$ are also shown significant for a 95% confidence interval (p < 0.05) for each coefficient. And the validity of HEM is also surveyed by the analysis of normal probability distribution of risk level RL to each deck officer.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.4
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• pp.56-67
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• 2004

This study analyzes human error of workers performing simple repetitive tasks, and in order to prepare preventative measures, 486 people were used as subjects. The results of the study are like the following. First, the biggest cause of human error showed to be the worker himself in $77.8\%$ of the cases, machinery showed to be the cause in $16.3\%$ of the cases and management showed to be the cause in $6.0\%$ of the cases. The results show that most of the human error occurred due to the worker performing simple repetitive tasks and the human errors showed to be caused more by bad ergonomics and long hours rather than by problems with machinery. In addition, the area with the highest rate of human error showed to be the Human Information Processing System with Task Input Error being the highest with $46.9\%$, followed by Judgement and Memory Error with $36.4\%$ and Recognition Verification Error with $16.7\%$. Although fully automated tasks may reduce the rate of human error we must focus on lowering the rate of problems arising from spontaneous errors caused by workers performing simple repetitive tasks by continuously renewing plans and budgets in order to standardize tasks by incorporating cyclic positioning according to experience and positional exchange and by inspecting the workplace to increase efficiency of the workers.

• The Journal of the Korea Contents Association
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• v.11 no.7
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• pp.234-238
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• 2011

This paper will evaluate the usefulness of 3D target of CBCT by comparing human body's posture and position when simulated treatment is being carried out as well as human phantom posture and position using CBCT which is applying OBI. From the Rando Phantom which is located in the datum point moved in parallel and rotationary direction using CBCT. Then the mean and standard deviation difference on images location difference that are acquired were compared with real the Rando Phantom' moved distance. To make a plan of simulated treatment with the same procedure of real radiation therapy, we are going to setup the Rando Phantom. With an assumption that the position is set in accurate place, we measured the setup errors accroding to the change of the translation and rotation. Tests are repeated 10 times to get the standard deviation of the error values. The variability in couch shift after positioning equivalent to average residual error showed lateral $0.2{\pm}0.2$mm, longitudinal $0.4{\pm}0.3$mm, vertical $-0.4{\pm}0.1$mm. The average rotation erroes target localization after simulated $0.4{\pm}0.2$ mm, $0.3{\pm}0.3$ mm, and $0.3{\pm}0.4$ mm. The detection error by rotation is $0{\sim}0.6^{\circ}$ CBCT 3D/3D matching using the Rando Phantom minimized the errors by realizing accurate matching during simulated treatment and patient caring.

• International Journal of Reliability and Applications
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• v.2 no.1
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• pp.37-48
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• 2001

This paper presents a new dynamic human reliability analysis method and its application for quantifying the human error probabilities in implementing management action. For comparisons of current HRA methods with the new method, the characteristics of THERP, HCR, and SLIM-MAUD, which are most frequency used method in PSAs, are discussed. The action associated with implementation of the cavity flooding during a station blackout sequence is considered for its application. This method is based on the concepts of the quantified correlation between the performance requirement and performance achievement. The MAAP 3.0B code and Latin Hypercube sampling technique are used to determine the uncertainty of the performance achievement parameter. Meanwhile, the value of the performance requirement parameter is obtained from interviews. Based on these stochastic obtained, human error probabilities are calculated with respect to the various means and variances of the things. It is shown that this method is very flexible in that it can be applied to any kind of the operator actions, including the actions associated with the implementation of accident management strategies.

• The Journal of Korean Society for Radiation Therapy
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• v.16 no.2
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• pp.81-89
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• 2004

Introduction : The setup error due to the patient and the staff from radiation treatment as the reason which is important the treatment record could be decided is a possibility of effect. The SET-UP ERROR of the patient analyzes the effect of dose distribution and DVH from radiation treatment of the patient. Material & Methode : This test uses human phantom and when C-T scan doing, It rotated the Left direction of the human phantom and it made SET-UP ERROR , Standard plan and 3mm, 5mm, 7mm, 10mm, 15mm, 20mm with to distinguish, it made the C-T scan error. With the result, The SET-UP ERROR got each C-T image Using RTP equipment It used the plan which is used generally from clinical - Box plan, 3Dimension plan( identical angle 5beam plan) Also, ( CTV+1cm margin, CTV+0.5cm margin, CTV+0.3,cm margin = PTV) it distinguished the standard plan and each set-up error plan and The plan used a dose distribution and the DVH and it analyzed Result : The Box4 the plan and 3Dimension plan which it bites it got similar an dose distribution and DVH in 3mm, 5mm From rotation error and Rectilinear movement( $0\%{\sim}2\%$ ). Rotation error and rectilinear error 7mm, 10mm, 15mm, 20mm appeared effect it will go mad to a enough change in treatment ( $2\%{\sim}^11\%$ ) Conclusion : The diminishes the effect of the SET-UP ERROR must reduce move with tension of the patient Also, we are important accessory development and the supply that it reducing of reproducibility and the move

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.5
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• pp.515-523
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• 2015

This study reviewed 612 DP LOP(Loss of Position) incident reports which submitted to IMCA from 2001~2010 and identified 103 human error caused incidents and classified it through HFACS. And, this study analysis of conditional probability of human error on DP LOP incidents through application of bayesian network. As a result, all 103 human error related DP LOP incidents were caused by unsafe acts, and among unsafe acts 70 incidents(68.0 %) were related to skill based error which are the largest proportion of human error causes. Among skill based error, 60(58.3%) incidents were involved inadvertent use of controls and 8(7.8%) incidents were involved omitted step in procedure. Also, 21(20.8%) incidents were involved improper maneuver because of decision error. Also this study identified that unsafe supervision(68%) is effected as the largest latent causes of unsafe acts through application to bayesian network. As a results, it is identified that combined analysis of HFACS and bayesian network are useful tool for human error analysis. Based on these results, this study suggest 9 recommendations such as polices, interpersonal interaction, training etc. to prevent and mitigate human errors during DP operations.

• Korean Journal of Human Ecology
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• v.19 no.3
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• pp.555-563
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• 2010

With recent advances in 3D scanning technology, three-dimensional (3D) patternmaking is becoming a powerful way to develop garments pattern. This technology is now applicable to the made to measure (MTM) system of both ordinary and tightly fitting garments. Although the pattern of fitted clothing has been developed using 3D human data, it is still interesting to develop cycling pants by considering while-cycling body posture and fabric elasticity. This study adopted the Garland's triangle simplification method in order to simplify data without distorting the original 3D scan. Next, the Runge-Kutta method (2C-AN program) was used to develop a 2D pattern from the triangular pixels in the 3D scanned data. The 3D scanned data of four male, university students aged from 21 to 25, was obtained using Whole body scanner (Model WB4, Cyberware, Inc., USA). Results showed the average error of measurement was $4.58cm^2$ (0.19%) for area and 0~0.61cm for the length between the 3D body scanned data and the 2D developed pattern data. This is an acceptable range of error for garment manufacture. Additionally, the 2D pattern developed, based on the 3D body scanned data, did not need ease for comfort or ease of movement when cycling. This study thus provides insights into how garment patterns may be developed for ergonomic comfort in certain special environments.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.7
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• pp.34-42
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• 2022

Minimizing the backlash of gears and reducers is important for their proper and precise functioning. In this study, an automatic backlash measuring system was developed for the mass production and quality control of a military-grade reducer. The developed automatic backlash measurement system eliminates human error during the backlash measurement process. It also reduces the manufacturing time and digitizes the backlash number. The system was tested for an aircraft machine gun control reducer that required low-torque and high-precision conditions. The test results show that the torque range was 0.820-4.788 Nm. The maximum torque error is less than 0.231 N·m at 2.943 N·m, and 1.2 arcmin of the maximum backlash error with ± 0.3 arcmin of repeatability. The developed system satisfies all required conditions: torque of 1-3 Nm, torque accuracy within ± 0.5 N·m, and backlash accuracy of ± 3 arcmin.

• Journal of Korean Ophthalmic Optics Society
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• v.4 no.1
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• pp.7-14
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• 1999

The purpose of this study is to evaluate the relationship between ocular components and refractive error for human eye. Ocular components were measured by keratometry, phakometry, and ultrasonography. Refractive error was measured by subjective refraction on 38 subjects aged from 17 to 30. The results were as follows; 1) Refractive error and axial length, vitreous chamber depth, axial length/corneal radius were highly correlated that the correlation coefficients were 0.95, 0.96, 0.95, respectively. 2) Refractive error and corneal radius, corneal power, lens thickness were correlated with the correlation coefficients for 0.60, 0.66, 0.67 respectively. 3) There were no significant correlation between refractive error and corneal thickness.

• Journal of Animal Science and Technology
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• v.64 no.3
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• pp.531-538
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• 2022

In Italy, buffalo mozzarella is a largely sold and consumed dairy product. The fraudulent adulteration of buffalo milk with cheaper and more available milk of other species is very frequent. In the present study, Fourier transform infrared spectroscopy (FTIR), in combination with multivariate analysis by partial least square (PLS) regression, was applied to quantitatively detect the adulteration of buffalo milk with cow milk by using a fully automatic equipment dedicated to the routine analysis of the milk composition. To enhance the heterogeneity, cow and buffalo bulk milk was collected for a period of over three years from different dairy farms. A total of 119 samples were used for the analysis to generate 17 different concentrations of buffalo-cow milk mixtures. This procedure was used to enhance variability and to properly randomize the trials. The obtained calibration model showed an R² ≥ 0.99 (R² cal. = 0.99861; root mean square error of cross-validation [RMSEC] = 2.04; R² val. = 0.99803; root mean square error of prediction [RMSEP] = 2.84; root mean square error of cross-validation [RMSECV] = 2.44) suggesting that this method could be successfully applied in the routine analysis of buffalo milk composition, providing rapid screening for possible adulteration with cow's milk at no additional cost.