• Journal of the Korean Society of Safety
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• v.29 no.3
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• pp.79-84
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• 2014

Human error is one of the major contributors to the accidents. A lot of risk assessment techniques have been developed for prevention of accidents. Nevertheless, most of them were interested in physical factors, because quantitative evaluation of human errors was difficult quantitatively. According to lack of risk assessment techniques about human errors, most of industrial risk assessment for human errors were based on data of accident analysis. In order to develop an effective countermeasure to reduce the risk caused by human errors, a systematic analysis is needed. Generally, risk assessment system is composed of 5 step(classification of work activity, identification of hazards, risk estimation, evaluation and improvement). This study aimed to develop a risk identification technique for human errors that could mainly be applied to industrial fields. In this study, Ergo-HAZOP and Comprehensive Human Error Analysis Technique were used for developing the risk identification technique. In the proposed risk identification technique, Ergo-HAZOP was used for broad-brush risk identification. More critical risks were analysed by Comprehensive Human Error Analysis Technique. In order to verify applicability, the proposed risk identification technique was applied to the work of pile head cutting. As a consequence, extensive hazards were identified and fundamental countermeasures were established. It is expected that much attention would be paid to prevent accidents by human error in industrial fields since safety personnel can easily fint out hazards of human factors if utilizing the proposed risk identification technique.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.142-148
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• 2016

Recently, human identification using various biological signals has been studied and human identification based on the gait has been actively studied. In this paper, we propose a human identification based on the EMG(Electromyography) signal of the thigh muscles that are used when walking. Various features such as RMS, MAV, VAR, WAMP, ZC, SSC, IEMG, MMAV1, MMAV2, MAVSLP, SSI, WL are extracted from EMG signal data and ANN(Artificial Neural Network) classifier is used for human identification. When we evaluated the recognition ratio per channel and features to select approptiate channels and features for human identification. The experimental results show that the rectus femoris, semitendinous, vastus lateralis are appropriate muscles for human identification and MAV, ZC, IEMG, MMAV1, MAVSLP are adaptable features for human identification. Experimental results also show that the average recognition ratio of method of using all channels and features is 99.7% and that of using selected 3 channels and 5 features is 96%. Therefore, we confirm that the EMG signal can be applied to gait based human identification and EMG signal based human identification using small number of adaptive muscles and features shows good performance.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.08a
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• pp.139-145
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• 2004

It is well known that human errors is involved in most of maritime accidents. For the purpose of reducing the influence of human elements on maritime activities, it is necessary to identify the human unsafe acts in those activities. The commonly used methods in identification of human unsafe acts are maritime accident statistics or case analysis. With the statistics data, people could roughly identify what kinds of unsafe acts or human errors have played active role in the accident, however, they often neglected some active unsafe acts while overestimated some mini-unsafe acts because of the inherent shortcoming of the methods. There should be some more accurate approaches for human error identification in maritime accidents. In this paper, the application of technique called grey relational analysis (GRA) into the identification of human unsafe acts is presented. GRA is used to examine the extent of connections between two digits by applying the, methodology of departing and scattering measurement to actual distance measurement. Based on the statistics data of maritime accidents occurred in Chinese waters in last 10years, the relationship between the happening times of maritime accidents and that of unsafe acts are established with GRA. In accordance with the value of grey relational grade, the identified main human unsafe acts involved in maritime accidents are ranked in following orders: improper lookout, improper use of radar and equivalent equipment, error of judgment, act not in time, improper communication, improper shiphandling, use of unsafe speed, violating the rule and ignorance of good seamanship. The result shows that GRA is an effective and practical technique in improving the accuracy of human unsafe acts identification.

• The Korean Journal of Legal Medicine
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• v.42 no.4
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• pp.141-145
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• 2018

There have been many radiographic studies on age estimation that evaluate reduction in size of dental pulp cavity with secondary dentin formation. The Paewinsky method reported high accuracy in estimating ages by measuring the width of the pulp cavity in panoramic radiographs. The aim of this study was to evaluate the application of the Paewinsky method to digital periapical radiographs. This study was conducted on 103 cases that reported to the Section of Human Identification of the National Forensic Service. The age was calculated by applying the Paewinsky method that measures the root and pulp canal width at three points in a tooth. The estimation results were compared with those calculated by the Johanson method. When the Paewinsky models were applied to digital periapical radiographs, the errors were significantly greater as compared to the original study. The errors of the maxillary second premolar and mandibular lateral incisor were greater than those of the maxillary central incisor, lateral incisor, mandibular canine, and first premolar. Furthermore, errors of the age estimation models in level C were greater than those in levels A and B. This study could be a reference for the application of the Paewinsky method to digital periapical radiographs.

• Biomedical Science Letters
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• v.24 no.4
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• pp.292-304
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• 2018

Microbes is becoming increasingly forensic possibility as a consequence of advances in massive parallel sequencing (MPS) and bioinformatics. Human DNA typing is the best identifier, but it is not always possible to extract a full DNA profile namely its degradation and low copy number, and it may have limitations for identical twins. To overcome these unsatisfactory limitations, forensic potential for bacteria found in evidence could be used to differentiate individuals. Prokaryotic cells have a cell wall that better protects the bacterial nucleoid compared to the cell membrane of eukaryotic cells. Humans have an extremely diverse microbiome that may prove useful in determining human identity and may even be possible to link the microbes to the person responsible for them. Microbial composition within the human microbiome varies across individuals. Therefore, MPS of human microbiome could be used to identify biological samples from the different individuals, specifically for twins and other cases where standard DNA typing doses not provide satisfactory results due to degradation of human DNA. Microbial forensics is a new discipline combining forensic science and microbiology, which can not to replace current STR analysis methods used for human identification but to be complementary. Among the fields of microbial forensics, this paper will briefly describe information on the current status of microbiome research such as metagenomic code, salivary microbiome, pubic hair microbiome, microbes as indicators of body fluids, soils microbes as forensic indicator, and review microbial forensics as the feasibility of microbiome-based human identification.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.149-154
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• 2015

Biometric techniques for authentication using body parts such as a fingerprint, face, iris, voice, finger-vein and also photoplethysmography have become increasingly important in the personal security field, including door access control, finance security, electronic passport, and mobile device. Finger-vein images are now used to human identification, however, difficulties in recognizing finger-vein images are caused by capturing under various conditions, such as different temperatures and illumination, and noise in the acquisition camera. The human photoplethysmography is also important signal for human identification. In this paper To increase the recognition rate, we develop camera based identification method by combining finger vein image and photoplethysmography signal. We use a compact CMOS camera with a penetrating infrared LED light source to acquire images of finger vein and photoplethysmography signal. In addition, we suggest a simple pattern matching method to reduce the calculation time for embedded environments. The experimental results show that our simple system has good results in terms of speed and accuracy for personal identification compared to the result of only finger vein images.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.903-909
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• 2018

We propose laser scanner sensor system based walking pattern and tracking method of multiple human. This system uses laser scanners sensors and is applicable to wide and crowded area such as hospital and medical care center. The primary objective of this research is to promote the development of robust, repeatable and transferable software for security system that can automatically detect, track and follow people in public area. We developed the method of human identification for this system. Our method is following: 1. Best-walking pattern data are obtained by the help of human position and direction data obtained by laser scanners. 2. Human identification is conducted by calculating the correlation between the step length of walking human. It becomes possible to conduct human identification even in crowded scenes by estimating the movements of waling human' feet are periodic. In the experiment in the station, some effectiveness of this method became clear.

• Biomedical Science Letters
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• v.15 no.3
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• pp.187-197
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• 2009

Fingerprinting is a frontier technique that is the most frequently applied for human identification throughout the world. All citizens over 17 year old living in the Republic of Korea must be fingerprinted to obtain a certificate of resident registration. In Korea, for this reason, human identification through fingerprints has been far better developed and used efficiently both in crime scene investigation and in confirmation of an unidentified body. Scientific approaches have been made to accurately extract the metamorphosed fingerprints in various environments. Because most of the studies on fingerprinting have been accomplished with biometric techniques, researches on restoration of human dermal tissue and taking custody data after collecting fingerprints have been comparatively undermined. In this study, a newly innovative method for fingerprint extraction was developed using the polyester film with print powders and the high temperature-moisturizing method. Compared to the conventional fingerprinting method of paper with ink, minutiae numbers of fingerprints were greatly increased in polyester film with print powders after restoration of fingertips by high temperature-moisturization. This newly developed procedure would be an efficient fingerprinting technique which could be utilized in scientific investigation and in personal identification in the future. Furthermore, the new method for restoration and extraction of fingerprints are easy and inexpensive to practice for a number of human identification.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.25 no.6
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• pp.522-531
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• 2016

In this study, we propose an object identification method for bin-picking developed for industrial robots. We identify the grasp posture and the associated geometric parameters of grasp objects using the joint data of a robotic gripper. Prior to grasp identification, we analyze the grasping motion in a low-dimensional space using principle component analysis (PCA) to reduce the dimensions. We collected the joint data from a human hand to demonstrate the grasp-identification algorithm. For data acquisition of the human grasp data, we conducted additional research on the motion characteristics of a human hand. We explain the method for using the algorithm of grasp identification for bin-picking. Finally, we present a subject for future research using our proposed algorithm of grasp model and identification.

• Journal of Preventive Medicine and Public Health
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• v.54 no.3
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• pp.218-219
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• 2021

The identification of human remains can be performed visually through families and next-of-kin, but it is not advisable to rely only on visual recognition; instead, it is preferable to conduct a forensic comparison of antemortem and postmortem data for primary identifiers (fingerprints, DNA, and dental data). A dental autopsy is particularly valuable in the identification process of skeletonized, carbonized, saponified, and fragmented human remains. The principal challenge in the identification process is the search and collection of antemortem data. To this end, all dental information held on a missing person can represent a precious source of individualizing information that families should share with the police or investigating agencies after reporting a disappearance.