• Journal of the Ergonomics Society of Korea
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• v.36 no.3
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• pp.221-230
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• 2017

Objective: The purpose of this study is to draw the accident prevention model using the signal detection theory, and to implement accident prevention program, based on a health promotion and support activities in a shipbuilding company. Background: Workers' health management is perceived important from the human resource management perspective, as well as from the personal perspective. Method: This study developed an accident prevention model by analyzing the correlation between 704 workers' health examination variables, and reviewed the verification of the model through a follow-up survey on the control variables and status of hazards targeting 650 workers for four years from 2007 to 2010. Also, a health promotion program was implemented targeting a production division to improve alcohol habits, smoking, musculoskeletal pain complaints and hearing control indices, which are the control variables of the model. Results: As a result of four years' implementation, the following effects were obtained: the days away from work fell 87.5%, and accident rate dropped 71.5% in 2010, respectively, compared to 2006, before the activity was implemented. Conclusion: This study shows that the accident prevention activities based on workers' health promotion activities are effective to prevent industrial accidents and injuries. Application: The research findings will serve as a practical guideline for establishing preventive measures in the shipbuilding company.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.4
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• pp.312-319
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• 2014

When distributed generation such as a wind power system is connected to the grid, it should meet grid requirements like IEEE Std. 1547, which regulates the anti-islanding method. Since the islanding may cause damage on electrical equipments or safety hazards for utility line worker, a distributed generation should detect it as soon as possible. This paper proposes a hybrid anti-islanding method coupled with the active and passive detection methods. To enhance the harmonic extraction capability for an active harmonic injection method, cascaded second-order band-pass filter and signal processing scheme are employed. Simulation and experiments are carried out under the islanding test condition specified in IEEE Std. 1547. Passive over/under voltage and over/under frequency methods are combined with the active method to improve the detection speed under certain condition. The simulation and experimental results are presented to verify that the proposed hybrid anti-islanding method can effectively detect the islanding.

• Molecules and Cells
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• v.40 no.1
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• pp.45-53
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• 2017

Aberrant hypermethylation of Wnt antagonists has been observed in gastric cancer. A number of studies have focused on the hypermethylation of a single Wnt antagonist and its role in regulating the activation of signaling. However, how the Wnt antagonists interacted to regulate the signaling pathway has not been reported. In the present study, we systematically investigated the methylation of some Wnt antagonist genes (SFRP2, SFRP4, SFRP5, DKK1, DKK2, and APC) and their regulatory role in carcinogenesis. We found that aberrant promoter methylation of SFRP2, SFRP4, DKK1, and DKK2 was significantly increased in gastric cancer. Moreover, concurrent hypermethylation of SFRP2 and DKK2 was observed in gastric cancer and this was significantly associated with increased expression of ${\beta}-catenin$, indicating that the joint inactivation of these two genes promoted the activation of the Wnt signaling pathway. Further analysis using a multivariate Cox proportional hazards model showed that DKK2 methylation was an independent prognostic factor for poor overall survival, and the predictive value was markedly enhanced when the combined methylation status of SFRP2 and DKK2 was considered. In addition, the methylation level of SFRP4 and DKK2 was correlated with the patient's age and tumor differentiation, respectively. In conclusion, epigenetic silencing of Wnt antagonists was associated with gastric carcinogenesis, and concurrent hypermethylation of SFRP2 and DKK2 could be a potential marker for a prognosis of poor overall survival.

• Smart Structures and Systems
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• v.31 no.1
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• pp.13-27
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• 2023

Fatigue crack is a fatal problem for steel structures. Early detection and maintenance can help extend the service life and prevent hazards. This paper presents the ultrasonic guided waves-based (UGWs-based) fatigue crack detection of a steel I-beam. The semi-analytical finite element model has been built to obtain the wave propagation characteristics. Damage indices in both time and frequency domains were analyzed by considering the characteristic variations of UGWs including the amplitude, phase angle, and wave packet energy. The pulse-echo and pitch-catch methods were combined in the detection scheme. Lab-scale experiments were conducted on welded steel I-beams to verify the proposed method. Results show that the damage indices based on the characteristic variations in the time domain can identify and localize the fatigue crack before it enters the rapid growth stage. The damage severity can be reasonably evaluated by analyzing the time-domain damage indices. Two nonlinear damage indices in the frequency domain give earlier warnings of the fatigue crack than the time-domain damage indices do. The identification results based on the above two nonlinear indices are found to be less consistent under various excitation frequencies. More robust nonlinear techniques needed to be searched and tested for early crack detection in steel I-beams in further study.

• The KIPS Transactions:PartB
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• v.18B no.4
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• pp.213-220
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• 2011

This paper proposes an effective, four-stage smoke detection method based on video that provides emergency response in the event of unexpected hazards in early fire-alarming systems. In the first phase, an approximate median method is used to segment moving regions in the present frame of video. In the second phase, a color segmentation of smoke is performed to select candidate smoke regions from these moving regions. In the third phase, a feature extraction algorithm is used to extract five feature parameters of smoke by analyzing characteristics of the candidate smoke regions such as area randomness and motion of smoke. In the fourth phase, extracted five parameters of smoke are used as an input for a K-nearest neighbor (KNN) algorithm to identify whether the candidate smoke regions are smoke or non-smoke. Experimental results indicate that the proposed four-stage smoke detection method outperforms other algorithms in terms of smoke detection, providing a low false alarm rate and high reliability in open and large spaces.

• Journal of Food Hygiene and Safety
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• v.34 no.1
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• pp.1-12
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• 2019

The health benefits associated with consumption of fresh produce have been clearly demonstrated and encouraged by international nutrition and health authorities. However, since fresh produce is usually minimally processed, increased consumption of fresh fruits and vegetables has also led to a simultaneous escalation of foodborne illness cases. According to the report by the World Health Organization (WHO), 1 in 10 people suffer from foodborne diseases and 420,000 die every year globally. In comparison to other processed foods, fresh produce can be easily contaminated by various routes at different points in the supply chain from farm to fork. This review is focused on the identification and characterization of possible sources of foodborne illnesses from chemical, biological, and physical hazards and the applicable methodologies to detect potential contaminants. Agro-chemicals (pesticides, fungicides and herbicides), natural toxins (mycotoxins and plant toxins), and heavy metals (mercury and cadmium) are the main sources of chemical hazards, which can be detected by several methods including chromatography and nano-techniques based on nanostructured materials such as noble metal nanoparticles (NMPs), quantum dots (QDs) and magnetic nanoparticles or nanotube. However, the diversity of chemical structures complicates the establishment of one standard method to differentiate the variety of chemical compounds. In addition, fresh fruits and vegetables contain high nutrient contents and moisture, which promote the growth of unwanted microorganisms including bacterial pathogens (Salmonella, E. coli O157: H7, Shigella, Listeria monocytogenes, and Bacillus cereus) and non-bacterial pathogens (norovirus and parasites). In order to detect specific pathogens in fresh produce, methods based on molecular biology such as PCR and immunology are commonly used. Finally, physical hazards including contamination by glass, metal, and gravel in food can cause serious injuries to customers. In order to decrease physical hazards, vision systems such as X-ray inspection have been adopted to detect physical contaminants in food, while exceptional handling skills by food production employees are required to prevent additional contamination.

• KIEE International Transactions on Power Engineering
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• v.3A no.4
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• pp.191-197
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• 2003

Accurate detection and classification of faults on transmission lines is vitally important. In this respect, many different types of faults occur, such as inter alia low impedance faults (LIF) and high impedance faults (HIF). The latter in particular pose difficulties for the commonly employed conventional overcurrent and distance relays, and if undetected, can cause damage to expensive equipment, threaten life and cause fire hazards. Although HIFs are far less common than LIFs, it is imperative that any protection device should be able to satisfactorily deal with both HIFs and LIFs. Because of the randomness and asymmetric characteristics of HIFs, their modeling is difficult and numerous papers relating to various HIF models have been published. In this paper, the model of HIFs in transmission lines is accomplished using the characteristics of a ZnO arrester, which is then implemented within the overall transmission system model based on the electromagnetic transients program (EMTP). This paper proposes an algorithm for fault detection and classification for both LIFs and HIFs using Adaptive Network-based Fuzzy Inference System (ANFIS). The inputs into ANFIS are current signals only based on Root-Mean-Square (RMS) values of 3-phase currents and zero sequence current. The performance of the proposed algorithm is tested on a typical 154 kV Korean transmission line system under various fault conditions. Test results demonstrate that the ANFIS can detect and classify faults including LIFs and HIFs accurately within half a cycle.

• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.76-80
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• 2018

In recent years, with the development of automobile technology, smart system technology that assists safe driving has been developed. A camera is installed on the front and rear of the vehicle as well as on the left and right sides to detect and warn of collision risks and hazards. Beyond the technology of simple black-box recording via cameras, we are developing intelligent systems that combine various computer vision technologies. However, most related studies have been developed to optimize performance in laboratory-like environments that do not take environmental factors such as weather into account. In this paper, we propose a method to detect object by restoring visibility in image with degraded image due to weather factors such as fog. First, the image quality degradation such as fog is detected in a single image, and the image quality is improved by restoring using an intermediate value filter. Then, we used an adaptive feature extraction method that removes unnecessary elements such as noise from the improved image and uses it to recognize objects with only the necessary features. In the proposed method, it is shown that more feature points are extracted than the feature points of the region of interest in the improved image.

• Fire Science and Engineering
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• v.29 no.4
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• pp.39-48
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• 2015

This research was done to develop a duct-dedicated intelligent fire detection system to prevent fires and minimize fire damage of the industrial duct having a high fire risk. To understand the fire hazards of the ducts, the analysis was centered on the Daegu Textile Industrial Complex, where industrial ducts are used frequently. With this in the background, dedicated fire detectors and fire alarm control panel, which can prevent fires and to minimize fire damages to the ducts, were designed and produced, after which the performance was confirmed. As a result of performance experiments, it was shown that a duct-dedicated intelligent fire detection system had excellent adaptability and temperature accuracy. Through real-time temperature monitoring of the inside of the ducts, it was confirmed that duct fires could be efficiently extinguished by stepwise control of linkage facilities according to the setting temperature.

• Food Science of Animal Resources
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• v.30 no.4
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• pp.590-596
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• 2010

Meat and meat products are a potential source of food-borne pathogens, including Staphylococcus aureus, Salmonella spp., Escherichia coli O157:H7, and Bacillus cereus. A sensitive and specific PCR assay for the detection of these pathogens in meat and meat products was developed in this study, as part of a broader effort to reduce the potential health hazards posed by these pathogens. Initially, PCR conditions were standardized with purified DNA. Under standard conditions, the detection level for PCR was as low as 10 pg of purified bacterial DNA. After overnight growth of bacteria in a broth medium, as few as $10^2$ CFU of bacteria were detected by PCR assay. The primers employed in the PCR assay were found to be highly specific for individual organisms, and evidenced no cross-reactivity with heterologous organisms. Additionally, the multiplex PCR assays also amplified some target genes from the four pathogens, and multiplex amplification was obtained from as little as 10 pg of DNA, thus illustrating the excellent specificity and high sensitivity of the assay. In conclusion, this PCR-based technique provides a sensitive and specific method for the detection of S. aureus, Salmonella spp., E. coli O157:H7, and B. cereus in meat and meat products.