• Journal of the Korean Society for Precision Engineering
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• v.18 no.11
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• pp.148-154
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• 2001

Drilling is one of the most important operations in machining industry and usually the most efficient and economical method of cutting a hole in metal. From automobile parts to aircraft components, almost every manufactured product requires that holes are to be drilled for the purpose of assembly, creation of fluid passages, and so on. It is therefore desirable to monitor drill wear and hole quality changes during the hole drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. A drill-wear monitoring system provides information about drill status. With the information, optimum planning for tool change is possible. And drill-wear monitoring system in needed to evaluated drilled hole quality and the wear of drill. Accordingly, this paper deals with an on-line drill wear monitoring system of the detection of tool wear with the computer vision and the area of the drill flank wear is analyzed quantitatively by the system.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.38-44
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• 2018

In this paper, we propose Intelligent Driver Assistance System (I-DAS) for driver safety. The proposed system recognizes safety and danger status by analyzing blind spots that the driver cannot see because of a large angle of head movement from the front. Most studies use image pre-processing such as face detection for collecting information about the driver's head movement. This not only increases the computational complexity of the system, but also decreases the accuracy of the recognition because the image processing system dose not use the entire image of the driver's upper body while seated on the driver's seat and when the head moves at a large angle from the front. The proposed system uses a convolutional neural network to replace the face detection system and uses the entire image of the driver's upper body. Therefore, high accuracy can be maintained even when the driver performs head movement at a large angle from the frontal gaze position without image pre-processing. Experimental result shows that the proposed system can accurately recognize the dangerous conditions in the blind zone during operation and performs with 95% accuracy of recognition for five drivers.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.2
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• pp.148-156
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• 2003

Many car manufacturers have frequently adopted an aggressive inflator and a lower threshold speed for airbag deployment in order to meet an injury requirement for unbolted occupant at high speed crash test. Consequently, today's occupant safety restraint system has a weakness due to an airbag induced injury at low speed crash event. This paper proposes a new crash algorithm to improve the weakness by suppressing airbag deployment at low speed crash event in case of belted condition. The proposed algorithm consists of two major blocks-crash severity algorithm and deployment logic block. The first block decides crash severity with two levels by means of velocity and crash energy calculation from acceleration signal. The second block implemented by simple AND/OR logic combines the crash severity level and seat belt status information to generate firing commands for airbag and belt pretensioner. Furthermore, it can be extended to adopt additional sensor information from passenger presence detection sensor and safing sensor. A simulation using real crash data for a 1,800cc passenger vehicle has been conducted to verify the performance of proposed algorithm.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.1
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• pp.9-17
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• 2022

Rural spaces are increasingly valuable as areas for introducing renewable energy infrastructure to achieve carbon neutrality. Rural areas are the living grounds of rural residents, and the balance of conservation and development for rural areas is important for the introduction of reasonable facilities. In order to maintain a balance between development and preservation and to introduce reasonable renewable energy facilities, it is necessary to develop a current status survey and an effective survey method to utilize a space capable of introducing renewable energy facilities such as idle land and vacant houses. Therefore, this study was conducted to verify the readability using an unmanned aerial vehicle, and the main results are as follows. The detection of photovoltaic power generation facilities using unmanned aerial vehicles was effective in analyzing the location and area of photovoltaic panels located on the roofs of buildings, and it was possible to calculate the expected power generation by region through the area calculation of photovoltaic panels. The vacant house detection can be used to select an investigation target for an vacant house condition survey as it can identify damage to buildings that are expected to be empty houses, management status, and electricity supply facilities through aerial photos. It is judged that the unmanned aerial vehicle detection capability can be utilized as a method to improve the efficiency of investigation and supplement the data related to solar power generation facilities and vacant houses provided by public institutions. Although this study detected the status of solar power generation facilities and vacant houses through high-resolution aerial image analysis, as a follow-up study, automatic measurement methods using the temperature difference of solar power generation facilities and general characteristics of vacant houses that can be read from the air were investigated. If the deriving research is carried out, it is judged that it will be possible to contribute to the improvement of the accuracy of the detection result using the unmanned aerial vehicle and the expansion of the application range.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.11
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• pp.4377-4384
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• 2014

According to the World Health Organization (WHO), 1.37 million people died of lung cancer all around the world in 2008, occupying the first place in all cancer-related deaths. However, this number might be decreased if patients were detected earlier and treated appropriately. Unfortunately, traditional imaging techniques are not sufficiently satisfactory for early detection of lung cancer because of limitations. As one alternative, breath volatile organic compounds (VOCs) may reflect the biochemical status of the body and provide clues to some diseases including lung cancer at early stage. Early detection of lung cancer based on breath analysis is becoming more and more valued because it is non-invasive, sensitive, inexpensive and simple. In this review article, we analyze the limitations of traditional imaging techniques in the early detection of lung cancer, illustrate possible mechanisms of the production of VOCs in cancerous cells, present evidence that supports the detection of such disease using breath analysis, and summarize the advances in the study of E-noses based on gas sensitive sensors. In conclusion, the analysis of breath VOCs is a better choice for the early detection of lung cancer compared to imaging techniques. We recommend a more comprehensive technique that integrates the analysis of VOCs and non-VOCs in breath. In addition, VOCs in urine may also be a trend in research on the early detection of lung cancer.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.17
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• pp.7079-7083
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• 2014

The International Prostate Symptom Score (IPSS) is often used as an interview sheet for assessing lower urinary tract symptoms (LUTS) at the time of prostate-specific antigen (PSA) testing during population-based screening for prostate cancer. However, the relationship between prostate cancer detection and LUTS status remains controversial. To elucidate this relationship, the cumulative probability of prostate cancer detection using IPSS in biopsy samples from patients categorized by serum PSA levels was investigated. The clinical characteristics of prostate cancer detected using IPSS during screening were also investigated. A total of 1,739 men aged 54-75 years with elevated serum PSA levels who completed the IPSS questionnaire during the initial population screening in Kanazawa City, Japan and underwent systematic transrectal ultrasonography-guided prostate biopsy between 2000 and 2013 were enrolled in the present study. Of the 1,739 men, 544 (31.3%) were diagnosed with prostate cancer during the observation period. The probability of cancer detection at 3 years in the entire study population was 27.4% and 32.7% for men with $IPSS{\leq}7$ and those with $IPSS{\geq}8$, respectively; there was no statistically significant difference between groups. In men with serum PSA levels of 6.1 to 12.0ng/mL at initial screening, the probability of cancer detection was significantly higher in men with $IPSS{\leq}7$ than in those with $IPSS{\geq}8$. There were no significant differences in clinical characteristics between groups of patients stratified by IPSS. These findings indicate that the use of IPSS for LUTS status evaluation may be useful for prostate cancer detection in the limited range of serum PSA levels.

• Annual Conference of KIPS
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• 2001.10b
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• pp.1355-1358
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• 2001

IP Multicast can efficiently provide enormous bandwidth savings by enabling sources to send a single copy of a message to multiple recipients who explicitly want to receive the information. But due to the complexity of IP multicast and its fundamental differences from unicast, there are not very many tools available fer monitoring and debugging multicast networks, and only a few experts understand the tools that do exist. This thesis proposes a Multicast Routing Debugger (MRD) system that monitor the status of a multicast network. This system is aimed to multicast-related faults detection. In thesis, first, we define the set of information that should be monitored. Second, the method is developed to take out such information from multicast routers. Third, MRD system is prototyped to collect, process information from heterogeneous routers on a multicast network and to display the various status of the network comprehensively. The prototype of MRD system is implemented and deployed. We perform experiments with several scenarios. Experimental results show we can detect various problems as information that we define is monitored. The MRD system is simple to use, web-based and intuitive tool that can monitor the status of a specific multicast network.

• Genomics & Informatics
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• v.6 no.3
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• pp.136-141
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• 2008

A large number of studies have been performed to identify biomarkers that will allow efficient detection and determination of the precise status of a patient’s disease. The use of microarrays to assess biomarker status is expected to improve prediction accuracies, because a whole-genome approach is used. Despite their potential, however, patient samples can differ with respect to biomarker status when analyzed on different platforms, making it more difficult to make accurate predictions, because bias may exist between any two different experimental conditions. Because of this difficulty in experimental standardization of microarray data, it is currently difficult to utilize microarray-based gene sets in the clinic. To address this problem, we propose a method that predicts disease status using gene expression data that are transformed by their ranks, a concept that is easily applied to two datasets that are obtained using different experimental platforms. NCI and colon cancer datasets, which were assessed using both Affymetrix and cDNA microarray platforms, were used for method validation. Our results demonstrate that the proposed method is able to achieve good predictive performance for datasets that are obtained under different experimental conditions.

• Journal of the Korea Safety Management & Science
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• v.23 no.3
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• pp.27-33
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• 2021

The purpose of this study is to present a novel indicator for analyzing machine failure based on its idle time and productivity. Existing machine repair plan was limited to machine experts from its manufacturing industries. This study evaluates the repair status of machines and extracts machines that need improvement. In this study, F-RPN was calculated using the etching process data provided by the 2018 PHM Data Challenge. Each S(S: Severity), O(O: Occurence), D(D: Detection) is divided into the idle time of the machine, the number of fault data, and the failure rate, respectively. The repair status of machine is quantified through the F-RPN calculated by multiplying S, O, and D. This study conducts a case study of machine in a semiconductor etching process. The process capability index has the disadvantage of not being able to divide the values outside the range. The performance of this index declines when the manufacturing process is under control, hereby introducing F-RPN to evaluate machine status that are difficult to distinguish by process capability index.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.5
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• pp.662-673
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• 2012

This study introduces a condition diagnosis technique for a turbine governor system. The governor system is an important control system to handle turbine speed in a nuclear power plant. The turbine governor system includes turbine valves and stop valves which have their own functions in the system. Because a turbine governor system is operated by high oil pressure, it is very difficult to maintain under stable operating conditions. Turbine valves supply oil pressure to the governor system for proper operation. Using the pressure variation of turbine and governor valves, operating conditions of the turbine governor control system are detected and identified. To achieve automatic detection of valve status, time-based and frequency-based analysis is employed. In this study, a new approach, wavelet decomposition, was used to extract specific features from the pressure signals of the governor and stop valves. The extracted features, which represent the operating conditions of the turbine governor system, include important information to control and diagnose the valves. After extracting the specific features, decision rules were used to classify the valve conditions. The rules were generated by a decision tree algorithm (a typical simple method for data-based rule generation). The results given by the wavelet-based analysis were compared to detection results using time- and frequency-based approaches. Compared with the several related studies, the wavelet transform-based analysis, the proposed in this study has the advantage of easier application without auxiliary features.