• Journal of Navigation and Port Research
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• v.32 no.1
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• pp.103-108
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• 2008

In the maritime universities, cadets of deck part should practice on board training using training ships of university or merchant vessels of company for 1 year according to STCW Convention. For training period, trainees are educated many education items as to positioning ability, chart work ability, vessel operation ability and cargo operation ability etc. Among many abilities, vessel avoiding ability which is demanded as a basic ability for deck officer can't be gained easily, because avoiding maneuver of ship controlled by cadets is not allowable regally and encounter situations occur randomly. This paper investigated CPA to the various encounter types with other vessels during the ocean going navigation of T.S Hannara. We analysis danger degree per each encounter type, and proposed a basic material of efficient training education about proper look-out and avoiding maneuver.

• Journal of Korean Society of Forest Science
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• v.85 no.1
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• pp.15-23
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• 1996

Preparing the era of forest resources management requires studies on forest fire. This study attempted to develop forest fire occurrence model using meteorological characteristics for the practical purposes of forecasting forest fire danger rate. To accomplish this goal, the relationships between forest fire occurrence and meteorological characteristics are estimated. In the process, the forest fire occurrence pattern of the study region(Taegu-Kyungpook) is categorized by employing qualification IV method. The study region was divided into three areas such as, Taegu, Andong and Pohang area. The meteorological variables emerged as affective to forest fire occurrence are relative humidity, longitude of sunshine, and duration of precipitation. To estimate the probability of forest fire danger, forest fire occurrence of three areas are regressed on the time series data of affective meteorological variables using logistic and probit model. The effectiveness of the models estimated are tested and showed acceptable degree of goodness. Those models developed would be helpful to increase the efficiency of forest fire management such as detection of forest fire occurrence and effective disposition of forest fire fight equipments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.6098-6104
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• 2012

Currently, dozens of CCTVs are widely used in railway station for monitoring passengers in danger and security areas. The most frequent accidents occur at the platform area where passengers boarding the train. However, It is almost impossible that station operator monitors dozens of CCTV screens and recognizes immediately accidents and handle them. Therefore, railway platform monitoring system using image processing technology which automatically detects platform accidents is needed, and in order to that, preferentially, accurate determination of train state in the platform is required. In the paper, we propose train state detection algorithm for vision based railway platform monitoring system. the proposed algorithm determines four different states i.e. trains approach(IN), departure(OUT), stop(ON), and empty(OFF) of the train, in the platform. To evaluate the proposed algorithm, we present the train detection results for the Seoul Metro Line 4 Dongjak and Namtaeryeong Station.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.12
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• pp.54-61
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• 2011

We propose a surveillance-alert system based on optimal placements of PDR(Pulsed Doppler Radar) sensors in USN. By using the detection information of moving target from PDR sensor and by considering the covered detection region and geographical property of the strategic area, three optimal placements of sensors are proposed. The proposed placement are named as the grid type, the linear type and the zigzag type. Also, the surveillance alert system based on three sensor placements are developed. The alert level of the proposed surveillance-alert system are 'Perception', 'Caution', 'Warning' and 'Danger' which are decided by the distance change between the moving targets and the command post. The performace of the developed system is verified via outdoor experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1077-1085
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• 2020

In order to Mine Countermeasure (MCM), the search is carried out for the expected mine zone. At this time, mine hunting uses Autonomous Unmanned Vehicle(AUV), taking into account the danger of mine and the stability of our forces. Sonar system for identifying buried mines are equipped with Side Scan Sonar(SSS) or Synthetic Aperture Sonar(SAS). This paper describes the analysis of mine hunting effects according to the commercial SSS characteristics. Based on the characteristics of each SSS, the insonified area and recognition probability were modeled, and the analysis was performed according to the search pattern of the AUV. AUV's search pattern defines three patterns depending on the presence or absence of SSS or shaded areas. The analysis results derived search time and detection probability for each search pattern, and finally, the improvement of search depending on the presence or absence of side injection or shaded area.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.2
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• pp.45-50
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• 2021

With the recent development of IT technology, research and interest in various bio-signal measuring devices are increasing. But studies related to ECG(electrocardiogram), which is one of the most representative bio-signals, particularly arrhythmic signal detection, are incomplete. Since arrhythmia has various causes and has a poor prognosis after onset, preventive treatment through early diagnosis is best. However, the 24-hour Holter electrocardiogram, a tool for diagnosing arrhythmia, has disadvantages in the limitation of use time, difficulty in analyzing motion artifact due to daily life, and the user's real-time alarm function in danger. In this study, an ECG and pulse monitoring device capable of continuous measurement for a long time, a real-time monitoring app, and software for analysis were developed, and the trend of the measured values was confirmed. In future studies, research on derivation of quantitative results of ECG signal measurement analysis is required, and further research on the development of an arrhythmic signal detection algorithm based on this is required.

• Fashion & Textile Research Journal
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• v.24 no.5
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• pp.647-654
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• 2022

Wearable devices come in a variety of shapes and sizes in numerous fields in numerous fields and are available in various forms. They can be integrated into clothing, gloves, hats, glasses, and bags and used in healthcare, the medical field, and machine interfaces. These devices keep track individuals' biological and behavioral data to help with health communication and are often used for injury prevention. Those with hearing loss or impaired vision find it more difficult to recognize an approaching person or object; these sensing devices are particularly useful for such individuals, as they assist them with injury prevention by alerting them to the presence of people or objects in their immediate vicinity. Despite these obvious preventive benefits to developing Internet of Things based devices for the disabled, the development of these devices has been sluggish thus far. In particular, when compared with people without disabilities, people with hearing impairment have a much higher probability of averting danger when they are able to notice it in advance. However, research and development remain severely underfunded. In this study, we incorporated a wearable detection system, which uses an infrared proximity sensor, into a backpack. This system helps its users recognize when someone is approaching from behind through visual and tactile notification, even if they have difficulty hearing or seeing the objects in their surroundings. Furthermore, this backpack could help prevent accidents for all users, particularly those with visual or hearing impairments.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.3
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• pp.481-489
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• 2020

Safety and security during the handling of hazardous materials is a great concern for anyone in the field. One driving point in the security field is the ability to detect the source of the danger and take action against it as quickly as possible. Via the usage of a fully convolutional network, it is possible to create the label map of an input image, indicating what object is occupying the specific area of the image. This research employs the usage of U-net, which was constructed in biomedical field segmentation to segment cells, instead of the original FCN. One of the challenges that this research faces is the availability of ground truth with precise labeling for the dataset. Testing the network after training resulted in some images where the network pronounces even better detail than the expected label map. With better detailed label map, the network might be able to produce better segmentation is something to be studied in further research.

• Proceedings of the KIEE Conference
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• 1998.11c
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• pp.941-943
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• 1998

Exploitation of equipment with cross linked polyethylene (XLPE) insulation requires its condition monitoring and diagnostic. Traditionally diagnostics of insulation is carried out by means of partial discharge detection. Many researchers have developed a lot of methods to identify the defect by the PD form. However, such identification of a defect, for example, void, inclusion or treeing, does not say about its danger from a point of view of full insulation gap breakdown and insulation construction failure. The information about the form and size of formed upon high voltage treeing is necessary for prediction of the remained resource of XLPE insulation. For this purpose we carry out experimental research for determination of the dependencies between PD characteristics in XLPE upon time and three dimension PD patterns of corresponding treeing. The investigations were carried out by means of electrical measurement of PD current and simultaneous optical recording of treeing image. Test results show that the PD patterns can be applied for detecting tree growth well.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.580-585
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• 2005

A QRT(Quad-Rotor Type) hovering robot system is developed for quick detection and observation of the circumstances under calamity environment such as indoor fire spots. The UAV(Unmanned Aerial Vehicle) is equipped with four propellers driven by each electric motor, an embedded controller using a DSP, INS(Inertial Navigation System) using 3-axis rate gyros, a CCD camera with wireless communication transmitter for observation, and an ultrasonic range sensor for height control. The developed hovering robot shows stable flying performances under the adoption of RIC(Robust Internal-loop Compensator) based disturbance compensation and the vision based localization method. The UAV can also avoid obstacles using eight IR and four ultrasonic range sensors. The VTOL(Vertical Take-Off and Landing) flying object flies into indoor fire spots and sends the images captured by the CCD camera to the operator. This kind of small-sized UAV can be widely used in various calamity observation fields without danger of human beings under harmful environment.