• The KIPS Transactions:PartB
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• v.11B no.7 s.96
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• pp.821-830
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• 2004

In this paper, we model the downward collision of a falling object to the base. We aim to provide maximum diversity of response to physical. collision. To this end, the primary design concern of the model is to unfold the collision phenomenon in a logical and natural manner, detailed enough to construct an immersive virtual environment. To achieve these requirements, first we determine domains for the characteristic of the material of the falling objects, and select the dominant force of the collision. We formulate the collision phenomena with combination of primitive attributes and their relationships. The formulated function evaluates the results of the collision in qualitative aspects as well as in quantitative aspects. Between the collision issues, 'Collision Detection' and 'Collision Response', this paper focuses on Collision Response issue.

• Journal of East-West Nursing Research
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• v.28 no.2
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• pp.122-131
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• 2022

Purpose: This study aimed to identify the factors related to fear of falling (FOF) in different age groups from community-dwelling mid to late-adults. Methods: To identify the factors related to FOF, data of 162,684 adults over 45 years of age from 2019 Community Health Survey was analyzed using logistic regression with complex samples. Results: Factors related to FOF found in all age groups were sex, previous experience of falls, physical activity levels over moderate intensity, subjective health status, number of chronic diseases, stress, depression, and cognitive decline. In the 45-64 age group, the FOF was significantly higher in the groups of low education level and low monthly household income. In the 65-74 and over 75 age groups, the FOF was significantly higher in the groups of not living with spouse and walking not practiced. Conclusion: We suggests that understanding of risk factors and early detection of fall risk patients in each age group are necessary to establish and apply tailored fall prevention programs for prevention and management of the FOF in community-dwelling mid to late-adults.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1325-1334
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• 2016

The video incident detection System is a probe for rapid detecting the walker, falling, stopped, backwards, smoke situation in tunnel. Recently, the importance is increases from the downtown double deck tunnel in great depth underground space[1], but the legal basis is weak and the vulnerable situation experimental data. So, In this paper, we introduce a long-term log data analysis information in the tunnenl video incident detection system installed and experimental results in order to verify the feasibility of apply to video incident detection system for the double deck tunnel. It is proposed a few things about derives the problem of existing video incident detection system, improvements and reflect attributes for double deck tunnel. The contents described in this paper will contribute to refine the prototype of video incident detection system will apply to future double deck multi-layer tunnels.

• Journal of Internet Computing and Services
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• v.13 no.4
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• pp.23-31
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• 2012

Nowadays, recognizing human activities is an important subject; it is exploited widely and applied to many fields in real-life, especially in health care and context aware application. Research achievements are mainly focused on activities of daily living which are useful for suggesting advises to health care applications. Falling event is one of the biggest risks to the health and well-being of the elderly especially in independent living because falling accidents may be caused from heart attack. Recognizing this activity still remains in difficult research area. Many systems equipped wearable sensors have been proposed but they are not useful if users forget to wear the clothes or lack ability to adapt themselves to mobile systems without specific wearable sensors. In this paper, we develop a novel method based on analyzing the change of acceleration, orientation when the fall occurs and measure their similarity to featured fall patterns. In this study, we recruit five volunteers in our experiment including various fall categories. The results are effective for recognizing fall activity. Our system is implemented on G1 smart phone which are already plugged accelerometer and orientation sensors. The popular phone is used to get data from accelerometer and results showthe feasibility of our method and significant contribution to fall detection.

• Journal of the Semiconductor & Display Technology
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• v.15 no.1
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• pp.27-32
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• 2016

A new lane detection algorithm is proposed for the analysis of DNA fingerprints from a polymerase chain reaction (PCR) gel electrophoresis image. Although several research results have been previously reported, it is still challenging to extract lanes precisely from images having abrupt background brightness difference and bent lanes. We propose an edge based algorithm for calculating the average lane width and lane cycle. Our method adopts sub-pixel algorithm for extracting rising-edges and falling edges precisely and estimates the lane width and cycle by using k-means clustering algorithm. To handle the curved lanes, we partition the gel image into small portions, and track the lane centers in each partitioned image. 32 gel images including 534 lanes are used to evaluate the performance of our method. Experimental results show that our method is robust to images having background difference and bent lanes without any preprocessing.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.97-113
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• 2023

Swift and appropriate responses in emergency situations like objects falling on the road can bring convenience to road users and effectively reduces secondary traffic accidents. In Korea, current intelligent transportation system (ITS)-based detection systems for emergency road situations mainly rely on loop detectors and CCTV cameras, which only capture road data within detection range of the equipment. Therefore, a new detection method is needed to identify emergency situations in spatially shaded areas that existing ITS detection systems cannot reach. In this study, we propose a ResNet-based algorithm that detects and classifies emergency situations from vehicle camera footage. We collected front-view driving videos recorded on Korean highways, labeling each video by defining the type of emergency, and training the proposed algorithm with the data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1794-1799
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• 2022

Recently, the increasing number of overloaded vehicles on the road poses a risk to traffic safety, such as falling objects, road damage, and chain collisions due to the abnormal weight distribution, and can cause great damage once an accident occurs. therefore we propose to build an object detection-based AI model to identify overloaded vehicles that cause such social problems. In addition, we present a simple yet effective method to construct an object detection model for the large-scale vehicle images. In particular, we utilize the large-scale of vehicle image sets provided by open AI-Hub, which include the overloaded vehicles. We inspected the specific features of sizes of vehicles and types of image sources, and pre-processed these images to train a deep learning-based object detection model. Also, we propose an integrated system for tracking the detected vehicles. Finally, we demonstrated that the detection performance of the overloaded vehicle was improved by about 23% compared to the one using raw data.

• Journal of dental hygiene science
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• v.4 no.1
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• pp.7-11
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• 2004

The purpose of this study was to investigate the distribution of microorganisms and the degree of contamination in the air of the dental clinics and to offer basic data as to the contamination of medical equipment and the prevention of the clinics. With this in mind, the researcher gathered air samples from the waiting rooms and medical offices of nine dental clinics in the city of J, South Korea with the use of a method of natural inattention and an air sampler and cultivated the samples on the plain table and drew from it bacteria falling and separated and sorted out the colony with the help of ATB and detected the distribution of the germs. The results are following, The number of bacteria falling in the air of the dental clinics was less than 10(CFU/Plate) with the exception of one dental clinic. This implies that they fit in with standards for hygiene. The number of bacteria falling in the air of the medical offices was less than 10(CFU/Plate) with the exception of one dental clinic. This implies that they fit in with standards for hygiene. The survey on the detection of staph. aureus reveals that all the dental clinics with the exception of B dental clinic proving to be positive had non-pathogenic staphylococci detected. The survey on the detection of pathogenic gram negative bacilli indicates that all the dental clinics but one were none detected. The survey on the distribution of germs shows that germs in 7 out of 9 dental clinics were none detected, and that they in four out of 9 waiting rooms were none detected. All the germs detected in the others were mostly non-pathogenic. The study shows that all the subject dental clinics but one were hygienically controlled and that there was a difference in accordance with cleaning and sterilization. This means that dental clinics should be equipped with systematic programs for cleaning and sterilization designed to prevent infection.

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.6
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• pp.584-591
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• 2000

Power Quality Compensator(PQC) has been installed to protect the sensitive loads against the voltage disturbances, such as voltage sag and interruption. In general, static switch is used for the purpose of link between utility and PQC. So transfer operation of the static switch play a important part in the PQC. Many studies on the structure and control of PQC have been progressed in active, but these researches have been rarely mentioned about any voltage-disturbances-detection method to start the PQC operation. In this paper, a new voltage-disturbances-detection algorithm for computer application loads using the CBEMA/ITIC curve is proposed for transfer operation of the static switch. The proposed detection algorithm is implemented to get fast detecting time through the comparison of instantaneous 3-phase voltage values transferred to DC values in the synchronous reference frame with the operating reference values. To get the robust characteristics against the noise, a first order digital filter is designed. The magnitude falling and phase delay caused by the filter are compensated through the error normalizing and numerical analysis using transfer function, respectively. Finally, the validity of the proposed algorithm is proved by ACSL simulation and experimental results.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.407-417
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• 2019

When a free-falling ballistic missile intercepts a maritime target in a sea clutter environment at high grazing angle, detection performance of the ballistic missile's seeker can be rapidly degraded by the effect of sea clutter. To solve this problem, it is necessary to verify the performance of maritime target detection via simulations based on various scenarios. We accomplish this by applying a two-dimensional cell -averaging constant false alarm rate detector to a two-dimensional radar image, which is generated by merging a sea clutter signal at high grazing angle with a maritime target signal corresponding to the signal-to-clutter ratio. Simulation results using a computer-aided design model and commercial numerical electromagnetic solver in various scenarios show that the performance of maritime target detection significantly depends on the grazing and azimuth angles.