• Annual Conference of KIPS
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• 2009.11a
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• pp.465-466
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• 2009

This paper investigates congestion detection and control strategies for multi-path traffic (CDCM) diss emination in lifetime-constrained wireless sensor networks. CDCM jointly exploits packet arrival rate, succ essful packet delivery rate and current buffer status of a node to measure the congestion level. Our objec tive is to develop adaptive traffic rate update policies that can increase the reliability and the network lif etime. Our simulation results show that the proposed CDCM scheme provides with good performance.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.102-107
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• 2015

In this paper, we propose a technique of drowsiness detection using a histogram for vehicle safety. The drowsiness of vehicle drivers is often the main cause of many vehicle accidents. Therefore, the checking of eye images in order to detect the drowsiness status of a driver is very important for preventing accidents. In our suggested method, we analyse the changes of a histogram of eye region images which are acquired using a CCD camera. We develop a drowsiness detection system using this histogram change information. The experimental results show that the proposed method enhances the accuracy of detecting drowsiness to nearly 97%, and can be used to prevent accidents due to driver drowsiness.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.2
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• pp.96-102
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• 2011

There are many problems with the fire detection devices being used in currently, because it is difficult to find location of the source of fire and determine where devices are working or not. In this paper, we proposed fire detection and rescue system using wireless sensor network that can be real-time monitoring and determine safe exit. Fire detection and rescue system based on ubiquitous sensor network can know exactly source of fire and help determine rescue tactics using sensing data from wireless sensor nodes. Transmitted wirelessly in real-time thermal sensor and gas sensor information to analyze the GUI to monitor the status information output to the screen by use of a system implemented in everyday life, looked at the possibility.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.46-48
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• 2007

This paper presents research about improvement of fault detection algorithm in FRTU on the feeder of distribution system. FRTU(Feeder Remote Terminal Unit) is applied to fault detection schemes for phase fault, ground fault, and cold load pickup and Inrush restraint functions distinguish the fault current and the normal load current. FRTU is occurred FI(Fault Indicator) when current is over pick-up value also inrush current is occurred FRTU indicate FI. Discrete wavelet transform(DWT) analysis gives the frequency and time-scale information. The neural network system as a fault detector was trained to discriminate inrush current from the fault status by a gradient descent method. In this paper, fault detection is improved using voltage monitoring system with DWT and neural network. These data were measured in actual 22.9kV distribution system.

• Journal of Microbiology and Biotechnology
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• v.25 no.11
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• pp.1773-1781
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• 2015

Environmental security is one of the major concerns for the safety of living organisms from a number of harmful pollutants in the atmosphere. Different initiatives, legislative actions, as well as scientific and social concerns have been discussed and adopted to control and regulate the threats of environmental pollution, but it still remains a worldwide challenge. Therefore, there is a need for developing certain sensitive, rapid, and selective techniques that can detect and screen the pollutants for effective bioremediation processes. In this perspective, isolated enzymes or biological systems producing enzymes, as whole cells or in immobilized state, can be used as a source for detection, quantification, and degradation or transformation of pollutants to non-polluting compounds to restore the ecological balance. Biosensors are ideal for the detection and measurement of environmental pollution in a reliable, specific, and sensitive way. In this review, the current status of different types of microbial biosensors and mechanisms of detection of various environmental toxicants are discussed.

• Korean Journal of Veterinary Service
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• v.39 no.1
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• pp.35-39
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• 2016

The purpose of this study was to survey on infection status of pathogens of diarrhea from Korean indigenous goat. A total of 800 fecal samples was collected from 50 farms from January to October 2015 and was tested by automatic biochemical machine and polymerase chain reaction (PCR). The overall detection ratio of bacterial pathogens was 22.4% and viral pathogens was 16.3%, respectively. The detection ratio of Escherichia coli (E. coli), Salmonella spp., bovine viral diarrhea virus (BVDV), rotavirus and coronavirus were 21.5%, 0.9%, 7.6%, 5.6% and 3.0%, respectively. In the rates of mixed detection, single was 78.2%, double 8.4%, triple 11.6% and quadruple 1.8% in each sample and 38%, 12%, 16%, 20% in each farm, respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.344-352
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• 2005

The modem production systems are required to produce many items. This is due to the fact that society has become more complex and the customers' demands have become more varied. The demand for complex production systems of various purposes, which can flexibly change the content of work, has increased. One of such production systems is FMS (Flexible Manufacturing System). Limited resources must be used in FMS when a number of working procedures are simultaneously being undertaken because the conditions of stand-by job processes cannot be changed. Researchers are currently being conducted to determine ways of preventing deadlocks. In this study, we proposes the algorithm for detection and recovery of a deadlock status using the DDAPN(Deadlock Detection Avoidance Petri Net). Also, we apply the proposed algorithm has a feature to the FMS.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.173-174
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• 2023

In this paper, we introduce a model for detecting Personal Protective Equipment (PPE) using YOLO (You Only Look Once), an object detection neural network. PPE is used to maintain a safe working environment, and proper use of PPE protects workers' safety and health. However, failure to wear PPE or wearing it improperly can cause serious safety issues. Therefore, a PPE detection system is crucial in industrial settings.

• Journal of Korea Multimedia Society
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• v.19 no.11
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• pp.1852-1861
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• 2016

Drowsy driving is a significant factor in traffic accidents, so driver drowsiness detection system based on computer vision for convenience and safety has been actively studied. However, it is difficult to accurately detect the driver drowsiness in complex background and environmental change. In this paper, it proposed the driver drowsiness detection algorithm to determine whether the driver is drowsy through the measurement standard of a yawn, eyes drowsy status, and nod based on facial features. The proposed algorithm detect the driver drowsiness in the complex background, and it is robust to changes in the environment. The algorithm can be applied in real time because of the processing speed faster. Throughout the experiment, we confirmed that the algorithm reliably detected driver drowsiness. The processing speed of the proposed algorithm is about 0.084ms. Also, the proposed algorithm can achieve an average detection rate of 98.48% and 97.37% for a yawn, drowsy eyes, and nod in the daytime and nighttime.

• Journal of IKEEE
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• v.27 no.4
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• pp.531-536
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• 2023

This paper proposes a sliding window method with frame feature insertion for immediate attack detection on in-vehicle networks. This method guarantees real-time attack detection by labeling based on the attack status of the current frame. Experiments show that the proposed method improves detection performance by giving more weight to the current frame in CNN computation. The proposed model was designed based on a lightweight LeNet-5 architecture and it achieves 100% detection for DoS attacks. Additionally, by comparing the complexity with conventional models, the proposed model has been proven to be more suitable for resource-constrained devices like ECUs.