• Journal of Animal Science and Technology
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• 제64권6호
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• pp.1237-1244
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• 2022

Horse breeders suffer massive economic losses due to dystocia, abortion, and stillbirths. In Thoroughbred mares, breeders often miss the foaling process because approximately 86% of the foaling events occur from 19:00 to 7:00; consequently, breeders cannot assist mares experiencing dystocia. To solve this problem, various foaling alarm systems have been developed. However, there is a need to develop a new system to overcome the shortcomings of the existing devices and improve their accuracy. To this end, the present study aimed to (1) develop a novel foaling alarm system and (2) compare its accuracy with that of the existing Foalert^TM system. Specifically, eighteen Thoroughbred mares (11.9 ± 4.0 years old) were included. An accelerometer was used to analyze specific foaling behaviors. Behavioral data were transmitted to a data server every second. Depending on the acceleration value, behaviors were automatically classified by the server as categorized behaviors 1 (behaviors without change in body rotation), 2 (behaviors with sudden change in body rotation, such as rolling over), and 3 (behaviors with long-term change in body rotation, such as lying down laterally). The system was designed to alarm when the duration of categorized behaviors 2 and 3 was 12.9% and that of categorized behavior 3 was 1% during 10 min. The system measured the duration of each categorized behavior every 10 min and transmitted an alarm to the breeders when foaling was detected. To confirm its accuracy, the foaling detection time of the novel system was compared with that of Foalert^TM. The novel foaling alarm system and Foalert^TM alarmed foaling onset respectively 32.6 ± 17.9 and 8.6 ± 1.0 min prior to foal discharge, and the foaling detection rate of both systems was 94.4%. Therefore, the novel foaling alarm system equipped with an accelerometer can precisely detect and alert foaling onset.

• Journal of the Korea Convergence Society
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• 제8권3호
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• pp.15-22
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• 2017

People generally believe that disaster forecast and warning systems and response systems are well established in the age of cutting edge technology. As a matter of fact, reliable systems to respond to disasters are not properly equipped, as we witnessed the Sewol ferry disaster in 2014. The existing forecast and warning systems are based on sensor information with low efficiency, and image information is only operated by monitoring staff manually. In addition, the interconnection between a warning system and a response system in order to decide how to cope with the recognized disaster is very insufficient. This paper introduces the CCTV based disaster recognition and real time crisis response system composed of the CCTV image recognition engine and the crisis response technique. This system has brought the possibility to overcome the limitations of existing sensor based forecast and warning systems, and to resolve the problems in the absence of monitoring staff when responding to crisis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.882-885
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• 2014

The duration and frequency of flooding and not last long, by the time climate change drought. The increased accordingly by reducing stream flow and year variation. This trend is expected to continue, and change towards a comprehensive analysis of such quantity, quality and management of water resources are managed. Flood warning system is called to perform them electronically to the management of water resources such as these to be in the organic water-related basic data acquisition, storage, processing and utilization. Can be divided into hydrological observations and flood warning systems alert system broadcast system. Hydrological observation system is the measurement from the hydrological stations (water level, rainfall, water) that can be observed hydrological status of the dam basin hydrological observation data transmitted to the central office, located at the dam monitoring and control system through a variety of networks including satellite, and the collected defined as the system that sent the K-water head office in 1 minute increments hydrological observation data. Headquartered in support of this decision. Dimensions of the dam are provided in addition to inward. Channeled through various hydrologic analysis and leveraging the data transfer. This paper looks at ways to build out hydrological observation system.

• Journal of Advanced Navigation Technology
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• 제24권6호
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• pp.485-490
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• 2020

Recently, amid active research on domestic shipbuilding industry and IT convergence technology, with the development of satellite detection technology for ship safety operation, ships monitored the movement of ships with the mandatory long-range identification & tracking of vessels and automatic identification system. It is possible to help safe navigation, but it is necessary to develop safety device that alert the marine officer who rely on radar to correct conditions in case of weightlessness. Therefore, an ocean fog alarm system was developed to detect and inform using photo sensors. The fabricated ocean fog detect and alarm system consists of a small, low-power optical sensor transceiver and data sensing processing module. Through experiment, it is confirmed that the fabricated ocean fog detect and alarm system measure the corresponding concentration of ocean fog for fogless circumstance and fogbound circumstance, respectively. Furthermore, the fabricated system can control RPM of ship engine according to the concentration of ocean fog, and consequently, the fabricated system can be applied to assistant device for ship safety operation.

• International Journal of Computer Science & Network Security
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• 제23권5호
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• pp.135-147
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• 2023

Internet of things has revolutionaries every field of life due to the use of artificial intelligence within Machine Learning. It is successfully being used for the study of Radiation monitoring, prediction of Ultraviolet and Electromagnetic rays. However, there is no particular system available that can monitor and detect waves. Therefore, the present study designed in which IOT enables intelligence system based on machine learning was developed for the prediction of the radiation and their effects of human beings. Moreover, a sensor based system was installed in order to detect harmful radiation present in the environment and this system has the ability to alert the humans within the range of danger zone with a buzz, so that humans can move to a safer place. Along with this automatic sensor system; a self-created dataset was also created in which sensor values were recorded. Furthermore, in order to study the outcomes of the effect of these rays researchers used Support Vector Machine, Gaussian Naïve Bayes, Decision Trees, Extra Trees, Bagging Classifier, Random Forests, Logistic Regression and Adaptive Boosting Classifier were used. To sum up the whole discussion it is stated the results give high accuracy and prove that the proposed system is reliable and accurate for the detection and monitoring of waves. Furthermore, for the prediction of outcome, Adaptive Boosting Classifier has shown the best accuracy of 81.77% as compared with other classifiers.

• Journal of Aerospace System Engineering
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• 제18권1호
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• pp.99-107
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• 2024

This paper introduces an emergency response system in urban air mobility scenarios. A biometric responsive smartwatch was designed to monitor passengers' real-time heart rates. When an anomaly was detected, the system would send an alert via Morse code vibration and voice notification. It was integrated with the assumed control system of the ROS environment and communicates to implement a system for generating the shortest path for emergency landing to a nearby vertical port during urban air mobility operations. System stability was verified through high-fidelity simulation environments and testing based on actual geographic locations. Our technology improved the reliability and convenience of urban air mobility, demonstrating its effectiveness through simulations and tests in real-world scenarios.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• 제44권7호
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• pp.611-619
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• 2016

This paper proposes a collision prevention system for an agricultural unmanned helicopter. The collision prevention system consists of an obstacle detection system, a mapping algorithm, and a collision avoidance algorithm. The obstacle detection system based on a LiDAR sensor is implemented in the unmanned helicopter and acquires distance information of obstacles in real-time. Then, an obstacle mapping is carried out by combining the distance to the obstacles with attitude/location data of the unmanned helicopter. In order to prevent a collision, alert is activated to an operator based on the map when the vehicle approaches to the obstacles. Moreover, the developed collision prevention system is verified through flight test simulating a flight pattern aerial spraying.

• Journal of Korean Society for Geospatial Information Science
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• 제8권1호
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• pp.97-103
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• 2000

The main purpose of 1-1-9 Caller Location Information System is to identify and display the precise location of emergency incidents such as natural or man - made fires, medical emergencies and accidents. The state - of- the - art technologies such as Am (Automatic Number Identification), GIS(Geographical Information System) and GPS (Global Positioning System) were applied and integrated in the system for efficient and effective location identification. It displays a radius of 25M, 50M and 100M on the map after location identification. The system can also provide the shortest path to an incident location from a fire station or a fire engine. In case of a fire breakout in or near a building, the attribute information of the building, called a building attribute card, is displayed along with the map location. The system then matches the information with the fire situation and sends an alert to a responsible fire station by phone or fax in order to help promptly react to the problem. An attribute card includes the critical information of a premise such as building's location, number of stories, floor plans, capacity, construction history, indoor fire detection and Prevention facilities, etc.

• Journal of KIISE:Information Networking
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• 제36권3호
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• pp.173-183
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• 2009

We present a real-time monitoring system for detecting anomalous network events using the entropy. The entropy accounts for the effects of disorder in the system. When an abnormal factor arises to agitate the current system the entropy must show an abrupt change. In this paper we deliberately model the Internet to measure the entropy. Packets flowing between these two networks may incur to sustain the current value. In the proposed system we keep track of the value of entropy in time to pinpoint the sudden changes in the value. The time-series data of entropy are transformed into the two-dimensional domains to help visually inspect the activities on the network. We examine the system using network traffic traces containing notorious worms and DoS attacks on the testbed. Furthermore, we compare our proposed system of time series forecasting method, such as EWMA, holt-winters, and PCA in terms of sensitive. The result suggests that our approach be able to detect anomalies with the fairly high accuracy. Our contributions are two folds: (1) highly sensitive detection of anomalies and (2) visualization of network activities to alert anomalies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제18권5호
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• pp.112-125
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• 2019

An acoustic signal-based, tunnel-incident detection system was developed and evaluated. The system was comprised of three components: algorithm, acoustic signal collector, and server system. The algorithm, which was based on nonnegative tensor factorization and a hidden Markov model, processes the acoustic signals to attenuate noise and detect incident-related signals. The acoustic signal collector gathers the tunnel sounds, digitalizes them, and transmits the digitalized acoustic signals to the center server. The server system issues an alert once the algorithm identifies an incident. The performance of the system was evaluated thoroughly in two steps: first, in a controlled tunnel environment using the recorded incident sounds, and second, in an uncontrolled tunnel environment using real-world incident sounds. As a result, the detection rates ranged from 80 to 95% at distances from 50 to 10 m in the controlled environment, and 94 % in the uncontrolled environment. The superiority of the developed system to the existing video image and loop detector-based systems lies in its instantaneous detection capability with less than 2 s.