• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.1
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• pp.51-60
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• 2014

In this study, ICT medical service provider's level of knowledge fire fighting safety and methods on coping with fires in the regions of Gwangju and Jeonam Province of Korea were investigated to determine the elements affecting such levels and provide basic information on the manuals for educating how to cope with the fire fighting safety in medical facilities. The data were analyzed using SPSS Win 14.0. The scores of level of knowledge fire fighting safety of ICT medical service provider's were 7.06(10 point scale), and the scores of level of recognizing how to cope with fire fighting safety were 6.61(11 point scale). level of recognizing how to cope with fire fighting safety were significantly different according to gender(t=4.12, p<.001), age(${\chi}^2$=17.24, p<.001), length of career(${\chi}^2$=22.76, p<.001), experience with fire fighting safety education(t=6.10, p<.001), level of subjective knowledge on fire fighting safety(${\chi}^2$=53.83, p<.001). In order to enhance the level of understanding of fire fighting safety and methods of coping by the ICT medical service providers it is found that: self-directed learning through avoiding the education just conveying knowledge by lecture tailored learning for individuals fire fighting education focused on experiencing actual work by developing various contents emphasizing cooperative learning deploying patients by classification systems using simulations and a study on the implementation of digital anti-fire monitoring system with multipoint communication protocol, a design and development of the smoke detection system using infra-red laser for fire detection in the wide space, video based fire detection algorithm using gaussian mixture mode developing an education manual for coping with fire fighting safety through multi learning approach at the medical facilities are required.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.566-573
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• 2004

This paper describes the ubiquitous home network (uHome-net) testbed and LonRF intelligent devices based on LonWorks technology. These devices consist of Neuron Chip, RF transceiver, sensor, and other peripheral components. Using LonRF devices, a home control network can be simplified and most devices can be operated on LonWorks control network. Also, Indoor Positioning System (IPS) that can serve various location based services was implemented in uHome-net. Smart Badge of IPS, that is a special LonRF device, can measure the 3D location of objects in the indoor environment. In the uHome-net testbed, remote control service, cooking help service, wireless remote metering service, baby monitoring service and security ＆ fire prevention service were realized. This research shows the vision of the ubiquitous home network that will be emerged in the near future.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1006-1008
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• 2003

In this paper, we describe the development of a Southeast Asia environmental information web portal based on near real time MODIS Level 2 and higher level products generated from the direct broadcast data received at the Centre for Remote Imaging, Sensing and Processing (CRISP). This web portal aims to deliver timely environmental information to interested users in the region. Interpreted data will be provided instead of raw satellite data to reduce operational requirements on our system, and to enable users with limited bandwidths to have access to the system.

• Journal of IKEEE
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• v.22 no.4
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• pp.959-964
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• 2018

In this study, a study is conducted on a monitoring system that can control the environment of plants using sensors in conjunction with the LED light system and the plant growth control system. To verify the performance of the developed plant growth system, an experiment was conducted on the characteristics of energy efficiency, data transmission rate, and light volume control. The experiment resulted in a satisfactory result by controlling more than 80% energy efficiency, 1Mb/sec wireless communication speed, and 5 levels of optical control. The proposed system can be applied to LED plant facilities and will contribute to the automation of agriculture by organizing an automated system for production efficiency and labor cost reduction for future commercialization.

• Journal of the Korea Institute of Building Construction
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• v.9 no.5
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• pp.79-86
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• 2009

In a steel structure, spray-applied fire resistive materials are crucial in preventing structural strength from being weakened in the event of a fire. The quality control of such materials, however, is difficult for manual workers, who can frequently be in short supply. These skilled workers are also very likely to be exposed to environmental hazards. Problems with construction work such as this, which are specifically the difficulty of achieving quality control and the dangerous nature of the work itself, can be solved to some degree by the introduction of automated equipment. It is, however, very difficult to automate the work process, from operation to the selection of a location for the equipment, as the environment of a construction site has not yet been structured to accommodate automation. This is a fundamental study on the possibility of the automation of spray-applied fire resistive coating work. In this study, the linkability of the cutting-edge RTLS to an automation system is reviewed, and a scenario for the automation of spray-applied fire resistive coating work and system composition is presented. The system suggested in this study is still in a conceptual stage, and as such, there are many restrictions still to be resolved. Despite this fact, automation is expected to have good effectiveness in terms of preventing fire from spreading by maintaining a certain level of strength at a high temperature when a fire occurs, as it maintains the thickness of the fire-resistive coating at a specified level, and secures the integrity of the coating with the steel structure, thereby enhancing the fire-resistive performance. It also expected that if future research is conducted in this area in relation to a cutting-edge monitoring TRS, such as the ubiquitous sensor network (USN) and/or building information model (BIM), it will contribute to raising the level of construction automation in Korea, reducing costs through the systematic and efficient management of construction resources, shortening construction periods, and implementing more precise construction

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2147-2150
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• 2003

Recently, many technologies of the P.L.C (Power Line Carrier) are introduced for an efficient communication. P.L.C communication sends information in the carrier signals by conduction over the power wire. An arc detector is proposed in this paper for the effective transmission. The Power Line Carrier has an advantage in low cost because it uses existent power line. It can be easily applied anywhere that a power line socket is available. But the P.L.C. is very noisy, because many electronic devices in generate electronic noise in modulated signals. This problem should be considered carefully in the design of the arc detector system using P.L.C in railway. The proposed system can be applied for monitoring the arc detector system and the arc locator system in railway. Hence the system will be able to exchange the arc information to be T.C.M.S. (Train Control Management System), bogies and even between a station and trains in railway and use to suspicion fire in train.

• Journal of the Korea Society of Computer and Information
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• v.16 no.5
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• pp.135-145
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• 2011

These days, the research of a sensor data management system for USN based real-time monitoring application is active thanks to the development and diffusion of sensor technology. The sensor data is rapidly changeable, continuous and massive row level data. However, end user is only interested in high level data. So, it is essential to effectively process the row level data which is changeable, continuous and massive. In this paper, we propose a sensor data management system with multi-analytical query function using OLAP and anomaly detection function using learning based classifier. In the experimental section, we show that our system is valid through the some experimental scenarios. For the this, we use a sensor data generator implemented by ourselves.

• Analytical Science and Technology
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• v.25 no.4
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• pp.230-235
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• 2012

It is to use many plastic materials as living essential goods. But when the fire is happened, owing to noxious gases, many men should be injured. Therefore as the noxious gases are measured by open path FT-IR spectrometer as remote monitoring, the demage of men could be minimized. Such this system consists of a Fourier transform spectrometer and infrared lamp fitted to long length. The study was to do the quantitative analysis on CO, $NO_2$, HCl, HF gas by remote monitoring open path FT-IR spectrometer. And the method of it should use MLR (multiple linearity regression) method. As result, It was confirmed to be more than 0.95 as $R^2$ of MLR. And then Urethane and PVC of plastic materials selected was burned, the concentration of polluted gases were measured by remote monitoring method.

• The Transactions of the Korea Information Processing Society
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• v.13 no.9
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• pp.444-452
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• 2024

This study proposes a deep learning architecture optimized for fire detection derived through Layer Importance Evaluation. In order to solve the problem of unnecessary complexity and operation of the existing Convolutional Neural Network (CNN)-based fire detection system, the operation of the inner layer of the model based on the weight and activation values was analyzed through the Layer Importance Evaluation technique, the layer with a high contribution to fire detection was identified, and the model was reconstructed only with the identified layer, and the performance indicators were compared and analyzed with the existing model. After learning the fire data using four transfer learning models: Xception, VGG19, ResNet, and EfficientNetB5, the Layer Importance Evaluation technique was applied to analyze the weight and activation value of each layer, and then a new model was constructed by selecting the top rank layers with the highest contribution. As a result of the study, it was confirmed that the implemented architecture maintains the same performance with parameters that are about 80% lighter than the existing model, and can contribute to increasing the efficiency of fire monitoring equipment by outputting the same performance in accuracy, loss, and confusion matrix indicators compared to conventional complex transfer learning models while having a learning speed of about 3 to 5 times faster.

• BMB Reports
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• v.43 no.2
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• pp.110-114
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• 2010

The yeast three-hybrid system (Y3H), a powerful method for identifying RNA-binding proteins, still suffers from many false positives, due mostly to RNA-independent interactions. In this study, we attempted to efficiently identify false positives by introducing a tetracycline operator (tetO) motif into the RPR1 promoter of an RNA hybrid expression vector. We successfully developed a tight tetracycline-regulatable RPR1 promoter variant containing a single tetO motif between the transcription start site and the A-box sequence of the RPR1 promoter. Expression from this tetracycline-regulatable RPR1 promoter in the presence of tetracycline-response transcription activator (tTA) was positively controlled by doxycycline (Dox), a derivative of tetracycline. This on-off control runs opposite to the general knowledge that Dox negatively regulates tTA. This positively controlled RPR1 promoter system can therefore efficiently eliminate RNA-independent false positives commonly observed in the Y3H system by directly monitoring RNA hybrid expression.