• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.4
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• pp.370-377
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• 2011

Korea Astronomy and Space Science Institute(KASI) has been developing one mobile SLR system since 2008 named as ARGO-M. Control logic in real-time laser ranging and data processing for normal point from the ranging data are key elements in the operation system of ARGO-M. KASI operation system team performed software logic analysis and related operations for SLR observation with help of Graz SLR station in Austria. This paper describes the algorithm required for SLR operation based on the method in Graz station. We figured out the essential logic for SLR operation and the remedy for the observation quality enhancement through this study.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.24-32
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• 2010

In this paper we proposed an object tracking system that detects the abandoned and removed objects, which is to be used in the intelligent surveillance applications. After the GMM based background subtraction and by using histogram method, the static region is identified to detect abandoned and removed objects. Since the system is implemented on DSP chip, it operates in realtime and is programmable. The input videos used in the experiment contain various indoor and outdoor scenes, and they are categorized into three different complexities; low, midium and high. By 10 times of experiment, we obtained high detection ratio at low and medium complexity sequences. On the high complexity video, successful detection ratio was relatively low because the scene contains crowdedness and repeated occlusion. In the future work, these complicated situation should be solved.

• Journal of Ocean Engineering and Technology
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• v.26 no.5
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• pp.63-72
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• 2012

The product lifecycle of a marine vessel can be classified into the design-production, operation-maintenance, and disposal phases. During the operation and maintenance phase, status data should be gathered from the major machinery and instruments installed on the marine vessel in order to perform efficient maintenance work. Although a PLM (product lifecycle management) system can manage the product information during the design and assembly stage, a PLM based on asset management technology is more appropriate for product information management during the operation stage. Product embedded information devices (PEIDs) are suggested for gathering real-time maintenance information during the operation and maintenance lifecycle. A PEID allows PLM to provide the capability of offering active information exchange between the lifecycle management system and equipment. This study designed a PEID to effectively obtain information and interact with a PLM system. It consists of sensors, wireless communication, and a micro-processor, which allow it to accumulate status data on the PLM system. The embedded information device and PLM enable the seamless information flow, tracking, and updating of MRO (maintenance repair and overhaul) information for a product throughout the middle of the product lifecycle.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.143-146
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• 2009

The restaurants have been forced to inform the origin of ingredients to consumers due to the origin obligation policy enacted in 2008 October. However, it is difficult to trust the policy because the origin is represented by a manager's conscience. Therefore, in order to provide consumers with reliable information, we have designed, and embodied the agricultural management system using RFID and USN technology. By installing system on agricultural plantations this system not only manages environmental data such as temperature, illumination and humidity collected in real time but also offers consumers the information of fertilizers or pesticides sprayed on the crops. Before purchasing, consumers will be able to check raw flesh process and the fertilizer and agricultural chemical scattering scene of the crops as an image by using RFID tags with a leader, which more increase the reliability.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.25-41
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• 2024

For the scenario of open pit mining, at present, manual periodic verification is mainly carried out in China with the help of video surveillance, which requires continuous investment in labor cost and has poor timeliness. In order to solve this difficult problem of early warning and monitoring, this paper researches a spatialized algorithmic model and designs an early warning system for open-pit mine transboundary mining, which is realized by calculating the coordinate information of the mining and extracting equipments and comparing it with the layer coordinates of the approval range of the mines in real time, so as to realize the determination of the transboundary mining behavior of the mines. By taking the Pingxiang area of Jiangxi Province as the research object, after the field experiment, it shows that the system runs stably and reliably, and verifies that the target tracking accuracy of the system is high, which can effectively improve the early warning capability of the open-pit mines' overstepping the boundary, improve the timeliness and accuracy of mine supervision, and reduce the supervision cost.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.16-23
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• 2019

Fine particulate matter known as PM 2.5 refers to the atmospheric particulate matter that has a diameter less than 2.5 micrometer identified as dangerous element for human health and its concentration can provide us a clear picture about air dust concentration. Humans stay indoor almost 90% of their life time and also there is no official indoor dust concentration data, so our study is focused on measuring the indoor air quality. Indoor dust data monitoring is very important in hospital environments beside that other places can also be considered for monitoring like classrooms, cements factories, computer server rooms, petrochemical storage etc. In this paper, visible light communication system is proposed by Manchester encoding technique for electromagnetic interference (EMI)-free indoor dust monitoring. Important indoor environment information like dust concentration is transferred by visible light channel in wide range. An average voltage-tracking technique is utilized for robust light detection to eliminate ambient light and low-frequency noise. The incoming light is recognized by a photo diode and are simultaneously processed by a receiver micro-controller. We can monitor indoor air quality in real-time and can take necessary action according to the result.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.4
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• pp.289-297
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• 2010

In this paper, A method to prevent the external acoustic noise from being misrecognized as the speech recognition object is presented in the speech activity detection process for the speech recognition. Also this paper confirmed besides the acoustic energy to the lip movement image signals. First of all, the successive images are obtained through the image camera for personal computer and the lip movement whether or not is discriminated. The next, the lip movement image signal data is stored in the shared memory and shares with the speech recognition process. In the mean time, the acoustic energy whether or not by the utterance of a speaker is verified by confirming data stored in the shared memory in the speech activity detection process which is the preprocess phase of the speech recognition. Finally, as a experimental result of linking the speech recognition processor and the image processor, it is confirmed to be normal progression to the output of the speech recognition result if face to the image camera and speak. On the other hand, it is confirmed not to the output the result of the speech recognition if does not face to the image camera and speak. Also, the initial feature values under off-line are replaced by them. Similarly, the initial template image captured while off-line is replaced with a template image captured under on-line, so the discrimination of the lip movement image tracking is raised. An image processing test bed was implemented to confirm the lip movement image tracking process visually and to analyze the related parameters on a real-time basis. As a result of linking the speech and image processing system, the interworking rate shows 99.3% in the various illumination environments.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.717-722
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• 2001

This paper presents a methodology on the backward path tracking control of a trailer type robot which consists of two parts: a tractor and a trailer. It is difficult to control the motion of a trailer vehicle since its dynamics is non-holonomic. Therefore, in this paper, the modeling and parameter estimation of the system using a real-coded genetic algorithm(RCGA) is proposed and a backward path tracking control algorithm is then obtained based on the linearized model. Experimental results verify the effectiveness of the proposed method.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.411-418
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• 2003

The proposed system in this paper uses a camera attached to a mobile device in order to inquire a car and track its location anywhere. To do this, the system recognizes and verifies license plates on the front and back of a cu. The plates are scanned by the camera attached to a mobile device. The technology enables us to detect a car registration number and to transmit the number along with the location of the device to a server through a wireless communication network. The information of a car obtained through the terminal is encoded and transmitted to a server in a remote place through a wireless communication network also. The car registration number and its location information are decoded and transmitted as a text to the server in a remote place. In order to track a user´s location through spatial relative distance estimated in real-time, the server uses the spatial and attribute information which are the most prior to the desired data value. With this property information, the right location can be calculated.