• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.9
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• pp.67-74
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• 2008

This paper proposes, designs and implements an architecture of a server involved with the network camera based video surveillance systems to solve common problems including lack of inter-network operability at the video information sharing, drawback of bandwidth and processing-overhead caused by increase of the number of users, and difficulty of continuous monitoring over changes of network configurations. The proposed saver was designed to manage and service numerous network cameras and users as well as solving the existing problems by providing video distribution facility. Through the empirical study after applying the implemented server to a real video surveillance system we proved that the server can provide reasonable service quality while it processes several hundreds of simultaneous user connections under persisting more than one hundred connections to network cameras. We expect the developed video distribution server to enhance service quality of the large scale video surveillance systems for citizen-wide services such as traffic reporting informatics or natural calamities supporting.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.1-8
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• 2024

Busan is the 6th largest port city in the world, where nitrogen dioxide (NO₂) emissions from transportation and port industries are significant. This study aims to assess the NO₂ products of the Geostationary Environment Monitoring Spectrometer (GEMS) over Busan using ground-based instruments (i.e., surface in-situ network and Pandora). The GEMS vertical column densities of NO₂ showed reasonable consistency in the spatiotemporal variations, comparable to the previous studies. The GEMS data showed a consistent seasonal trend of NO₂ with the Korea Ministry of Environment network and Pandora in 2022, which is higher in winter and lower in summer. These agreements prove the capability of the GEMS data to monitor the air quality in Busan. The correlation coefficient and the mean bias error between the GEMS and Pandora NO₂ over Busan in 2022 were 0.53 and 0.023 DU, respectively. The GEMS NO₂ data were also positively correlated with the ground-based in-situ network with a correlation coefficient of 0.42. However, due to the significant spatiotemporal variabilities of the NO₂, the GEMS footprint size can hardly resolve small-scale variabilities such as the emissions from the road and point sources. In addition, relative biases of the GEMS NO₂ retrievals to the Pandora data showed seasonal variabilities, which is attributable to the air mass factor estimation of the GEMS. Further studies with more measurement locations for longer periods of data can better contribute to assessing the GEMS NO₂ data. Reliable GEMS data can further help us understand the Asian air quality with the diurnal variabilities.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.135-146
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• 2023

An effective educational program warrants the inclusion of an innovative construction which enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational Decision Support System (EDSS) has currently been a hot topic in educational systems, facilitating the pupil result monitoring and evaluation to be performed during their development. Insufficient information systems encounter trouble and hurdles in making the sufficient advantage from EDSS owing to the deficit of accuracy, incorrect analysis study of the characteristic, and inadequate database. DMTs (Data Mining Techniques) provide helpful tools in finding the models or forms of data and are extremely useful in the decision-making process. Several researchers have participated in the research involving distributed data mining with multi-agent technology. The rapid growth of network technology and IT use has led to the widespread use of distributed databases. This article explains the available data mining technology and the distributed data mining system framework. Distributed Data Mining approach is utilized for this work so that a classifier capable of predicting the success of students in the economic domain can be constructed. This research also discusses the Intelligent Knowledge Base Distributed Data Mining framework to assess the performance of the students through a mid-term exam and final-term exam employing Multi-agent system-based educational mining techniques. Using single and ensemble-based classifiers, this study intends to investigate the factors that influence student performance in higher education and construct a classification model that can predict academic achievement. We also discussed the importance of multi-agent systems and comparative machine learning approaches in EDSS development.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.494-497
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• 1999

Neural networks are shown to be effective in being able to distinguish incomplete penetration-like weld defects by directly analyzing the plasma which is generated on each impingement of the laser on the materials. The performance is similar to that of existing methods based on extracted feature parameters. In each case around 93% of the defects in a database derived from 100 artificially produced defects of known types can be placed into one of two classes: incomplete penetration and bubbling. Especially we present simulator for weld defects classification and data analysis. The present method based on classification using plasma is faster, and the speed is sufficient to allow on-line classification during data collection.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.173-178
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• 2016

Many studies have been carried out on monitoring the target by cooperating a drone with remote sensors recently. This monitoring system uses static sensors to measure environmental data and drones to collect measured data. In geotechnical engineering, inspectors go around measuring the safety of construction site and it is impractical to compose a network among numerous sensors in terms of the cost efficiency. In this paper, we propose a data collection system based on interaction between a drone and a few sensors that are installed around the target structure for geotechnical projects. Through experimental results, we also verify the availability and the time and cost efficiency of the proposed system comparing with using inspectors.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.6
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• pp.445-450
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• 2012

We have developed an implantable wireless sensor for real time pressure monitoring of blood circulation system. MEMS (micro-electro-mechanical system) technology was adopted as a sensor development method. The sensor is composed of photolithographically patterned inductors and a distributed capacitor in gap between the inductors. A resulting LC resonant system produces its resonant frequency in range of 269 to 284 MHz at 740 mmHg. To read the resonant frequency changed by blood pressure variation, we developed a custom readout system based on a network analyzer functionality. The bench-top testing of the pressure sensors showed good mechanical and electrical functionality. A sensor was implanted into tibial artery of farm pig, and interrogated wirelessly with accurate readings of blood pressure. After 45 days, the sensor's electrical response and histopathology were studied with good frequency reading and biocompatibility.

• Journal of Advanced Navigation Technology
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• v.11 no.3
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• pp.233-238
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• 2007

In this paper, a wireless sensor network system was embodied inside the shipping for digital ship. First, the analysis of radio environment inside ship are investigated. As a result, it was confirmed that a wireless sensor network system can be applied inside the ship. Using Shipboard Wireless Sensor Network System based on IEEE 802.15.4 technique, we designed, and made the prototype of Zigbee Node and RFID Reader. We could be sensing on shipboard and testing entrance of crew by using Zigbee Node and RFID Reader. The sensing and exit or entry control data are transmitted a server system through internet that connected Wireless Gateway with AP, so we can monitoring the saved data on shipboard database.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.1
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• pp.21-26
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• 2012

This paper presents a real-time image transferring and localization system utilizing HSDPA, a commercial wireless network system. A novel image compression algorithm is developed based on MPEG4 to comply with uploading bandwidth of 130 kbps and QVGA image transmission of 30 fps. Aiming at being embedded in moving vehicles, the proposed system has a small size, low power consumption, and robustness to disturbances. We validate the performance of the system by presenting captured images of transferring video and localization data. Our system can be applied to real-time surround monitoring in moving vehicles or real-time ecology observation in remote places.

• Smart Structures and Systems
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• v.29 no.4
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• pp.625-640
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• 2022

Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.36-44
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• 2010

In this paper, we propose video quality control system(VQCS) which can control video service quality through the monitoring of end-to-end available bandwidth for video streaming service like IPTV in NGN convergence network. Various multimedia services such as video, voice and gaming service can be provided by IPTV, and these services require large amounts of bandwidth. At this time, video quality degradation like video jerkiness, block distortion and blurring is caused when network available bandwidth is insufficient. Available bandwidth monitoring method is need to stably control video streaming quality. So, we periodically calculate the amount of the packets in link and measure available bandwidth by using total length field in IP header at terminal. Scalability extractor in network selects suitable video streaming data rate based on available bandwidth and transports video streaming with adaptive data rate to prevent video quality deterioration.