• The Transactions of the Korea Information Processing Society
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• v.3 no.2
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• pp.369-380
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• 1996

Inductive Loop Detector(ILD) has been commonly used in collecting traffic data such as occupancy time and non-occupancy time. From the data, the traffic volume and type of passing vehicle is calculated. To provide reliable data for traffic control and plan, accuracy is required in type recognition which can be utilized to determine split of traffic signal and to provide forecasting data of queue-length for over-saturation control. In this research, a new recognition model issuggested for recognizing typeof vehicle from thecollected data obtained through ILD systems. Two clustering methods, based on statistical algorithms, and one neural network clustering method were employed to test the reliability and occuracy for the methods. In a series of experiments, it was found that the new model can greatly enhance the reliability and accuracy of type recongition rate, much higher than conventional approa-ches. The model modifies the neural network clustering method and enhances the recongition accuracy by iteratively applying the algorithm until no more unclustered data remains.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.827-830
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• 2011

In this paper, a wind speed & direction module and the DSP(Digital Signal Processor) sensor interface circuit board are proposed. This DSP system accepts and process the informations from a wind speed & direction module, the atmospheric pressure sensor, the ambient air temperature sensor and transfers it to the PC monitering system. Especially, a wind speed & direction module and a DSP hardware are directly designed and applied. A wind speed & direction module have a construction that it have four film type RTD(Resistive Temperature Detectors) or film type Piezo sensors adhered around the circular metal body for obtaining vector informations about wind. By this structure, the module is enabled precise measurement having a robustness about vibration, humidity, corrosion. A sensor signal processing circuit is using TMS320F2812 TI(Texas Instrument) Corporation high speed DSP.

• The KIPS Transactions:PartD
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• v.18D no.3
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• pp.197-204
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• 2011

Set-top Box which receives broadcasting signal and delivers it to display device such as TV usually doesn't have low-power mode, standby power mode. On the other side, most consumer electronics support standby power mode. The main reasons come from technical barriers and operational stability. Set-top box normally consumes 80~90% power of active mode even though turning off. This is much higher compared to other consumer electronics which consume less than 1W in standby power mode. However, most developed countries including Korea are enforcing the regulations which enhance energy efficiency of set-top box. This paper describes design and development of low-power set-top box. Key technologies are SoC supporting low-power mode, system hardware and software operating in separated power mode, and middleware managing the power with broadcasting system. Finally, we show energy saving expectation through development and proliferation.

• The KIPS Transactions:PartB
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• v.14B no.6
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• pp.401-406
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• 2007

This study discusses the development of a u-Health care system that can detect quickly and cope actively with emergent situations of chronic disease patients who lead everyday life. If a patient's emergent situation is detected by personal health care host(PHCH), which is composed of acceleration and vibration sensors, GPS, and CDMA communication module, a text message on the patient's current location is transmitted to the hospital and the guardian's mobile terminal so that they can cope with the situation immediately. Especially, the system analyzes data from sensors by using neural network and determines emergent situations such as syncope and convulsion promptly. The exact location of patients can also be found in the electronic map by using GPS information. The experiments show that this system is very effective to find emergencies promptly for chronic disease patients who cannot take care of themselves and it is expected to save many lives.

• Plant Journal
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• v.17 no.3
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• pp.37-41
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• 2021

P&ID((Piping and Instrument Diagram) is a key drawing in the engineering industry because it contains information about the units and instrumentation of the plant. Until now, simple repetitive tasks like listing symbols in P&ID drawings have been done manually, consuming lots of time and manpower. Currently, a deep learning model based on CNN(Convolutional Neural Network) is studied for drawing object detection, but the detection time is about 30 minutes and the accuracy is about 90%, indicating performance that is not sufficient to be implemented in the real word. In this study, the detection of symbols in a drawing is performed using 1-stage object detection algorithms that process both region proposal and detection. Specifically, build the training data using the image labeling tool, and show the results of recognizing the symbol in the drawing which are trained in the deep learning model.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.231-238
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• 2022

In this paper, among short-range wireless communication technologies such as Beacon, Bluetooth, UWB (Ultra-wideband), ZigBee, NFC (Near Field Communication), Z-Wave, 6LoWPAN (IPv6 over Low power WPAN), D2D (Device to Device), etc., proposed an IoT service platform based on a beacon that can provide indoor positioning. And, a beacon-linked web server was designed by blocking indiscriminate beacon spam signals and applying REST web service technology with flexibility and scalability. Data accessibility between different devices was verified by testing the success rate of data transmission, the success rate of blocking beacon push, the success rate of IoT interlocking processing, the accuracy of location positioning, and the success rate of REST web service-based data processing. Through the designed IoT service platform, various proposals and research on short-distance-based business models and service platforms will be conducted in the future.

• Journal of KIISE:Information Networking
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• v.37 no.4
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• pp.272-283
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• 2010

Wireless Mesh Networks (WMNs) have gained a lot of attention recently. Based on the characteristic of WMNs as a highly connected wireless infrastructure, many efforts from research organizations are made in order to improve the performance of the flow throughput in WMNs. Therefore, it is very critical issue to establish efficient routing paths for multiple concurrent ongoing flows. In this paper, we propose a general modeling methodology to analyze the end-to-end throughput of multiple concurrent flows by analytical calculation taking into account the carrier sensing behaviors, interference and the IEEE 802.11 Distributed Coordination Function mechanism. After the comparison of the average service time for each successful transmission at each node, we analyze the bottlenecks of flows, and hence obtain the maximum end-to-end throughput of them. By using our proposed model, it is possible to predicate the throughput of several candidate routing paths for multiple concurrent ongoing data flows, so we can select the most efficient route that can achieve the highest throughput. We carry out simulations with various traffic patterns of multiple flows in WMNs to validate our modeling and our efficient route selection mechanism.

• Investigative Magnetic Resonance Imaging
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• v.4 no.2
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• pp.128-135
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• 2000

Purpose : The aim of this study is to develope the Magnetic Resonance Spectroscopy(MRS) data processing S/W which plays an important role as a diagnostic tool in clinical field. Materials and methods : Post-processing software of MRS based on graphical user interface(GUI) under windows operating system of personal computer(PC) was developed using MATLAB(Mathwork, U.S.A.). This tool contains many functions to increase the quality of spectrum data such as DC correction, zero filling, line broadening, Gauss-Lorentzian filtering, phase correction, etc. And we obtained the normal human brain $^1H$ MRS data from parietal white matter, basal ganglia and occipital grey matter region using 1.5T Gyroscan ACS-NT R6 (philips, Amsterdam, Netherland) MRS package. The analysis of the MRS peaks were performed by obtaining the ratio of peak area. Results : The peak ratios of NAA/Cr, Cho/Cr, MI/Cr for the different MRS machines have a little different values. But these peak ratios were not significantly different between different echo time MRS peak ratios in the same machine (p<0.05). Conclusion : MRS post-processing S/W based on GUI using PC was developed and applied to the analysis of normal human brain $^1H$ MRS. This independent MRS processing job increases the performance and throughput of patient scan of main console. Finally, we suggest that the database for normal in-yivo human MRS data should be obtained before clinical applications.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.3
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• pp.125-132
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• 2018

KVN(Korean VLBI Network) introduced the Mark6 system of the MIT haystack observatory as a recorder for data recording up to 32 Gbps for VLBI(Very Long Baseline Interferometry) observation. The Mark6 recorder can record data at up to 32Gbps when two systems and 64 HDDs are installed. However, because of the unique recording method that is characteristic of Mark6, we are introducing a large amount of data into a virtual file system, or using a general RAID method, which causes data loss when reading and transferring files at the highest recording speed or file system have. The Flexbuff system, a software recorder developed by JIVE(Joint Institute for VLBI ERIC), can be configured to operate as a data recorder through RAID configuration and network upgrades. In particular, when installed in the Mark6 system, it can record VLBI data at a maximum speed of 32 Gbps with less loss of data compared to the existing Mark6 by utilizing Mark6 resources well. In this paper, we propose that the existing Mark6 system can be operated as Mark6-Flexbuff by installing jive5ab software, and it is verified through experiment that it can be effectively used for VLBI observation operation through data recording test.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.245-251
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• 2019

Sonar bearing accuracy is the correspondence between the target orientation predicted by sonar and actual target orientation, and is obtained from measurements. However, when measuring sonar bearing accuracy, many errors are included in the results because they are made at sea, where complex and diverse environmental factors are applied. In particular, parallax error caused by the difference between the position of the GPS receiver and the sonar sensor, and the time delay error generated between the speed of underwater sound waves and the speed of electromagnetic waves in the air have a great influence on the accuracy. Correcting these parallax errors and time delay errors without an automated tool is a laborious task. Therefore, in this study, we propose a sonar bearing accuracy measurement equipment with parallax error and time delay error correction. The tests were carried out through simulation data and real data. As a result of the test it was confirmed that the parallax error and time delay error were systematically corrected so that 51.7% for simulation data and more than 18.5% for real data. The proposed method is expected to improve the efficiency and accuracy of sonar system detection performance verification in the future.