• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5135-5142
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• 2011

A flexible mechanism is proposed in this paper to improve the dynamic response performance of a traffic flow control system in an urban area. The roads, vehicles, and traffic control systems are all modeled as intelligent systems, wherein a wireless communication network is used as the medium of communication between the vehicles and the roads. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads, based on all the information from the vehicles and the roads. This improves the flexibility of traffic flow and offers a much more efficient use of the roads over a traditional traffic control system. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm, and simulation results showed that the proposed mechanism can improve the traffic efficiency and the waiting time at the signal light by more than 30% in various conditions compare to the traditional signaling system.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.36-43
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• 2015

A pixel-level readout circuit is studied for 2-dimensional microbolometer focal plane arrays (FPAs). A current mirroring injection (CMI) input circuit with 2-step current-mode bias suppression is proposed for a pixel-level architecture with high responsivity and long integration time. The proposed circuit has been designed using a $0.35-{\mu}m$ 2-poly 4-metal CMOS process for a $320{\times}240$ microbolometer array with a pixel size of $50{\mu}m{\times}50{\mu}m$. The proposed 2-step bias-current suppression has sufficiently low calibration error with wide calibration range, and the calibration range and error can be easily optimized by controlling some design parameters. Due to high responsivity and a long integration time of more than 1 ms, the noise equivalent temperature difference (NETD) of the proposed circuit can be improved to 26 mK, which is much better than that of the conventional circuits, 67 mK.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.392-399
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• 2019

In this paper, we have studied wireless time division duplex(TDD) time synchronization technique considering the propagation delay between mobile vehicles. The existing IEEE 1588 precision time protocol(IEEE 1588 PTP) algorithm was applied and the time synchronization between the two nodes was achieved through the propagation delay and clock offset time correction calculated between master slave nodes during wireless TDD communication. The time synchronization process and procedure of IEEE 1588 PTP algorithm were optimized, thereby reducing the propagation delay error sensitivity for real-time moving vehicles. The sync flag signal generated through the time correction has a time synchronization accuracy of max +252.5 ns within 1-symbol(1.74 M symbol/sec, ${\pm}287.35ns$) through test and measurement, and it was confirmed that the time synchronization between master slave nodes can be achieved through sync flag signal generated during GPS disturbance.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.253-263
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• 2021

Machine learning is the process of constructing a cost function using learning data used for learning and an artificial neural network to predict the data, and finding parameters that minimize the cost function. Parameters are changed by using the gradient-based method of the cost function. The more complex the digital signal and the more complex the problem to be learned, the more complex and deeper the structure of the artificial neural network. Such a complex and deep neural network structure can cause over-fitting problems. In order to avoid over-fitting, a weight decay regularization method of parameters is used. We additionally use the value of the cost function in this method. In this way, the accuracy of machine learning is improved, and the superiority is confirmed through numerical experiments. These results derive accurate values for a wide range of artificial intelligence data through machine learning.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.987-994
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• 2020

In this paper, we studied the effect of kernel size of CNN layer on performance in acoustic noise attenuators. This system uses a deep learning algorithm using a neural network adaptive prediction filter instead of using the existing adaptive filter. Speech is estimated from a single input speech signal containing noise using a 100-neuron, 16-filter CNN filter and an error back propagation algorithm. This is to use the quasi-periodic property in the voiced sound section of the voice signal. In this study, a simulation program using Tensorflow and Keras libraries was written and a simulation was performed to verify the performance of the noise attenuator for the kernel size. As a result of the simulation, when the kernel size is about 16, the MSE and MAE values are the smallest, and when the size is smaller or larger than 16, the MSE and MAE values increase. It can be seen that in the case of an speech signal, the features can be best captured when the kernel size is about 16.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.4
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• pp.202-208
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• 2020

Recently, the importance of non-face-to-face has been emphasized due to COVID-19, and the use of sharing spaces is also expanding. The use of uncontact check-in technology for access control of sharing spaces reduces waiting time and optimizes workers' efficiency, resulting in operational cost savings. In this paper, we propose a sharing space access management system based on a mobile key and RCU (Room Control Unit), access to the facility using a mobile key, and monitor the facility using an RCU. Proposal system is for shared accommodation, rental field (residence, sale-selling hotel), shared office, etc. when there is a one-time visitor on a specific day and time, the corresponding password is delivered to the mobile platform to expose and key the existing password. It is supported by a field-adaptive system that can reduce discomfort such as delivery. In order to test the operation of the proposed integrated system, tests were conducted according to scenarios to understand the overall status of the user's reservation, check-in, and check-out, and a 100% success rate was derived for each item by setting performance indicators to prove test reliability.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.12
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• pp.1013-1020
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• 2020

Spark-induced breakdown spectroscopy (SIBS) utilizes an electric spark to induce a strong plasma for collecting atomic emissions. This study analyses the potential for usinga compact SIBS instead of conventional laser-induced breakdown spectroscopy (LIBS) in discriminating rocks and soils for planetary missions. Targeting bulky solids using SIBS has not been successful in the past, and therefore a series of optimizations of electrode positioning and electrode materials were performed in this work. The limit of detection (LOD) was enhanced up to four times compared to when LIBS was used, showing a change from 78 to 20 ppm from LIBS to SIBS. Because of the higher energy of plasma generated, the signal intensity by SIBS was higher than LIBS in three orders of magnitude with the same spectrometer setup. Changing the electrode material and locating the optimum position of the electrodes were considered for optimizing the current SIBS setup being tested for samples of planetary origin.

• Journal of Platform Technology
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• v.10 no.1
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• pp.29-34
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• 2022

The emergence of new diseases such as the Covid 19 pandemic that occurs in the 21st century and the occurrence of health abnormalities according to the busy daily life of modern people are increasing. Accordingly, the importance of health care management and data-based health management is being highlighted, and in particular, interest in personal health management data based on personal health care data of patients is rapidly increasing. In this study, to solve the difficult problems of personal health management, we developed a personal health care platform incorporating IT for self-diagnosis and solution and developed an application that measures bio-signals generated in the human body and transmits them to the platform. A health management system was established. Through this, not only the health care of modern people, but also the psychological and emotional care support needs through psychological and emotional monitoring of the developmentally disabled and the vulnerable who have difficulty in expressing their opinions are to be addressed. In addition, the overall health and living environment data of the individual was integrated to develop an optimized medical and health management service for the individual.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.914-922
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• 2022

In this paper, we construct a commercial 4K UHD(Ultra High Definition) streaming device that utilizes a 5G mobile communication network as a transport channel and conduct a streaming performance test. It uses RTP(Realtime Transport Protocol) which has transmission quality monitoring capability as a transmission protocol to apply adaptive streaming. In addition, it provides the function to adjust the encoding rate of the video signal so that encoding can be optimized for the change in the bandwidth of the transmission channel. Through the performance test, it is confirmed that the H.265 encoding rate for 4K UHD signal is 48.69Mbps, the average glass-to-glass delay time is 293.60ms, and the average time difference between video and audio for lip sync is 120ms. With the result of performance test, it is shown that the streaming device is applied to 4K UHD Streaming device over 5G mobile communication network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.243-245
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• 2021

Existing beacons are suitable for providing untact services, but they have the disadvantage of difficulty in accurate indoor positioning because the deviation in signal strength increases depending on the environment. In general, trilateration technique can reduce deviation, but if the distance between beacons is quite irregular, it becomes difficult to apply the algorithm. Therefore, in this paper, we studied how to reduce the signal power measurement error between beacons. First, we transformed the distance measurement formula using RSSI, assuming that the TX values were the same. In addition, we compared measurement errors with existing beacons by searching beacons with beacons scanner applications implemented with Android. As a result, it was confirmed that if a certain distance was further away, the measurement was measured more accurately than the non-changing beacon. Through this, accurate indoor positioning will be possible even in various disability situations. It is also expected that there will be more cases of establishing services that combine beacon with non-face-to-face services.