The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.9
no.5
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pp.451-457
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2016
To improve security in the data communication field, many studies on the application of chaotic signals to encryption have been conducted in recent years. In this study, a new security protocol where the initial value sensitivity and noise similarity of chaotic signals have been applied to an RFID communication channel was designed. In the case of chaotic systems, if the initial values become identical, the same signals are generated at the same time after that point even though the two systems have been calculated independently. Therefore, an unpredictable security channel can be produced based on such characteristics. However, a security channel can be produced only when an initial value is shared in advance, and thus there is a potential problem of infringement during the transmission of the initial value. To resolve this problem, a method in which a certain proportion of new chaotic signals are applied to two chaotic systems for communication and are then synchronized after some time was proposed. This new method can conceal the initial value, and thus can resolve the problem of the existing communication method using chaotic signals. The designed method was verified with the encryption and decryption of images. It is expected that a more secure RFID system could be established by applying the communication protocol proposed in this study to insecure RFID communication channels.
The Computed tomography (CT) scan can have high radiation in a few tests, and this risk is significant given that it is often repeated in one patient. In children, the incidence of radiation-induced cancer is reported because organs are growing, are more sensitive to radiation. 3D printing has recently been studied to be applied to various applications as a research field for 3D printing applications, research on fabrication of radiation shields and materials has been conducted. The purpose of the 3D printer is to replace the existing panel-type shields and to make customized designs according to the shape of the human body. Therefore, research on 3D information processing to be input to the 3D printer is also necessary. In this study, 3D data of the human body surface, which is the preliminary step of the manufacture of patient-specific eye shield using stereo vision depth map technology, was studied. This study aims to increase the possibility of three-dimensional output. As a result of experimenting with this method, which is relatively simple compared with other methods of 3D information processing, the minimum coordinates for 3D information are extracted. The results of this study provided the advantages and limitations of stereo images using natural light and will be the basic data for the manufacture of eye shields in the future.
Kim, Yun-Hee;Kim, Hyun-Gi;Kim, Seong-Yong;Kim, Hyoung-Ihl;Todd. B. Parrish;Hong, In-Ki;Sohn, Jin-Hun
Proceedings of the Korean Society for Emotion and Sensibility Conference
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2000.04a
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pp.113-119
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2000
The Pansori is a Korean traditional vocal music that has a unique story and melody which converts deep emotion into art. It has both verbal and emotional components. which can be coordinated by large-scale neural network. The purpose of this study is to illustrate the cortical network activated by a Korean traditional opera, Pansori, with different emotional valence using functional MRI (fMRI).Nine right-handed volunteers participated. Their mean age was 25.3 and the mean modified Edinburgh score was +90.1. Activation tasks were designed for the subjects to passively listen to the two parts of Pansories with sad or hilarious emotional valence. White noise was introduced during the control periods. Imaging was conducted on a 1.5T Siemens Vision Vision scanner. Single-shot echoplanar fMRI scans (TR/TE 3840/40 ms, flip angle 90, FOV 220, 64 x 64 matrix, 6mm thickness) were acquired in 20 contiguous slices. Imaging data were motion-corrected, coregistered, normalized, and smoothed using SPM-96 software.Bilateral posterior temporal regions were activated in both of Pansori tasks, but different asymmetry between the tasks was found. The Pansori with sad emotion showed more activation in the light superior temporal regions as well as the right inferior frontal and the orbitofrontal areas than in the right superior temporal regions as well as the right inferior frontal and the orbitofrontal areas than in the left side. In the Pansori with hilarious emotion, there was a remarkable activation in the left hemisphere especially at the posterior temporal and the temporooccipital regions as well as in the left inferior and the prefrontal areas. After subtraction between two tasks, the sad Pansori showed more activation in the right temporoparietal and the orbitofrontal areas, in contrast, the one with hilarious emotion showed more activation in the left temporal and the prefrontal areas. These results suggested that different hemispheric asymmetry and cortical areas are subserved for the processing of different emotional valences carried by the Pansories.
The purpose of this study was firstly, to explore the design preference, consumer experience and purchasing factors of parents for smart animal toys and secondly, investigate whether there is a difference by children's sex and age. For this purpose, the questionnaire survey was conducted with 344 parents of younger children in Seoul and Gyeonggi Province. As a result, the white or brown colored 20~30cm, dog-type smart toy was preferred and the sound was considered as the most important function. Besides role of toy, smart toy was expected to play as a pet, a friend and a younger sibling. Actually, dog-type smart toy were most frequently purchased. And main satisfied causes were fun, interactivity and design and dissatisfied causes were noise, price, battery life and durability of purchased smart toys. Finally, the important factors in purchasing smart toy were the safety, durability, battery life, sustainable play, education and washability. The parents' preference, customer experience and purchasing factors showed little significant differences according to the sex and the age of the children. This research will be useful in understanding parents purchasing activity of smart animal toys and provide valuable data for function construction, design and service planning necessary to develop the smart animal toy.
Journal of the Korea Academia-Industrial cooperation Society
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v.19
no.4
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pp.543-550
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2018
The rapid growth of IoT technology induced by the fourth industrial revolution has resulted in research into various types of wireless sensors, and applications based on this technology are prevalent in many areas. However, among the various sites where this technology is used, railway bridges and tunnels with lengths of tens of kilometers have problems with data acquisition, due to the signal noise induced by the long distance measurement and EMI induced by the high voltage power feeding system, when conventional electric sensors are used. To overcome these problems, many studies on fiber optic sensors have been conducted as a substitute for the conventional electric sensors. However, restrictions on the types of fiber optic sensors have limited their application in railways. For this reason, a hybrid measurement system with IoT based wireless data communication, in which both electric and fiber optic sensors can be applied simultaneously, has been developed. In this study, in order to evaluate the applicability of the hybrid measurement system developed in the previous study, a real-time test for 4 types of measurement environments, which reflect possible railway sites, is performed. As a result, it was confirmed that the signals from both the electric and fiber optic sensors, which were acquired at a remote area in real-time, showed good agreement with each other and that this measurement system has the potential to handle sensors with a sampling rate of 2.5 kHz. In the future, it is expected that the IoT-based hybrid measurement system will contribute to the improvement of structural safety by enabling real-time structural health monitoring when applied to various measurement sites.
Green house gas emissions are increasing as development of the industrial economy of the international community. Many countries in the world are endeavoring to reduce green house gas emissions under severe climate change. In order to protect grobal warming, government is trying to reduce green gas emissions under "Low Carbon Green Growth Policy" and investing climiate-firendly industries such as renewable energy harvesting. Renewable energy has been rapidly developing as a result of investment for development technology of using natural energy such as solar, wind, tidal, etc. There are lots of waste energy in the road space. However, nobody is not interested in waste energy from the road space. This paper present a fundamentally experimental study of energy harvesting technique to use waste energy in the road. The waste energy in the road is covered a pressure and impact of vehicles on the road, the radiant heat from asphalt pavement, road noise and vibration etc. In this study, an energy harvesting device using piezoelectric element is proposed and various tests are conducted to investigate a characteristic of this device as function of impact loading based on piezoelectric effect behavior. This paper shows the energy harvesting results of the device using domestic piezoelectirc element as a function of impact load size and pavement types.
In this study, we have developed a drone magnetic exploration system (proto-type) using a fluxgate magnetic sensor. Hardware of the system consists of a fluxgate magnetometer, an inertial measurement unit (IMU), a GPS, and a communication module. And we have developed monitoring software, which enables it to transmit the measured data to the ground control system (GCS) in real time. The measured magnetic data are finally saved as 1 Hz data after passing through a notch filter and a band-pass filter. For verification of this system, a preliminary test was conducted to check the magnetic responses of a magnetic object first, then the field test was carried out in two iron mines. We tested the developed system on the field test in Pocheon, Gyeonggi and Jeongseon, Gangwon. The magnetic data from the developed drone system was very similar to those from unmanned airship system developed by Korea Institute of Geoscience and Mineral Resources (KIGAM). As a result, preliminary experiment and field test have demonstrated that this system is applicable for outdoor aeromagnetic exploration. It requires more studies to improve filter function and instrument performance to minimize noise in the future.
Korea, which has undergone a rapid urbanization, faces various problems such as the management of facilities, safety, environment and transportation. To solve civil complaints, local governments receive electronic complaints, but complaints are increasing. Therefore, this study conducted the spatial distribution pattern analysis and the trend analysis by presenting location data on spatial information through Geo-coding by collecting electronic civil petition data over the last 10 years targeting Jinju city. Using the ARIMA model, this study predicted the occurrence of complaints over the next two years (2016~2017) through a time series forecast analysis. As a result, the complaints related to illegal parking were the highest, the complaint related to noise was the second highest, and the complaints related to illegal garbage dumping was the third highest. In addition, the analysis of the spatial distribution pattern shows that the largest hot spot was formed in the central commercial district every year. As a result of the time series forecasting analysis for the crackdown of the illegal parking, complaints increased slightly. To compare the predicted value and the actual data showed a similar pattern. It is judged that this study will be utilized to establish effective countermeasures against civil complaints.
Objectives This study was designed to review animal studies about the efficacy of herbal medicine for Rheumatoid arthritis animal model which was published in Korea after 2008. We also systematically investigated the reporting quality of the animal studies. Methods We systematically searched original articles in 8 databases since 2008. And manual searching was conducted through 10 Korean medicine journals from 2008. Studies were included if they used animal experimental model(s) with orally administered herbal medicine. Data were extracted regarding animal model, rheumatoid arthritis indicator and detail of intervention. Reporting quality of each study was also assessed by the STARA and ARRIVE guidelines. Results Nine hundred two articles were screened. Finally, 35 articles were included. 35 studies all showed that the herbal medicine used in the studies has significant effect on alleviating the macroscopic indicators, hematological indicators, histological indicators, genetic indicators, osteological indicator of Rheumatoid Arthritis and others. Species of animals was reported in 100% while ventilation and noise were reported in 0% in STRASA guidelines. Ethical statement was reported in 42.9%, experimental animals and sample size were reported in 24%, 29% and there was no study reporting funding. Conclusions These results suggest that herbal medicine might be effective treatment for Rheumatoid Arthritis. It should be improved by clinical studies. And there is a need for studying about efficacy and safety of each specific herbal medicine. And we should improve the Reporting quality of the animal studies published in Korea.
In this paper, we propose a video enhancement method using generative adversarial networks to remove raindrops and restore the background information on the removed region in the coastal wave video imagery distorted by raindrops during rainfall. Two experimental models are implemented: Pix2Pix network widely used for image-to-image translation and Attentive GAN, which is currently performing well for raindrop removal on a single images. The models are trained with a public dataset of paired natural images with and without raindrops and the trained models are evaluated their performance of raindrop removal and background information recovery of rainwater distortion of coastal wave video imagery. In order to improve the performance, we have acquired paired video dataset with and without raindrops at the real coast and conducted transfer learning to the pre-trained models with those new dataset. The performance of fine-tuned models is improved by comparing the results from pre-trained models. The performance is evaluated using the peak signal-to-noise ratio and structural similarity index and the fine-tuned Pix2Pix network by transfer learning shows the best performance to reconstruct distorted coastal wave video imagery by raindrops.
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