• Title/Summary/Keyword: Continuous Sensor

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Airway Narrowing Patterns during Obstructive Sleep Apnea : Airway CT and Multi-level Airway Pressure Monitoring (수면무호흡 중에 관찰된 다양한 기도협착의 형태:상기도 CT 및 상기도 압력 측정법)

  • Jeong, Seung-Cheol;Hong, Seung-Bong;Kyung, Seung-Hyun;Kim, Hoo-Won
    • Sleep Medicine and Psychophysiology
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    • v.7 no.1
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    • pp.18-26
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    • 2000
  • Objectives: To investigate the airway narrowing patterns by multi-level airway pressure(MAP) monitoring during sleep and to evaluate the value of CT scan taken during waking and sleep apneic periods to identify the level of airway narrowing(LAN) in patients with obstructive sleep apnea syndrome(OSAS). Methods: Eleven patients with OSAS underwent a night polysomnography with continuous MAP monitoring by 4-sensor(placed at nasopharynx, caudal-uvula, hypopharynx, esophagus) or 2-sensor(placed at caudal-uvula and esophagus) catheter. All patients had cine CT at five levels of high retro and alatal, low retropalatal, retroglossal, epiglottis and hypopharynx during awake and sleep periods. In each patient, LAN determined by CT scan($LAN_{CT}$) during sleep apnea was compared with LAN by MAP monitoring($LAN_{MAP}$). Results: MAP monitoring showed that four patients(36%) had a single pattern of LAN while the other seven patients(64%) showed two or more different LANs in different apneic episodes. Velopharynx was the most common level of frequently observed airway narrowing during sleep apnea(63.6%). However, a single pattern of airway narrowing was more frequent(72.7%) in airway CT during sleep apnea. Velopharynx was the most common narrowest level also in apneic CT(66%). In comparing $LAN_{CT}$ with $LAN_{MAP}$, the $LAN_{CT}$ of five patients(45.5%) were high-concordant, those of another five(45.5%) low-concordant, and that of one(9%) discordant with $LAN_{MAP}$. Conclusions: Cine CT scan during the awake state or sleep apnea may not reflect the LAN correctly in OSAS because most patients showed two or more different airway narrowing patterns during different episodes of sleep apnea in each patient.

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A Comparative Errors Assessment Between Surface Albedo Products of COMS/MI and GK-2A/AMI (천리안위성 1·2A호 지표면 알베도 상호 오차 분석 및 비교검증)

  • Woo, Jongho;Choi, Sungwon;Jin, Donghyun;Seong, Noh-hun;Jung, Daeseong;Sim, Suyoung;Byeon, Yugyeong;Jeon, Uujin;Sohn, Eunha;Han, Kyung-Soo
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1767-1772
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    • 2021
  • Global satellite observation surface albedo data over a long period of time are actively used to monitor changes in the global climate and environment, and their utilization and importance are great. Through the generational shift of geostationary satellites COMS (Communication, Ocean and Meteorological Satellite)/MI (Meteorological Imager sensor) and GK-2A (GEO-KOMPSAT-2A)/AMI (Advanced Meteorological Imager sensor), it is possible to continuously secure surface albedo outputs. However, the surface albedo outputs of COMS/MI and GK-2A/AMI differ between outputs due to Differences in retrieval algorithms. Therefore, in order to expand the retrieval period of the surface albedo of COMS/MI and GK-2A/AMI to secure continuous climate change monitoring linkage, the analysis of the two satellite outputs and errors should be preceded. In this study, error characteristics were analyzed by performing comparative analysis with ground observation data AERONET (Aerosol Robotic Network) and other satellite data GLASS (Global Land Surface Satellite) for the overlapping period of COMS/MI and GK-2A/AMI surface albedo data. As a result of error analysis, it was confirmed that the RMSE of COMS/MI was 0.043, higher than the RMSE of GK-2A/AMI, 0.015. In addition, compared to other satellite (GLASS) data, the RMSE of COMS/MI was 0.029, slightly lower than that of GK-2A/AMI 0.038. When understanding these error characteristics and using COMS/MI and GK-2A/AMI's surface albedo data, it will be possible to actively utilize them for long-term climate change monitoring.

Smartphone Security Using Fingerprint Password (다중 지문 시퀀스를 이용한 스마트폰 보안)

  • Bae, Kyoung-Yul
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.45-55
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    • 2013
  • Thereby using smartphone and mobile device be more popular the more people utilize mobile device in many area such as education, news, financial. In January, 2007 Apple release i-phone it touch off rapid increasing in user of smartphone and it create new market and these broaden its utilization area. Smartphone use WiFi or 3G mobile radio communication network and it has a feature that can access to internet whenever and anywhere. Also using smartphone application people can search arrival time of public transportation in real time and application is used in mobile banking and stock trading. Computer's function is replaced by smartphone so it involves important user's information such as financial and personal pictures, videos. Present smartphone security systems are not only too simple but the unlocking methods are spreading out covertly. I-phone is secured by using combination of number and character but USA's IT magazine Engadget reveal that it is easily unlocked by using combination with some part of number pad and buttons Android operation system is using pattern system and it is known as using 9 point dot so user can utilize various variable but according to Jonathan smith professor of University of Pennsylvania Android security system is easily unlocked by tracing fingerprint which remains on the smartphone screen. So both of Android and I-phone OS are vulnerable at security threat. Compared with problem of password and pattern finger recognition has advantage in security and possibility of loss. The reason why current using finger recognition smart phone, and device are not so popular is that there are many problem: not providing reasonable price, breaching human rights. In addition, finger recognition sensor is not providing reasonable price to customers but through continuous development of the smartphone and device, it will be more miniaturized and its price will fall. So once utilization of finger recognition is actively used in smartphone and if its utilization area broaden to financial transaction. Utilization of biometrics in smart device will be debated briskly. So in this thesis we will propose fingerprint numbering system which is combined fingerprint and password to fortify existing fingerprint recognition. Consisted by 4 number of password has this kind of problem so we will replace existing 4number password and pattern system and consolidate with fingerprint recognition and password reinforce security. In original fingerprint recognition system there is only 10 numbers of cases but if numbering to fingerprint we can consist of a password as a new method. Using proposed method user enter fingerprint as invested number to the finger. So attacker will have difficulty to collect all kind of fingerprint to forge and infer user's password. After fingerprint numbering, system can use the method of recognization of entering several fingerprint at the same time or enter fingerprint in regular sequence. In this thesis we adapt entering fingerprint in regular sequence and if in this system allow duplication when entering fingerprint. In case of allowing duplication a number of possible combinations is $\sum_{I=1}^{10}\;{_{10}P_i}$ and its total cases of number is 9,864,100. So by this method user retain security the other hand attacker will have a number of difficulties to conjecture and it is needed to obtain user's fingerprint thus this system will enhance user's security. This system is method not accept only one fingerprint but accept multiple finger in regular sequence. In this thesis we introduce the method in the environment of smartphone by using multiple numbered fingerprint enter to authorize user. Present smartphone authorization using pattern and password and fingerprint are exposed to high risk so if proposed system overcome delay time when user enter their finger to recognition device and relate to other biometric method it will have more concrete security. The problem should be solved after this research is reducing fingerprint's numbering time and hardware development should be preceded. If in the future using fingerprint public certification becomes popular. The fingerprint recognition in the smartphone will become important security issue so this thesis will utilize to fortify fingerprint recognition research.

Evaluation for applicability of river depth measurement method depending on vegetation effect using drone-based spatial-temporal hyperspectral image (드론기반 시공간 초분광영상을 활용한 식생유무에 따른 하천 수심산정 기법 적용성 검토)

  • Gwon, Yeonghwa;Kim, Dongsu;You, Hojun
    • Journal of Korea Water Resources Association
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    • v.56 no.4
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    • pp.235-243
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    • 2023
  • Due to the revision of the River Act and the enactment of the Act on the Investigation, Planning, and Management of Water Resources, a regular bed change survey has become mandatory and a system is being prepared such that local governments can manage water resources in a planned manner. Since the topography of a bed cannot be measured directly, it is indirectly measured via contact-type depth measurements such as level survey or using an echo sounder, which features a low spatial resolution and does not allow continuous surveying owing to constraints in data acquisition. Therefore, a depth measurement method using remote sensing-LiDAR or hyperspectral imaging-has recently been developed, which allows a wider area survey than the contact-type method as it acquires hyperspectral images from a lightweight hyperspectral sensor mounted on a frequently operating drone and by applying the optimal bandwidth ratio search algorithm to estimate the depth. In the existing hyperspectral remote sensing technique, specific physical quantities are analyzed after matching the hyperspectral image acquired by the drone's path to the image of a surface unit. Previous studies focus primarily on the application of this technology to measure the bathymetry of sandy rivers, whereas bed materials are rarely evaluated. In this study, the existing hyperspectral image-based water depth estimation technique is applied to rivers with vegetation, whereas spatio-temporal hyperspectral imaging and cross-sectional hyperspectral imaging are performed for two cases in the same area before and after vegetation is removed. The result shows that the water depth estimation in the absence of vegetation is more accurate, and in the presence of vegetation, the water depth is estimated by recognizing the height of vegetation as the bottom. In addition, highly accurate water depth estimation is achieved not only in conventional cross-sectional hyperspectral imaging, but also in spatio-temporal hyperspectral imaging. As such, the possibility of monitoring bed fluctuations (water depth fluctuation) using spatio-temporal hyperspectral imaging is confirmed.