• Title/Summary/Keyword: Low-Energy Algorithm

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The Medium Access Scheduling Scheme for Efficient Data Transmission in Wireless Body Area Network (WBAN 환경에서 효율적 데이터 전송을 위한 매체 접근 스케줄링 기법)

  • Jang, EunMee;Park, TaeShin;Kim, JinHyuk;Choi, SangBan
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.2
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    • pp.16-27
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    • 2017
  • IEEE 802.15.6 standard, a Wireless Body Area Network, aims to transfer not only medical data but also non-medical data, such as physical activity, streaming, multimedia game, living information, and entertainment. Services which transfer those data have very various data rates, intervals and frequencies of continuous access to a medium. Therefore, an efficient anti-collision operations and medium assigning operation have to be carried out when multiple nodes with different data rates are accessing shared medium. IEEE 802.15.6 standard for CSMA/CA medium access control method distributes access to the shared medium, transmits a control packet to avoid collision and checks status of the channel. This method is energy inefficient and causes overhead. These disadvantages conflict with the low power, low cost calculation requirement of wireless body area network, shall minimize such overhead for efficient wireless body area network operations. Therefore, in this paper, we propose a medium access scheduling scheme, which adjusts the time interval for accessing to the shared transmission medium according to the amount of data for generating respective sensor node, and a priority control algorithm, which temporarily adjusts the priority of the sensor node that causes transmission concession due to the data priority until next successful transmission to ensure fairness.

Accuracy Evaluation of CT-Based Attenuation Correction in SPECT with Different Energy of Radioisotopes (SPECT/CT에서 CT를 기반으로 한 Attenuation Correction의 정확도 평가)

  • Kim, Seung Jeong;Kim, Jae Il;Kim, Jung Soo;Kim, Tae Yeop;Kim, Soo Mee;Woo, Jae Ryong;Lee, Jae Sung;Kim, Yoo Kyeong
    • The Korean Journal of Nuclear Medicine Technology
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    • v.17 no.1
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    • pp.25-29
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    • 2013
  • Purpose: In this study, we evaluated the accuracy of CT-based attenuation correction (AC) under the conventional CT protocol (140 kVp, on average 50-60 keV) by comparing the SPECT image qualities of different energy of radioisotopes, $^{201}Tl,\;^{99m}Tc$ and $^{131}I$. Materials and Methods: Using a cylindrical phantom, three different SPECT scans of $^{201}Tl$ (70 keV, 55.5 MBq), $^{99m}Tc$ (140 keV, 281.2 MBq) and $^{131}I$ (364 keV, 96.2 MBq) were performed. The CT image was obtained with 140 kVp and 2.5 mA in GE Hawkeye 4. The OSEM reconstruction algorithm was performed with 2 iterations and 10 subsets. The experiments were performed in the 4 different conditions; non-AC and non-scatter correction (SC), only AC, only SC, AC and SC in terms of uniformity and center to peripheral ratio (CPR). Results: The uniformity was calculated from the uniform whole region in the reconstructed images. For $^{201}Tl$ and $^{99m}Tc$, the uniformities were improved by about 10-20% AC was applied, but these were decreased by about 2% as SC was applied. The uniformity of $^{131}I$ was slightly increased as both AC and SC were applied. The CPR of the reconstructed image was close to one, when AC was applied for $^{201}Tl$ and $^{99m}Tc$ scans and $^{131}I$ was distant from 1 and that is only AC. Conclusion: The image uniformity improved by AC on low energy likely to $^{201}Tl$ and $^{99m}Tc$. However, image uniformity of high energy such as $^{131}I$ was improved, when both AC and SC was applied.

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Utilizing the Idle Railway Sites: A Proposal for the Location of Solar Power Plants Using Cluster Analysis (철도 유휴부지 활용방안: 군집분석을 활용한 태양광발전 입지 제안)

  • Eunkyung Kang;Seonuk Yang;Jiyoon Kwon;Sung-Byung Yang
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.79-105
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    • 2023
  • Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.

A prediction model for adolescents' skipping breakfast using the CART algorithm for decision trees: 7th (2016-2018) Korea National Health and Nutrition Examination Survey (의사결정나무 CART 알고리즘을 이용한 청소년 아침결식 예측 모형: 제7기 (2016-2018년) 국민건강영양조사 자료분석)

  • Sun A Choi;Sung Suk Chung;Jeong Ok Rho
    • Journal of Nutrition and Health
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    • v.56 no.3
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    • pp.300-314
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    • 2023
  • Purpose: This study sought to predict the reasons for skipping breakfast by adolescents aged 13-18 years using the 7th Korea National Health and Nutrition Examination Survey (KNHANES). Methods: The participants included 1,024 adolescents. The data were analyzed using a complex-sample t-test, the Rao Scott χ2-test, and the classification and regression tree (CART) algorithm for decision tree analysis with SPSS v. 27.0. The participants were divided into two groups, one regularly eating breakfast and the other skipping it. Results: A total of 579 and 445 study participants were found to be breakfast consumers and breakfast skippers respectively. Breakfast consumers were significantly younger than those who skipped breakfast. In addition, breakfast consumers had a significantly higher frequency of eating dinner, had been taught about nutrition, and had a lower frequency of eating out. The breakfast skippers did so to lose weight. Children who skipped breakfast consumed less energy, carbohydrates, proteins, fats, fiber, cholesterol, vitamin C, vitamin A, calcium, vitamin B1, vitamin B2, phosphorus, sodium, iron, potassium, and niacin than those who consumed breakfast. The best predictor of skipping breakfast was identifying adolescents who sought to control their weight by not eating meals. Other participants who had low and middle-low household incomes, ate dinner 3-4 times a week, were more than 14.5 years old, and ate out once a day showed a higher frequency of skipping breakfast. Conclusion: Based on these results, nutrition education targeted at losing weight correctly and emphasizing the importance of breakfast, especially for adolescents, is required. Moreover, nutrition educators should consider designing and implementing specific action plans to encourage adolescents to improve their breakfast-eating practices by also eating dinner regularly and reducing eating out.

Analysis of Small Cell Technology Application for Performance Improvement in Simulation-based 5G Communication Environment (시뮬레이션 기반 5G 통신 환경에서 성능향상을 위한 스몰셀 기술 적용 분석)

  • Kim, Yoon Hwan;Kim, Tae Yeun;Lee, Dae Young;Bae, Sang Hyun
    • Smart Media Journal
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    • v.9 no.2
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    • pp.16-21
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    • 2020
  • Recently, mobile traffic is increasing exponentially as major traffic is transferred to IoT and visual media data in the dissemination of mobile communication terminals and contents use. In order to overcome the limitations of the existing LTE system, 5G mobile communication technology (5G) is a technology that meets 1000 times data traffic capacity, 4G LTE system acceptance, low latency, high energy efficiency, and high cost compared to 4G LTE system. The path loss due to the use of the frequency domain is very high, so it may be difficult to provide a service compared to the existing 4G LTE system. To overcome these shortcomings, various techniques are under study. In this paper, small cell technology is introduced to improve the system performance of 5G mobile communication systems. The performance is analyzed by comparing the results of small cell technology application, macro communication and small cell communication, and the results of the proposed algorithm application for power control. The analysis results show that the use of small cell technology in the 5th generation mobile communication system can significantly reduce the shadow area and reduce the millimeter wave path loss problem.

Combining Bias-correction on Regional Climate Simulations and ENSO Signal for Water Management: Case Study for Tampa Bay, Florida, U.S. (ENSO 패턴에 대한 MM5 강수 모의 결과의 유역단위 성능 평가: 플로리다 템파 지역을 중심으로)

  • Hwang, Syewoon;Hernandez, Jose
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.14 no.4
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    • pp.143-154
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    • 2012
  • As demand of water resources and attentions to changes in climate (e.g., due to ENSO) increase, long/short term prediction of precipitation is getting necessary in water planning. This research evaluated the ability of MM5 to predict precipitation in the Tampa Bay region over 23 year period from 1986 to 2008. Additionally MM5 results were statistically bias-corrected using observation data at 33 stations over the study area using CDF-mapping approach and evaluated comparing to raw results for each ENSO phase (i.e., El Ni$\tilde{n}$o and La Ni$\tilde{n}$a). The bias-corrected model results accurately reproduced the monthly mean point precipitation values. Areal average daily/monthly precipitation predictions estimated using block-kriging algorithm showed fairly high accuracy with mean error of daily precipitation, 0.8 mm and mean error of monthly precipitation, 7.1 mm. The results evaluated according to ENSO phase showed that the accuracy in model output varies with the seasons and ENSO phases. Reasons for low predictions skills and alternatives for simulation improvement are discussed. A comprehensive evaluation including sensitivity to physics schemes, boundary conditions reanalysis products and updating land use maps is suggested to enhance model performance. We believe that the outcome of this research guides to a better implementation of regional climate modeling tools in water management at regional/seasonal scale.

Comparison of Co-registration Algorithms for TOPS SAR Image (TOPS 모드 SAR 자료의 정합기법 비교분석)

  • Kim, Sang-Wan
    • Korean Journal of Remote Sensing
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    • v.34 no.6_1
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    • pp.1143-1153
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    • 2018
  • For TOPS InSAR processing, high-precision image co-registration is required. We propose an image co-registration method suitable for the TOPS mode by comparing the performance of cross correlation method, the geometric co-registration and the enhanced spectral diversity (ESD) matching algorithm based on the spectral diversity (SD) on the Sentinel-1 TOPS mode image. Using 23 pairs of interferometric pairs generated from 25 Sentinel-1 TOPS images, we applied the cross correlation (CC), geometric correction with only orbit information (GC1), geometric correction combined with iterative cross-correlation (GC2, GC3, GC4), and ESD iteration (ESD_GC, ESD_1, ESD_2). The mean of co-registration errors in azimuth direction by cross correlation and geometric matching are 0.0041 pixels and 0.0016 pixels, respectively. Although the ESD method shows the most accurate result with the error of less than 0.0005 pixels, the error of geometric co-registration is reduced to 0.001 pixels by repetition through additional cross correlation matching between the reference and resampled slave image. The ESD method is not applicable when the coherence of the burst overlap areas is low. Therefore, the geometric co-registration method through iterative processing is a suitable alternative for time series analysis using multiple SAR data or generating interferogram with long time intervals.

Development of Graph based Deep Learning methods for Enhancing the Semantic Integrity of Spaces in BIM Models (BIM 모델 내 공간의 시멘틱 무결성 검증을 위한 그래프 기반 딥러닝 모델 구축에 관한 연구)

  • Lee, Wonbok;Kim, Sihyun;Yu, Youngsu;Koo, Bonsang
    • Korean Journal of Construction Engineering and Management
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    • v.23 no.3
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    • pp.45-55
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    • 2022
  • BIM models allow building spaces to be instantiated and recognized as unique objects independently of model elements. These instantiated spaces provide the required semantics that can be leveraged for building code checking, energy analysis, and evacuation route analysis. However, theses spaces or rooms need to be designated manually, which in practice, lead to errors and omissions. Thus, most BIM models today does not guarantee the semantic integrity of space designations, limiting their potential applicability. Recent studies have explored ways to automate space allocation in BIM models using artificial intelligence algorithms, but they are limited in their scope and relatively low classification accuracy. This study explored the use of Graph Convolutional Networks, an algorithm exclusively tailored for graph data structures. The goal was to utilize not only geometry information but also the semantic relational data between spaces and elements in the BIM model. Results of the study confirmed that the accuracy was improved by about 8% compared to algorithms that only used geometric distinctions of the individual spaces.

Sea Ice Drift Tracking from SAR Images and GPS Tracker (SAR 영상과 GPS 추적기를 이용한 여름철 해빙 이동 궤적 추적)

  • Jeong-Won Park;Hyun-Cheol Kim;Minji Seo;Ji-Eun Park;Jinku Park
    • Korean Journal of Remote Sensing
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    • v.39 no.3
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    • pp.257-268
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    • 2023
  • Sea ice plays an important role in Earth's climate by regulating the amount of solar energy absorbed and controlling the exchange of heat and material across the air-sea interface. Its growth, drift, and melting are monitored on a regular basis by satellite observations. However, low-resolution products with passive microwave radiometer have reduced accuracy during summer to autumn when the ice surface changes rapidly. Synthetic aperture radar (SAR) observations are emerging as a powerful complementary, but previous researches have mainly focused on winter ice. In this study, sea ice drift tracking was evaluated and analyzed using SAR images and tracker with global positioning system (GPS) during late summer-early autumn period when ice surface condition changes a lot. The results showed that observational uncertainty increases compared to winter period, however, the correlation coefficient with GPS measurements was excellent at 0.98, and the performance of the ice tracking algorithm was proportional to the sea ice concentration with a correlation coefficient of 0.59 for ice concentrations above 50%.

Operational Ship Monitoring Based on Multi-platforms (Satellite, UAV, HF Radar, AIS) (다중 플랫폼(위성, 무인기, AIS, HF 레이더)에 기반한 시나리오별 선박탐지 모니터링)

  • Kim, Sang-Wan;Kim, Donghan;Lee, Yoon-Kyung;Lee, Impyeong;Lee, Sangho;Kim, Junghoon;Kim, Keunyong;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.36 no.2_2
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    • pp.379-399
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    • 2020
  • The detection of illegal ship is one of the key factors in building a marine surveillance system. Effective marine surveillance requires the means for continuous monitoring over a wide area. In this study, the possibility of ship detection monitoring based on satellite SAR, HF radar, UAV and AIS integration was investigated. Considering the characteristics of time and spatial resolution for each platform, the ship monitoring scenario consisted of a regular surveillance system using HFR data and AIS data, and an event monitoring system using satellites and UAVs. The regular surveillance system still has limitations in detecting a small ship and accuracy due to the low spatial resolution of HF radar data. However, the event monitoring system using satellite SAR data effectively detects illegal ships using AIS data, and the ship speed and heading direction estimated from SAR images or ship tracking information using HF radar data can be used as the main information for the transition to UAV monitoring. For the validation of monitoring scenario, a comprehensive field experiment was conducted from June 25 to June 26, 2019, at the west side of Hongwon Port in Seocheon. KOMPSAT-5 SAR images, UAV data, HF radar data and AIS data were successfully collected and analyzed by applying each developed algorithm. The developed system will be the basis for the regular and event ship monitoring scenarios as well as the visualization of data and analysis results collected from multiple platforms.