• Title/Summary/Keyword: Random Process

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Structurization in Community Composition and Diversity Pattern of Soil Seed Banks in Gwangneung Forest, South Korea (한국 광릉숲 매토종자에서 군집 종조성 및 다양성 양상의 구조화)

  • Kim, Han-Gyeol;Oh, Seung-Hwan;Cho, Yong-Chan
    • Journal of Korean Society of Forest Science
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    • v.110 no.4
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    • pp.577-589
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    • 2021
  • Soil seed bank community contributes to the long-term conservation of plant diversity and vegetation dynamics, and their decreasing diversity and density with soil depth provide critical perspectives (deterministic and stochastic) for understanding the community disassembly process. We analyzed changes in species composition and diversity and structuring patterns by soil layer (top and bottom), including surface vegetation, in Gwangneung Forest, a mature forest with a vegetation climate in the temperate central part of the Korean Peninsula. From two layers of soil collected with a vertical difference of 10 cm, 934 specimens of 27 families, 40 genera, 44 species, three varieties, and 47 taxa, germinated. Although species diversity and germination density decreased in most comparative characteristics, including growth type, there was no statistical significance due to large deviations. Within-group variability of species composition was similar in the upper and lower soils, as was the decline pattern in co-occurred species (ζ-diversity) and change in species retention probability. The structuring process of the community composition in the two soil layers was fitted with an exponential correlation rather than a power function, demonstrating the dominance of the stochastic process. The pattern in diversity and species turnover according to soil depth in Gwangneung Forest was discovered to be structured by stochastic random events, such as seed vertical movement rather than interaction with trait characteristics.

The Effects of the Online Learning Using Virtual Reality (VR) Geological Data: Focused on the Geo-Big Data Open Platform (가상현실(VR) 지질자료 개발을 통한 원격수업의 효과 분석: 지오빅데이터 오픈플랫폼 활용을 중심으로)

  • Yoon, Han Do;Kim, Hyoungbum;Kim, Heoungtae
    • Journal of the Korean Society of Earth Science Education
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    • v.15 no.1
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    • pp.47-61
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    • 2022
  • In this study, We developed VR (Virtual Reality) geological resources based on the Geo Big Data of the Big Data platform that provided by the Korea Institute of Geoscience and Mineral Material (KIGAM). So students selected the theme of lessons by using these resources and we operated Remote classes using the materials that developed as to Virtual Reality. Therefore, the geological theme maps provided by the Geo Big Data Open Platform were reconstructed and produced materials were created for Study about Real Korean geological outcrops grounded in Virtual Reality. And Topographic information data was used to produce class materials for Remote classes. Twenty students were selected by Random sampling, and data were collected by conducting a survey including interviews to confirm the change in students' perception of remote classes in virtual reality geological data development and the effect of the classes, so data were analyzed through inductive categorization. The results of this study are as follows. First, students showed positive responses in terms of interest, utilization, and knowledge utilization as taking remote classes for developing geological data in virtual reality geological data. This is the result of showing the adaptability of diverse and flexible learning getting away from a fixed framework by motivating and encouraging students and inducing cooperation for communication. Second, students recognized distance education in the development of Virtual Reality geological data as 'Realistic hands-on learning process', 'Immersive learning process by motivation', and 'Learning process of acquiring knowledge in the field of earth science'.

EEG Feature Engineering for Machine Learning-Based CPAP Titration Optimization in Obstructive Sleep Apnea

  • Juhyeong Kang;Yeojin Kim;Jiseon Yang;Seungwon Chung;Sungeun Hwang;Uran Oh;Hyang Woon Lee
    • International journal of advanced smart convergence
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    • v.12 no.3
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    • pp.89-103
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    • 2023
  • Obstructive sleep apnea (OSA) is one of the most prevalent sleep disorders that can lead to serious consequences, including hypertension and/or cardiovascular diseases, if not treated promptly. Continuous positive airway pressure (CPAP) is widely recognized as the most effective treatment for OSA, which needs the proper titration of airway pressure to achieve the most effective treatment results. However, the process of CPAP titration can be time-consuming and cumbersome. There is a growing importance in predicting personalized CPAP pressure before CPAP treatment. The primary objective of this study was to optimize the CPAP titration process for obstructive sleep apnea patients through EEG feature engineering with machine learning techniques. We aimed to identify and utilize the most critical EEG features to forecast key OSA predictive indicators, ultimately facilitating more precise and personalized CPAP treatment strategies. Here, we analyzed 126 OSA patients' PSG datasets before and after the CPAP treatment. We extracted 29 EEG features to predict the features that have high importance on the OSA prediction index which are AHI and SpO2 by applying the Shapley Additive exPlanation (SHAP) method. Through extracted EEG features, we confirmed the six EEG features that had high importance in predicting AHI and SpO2 using XGBoost, Support Vector Machine regression, and Random Forest Regression. By utilizing the predictive capabilities of EEG-derived features for AHI and SpO2, we can better understand and evaluate the condition of patients undergoing CPAP treatment. The ability to predict these key indicators accurately provides more immediate insight into the patient's sleep quality and potential disturbances. This not only ensures the efficiency of the diagnostic process but also provides more tailored and effective treatment approach. Consequently, the integration of EEG analysis into the sleep study protocol has the potential to revolutionize sleep diagnostics, offering a time-saving, and ultimately more effective evaluation for patients with sleep-related disorders.

A Study on the Development of a Program for Predicting Successful Welding of Electric Vehicle Batteries Using Laser Welding (레이저 용접을 이용한 전기차 배터리 이종접합 성공 확률 예측 프로그램 개발에 관한 연구)

  • Cheol-Hwan Kim;Chan-Su Moon;Kwan-Su Lee;Jin-Su Kim;Ae-Ryeong Jo;Bo-Sung Shin
    • Journal of the Microelectronics and Packaging Society
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    • v.30 no.4
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    • pp.44-49
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    • 2023
  • In the global pursuit of carbon neutrality, the rapid increase in the adoption of electric vehicles (EVs) has led to a corresponding surge in the demand for batteries. To achieve high efficiency in electric vehicles, considerations of weight reduction and battery safety have become crucial factors. Copper and aluminum, both recognized as lightweight materials, can be effectively joined through laser welding. However, due to the distinct physical characteristics of these two materials, the process of joining them poses technical challenges. This study focuses on conducting simulations to identify the optimal laser parameters for welding copper and aluminum, with the aim of streamlining the welding process. Additionally, a Graphic User Interface (GUI) program has been developed using the Python language to visually present the results. Using machine learning image data, this program is anticipated to predict joint success and serve as a guide for safe and efficient laser welding. It is expected to contribute to the safety and efficiency of the electric vehicle battery assembly process.

Predicting the Effects of Rooftop Greening and Evaluating CO2 Sequestration in Urban Heat Island Areas Using Satellite Imagery and Machine Learning (위성영상과 머신러닝 활용 도시열섬 지역 옥상녹화 효과 예측과 이산화탄소 흡수량 평가)

  • Minju Kim;Jeong U Park;Juhyeon Park;Jisoo Park;Chang-Uk Hyun
    • Korean Journal of Remote Sensing
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    • v.39 no.5_1
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    • pp.481-493
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    • 2023
  • In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

Application of Westgard Multi-Rules for Improving Nuclear Medicine Blood Test Quality Control (핵의학 검체검사 정도관리의 개선을 위한 Westgard Multi-Rules의 적용)

  • Jung, Heung-Soo;Bae, Jin-Soo;Shin, Yong-Hwan;Kim, Ji-Young;Seok, Jae-Dong
    • The Korean Journal of Nuclear Medicine Technology
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    • v.16 no.1
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    • pp.115-118
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    • 2012
  • Purpose: The Levey-Jennings chart controlled measurement values that deviated from the tolerance value (mean ${\pm}2SD$ or ${\pm}3SD$). On the other hand, the upgraded Westgard Multi-Rules are actively recommended as a more efficient, specialized form of hospital certification in relation to Internal Quality Control. To apply Westgard Multi-Rules in quality control, credible quality control substance and target value are required. However, as physical examinations commonly use quality control substances provided within the test kit, there are many difficulties presented in the calculation of target value in relation to frequent changes in concentration value and insufficient credibility of quality control substance. This study attempts to improve the professionalism and credibility of quality control by applying Westgard Multi-Rules and calculating credible target value by using a commercialized quality control substance. Materials and Methods : This study used Immunoassay Plus Control Level 1, 2, 3 of Company B as the quality control substance of Total T3, which is the thyroid test implemented at the relevant hospital. Target value was established as the mean value of 295 cases collected for 1 month, excluding values that deviated from ${\pm}2SD$. The hospital quality control calculation program was used to enter target value. 12s, 22s, 13s, 2 of 32s, R4s, 41s, $10\bar{x}$, 7T of Westgard Multi-Rules were applied in the Total T3 experiment, which was conducted 194 times for 20 days in August. Based on the applied rules, this study classified data into random error and systemic error for analysis. Results: Quality control substances 1, 2, and 3 were each established as 84.2 ng/$dl$, 156.7 ng/$dl$, 242.4 ng/$dl$ for target values of Total T3, with the standard deviation established as 11.22 ng/$dl$, 14.52 ng/$dl$, 14.52 ng/$dl$ respectively. According to error type analysis achieved after applying Westgard Multi-Rules based on established target values, the following results were obtained for Random error, 12s was analyzed 48 times, 13s was analyzed 13 times, R4s was analyzed 6 times, for Systemic error, 22s was analyzed 10 times, 41s was analyzed 11 times, 2 of 32s was analyzed 17 times, $10\bar{x}$ was analyzed 10 times, and 7T was not applied. For uncontrollable Random error types, the entire experimental process was rechecked and greater emphasis was placed on re-testing. For controllable Systemic error types, this study searched the cause of error, recorded the relevant cause in the action form and reported the information to the Internal Quality Control committee if necessary. Conclusions : This study applied Westgard Multi-Rules by using commercialized substance as quality control substance and establishing target values. In result, precise analysis of Random error and Systemic error was achieved through the analysis of 12s, 22s, 13s, 2 of 32s, R4s, 41s, $10\bar{x}$, 7T rules. Furthermore, ideal quality control was achieved through analysis conducted on all data presented within the range of ${\pm}3SD$. In this regard, it can be said that the quality control method formed based on the systematic application of Westgard Multi-Rules is more effective than the Levey-Jennings chart and can maximize error detection.

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Seed-dependent Accelerated Fibrillation of ${\alpha}$-Synuclein Induced by Periodic Ultrasonication Treatment

  • Kim, Hyun-Jin;Chatani, Eri;Goto, Yuji;Paik, Seung-R.
    • Journal of Microbiology and Biotechnology
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    • v.17 no.12
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    • pp.2027-2032
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    • 2007
  • [ ${\alpha}$ ]-Synuclein is the major component of Lewy bodies and responsible for the amyloid deposits observed in Parkinson's disease. Ordered filamentous aggregate formation of the natively unfolded ${\alpha}$-synuclein was investigated in vitro with the periodic ultrasonication. The ultrasonication induced the fibrillation of ${\alpha}$-synuclein, as the random structure gradually converted into a ${\beta}$-sheet structure. The resulting fibrils obtained at the stationary phase appeared heterogeneous in their size distribution, with the average length and height of $0.28\;{\mu}m{\pm}0.21\;{\mu}m$ and $5.6\;nm{\pm}1.9\;nm$, respectively. After additional extensive ultrasonication in the absence of monomeric ${\alpha}$-synuclein, the equilibrium between the fibril formation and its breakdown shifted to the disintegration of the preexisting fibrils. The resulting fragments served as nucleation centers for the subsequent seed-dependent accelerated fibrillation under a quiescent incubation condition. This self-seeding amplification process depended on the seed formation and subsequent alterations in their properties by the ultrasonication to a state that accretes the monomeric soluble protein more effectively than their reassociation of the seeds back to the original fibrils. Since many neurodegenerative disorders have been considered to be propagated via the seed-dependent amyloidosis, this study would provide a novel aspect of the significance of the seed structure and its properties leading to the acce]erated amyloid formation.

A Study on the Interregional Relationship of Housing Purchase Price Volatility (지역간 주택매매가격 변동성의 상관관계에 관한 연구)

  • Yoo, Han-Soo
    • Korean Business Review
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    • v.20 no.2
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    • pp.15-27
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    • 2007
  • This paper analyzed the relationship between Housing Purchase Price volatility of Seoul and Housing Purchase Price volatility of local large city. Other studies investigates the effect on the observed volatility Observed volatility consists of fundamental volatility and transitory volatility. Fundamental volatility is caused by information arrival and transitory volatility is caused by noise trading. Fundamental volatility is trend component and is modelled as a random walk with drift. Transitory volatility is cyclical component and is modelled as a stationary process. In contrast to other studies, this study investigates the effect on the fundamental volatility and transitory volatility individually. Observed volatility is estimated by GJR GARCH(1,1) model. We find that GJH GARCH model is superior to GARCH model and good news is more remarkable effect on volatility than bad news. This study decomposes the observed volatility into fundamental volatility and transitory volatility using Kalman filtering method. The findings in this paper is as follows. The correlation between Seoul housing price volatility and Busan housing price volatility is high. But, the correlation between Seoul and Daejeon is low. And the correlation between Daejeon and Busan is low. As a distinguishing feature, the correlation between fundamental volatilities is high in the case of all pairs. But, the correlation between transitory volatilities turns out low. The reason is as follows. When economic information arrives, Seoul, Daejeon, and Busan housing markets, all together, are affected by this information.

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Reservation based Multichannel CSMA Protocol for Improvement of Energy Consumption and QoS in Wireless Sensor Networks (무선 센서 네트워크 환경에서 에너지 소비 및 QoS를 고려한 예약기반 Multichannel CSMA 프로토콜)

  • Han, Jung-Ahn;Kim, Yun-Hyung;Lee, Moon-Ho;Kim, Byung-Gi
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.2A
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    • pp.143-151
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    • 2007
  • One of the consideration things to design protocol in wireless sensor networks is to maximize lifetime of sensor node as reducing energy consumption. In this paper propose reserve based multichannel CSMA mac protocol for minimizing energy consumption which arise from collision and waiting retransmission at channel access process in mac layer Each sensor node which constitute sensor networks has data channel and control channel. And as sensor node reserve channel for data transmission by using control channel and receipt node allow reservation node to use data channel, sending node can abbreviate try of retransmission after random interval time. Also, When sending node delivers selects option channel in available channels to receipt node, the receipt node decide whether the channel is available to oneself and through the result select transmission channel ultimately. Performance evaluation compare with previous simple multichannel CSMA.

Joint Tx-Rx Optimization in Additive Cyclostationary Noise with Zero Forcing Criterion (가산성 주기정상성 잡음이 있을 때 Zero Forcing 기반에서의 송수신단 동시 최적화)

  • Yun, Yeo-Hun;Cho, Joon-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.7A
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    • pp.724-729
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    • 2007
  • In this paper, we consider a joint optimization of transmitter and receiver in additive cyclostationary noise with zero forcing criterion. We assume that the period of the cyclostationary noise is the same as the inverse of the symbol transmission rate and that the noise has a positive-definite autocorrelation function. The data sequence is modeled as a wide-sense stationary colored random process and the channel is modeled as a linear time-invariant system with a frequency selective impulse response. Under these assumptions and a constraint on the average power of the transmitted signal, we derive the optimum transmitter and receiver waveforms that jointly minimizes the mean square error with no intersymbol interference. The simulation results show that the proposed system has a better BER performance than the systems with receiver only optimization and the systems with no transmitter and receiver optimization.