• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.7 no.2
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• pp.128-138
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• 1996

In this paper, the Doppler phase error due to the relative velocity between a satellite and the earth station in communications using a low earth orbit mobile satellite is detected. The performance of BPSK system in the presence of Rician fading channel environment with Doppler phase error, inter- ference and noise is compared with that of the system disturbed by Doppler phase error and noise only, And adopted coding techniques are Hamming, BCH, RS and convolution codes. The expression of error rate performance of BPSK system is derived as the type of complementary error function. The main conclusion that can be drawn from this analysis is that Rician fading channel environment with Do- ppler phase error and interference, noise effect yields severe performance degradation then Doppler phase error and noise effect in satellite communication channel. The conclusion can be drawn from this analysis is that using coding technique then noncoding. And using the numerical calculation, we give a quantitative insight how much the satellite communication channel parameters degrade the system per- formance. Furthermore it is shown that an appropriate transmission power control for the performance enhancement is beneficial to the new satellite communication system planning.

• Journal of the Korean earth science society
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• v.28 no.2
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• pp.214-226
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• 2007

Because precipitation is influenced by various atmospheric variables, it is highly nonlinear. Although precipitation predicted by a dynamic model can be corrected by using a nonlinear Artificial Neural Network, this approach has limits such as choices of the initial weight, local minima and the number of neurons, etc. In the present paper, we correct simulated precipitation by using a multiple linear regression (MLR) method, which is simple and widely used. First of all, Ensemble hindcast is conducted by the PNU/CME Coupled General Circulation Model (CGCM) (Park and Ahn, 2004) for the period from April to August in 1979-2005. MLR is applied to precipitation simulated by PNU/CME CGCM for the months of June (lead 2), July (lead 3), August (lead 4) and seasonal mean JJA (from June to August) of the Northeast Asian region including the Korean Peninsula $(110^{\circ}-145^{\circ}E,\;25-55^{\circ}N)$. We build the MLR model using a linear relationship between observed precipitation and the hindcasted results from the PNU/CME CGCM. The predictor variables selected from CGCM are precipitation, 500 hPa vertical velocity, 200 hPa divergence, surface air temperature and others. After performing a leave-oneout cross validation, the results are compared with the PNU/CME CGCM's. The results including Heidke skill scores demonstrate that the MLR corrected results have better forecasts than the direct CGCM result for rainfall.

• Journal of Pharmacopuncture
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• v.19 no.3
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• pp.197-206
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• 2016

Introduction: This study aims to investigate the effects of acupuncture stimulation on the radial artery's pressure pulse wave, along with various hemodynamic parameters, and to explore the possible underlying mechanism of pulse diagnosis in healthy participants in their twenties. Methods and analysis: This study is a prospective, single-arm, exploratory clinical study. A total of 25 healthy participants, without regard to gender, in their twenties will be recruited by physicians. Written informed consent will be obtained from all participants. The participants will receive acupuncture once at ST36 on both sides. The radial arterial pulse waves will be measured on the left arm of the subjects by using an applicable pulse tonometric device (KIOM-PAS). On the right arm (appearing twice), electrocardiogram (ECG), photoplethysmogram (PPG), respiration and cardiac output (CO) signals, will be measured using a physiological data acquisition system (Biopac module), while the velocity of blood flow, and the diameter and the depth of the blood vessel will be measured using an ultrasonogram machine on the right arm (appearing twice). All measurements will be conducted before, during, and after acupuncture. The primary outcome will be the spectral energy at high frequencies above 10 Hz ($SE_{10-30Hz}$) calculated from the KIOM-PAS device signal. Secondary outcomes will be various variables obtained from the KIOM-PAS device, ECG, PPG, impedance cardiography modules, and an ultrasonogram machine. Discussion: The results of this trial will provide information regarding the physiological and the hemodynamic mechanisms underlying acupuncture stimulation and clinical evidence for the influence of acupuncture on the pressure pulse wave in the radial artery. Ethics and dissemination: This study was approved by the Institutional Review Board (IRB) of Kyung Hee University's Oriental Medical Center, Seoul, Korea (KOMCIRB-150818-HR-030). The study findings will be published in peer-reviewed journals and presented at national and international conferences. Trial registration number: This trial was registered with the Clinical Research Information Service (CRIS) at the Korea National Institute of Health (NIH), Republic of Korea (KCT0001663), which is a registry in the World Health Organization's (WHO's) Registry Network.

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.97-106
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• 2002

In 3GPP2 standard, MIP is used and a PDSN performs the function of FA to support macro mobility. When a MS is roaming from a PDSN area to another, the mobility supported is called macro mobility, while it is called micro mobility when a MS is roaming from a RN area to another in a PDSN area. Since a PDSN performs the function of FA in 3GPP2 standard, it is possible to support mobility but its mechanism is actually for supporting macro mobility, not for micro mobility, thus it is weak in processing fast and seamless handoff to support micro mobility. In this paper, we suggest the seamless handoff algorithm barred on multicast group mechanism to support micro mobility. Depending on the moving direction and velocity of a MS, the suggested algorithm constructs a multicast group of RNs on the forecasted MS's moving path, and maximally delays RNs'joining to a multicast group to increase the network efficiency. Moreover, to resolve the buffer overhead problem of the existent multicast scheme, the algorithm suggests that each RN buffers data only after the forecasted handoff time. To prove deadlock freeness and liveness of the algorithm. we use state transition diagrams, a Petri-net modeling and its reachability tree. Then, we evaluate the performance by simulation.

• Resources Recycling
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• v.22 no.4
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• pp.38-45
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• 2013

The porous ceramic beads using mine tailing were prepared and applied to catalytic converter for NOx/SOx removal. Catalytic support was used synthesized mesoporous silica (SBA-15) which coated on surface. Internal structure for porous ceramic beads was composed of three-dimensional network structure and porosity was about 80%. In addition, the specific surface area for mesoporous silica(SBA-15) coated on converter was significantly increased 55 $m^2/g$ compared with 0.8 $m^2/g$ before coating. NOx/SOx removal experiment was performed using $V_2O_5$ and $V_2O_5$/CuO converter. NOx conversion ratio for $V_2O_5$/CuO converter was approximately increased 10% compared to $V_2O_5$ converter. In addition, catalytic converter of $V_2O_5$/CuO was shown to remove 95% of NOx and 90% of SOx at reaction temperature of $350^{\circ}C$, space velocity of 10000 $h^{-1}$ and $O_2$ concentrations of 5%, respectively.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.77-88
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• 2021

Duck industry had a rapid growth in recent years. Nevertheless, researches to improve duck house environment are still not sufficient enough. Moisture generation of duck house litter is an important factor because it may cause severe illness and low productivity. However, the measuring process is difficult because it could be disturbed with animal excrements and other factors. Therefore, it has to be calculated according to the environmental data around the duck house litter. To cut through all these procedures, we built several machine learning regression model forecasting moisture generation of litter by measured environment data (air temperature, relative humidity, wind velocity and water contents). 5 models (Multi Linear Regression, k-Nearest Neighbors, Support Vector Regression, Random Forest and Deep Neural Network). have been selected for regression. By using R-Square, RMSE and MAE as evaluation metrics, the best accurate model was estimated according to the variables for each machine learning model. In addition, to address the small amount of data acquired through lab experiments, bootstrapping method, a technique utilized in statistics, was used. As a result, the most accurate model selected was Random Forest, with parameters of n-estimator 200 by bootstrapping the original data nine times.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.1-12
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• 2021

In this paper, a new algorithm is proposed to estimate the damage location in the composite panel by extracting the elastic wave signal reflected from the damaged area. The guided elastic wave is generated by a piezoelectric actuator and sensed by a piezoelectric sensor. The proposed algorithm adopts a diagnostic approach. It compares the non-damaged signal with the damaged signal, and extract damage information along with sensor network and lamb wave group velocity estimated by signal correlation. However, it is difficult to clearly distinguish the damage location due to the nonlinear properties of lamb wave and complex information composed of various signals. To overcome this difficulty, the cumulative summation feature vector algorithm(CSFV) and a visualization technique are newly proposed in this paper. CSFV algorithm finds the center position of the damage by converting the signals reflected from the damage to the area of distance at which signals reach, and visualization technique is applied that expresses feature vectors by multiplying damage indexes. Experiments are performed for a composite panel and comparative study with the existing algorithms is carried out. From the results, it is confirmed that the damage location can be detected by the proposed algorithm with more reliable accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.697-705
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• 2020

This paper deals with an analysis of crustal movement for the sourthern part of Korean peninsula using GNSS (Global Navigation Satellite System) data. An earthquake of more than 5.0 occurred in the southeastern region of the Korean Peninsula, and it is necessary to evaluate the risk of earthquakes in various ways.In order to reveal long-term tectonic movement patten in Pohang and Gyeongju provinces, we derived crustal movement parameters related with elastic theory. We used GAMIT/GLOBK for analyzing seven-year interval GNSS data of CORS (Continuously Operating Reference Stations). The azimuth of velocity vectors trended generally about 110° with an mean magnitude of 31mm/yr.The main characteristics of the strain change for seven-year in Korea obtaind from our study. Direction of the principal axis of the maximum compression is ENE-WSW as a whole, through there are some exceptions. The mean rate of the maximum shear strain change is (0.11±0.07)μ/yr, that is approximately one third that of Chubu district, Central Japan. Taking into account our results, the mean rate of maximum shear in southern part of Korean peninsula is considered as reasonable. The mean azimuth of principal strain is about (85.4°±26.8°). There are some exceptions of azimuth because the average azimuth differ from the left and right side in Yangsan fault which are about (73.2°±21.5°) and (105.2°±17.0°) respectively, It is noteworthy that the high seismicity areas in the southern part of Korea peninsula almost coincides with the area of large strain rate. As a conclusion, it could be stated that the our study represents the characteristics of crustal deformation in the southern part of peninsula, and contributes to the researches on earthquake disaster management.

• Advances in nano research
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• v.12 no.5
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• pp.501-514
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• 2022

This study aimed to investigate the effects and potential mechanisms of Chikusetsusaponin V (CsV) on endothelial nitric oxide synthase (eNOS) and vascular endothelial cell functions. Different concentrations of CsV were added to animal models, bovine aorta endothelial cells (BAECs) and human umbilical vein endothelial cells (HUVECs) cultured in vitro. qPCR, Western blotting (WB), and B ultrasound were performed to explore the effects of CsV on mouse endothelial cell functions, vascular stiffness and cellular eNOS mRNA, protein expression and NO release. Bioinformatics analysis, network pharmacology, molecular docking and protein mass spectrometry analysis were conducted to jointly predict the upstream transcription factors of eNOS. Furthermore, pulldown and ChIP and dual luciferase assays were employed for subsequent verification. At the presence or absence of CsV stimulation, either overexpression or knockdown of purine rich element binding protein A (PURA) was conducted, and PCR assay was employed to detect PURA and eNOS mRNA expressions, Western blot was used to detect PURA and eNOS protein expressions, cell NO release and serum NO levels. Tube formation experiment was conducted to detect the tube forming capability of HUVECs cells. The animal vasodilation function test detected the vasodilation functions. Ultrasonic detection was performed to determine the mouse aortic arch pulse wave velocity to identify aortic stiffness. CsV stimulus on bovine aortic cells revealed that CsV could upregulate eNOS protein levels in vascular endothelial cells in a concentration and time dependent manner. The expression levels of eNOS mRNA and phosphorylation sites Ser1177, Ser633 and Thr495 increased significantly after CsV stimulation. Meanwhile, CsV could also enhance the tube forming capability of HUVECs cells. Following the mice were gavaged using CsV, the eNOS protein level of mouse aortic endothelial cells was upregulated in a concentration- and time-dependent manner, and serum NO release and vasodilation ability were simultaneously elevated whereas arterial stiffness was alleviated. The pulldown, ChIP and dual luciferase assays demonstrated that PURA could bind to the eNOS promoter and facilitate the transcription of eNOS. Under the conditions of presence or absence of CsV stimulation, overexpression or knockdown of PURA indicated that the effect of CsV on vascular endothelial function and eNOS was weakened following PURA gene silence, whereas overexpression of PURA gene could enhance the effect of CsV upregulating eNOS expression. CsV could promote NO release from endothelial cells by upregulating the expression of PURA/eNOS pathway, improve endothelial cell functions, enhance vasodilation capability, and alleviate vessel stiffness. The present study plays a role in offering a theoretical basis for the development and application of CsV in vascular function improvement, and it also provides a more comprehensive understanding of the pharmacodynamics of CsV.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.