• Journal of Ginseng Research
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• v.45 no.4
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• pp.527-534
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• 2021

Background: Phenological studies are a prerequisite for accomplishing higher productivity and better crop quality in cultivated plants. However, there are no phenological studies on Panax ginseng that improve its production yield. This study aims to redefine the phenological growth stages of P. ginseng based on the existing Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie (BBCH) scale and proposes a disease control reference. Methods: This study was conducted at the Korea Ginseng Corporation Experiment Station in Gyeonggi province, South Korea. Phenological observations were performed once weekly or twice monthly, based on the developmental stages. The existing BBCH scale with a three-digit code was used to redefine and update P. ginseng's phenological growth codes. Results: The phenological description is divided into eight principal growth stages: three for vegetative growth (perennating bud, aerial shoot, and root development), four for reproductive growth (reproductive organ development, flowering, fruit development, and fruit maturation), and one for senescence according to the extended BBCH scale. A total of 58 secondary growth stages were described within the eight principal growth stages. Under each secondary growth stage, four mesostages are also taken into account, which contains the distinct patterns of the phenological characteristics in ginseng varieties and the process of transplanting seedlings. A practical management program for disease control was also proposed by using the BBCH code and the phenological data proposed in this work. Conclusion: The study introduces an extended BBCH scale for the phenological research of P. ginseng.

• The Journal of Korean Institute of Information Technology
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• v.17 no.11
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• pp.17-26
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• 2019

RAID-5 technology is one of the choice for flash storage device to enhance its reliability. However, RAID-5 has inherent parity update overhead, especially, parity overhead for partial stripe write is one of the crucial issues for flash-based RAID-5 technologies. In this paper, we design efficient parity log architecture for RAID-5 to eliminate runtime partial parity overhead. During runtime, partial parity is retained in buffer memory until full stripe write completed, and the parity is written with full strip write. In addition, parity log is maintained in memory until whole the stripe group is used for data write. With this parity log, partial parity can be recovered from the power loss. In the experiments, the parity log method can eliminate partial parity writes overhead with a little parity log writes. Hence it can reduce write amplification at the same reliability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.785-791
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• 2021

In this paper, we propose a methodology for estimating the optimal traversable destination from the location-based information of the object recognized by the mobile robot to perform the object delivery service. The location estimation process is to apply the generalized Voronoi graph to the grid map to create an initial topology map composed of nodes and links, recognize objects and extract location data using RGB-D sensors, and collect the shape and distance information of obstacles. Then, by applying the hybrid approach that combines the center of gravity and thinning method, the optimal moving position for the service robot to perform the task of grabbing is estimated. And then, the optimal node information for the robot's work destination is updated by comparing the geometric distance between the estimated position and the existing node according to the node update rule.

• Structural Engineering and Mechanics
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• v.81 no.3
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• pp.293-303
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• 2022

As infrastructure ages and traffic load increases, serious public concerns have arisen for the well-being of bridges. The current health monitoring practice focuses on large-scale bridges rather than short span bridges. However, it is critical that more attention should be given to these behind-the-scene bridges. The relevant information about the construction methods and as-built properties are most likely missing. Additionally, since the condition of a bridge has unavoidably changed during service, due to weathering and deterioration, the material properties and boundary conditions would also have changed since its construction. Therefore, it is not appropriate to continue using the design values of the bridge parameters when undertaking any analysis to evaluate bridge performance. It is imperative to update the model, using finite element (FE) analysis to reflect the current structural condition. In this study, a FE model is established to simulate a concrete culvert bridge in New South Wales, Australia. That model, however, contains a number of parameter uncertainties that would compromise the accuracy of analytical results. The model is therefore updated with a neural network (NN) optimisation algorithm incorporating Monte Carlo (MC) simulation to minimise the uncertainties in parameters. The modal frequency and strain responses produced by the updated FE model are compared with the frequency and strain values on-site measured by sensors. The outcome indicates that the NN model updating incorporating MC simulation is a feasible and robust optimisation method for updating numerical models so as to minimise the difference between numerical models and their real-world counterparts.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

• Journal of Korean Academy of Dental Administration
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• v.10 no.1
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• pp.53-65
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• 2022

The Primary Care Patient Measure of Safety (PC-PMOS) is a measure of safety that allows patients to evaluate contributing factors related to patient safety in primary care. This study aimed to examine which questionnaire items of the PC-PMOS could be used in Korean dental institutions. A survey of the Korean translation of the PC-PMOS, a self-reported questionnaire, was conducted in August 2022 by 400 adults who had used dental-care services within the last three years. Of the 77 items, 34 were selected using principal component analysis and two experts' evaluations based on face validity. Five domains were identified from factor analysis: patient centeredness, patient information update, complaint processing, communication, and information about the complaint process. The Cronbach's alpha of the data was 0.913, indicating high reliability. As a result of the generalized multiple regression analysis, regression coefficients were not statistically significant, except for household income. This indicated that there was no bias in the patient safety scores of dental institutions evaluated by patients within the range of independent variables used in this study. The five domains with 34 items identified in this study suggested the factors that contribute to the safety of patients who used dental care services in Korea. However, validation of this study result is still important to refine questionnaires suitable for dental institutions in Korea so as to further improve the quality of dental care.

• KNOM Review
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• v.23 no.2
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• pp.11-17
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• 2020

Currently, the web page that provides residual substance information provides information on residual acceptance criteria in food for pesticides and veterinary drugs. Residual substances refer to pesticides or veterinary drugs that are left in agricultural, livestock, or marine products after being used by diluting them thousands of times. However, users are experiencing inconvenience due to the lack of information on pesticides and veterinary drugs, delays in search time, and Web page errors. In addition, the manager has the inconvenience of manually entering information such as residual acceptance criteria and analysis methods. Thus, this paper proposes a system that can efficiently manage and update the history of changes in information, such as residual material standards for pesticides, animal medicines and the characteristics of drugs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3738-3760
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• 2022

Due to increasing spectrum demand for new wireless devices applications, cooperative spectrum sensing (CSS) paradigm is the most promising solution to alleviate the spectrum shortage problem. However, in the interweave cognitive radio (CR) system, the inherent nature of CSS opens a hole to Byzantine attack, thereby resulting in a significant drop of the CSS security and efficiency. In view of this, a weighted differential sequential single symbol (WD3S) algorithm based on MATLAB platform is developed to accurately identify malicious users (MUs) and benefit useful sensing information from their malicious reports in this paper. In order to achieve this, a dynamic Byzantine attack model is proposed to describe malicious behaviors for MUs in an interweave CR system. On the basis of this, a method of data transmission consistency verification is formulated to evaluate the global decision's correctness and update the trust value (TrV) of secondary users (SUs), thereby accurately identifying MUs. Then, we innovatively reuse malicious sensing information from MUs by the weight allocation scheme. In addition, considering a high spectrum usage of primary network, a sequential and differential reporting way based on a single symbol is also proposed in the process of the sensing information submission. Finally, under various Byzantine attack types, we provide in-depth simulations to demonstrate the efficiency and security of the proposed WD3S.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.409-416
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• 2022

This paper relates to the blind noise separation method of time-delayed convolutive mixed signals. Since the mixed model of acoustic signals in a closed space is multi-channel, a convolutive blind signal separation method is applied and time-delayed data samples of the two microphone input signals is used. For signal separation, the mixing coefficient is calculated using an inverse model rather than directly calculating the separation coefficient, and the coefficient update is performed by repeated calculations based on secondary statistical properties to estimate the speech signal. Many simulations were performed to verify the performance of the proposed blind signal separation. As a result of the simulation, noise separation using this method operates safely regardless of convolutive mixing, and PESQ is improved by 0.3 points compared to the general adaptive FIR filter structure.

• Journal of Society of Preventive Korean Medicine
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• v.26 no.3
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• pp.1-16
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• 2022

Backgrounds : Doctor of Osteopathy (D.O.) in the United States have drawn attention as one of the future models of Korean Medicine doctors in Korea in that they have their own fields of care and therapies that distinguish them from medical doctor (M.D.), but are also able to carry out the treatment of general doctors. By analyzing D.O.'s specialization strategy, this study intends to preview points for establishing the future role of Korean Medicine doctors. Methods : We searched books, research papers, reports, conference presentations, and media articles, and chronologically classified and organized the collected data. In addition, the latest update information on related institutions' web pages and expert opinions released were also reviewed. Results : The D.O. emerged as a form of doctor in alternative medicine, however it rapidly turned to an M.D. substitute during the pandemic of the 1910s and World War II in the 1940s. Through the American Osteopathic Association (AOA)'s organizational activity, curriculum specialization, research development, and financial support, D.O. now has secured the status of M.D. in 50 states and federal law in the US. It has its own and exclusive full practice rights, capable of prescribing drugs and practicing surgery, as well as manual therapy. Beginning in July 2020, M.D.-D.O. achieved the full integration-unification of the professional training and residency program. Conclusions : In order to introduce the D.O. model to Korean Medicine system, it is necessary to strengthen biomedicine in the curriculum, and significantly expand the educational infrastructure and faculty manpower.