• Ecology and Resilient Infrastructure
• /
• v.9 no.1
• /
• pp.24-35
• /
• 2022

For water quality management, it is necessary to continuously improve the forecasting by analyzing the past water quality, and a Data-driven model is emerging as an alternative. Because the Data-driven model is built based on a wide range of data, it is essential to apply the correlation analysis method for the combination of input variables to obtain more reliable results. In this study, the Gamma Test was applied as a preceding step to build a faster and more accurate data-driven water quality prediction model. First, a physical-based model (HSPF, EFDC) was operated to produce daily water quality reflecting the complexity of the watershed according to various hydrological conditions for Paldang Dam. The Gamma Test was performed on the water quality at the water quality prediction site (Paldangdam2) and major rivers flowing into the Paldang Dam, and the method of selecting the optimal input data combination was presented through the analysis results (Gamma, Gradient, Standar Error, V-Ratio). As a result of the study, the selection criteria for a more efficient combination of input data that can save time by omitting trial and error when building a data-driven model are presented.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.10
• /
• pp.11-17
• /
• 2022

In this paper, a model that can increase the efficiency of work in arranging interior furniture by applying augmented reality technology was studied. In the existing system to which augmented reality is currently applied, there is a problem in that information is limitedly provided depending on the size and nature of the company's product when outputting the image of furniture. To solve this problem, this paper presents an AR labeling algorithm. The AR labeling algorithm extracts feature points from the captured images and builds a database including indoor location information. A method of detecting and learning the location data of furniture in an indoor space was adopted using the CNN technique. Through the learned result, it is confirmed that the error between the indoor location and the location shown by learning can be significantly reduced. In addition, a study was conducted to allow users to easily place desired furniture through augmented reality by receiving detailed information about furniture along with accurate image extraction of furniture. As a result of the study, the accuracy and loss rate of the model were found to be 99% and 0.026, indicating the significance of this study by securing reliability. The results of this study are expected to satisfy consumers' satisfaction and purchase desires by accurately arranging desired furniture indoors through the design and implementation of AR labels.

• Journal of the Society of Disaster Information
• /
• v.19 no.1
• /
• pp.18-30
• /
• 2023

Purpose: This study is to contribute to the development of monitoring technology through the increase of confidence in construction monitoring by deriving the analysis of construction monitoring cost and improvement measures of railway tunnel construction in Seoul. Method: It presents the status on design and contract of construction monitoring cost, status on application construction monitoring cost and its analysis, analysis on safety management cost and quality management cost, expansion of application of the price calculation standard for monitoring management services to improve this, and monitoring for direct order of ordering organization. Results: If the monitoring management service that was meanwhile ordered as included in the construction work is performed by the directly selected company of ordering organization through the preliminary screening for bidding qualification, then the improvement of monitoring quality and the accurate monitoring data can be secured. Conclusion: For the price calculation standard for monitoring management service, the application of actual cost addition method under the Engineering Promotion Act and the calculation standard of monitoring management cost for standard estimation for ground survey should be extended through the direct order of ordering organization, not the method to be included in the net construction cost where it is performed by a subcontractor via contractor.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.2
• /
• pp.149-155
• /
• 2023

Photovoltaic power generation is the most familiar power generation facility among new and renewable energies, and its supply began to expand about 10 years ago, and at this point, interest in solutions and technologies for system maintenance management is increasing. In particular, it is necessary to take measures to maximize the overall efficiency of the solar power generation system, whether or not there is an abnormality in the solar power generation system, and when to replace parts. The PV inverter, one element of the photovoltaic power generation system, is a power conversion system that relies on power switching devices, and DC-Link capacitors are used according to the configuration of DC/DC converters and DC-AC inverters. These DC capacitors also affect system safety (Safety) through renewable energy facilities due to the decrease in power generation of PV inverters, power loss, and increase in harmonics (THD, total distortion of AC output current) due to aging and deterioration due to long-term use. factors can be analyzed. Therefore, in this paper, the PV inverter operating characteristics according to the DC capacitor capacity state currently operating in the photovoltaic power generation system were considered, and research contents were proposed to secure the safety and reliability of renewable energy facilities.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.67 no.4
• /
• pp.274-284
• /
• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.2
• /
• pp.93-104
• /
• 2023

Currently, the permanent road traffic volume surveys under Road Act are conducted using a intrusive Automatic Vehicle Classification (AVC) equipments to classify 12 categories of vehicles. However, intrusive AVC equipment inevitably have friction with vehicles, and physical damage to sensors due to cracks in roads, plastic deformation, and road construction decreases the operation rate. As a result, accuracy and reliability in actual operation are deteriorated, and maintenance costs are also increasing. With the recent development of ITS technology, research to replace the intrusive AVC equipment is being conducted. However multiple equipments or self-built DB operations were required to classify 12 categories of vehicles. Therefore, this study attempted to prepare a method for classifying 12 categories of vehicles using vehicle specification information of the Vehicle Management Information System(VMIS), which is collected and managed in accordance with Motor Vehicle Management Act. In the future, it is expected to be used to upgrade and diversify road traffic statistics using vehicle specifications such as the introduction of a road traffic survey system using Automatic Number Plate Recognition(ANPR) and classification of eco-friendly vehicles.

• Journal of the Korean Society for Library and Information Science
• /
• v.57 no.3
• /
• pp.325-350
• /
• 2023

This study focuses on the impact of research data metadata quality evaluation index on the revitalization of K-BDS, a research data platform in the bio field, and examines the mediating effect of motivation factors for utilizing the platform. The investigation employs a structural equation model analysis and bootstrap analysis to explore the interrelationships among the three variables. The findings demonstrate that researchers who prioritize the quality of metadata display higher motivation to use the research data platform, leading to an intention to activate the platform. The study also confirms the mediating effect of motivation factors. Moreover, a comprehensive understanding of the sub-factors within each variable is attained through regression analysis and Sobel test. The results highlight that enhancing searchability is crucial to activate research data sharing in the bio field, while improving discoverability is vital for research data reuse. Interestingly, the study reveals that citationability does not significantly impact platform activation. As a conclusion, to foster platform activation, it is imperative to provide systematic support by enhancing metadata quality. This improvement can not only increase trust in the platform but also institutionally solidify the benefits of citation.

• Journal of Life Science
• /
• v.33 no.8
• /
• pp.663-679
• /
• 2023

This review analyzes research trends related to new drug development using artificial intelligence from 2010 to 2022. This analysis organized the abstracts of 2,421 studies into a corpus, and words with high frequency and high connection centrality were extracted through preprocessing. The analysis revealed a similar word frequency trend between 2010 and 2019 to that between 2020 and 2022. In terms of the research method, many studies using machine learning were conducted from 2010 to 2020, and since 2021, research using deep learning has been increasing. Through these studies, we investigated the trends in research on artificial intelligence utilization by field and the strengths, problems, and challenges of related research. We found that since 2021, the application of artificial intelligence has been expanding, such as research using artificial intelligence for drug rearrangement, using computers to develop anticancer drugs, and applying artificial intelligence to clinical trials. This article briefly presents the prospects of new drug development research using artificial intelligence. If the reliability and safety of bio and medical data are ensured, and the development of the above artificial intelligence technology continues, it is judged that the direction of new drug development using artificial intelligence will proceed to personalized medicine and precision medicine, so we encourage efforts in that field.

• PNF and Movement
• /
• v.21 no.2
• /
• pp.171-183
• /
• 2023

Purpose: The purpose of this study was to compare universal goniometry (UG), which is commonly used in clinical practice to measure the range of motion (ROM) of finger joints with a wearable soft sensor glove, and to analyze the reliability to determine its usefulness. Methods: Ten healthy adults (6 males, 4 females) participated in this study. The metacarpophalangeal joint (MCP), interphalangeal joint (IP), and proximal interphalangeal joint (PIP) of both hands were measured using UG and Mollisen HAND soft sensor gloves during active flexion, according to the American Society for Hand Therapists' measurement criteria. Measurements were taken in triplicate and averaged. The mean and standard deviation of the two methods were calculated, and the 95% limits of agreement (LOA) of the measurements were calculated using the intraclass correlation coefficient (ICC) and Bland-Altman plot to examine the reliability and discrepancies between the measurements. Results: The results of the mean values of the flexion angles for the active range of motion (AROM) of the finger joints showed large angular differences in the finger joints, except for the MCP of the thumb. In the inter-rater reliability analysis according to the measurement method, the ICC (2, 1) value showed a low level close to 0, and the mean difference by the Bland-Altman plot showed a value greater than 0, showing a pattern of discrepancy. The 95% LOA had a wide range of differences. Conclusion: This study is a preliminary study investigating the usefulness of the soft sensor glove, and the reliability analysis showed a low level of reliability and inconsistency. However, if future studies can overcome the limitations of this study and the technical problems of the soft sensor glove in the development stage, it is suggested that the measurement instrument can show more accurate measurement and higher reliability when measuring ROM with UG.

• Journal of Navigation and Port Research
• /
• v.47 no.4
• /
• pp.231-238
• /
• 2023

The position of a light buoy is always flexible due to the influence of external forces such as tides and wind. The position can be checked through AIS (Automatic Identification System) or RTU (Remote Terminal Unit) for AtoN. As a result of analyzing the position data for the last five years (2017-2021) of a light buoy, the average position error was 15.4%. It is necessary to detect position error data and obtain refined position data to prevent navigation safety accidents and management. This study aimed to detect position error data and obtain refined position data by DBSCAN Clustering position data obtained through AIS or RTU for AtoN. For this purpose, 21 position data of Gunsan Port No. 1 light buoy where RTU was installed among western waters with the most position errors were DBSCAN clustered using Python library. The minPts required for DBSCAN Clustering applied the value commonly used for two-dimensional data. Epsilon was calculated and its value was applied using the k-NN (nearest neighbor) algorithm. As a result of DBSCAN Clustering, position error data that did not satisfy minPts and epsilon were detected and refined position data were acquired. This study can be used as asic data for obtaining reliable position data of a light buoy installed with AIS or RTU for AtoN. It is expected to be of great help in preventing navigation safety accidents.