• Transactions of the Korean hydrogen and new energy society
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• v.29 no.6
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• pp.642-647
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• 2018

Gas compressors are mostly driven by motors. It is important to measure the power of motors to evaluate their power efficiency, because the mechanical loads of gas compressors are always varied. In order to measure the power given to the driving motors, the torque should be measured. Manufacturers of compressors usually use the torque data to calculate the compressors qualities such as power consumption, efficiencies and failures. In general, measurements for the shaft torque of the compressors have been based upon contact types, strain gauges. In the cases of larger compressors, the contact type of strain gauges have several disadvantages such as large size and high cost. In this study, a relatively inexpensive and simple torque sensing technique that is not restricted to shaft diameter is introduced using visualization technique. Particle image velocimetry (PIV) has been adopted to complete non-contact torques measurements for rotating motors. In order to compare the performance of the newly constructed torque measurement technique, torque measurement by a transducer based on MEMS technology has been performed simultaneously during experiments.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.2
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• pp.79-85
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• 2019

The mission tasks of polar exploration utilizing unmanned systems such as glacier monitoring, ecosystem research, and inland exploration have been expanded. To facilitate unmanned exploration mission tasks, precise and robust navigation systems are required. However, limitations on the utilization of satellite navigation system are present due to satellite orbital characteristics at the polar region located in a high latitude. The orbital inclination of global positioning system (GPS), which was developed to be utilized in mid-latitude sites, was designed at $55^{\circ}$. This means that as the user is located in higher latitudes, the satellite visibility and vertical precision become worse. In addition, the use of satellite-based wide-area augmentation system (SBAS) is also limited in higher latitude regions than the maximum latitude of signal reception by stationary satellites, which is $70^{\circ}$. This study proposes a local-area augmentation system that additionally utilizes Global Navigation Satellite System (GLONASS) considering satellite navigation system environment in Polar Regions. The orbital inclination of GLONASS is $64.8^{\circ}$, which is suitable in order to ensure satellite visibility in high-latitude regions. In contrast, GLONASS has different system operation elements such as configuration elements of navigation message and update cycle and has a statistically different signal error level around 4 m, which is larger than that of GPS. Thus, such system characteristics must be taken into consideration to ensure data integrity and monitor GLONASS signal fault. This study took GLONASS system characteristics and performance into consideration to improve previously developed fault detection algorithm in the local-area augmentation system based on GPS. In addition, real GNSS observation data were acquired from the receivers installed at the Antarctic King Sejong Station to analyze positioning accuracy and calculate test statistics of the fault monitors. Finally, this study analyzed the satellite visibility of GPS/GLONASS-based local-area augmentation system in Polar Regions and conducted performance evaluations through simulations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.843-852
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• 2022

Despite continuous safety management, the death rate of construction workers is not decreasing every year. Accordingly, various studies are in progress to prevent construction site accidents. In this paper, we developed an AI-based priority inspection target selection model that preferentially selects sites are expected to cause construction accidents among construction sites with construction costs of less than 5 billion won (KRW). In particular, Random Forest (90.48 % of accident prediction AUC-ROC) showed the best performance among applied AI algorithms (Classification analysis). The main factors causing construction accidents were construction costs, total number of construction days and the number of construction performance evaluations. In this study an ROI (return of investment) of about 917.7 % can be predicted over 8 years as a result of better efficiency of manual inspections human resource and a preemptive response to construction accidents.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1729-1738
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• 2021

Machine learning has a close relationship with cognitive psychology and brain science and is developing together. This paper analyzes the OASIS-3 dataset using machine learning techniques and proposes a model for predicting dementia. Dimensional reduction through PCA (Principal Component Analysis) is performed on the data quantifying the volume of each area among OASIS-3 data, and only important elements (features) are extracted and then various machine learning including gradient boosting and stacking Apply the models and compare the performance of each. Unlike previous studies, the proposed technique has a great differentiation because it uses not only the brain biometric data, but also basic information data such as the participant's gender and medical information data of the participant. In addition, it was shown that the proposed technique through various performance evaluations is a model that can better predict dementia by finding features that are more related to dementia among various numerical data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1A
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• pp.101-108
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• 2009

The performance of high-early strength pavement concrete for large areas is influenced by the physical and chemical environment during service life. Generally, penetration, diffusion, and absorption of harmful materials that exist outside the concrete cause damage to its structure. Thus, we have to use a mixture for durability to keep the required quality for the planned service life. Moreover, in using high-early-strength cement and accelerators, a high heat of hydration to create the initial strength can cause cracks. Based on evaluations from optimal mix proportions of high-early-strength pavement concrete for large areas, we conducted water permeability, abrasion resistance, freeze-thaw, plastic, drying, and autogenous shrinkage tests. Test result showed that a mix of accelerator and PVA fibers showed excellent performance.

• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.81-93
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• 2022

Recently, research on processing a large-capacity graph using GPUs has been conducting. In order to process a large-capacity graph in a GPU with limited memory, the graph must be divided into subgraphs and then processed by scheduling subgraphs. In this paper, we propose an efficient graph algorithm processing scheme in GPU environments with limited memory and performance evaluation. The proposed scheme consists of a graph differential subgraph scheduling method and a graph segmentation method. The bulk graph segmentation method determines how a large-capacity graph can be segmented into subgraphs so that it can be processed efficiently by the GPU. The differential subgraph scheduling method schedule subgraphs processed by GPUs to reduce redundant transmission of the repeatedly used data between HOST-GPUs. It shows the superiority of the proposed scheme by performing various performance evaluations.

• Korean Journal of Legislative Studies
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• v.25 no.1
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• pp.79-106
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• 2019

Local governments within the boundaries of a state need increasing flexibility to satisfy diverse economic, social, and environmental goals in their particular geographical setting. However, many candidates in the local election in South Korea tend to see local politics as an extension of national-level politics. In particular, this paper mainly deals with how the voters' evaluation of a president's performance has influenced subnational elections in South Korea. Our analysis suggests that the fate of candidates in subnational elections is shaped by the performance of the incumbent president in both economic development and foreign affairs.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.259-266
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• 2023

In this paper, we propose an algorithm that can improve the accuracy performance of collaborative filtering using attribute-based opinion mining (ABOM). For the experiment, a total of 1,227 online consumer review data about smartphone apps from domestic smartphone users were used for analysis. After morpheme analysis using the KKMA (Kkokkoma) analyzer and emotional word analysis using KOSAC, attribute extraction is performed using LDA topic modeling, and the topic modeling results for each weighted review are used to add up the ratings of collaborative filtering and the sentiment score. MAE, MAPE, and RMSE, which are statistical model performance evaluations that calculate the average accuracy error, were used. Through experiments, we predicted the accuracy of online customers' app ratings (APP_Score) by combining traditional collaborative filtering among the recommendation algorithms and the attribute-based opinion mining (ABOM) technique, which combines LDA attribute extraction and sentiment analysis. As a result of the analysis, it was found that the prediction accuracy of ratings using attribute-based opinion mining CF was better than that of ratings implementing traditional collaborative filtering.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.911-917
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• 2023

In today's world, we find ourselves facing energy crises due to factors such as war and climate crises. To prepare for these energy crises, many researchers continue to study systems related to energy monitoring and conservation, such as energy management systems, energy monitoring, and energy conservation. In line with these efforts, nations are making it mandatory for energy-consuming facilities to implement these systems. However, these facilities, limited by space and energy constraints, are exploring ways to improve. This research explores the operation of a data collection system using low-performance embedded devices. In this context, it proves that an optimized version of RocksDB, a Key-Value store, outperforms traditional databases when it comes to time-series data. Furthermore, a comprehensive database evaluation tool was employed to assess various databases, including optimized RocksDB and regular RocksDB. In addition, heterogeneous databases and evaluations are conducted using a UD Benchmark tool to evaluate them. As a result, we were able to see that on devices with low performance, the time required was up to 11 times shorter than that of other databases.

• Animal Bioscience
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• v.37 no.5
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• pp.817-825
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• 2024

Objective: The aim of this study was to identify suitable polynomial regression for modeling the average growth trajectory and to estimate the relative development of the rib eye area, scrotal circumference, and morphometric measurements of Guzerat young bulls. Methods: A total of 45 recently weaned males, aged 325.8±28.0 days and weighing 219.9±38.05 kg, were evaluated. The animals were kept on Brachiaria brizantha pastures, received multiple supplementations, and were managed under uniform conditions for 294 days, with evaluations conducted every 56 days. The average growth trajectory was adjusted using ordinary polynomials, Legendre polynomials, and quadratic B-splines. The coefficient of determination, mean absolute deviation, mean square error, the value of the restricted likelihood function, Akaike information criteria, and consistent Akaike information criteria were applied to assess the quality of the fits. For the study of allometric growth, the power model was applied. Results: Ordinary polynomial and Legendre polynomial models of the fifth order provided the best fits. B-splines yielded the best fits in comparing models with the same number of parameters. Based on the restricted likelihood function, Akaike's information criterion, and consistent Akaike's information criterion, the B-splines model with six intervals described the growth trajectory of evaluated animals more smoothly and consistently. In the study of allometric growth, the evaluated traits exhibited negative heterogeneity (b<1) relative to the animals' weight (p<0.01), indicating the precocity of Guzerat cattle for weight gain on pasture. Conclusion: Complementary studies of growth trajectory and allometry can help identify when an animal's weight changes and thus assist in decision-making regarding management practices, nutritional requirements, and genetic selection strategies to optimize growth and animal performance.