• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.367-374
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• 2022

The purpose of this study was to propose a deep learning algorithm that applies to the fault diagnosis of fuel pumps and purifiers of autonomous ships. A deep learning algorithm reflecting the time dependence of the measured signal was configured, and the failure pattern was trained using the vibration signal, measured in the equipment's regular operation and failure state. Considering the sequential time-dependence of deterioration implied in the vibration signal, this study adopts Conv1D with sliding window computation for fault detection. The time dependence was also reflected, by transferring the measured signal from two-dimensional to three-dimensional. Additionally, the optimal values of the hyper-parameters of the Conv1D model were determined, using the grid search technique. Finally, the results show that the proposed data preprocessing method as well as the Conv1D model, can reflect the sequential dependency between the fault and its effect on the measured signal, and appropriately perform anomaly as well as failure detection, of the equipment chosen for application.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.143-151
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• 2010

Fingerprint classification is a step to increase the efficiency of an 1:N fingerprint recognition system and plays a role to reduce the matching time of fingerprint and to increase accuracy of recognition. It is difficult to classify fingerprints, because the ridge pattern of each fingerprint class has an overlapping characteristic with more than one class, fingerprint images may include a lot of noise and an input condition is an exceptional case. In this paper, we propose a novel approach to design a stochastic model and to accomplish fingerprint classification using a directional characteristic of fingerprints for an effective classification of various qualities. We compute the directional value by searching a fingerprint ridge pixel by pixel and extract a directional characteristic by merging a computed directional value by fixed pixels unit. The modified Markov model of each fingerprint class is generated using Markov model which is a stochastic information extraction and a recognition method by extracted directional characteristic. The weight list of classification model of each class is decided by analyzing the state transition matrixes of the generated Markov model of each class and the optimized value which improves the performance of fingerprint classification using GA (Genetic Algorithm) is estimated. The performance of the optimized classification model by GA is superior to the model before the optimization by the experiment result of applying the fingerprint database of various qualities to the optimized model by GA. And the proposed method effectively achieved fingerprint classification to exceptional input conditions because this approach is independent of the existence and nonexistence of singular points by the result of analyzing the fingerprint database which is used to the experiments.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.239-246
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• 2023

In this paper, we propose an open-loop algorithm to classify speech and music signals using the spectral flux parameters and Mel Frequency Cepstral Coefficients(MFCC) parameters for the audio coder. To increase responsiveness, the MFCC was used as a short-term feature parameter and spectral fluxes were used as a long-term feature parameters to improve accuracy. The overall voice/music signal classification decision is made by combining the short-term classification method and the long-term classification method. The Gaussian Mixed Model (GMM) was used for pattern recognition and the optimal GMM parameters were extracted using the Expectation Maximization (EM) algorithm. The proposed long-term and short-term combined speech/music signal classification method showed an average classification error rate of 1.5% on various audio sound sources, and improved the classification error rate by 0.9% compared to the short-term single classification method and 0.6% compared to the long-term single classification method. The proposed speech/music signal classification method was able to improve the classification error rate performance by 9.1% in percussion music signals with attacks and 5.8% in voice signals compared to the Unified Speech Audio Coding (USAC) audio classification method.

• Industry Promotion Research
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• v.8 no.4
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• pp.267-276
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• 2023

Based on the tourism input-output data of five provinces and cities in China's Bohai Rim region from 2015~2021, this study analyzes the efficiency of regional tourism using DEA-BCC and DEA-Malmquist index, as well as its contribution to regional economic efficiency, and identifies factors influencing the comprehensive efficiency. The research results indicate that the comprehensive efficiency of the tourism industry in the China Bohai Sea region has reached an optimal level of 88.9%, but there is still room for improvement, with overall fluctuations. The overall productivity of the tourism industry exhibits a "U"-shaped fluctuating pattern, with growth mainly driven by technological advancements. Due to the impact of the COVID-19 pandemic, the region experienced a nearly 50% decrease in total factor productivity in 2019~2020. However, in 2021, with the implementation of various government stimulus policies, the tourism efficiency rapidly recovered to 80% of pre-pandemic levels. In terms of the impact of the tourism industry on the regional economy in the China Bohai Sea region, Hebei Province stands out as a significant contributor. Based on the aforementioned research findings, the following recommendations are proposed in three aspects: optimizing the supply structure, increasing innovation investment, and strengthening internal collaboration. These recommendations provide valuable insights for enhancing regional tourism efficiency and promoting regional synergy.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.1-18
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• 2024

This study aimed to identify the optimal street tree planting method to improve the summer thermal environment in Seoul, Republic of Korea. The effects of road direction and street tree planting patterns on urban thermal environments using ENVI-met simulations were analyzed. The 68 scenarios were analyzed based on four road directions and 17 planting patterns. The results showed that tree planting had a reducing air temperature, mean radiant temperature, human thermal sensation (PET and UTCI). The most effective planting pattern among all scenarios was low tree height (6m), wide crown width (9m), high leaf area index (3.0), and narrow planting interval (8m). The largest improvement in the thermal environment was the northern sidewalk of the east-west road. Since this study used computer simulations, the difference from real urban spaces should be considered, and further research is needed through field measurement and consideration of more variables.

• Tunnel and Underground Space
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• v.34 no.3
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• pp.231-247
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• 2024

In the field of high-level radioactive waste disposal targeting deep rock environments, hydraulic characteristic information serves as the most important key factor in selecting relevant disposal sites, detailed design of disposal facilities, derivation of optimal construction plans, and safety evaluation during operation. Since various rock types are mixed and distributed in a small area in Korea, it is important to conduct preliminary work to analyze the hydrogeological characteristics of rock aquifers for various rock types and compile the resulting data into a database. In this paper, we obtained hydraulic conductivity data, which is the most representative field hydraulic characteristic of a high-depth volcanic bedrock aquifer, and also analyzed and evaluated the field data. To acquire field data, we used a high-performance hydraulic testing system developed in-house and applied standardized test methods and investigation procedures. In the process of hydraulic characteristic data analysis, hydraulic conductivity values were obtained for each depth, and the pattern of groundwater flow through permeable rock joints located in the test section was also evaluated. It is expected that the series of data acquisition methods, procedures, and analysis results proposed in this report can be used to build a database of hydraulic characteristics data for high-depth rock aquifers in Korea. In addition, it is expected that it will play a role in improving technical know-how to be applied to research on hydraulic characteristic according to various bedrock types in the future.

• Journal of the Korean GEO-environmental Society
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• v.25 no.8
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• pp.13-19
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• 2024

In this study, to reinforce the surface layer of weathered soil slopes where erosion and collapse of surface layer occur, compression strength tests were conducted by mixing carbon fiber and eco-friendly stabilizer (E.S.B.) To determine the optimal mixing ratio of E.S.B. and carbon fiber, E.S.B. was set at conditions of 10%, 20%, and 30%, and carbon fiber at 0.3%, 0.6%, 0.9%, and 1.2%. Additionally, to analyze the changes in compressive strength according to dry density and curing period, 85% and 95% of the maximum dry unit weight were applied, and curing periods were set to 3 days, 7 days, and 28 days. The standard strength for surface layer reinforcement of slopes is proposed as 4 MPa at 7 days and 6 MPa at 28 days according to ACI 230.1R-09 (2009). The compression test results showed that the unconfined compressive strength of E.S.B. reinforced soil met the standard strength at an E.S.B. mixing ratio of 10% or more for 95% compaction. Moreover, when carbon fiber was mixed with E.S.B. reinforced soil, a ductile fracture pattern was observed after the yield point due to compressive strength, indicating that the mixture could compensate for post-yield failure. It was analyzed that the maximum strength is exhibited at a carbon fiber mixing ratio of 0.6%. The unconfined compressive strength of carbon fiber reinforced soil increases by approximately 54-70% compared to the condition without carbon fiber.

• Journal of Bio-Environment Control
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• v.33 no.2
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• pp.107-113
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• 2024

For efficient soil water management in open fields, the proper use of soil moisture sensors is a prerequisite. Particularly in open-field environments like orchards with extensive root systems, the appropriate positioning of sensors is very important. The present study was conducted to identify the optimal placement of soil moisture sensors by assessing changes in soil water potential across various positions within orchard field soils after installing tensiometers. In apple and Asian pear orchards located in two regions of Korea, nine soil water potential sensors (TEROS 21, METER Group) were installed at distances of 20, 40, and 60 cm from the tree trunk and depths of 10, 20, and 30 cm from the soil surface, and monitored the soil water potential changes over two years. Results indicated that the positions closer to the tree trunk and the soil surface exhibited more pronounced changes in soil water potential. The greatest magnitude of change in soil water potential was observed at a distance of 20 cm and a depth of 10 cm, suggesting this position as the most suitable for soil moisture sensor installation. However, variations in the degree and pattern of changes in soil water potential were noted across sensor positions due to root system growth over time. Therefore, periodic observation and adjustments in sensor placement would be advisable to accurately monitor the soil moisture condition in long-term crops such as fruit trees in open fields.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.100-118
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• 2015

This study established a land-cover classification method on objects using satellite images, and figured out distributional patterns of land cover according to categories through spatial statistics techniques. Object-based classification generated each land cover classification map by spectral information, texture information, and the combination of the two. Through assessment of accuracy, we selected optimum land cover classification map. Also, to figure out spatial distribution pattern of land cover according to categories, we analyzed hot spots and quantified them. Optimal weight for an object-based classification has been selected as the Scale 52, Shape 0.4, Color 0.6, Compactness 0.5, Smoothness 0.5. In case of using the combination of spectral information and texture information, the land cover classification map showed the best overall classification accuracy. Particularly in case of dry fields, protected cultivation, and bare lands, the accuracy has increased about 12 percent more than when we used only spectral information. Forest, paddy fields, transportation facilities, grasslands, dry fields, bare lands, buildings, water and protected cultivation in order of the higher area ratio of DMZ according to categories. Particularly, dry field sand transportation facilities in Yanggu occurred mainly in north areas of the civilian control line. dry fields in Cheorwon, forest and transportation facilities in Inje fulfilled actively in south areas of the civilian control line. In case of distributional patterns according to categories, hot spot of paddy fields, dry fields and protected cultivation, which is related to agriculture, was distributed intensively in plains of Yanggu and in basin areas of Cheorwon. Hot spot areas of bare lands, waters, buildings and roads have similar distribution patterns with hot spot areas related to agriculture, while hot spot areas of bare lands, water, buildings and roads have different distributional patterns with hot spot areas of forest and grasslands.

• Journal of Dairy Science and Biotechnology
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• v.27 no.2
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• pp.7-16
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• 2009

Appenzeller cheese samples were prepared by addition of 0.5, 1.0, and 2.0% green tea (Camellia sinensis, CS) powder and control cheese. We examined various quality characteristics of the novel cheese, such as viable-cell counts, pH, water-soluble nitrogen (WSN), non-casein nitrogen (NCN), non-protein nitrogen (NPN), and catechin level during maturation for 16 weeks at $14^{\circ}C$. To develop a Korean natural cheese containing green tea powder, we also analyzed the changes in the polyacrylamide gel electrophoresis pattern, chemical composition, and sensory qualities. The viable cell counts of the samples were not significantly different. Until the $3^{rd}$ week, the pH of the CS cheese decreased with an increase in the maturation time. However, the pH gradually increased by the $12^{th}$ week, while WSN, NCN, NPN also increased. The WSN, NCN, NPN, and catechin values for the CS cheese samples were significantly higher than the values for the control cheese. The polyacrylamide gel electrophoretic pattern of caseins for the CS cheese indicated that this cheese degraded more rapidly than the control cheese did. In the sensory evaluation, cheese with 1.0% CS powder showed the highest scores in taste and appearance and good scores in flavor and texture. These results indicate that 1.0% CS is the optimal value for addition to cheese, and cheese containing 1.0% CS shows good physiological properties and reasonably high overall sensory acceptability.