• Current Optics and Photonics
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• v.7 no.3
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• pp.237-247
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• 2023

In middle- and long-distance imaging systems, due to the atmospheric turbulence caused by temperature, wind speed, humidity, and so on, light waves propagating in the air are distorted, resulting in image-quality degradation such as geometric deformation and fuzziness. In remote sensing, astronomical observation, and traffic monitoring, image information loss due to degradation causes huge losses, so effective restoration of degraded images is very important. To restore images degraded by atmospheric turbulence, an image-restoration method based on improved compound multibranch feature fusion (CMFNetPro) was proposed. Based on the CMFNet network, an efficient channel-attention mechanism was used to replace the channel-attention mechanism to improve image quality and network efficiency. In the experiment, two-dimensional random distortion vector fields were used to construct two turbulent datasets with different degrees of distortion, based on the Google Landmarks Dataset v2 dataset. The experimental results showed that compared to the CMFNet, DeblurGAN-v2, and MIMO-UNet models, the proposed CMFNetPro network achieves better performance in both quality and training cost of turbulent-image restoration. In the mixed training, CMFNetPro was 1.2391 dB (weak turbulence), 0.8602 dB (strong turbulence) respectively higher in terms of peak signal-to-noise ratio and 0.0015 (weak turbulence), 0.0136 (strong turbulence) respectively higher in terms of structure similarity compared to CMFNet. CMFNetPro was 14.4 hours faster compared to the CMFNet. This provides a feasible scheme for turbulent-image restoration based on deep learning.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.1
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• pp.79-91
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• 2023

In response to the recent surge in aviation demand, major airports and aviation authorities continue to make efforts to formulate arrival and approach procedures that take into account efficient aircraft separation, noise and environmental issues of carbon (CO2) emissions. In order to ensure efficient traffic control and environmental issues, as a result, a new concept Trombone, Point Merge, etc. have been introduced and widely used in the domestic airspace. However, these new concept procedures which do not properly reflect the characteristics of the aircraft operation performance and the FMS vertical descent guidance hinder flight efficiency as well as bring in turn negative factors such as level-off flight and the use of drag device at the busiest phase of the flight descent operation, like the Continuous Descent Operation (CDO). Accordingly, throughout modification the current Standard Terminal Arrival Route (STAR) and Instrument Approach Procedure(IAP) that reflect the aircraft descent performance and the FMS guidance, the flight operation safety and efficiency is expected to be improved eventually. We herewith analyze and propose the way of improving flight efficiency in the arrival operation procedure by supplementary modification which consequently contribute to the aviation industry international competitiveness.

• Current Optics and Photonics
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• v.7 no.1
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• pp.38-46
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• 2023

Optical Fourier-domain reflectometry (OFDR) sensors have been widely used to measure distances with high resolution and speed in a noncontact state. In the electroplating process of a printed circuit board, it is critically important to monitor the copper-plating thickness, as small deviations can lead to defects, such as an open or short circuit. In this paper we employ a phase-based OFDR sensor for in situ relative distance sensing of a sample with nanometer-scale resolution, during electroplating. We also develop an optical-path difference (OPD)-regulated sensing probe that can maintain a preset distance from the sample. This function can markedly facilitate practical measurements in two aspects: Optimal distance setting for high signal-to-noise ratio OFDR sensing, and protection of a fragile probe tip via vertical evasion movement. In a sample with a centimeter-scale structure, a conventional OFDR sensor will probably either bump into the sample or practically out of the detection range of the sensing probe. To address this limitation, a novel OPD-regulated OFDR system is designed by combining the OFDR sensing probe and linear piezo motors with feedback-loop control. By using multiple OFDR sensors, it is possible to effectively monitor copper-plating thickness in situ and uniformize it at various positions.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.4
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• pp.33-40
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• 2022

Sharehouse has been supplied as an alternative to solving the steadily increasing one-room housing problem of single-person households every year, and it is necessary to investigate the satisfaction of residents who actually live in sharehouse through P.O.E. Therefore, this study analyzed priror researches related to the existing one-person households, sharehouses, and satisfaction surveys, and summarized indicators with high relevance and frequency to derive satisfaction survey factors that can clearly evaluate the improvement architectural plan of sharehouses. As a result, it was classified into 4 items in the 'general information' category to investigate the status, housing rental type, and housing cost of the sharehouse, 15 factors in the 'peripheral environment' category to evaluate the safety, 3 factors in the 'community' category, and 17 factors in the space (facility) and service category. In the "General Information" section, the overall one-person housing satisfaction, desired sharehouse type, housing rental type, housing cost, and living expenses were reduced. In the "Surrounding Environment", accessibility to public office, accessibility to cultural facilities, accessibility to medical facilities, accessibility to work and school, convenience stores, noise pollution and safety. In addition, in the "community" section, it consists of interactions with various people, relationships with housemates and in the "space (facilities) and service" section, heating, waterproof, soundproof, ventilation, moisture and condensation blocking, facility management, interior, room size, built-in furniture, storage space, laundry, parking. Most of the scales for each factor were 5-point Likert scales, allowing evaluation of the degree of satisfaction, and some factors presented criteria to induce structured answers. Therfore, it is expected that the survey will be conducted on residents who actually live by deriving factors for the satisfaction survey of one-person households living in the sharehouse, and the current status of the sharehouse will be identified, and the degree of satisfaction will be analyzed to be used for research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1773-1793
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• 2023

Automated machine learning, often referred to as "AutoML," is the process of automating the time-consuming and iterative procedures that are associated with the building of machine learning models. There have been significant contributions in this area across a number of different stages of accomplishing a data-mining task, including model selection, hyper-parameter optimization, and preprocessing method selection. Among them, preprocessing method selection is a relatively new and fast growing research area. The current work is focused on the recommendation of preprocessing methods, i.e., feature subset selection (FSS) algorithms. One limitation in the existing studies regarding FSS algorithm recommendation is the use of a single learner for meta-modeling, which restricts its capabilities in the metamodeling. Moreover, the meta-modeling in the existing studies is typically based on a single group of data characterization measures (DCMs). Nonetheless, there are a number of complementary DCM groups, and their combination will allow them to leverage their diversity, resulting in improved meta-modeling. This study aims to address these limitations by proposing an architecture for preprocess method selection that uses ensemble learning for meta-modeling, namely AutoFE-Sel. To evaluate the proposed method, we performed an extensive experimental evaluation involving 8 FSS algorithms, 3 groups of DCMs, and 125 datasets. Results show that the proposed method achieves better performance compared to three baseline methods. The proposed architecture can also be easily extended to other preprocessing method selections, e.g., noise-filter selection and imbalance handling method selection.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.967-974
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• 2022

It is no news that Nigeria's infrastructure challenge is enormous. In the global ranking, Nigeria ranked low in quantity and quality of its infrastructural provision which has a great impact on the ease of business transaction. Low investments in transportation have brought about the current infrastructural deficit. Recently, the Nigerian government has made effort to address at least to some extent the infrastructural deficit through Public-Private Partnership, but this has not yielded the desired result. Moreover, the sustainability issues relating to railway projects such as, emissions, noise pollution, ecosystem, and other environmental issues calls for urgent attention. Hence, this necessitated consideration on sustainability appraisal for the Chinese rail project in Nigeria. This study reviews sustainability of railway projects built by the Chinese firm in Nigeria with particular emphasis on the environmental and social impact of these projects. The study further identified issues and challenges in project implementation with a particular focus on civil dialogue and community engagements. A detailed literature search was conducted on railway projects and infrastructure by systematically reviewing selected published articles.The analysis of the selected articles identified sustainability issues and potential for improvement of Chinese railway projects and how they contribute to or inhibit competitiveness in the Nigerian railway market. From the literature searched, some of the projects constructed by Chinese firm revealed that there is economic and social impact of railway projects delivered by the Chinese firm in terms of capacity development and knowledge transfer potentiality. For instance, in the just concluded Lagos-Ibadan railway projects, the study gathered that the project brought about 5000 jobs and local staff were trained by the Chinese company, this will boost man power and local content capability. Also, it will significantly improve Nigeria's infrastructure and boost its economic development. The study suggests that Nigerian government should ensure and provide an enabling environment that is conducive for investment on the continent. Peace, improved security, and decent governance are the best conditions for sustainable transportation growth.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.139-147
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• 2023

The metal bush assembling process is a process of inserting and compressing a metal bush that serves to reduce the occurrence of noise and stable compression in the rotating section. In the metal bush assembly process, the head diameter defect and placement defect of the metal bush occur due to metal bush omission, non-pressing, and poor press-fitting. Among these causes of defects, it is intended to prevent defects due to omission of the metal bush by using signals from sensors attached to the facility. In particular, a metal bush omission is predicted through various data mining techniques using left load cell value, right load cell value, current, and voltage as independent variables. In the case of metal bush omission defect, it is difficult to get defect data, resulting in data imbalance. Data imbalance refers to a case where there is a large difference in the number of data belonging to each class, which can be a problem when performing classification prediction. In order to solve the problem caused by data imbalance, oversampling and composite sampling techniques were applied in this study. In addition, simulated annealing was applied for optimization of parameters related to sampling and hyper-parameters of data mining techniques used for bush omission prediction. In this study, the metal bush omission was predicted using the actual data of M manufacturing company, and the classification performance was examined. All applied techniques showed excellent results, and in particular, the proposed methods, the method of mixing Random Forest and SA, and the method of mixing MLP and SA, showed better results.

• Journal of IKEEE
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• v.27 no.4
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• pp.518-523
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• 2023

The diagnosis of Inter Turn Short Circuits (ITSC) in induction motors is critical due to the escalating severity of faults resulting from even minor disruptions in the stator windings. However, diagnosing ITSC presents significant challenges due to similarities in noise and losses shared with 3-phase induction motors. Although artificial intelligence techniques have been explored for efficient diagnosis, practical applications heavily rely on model-based methods, necessitating further research to enhance diagnostic performance. This study proposed a diagnostic method applied the Clarke Transformation approach, focusing solely on current components while disregarding changes in rotating flux. Experimental results conducted over a 30-minute period, encompassing both normal and ITSC conditions, demonstrate the effectiveness of the proposed approach, with FAR(False Accept Rates) of 0.2% for normal-to-ITSC FRR(False Rejection Rates) and 0.26% for ITSC-to-normal FRR. These findings underscore the efficacy of the proposed approach.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.2
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• pp.15-25
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• 2024

For effective analysis of animal ecosystems, technology that can automatically identify the current status of animal habitats is crucial. Specifically, animal sound classification, which identifies species based on their sounds, is gaining great attention where video-based discrimination is impractical. Traditional studies have relied on a single deep learning model to classify animal sounds. However, sounds collected in outdoor settings often include substantial background noise, complicating the task for a single model. In addition, data imbalance among species may lead to biased model training. To address these challenges, in this paper, we propose an animal sound classification scheme that combines predictions from multiple models using Focal Loss, which adjusts penalties based on class data volume. Experiments on public datasets have demonstrated that our scheme can improve recall by up to 22.6% compared to an average of single models.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.1
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• pp.82-88
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• 2014

Purpose: The purpose of study was to evaluate radiation dose for pediatric patients by changing tube voltage (kVp) and tube current (mA) at minimum conditions. By evaluating radiation dose, we want to provide dose reduction for pediatric patients and maintain good quality of SPECT/CT images. Materials and Methods: Discovery NM/CT 670 Scanne was used as SPECT/CT. Tube voltages are 80 and 100 kvP. Tube currents are 10, 15, 20, 25 mA. Using PMMA (Polymethyl methacrylate) Phantom, radiation dose which were calculated at center and peripheral dose and SNRD (Signal to Noise Ratio Dose) were evaluated. Using the CT performance phantom, spatial resolution was evaluated as the MTF (Modulation Transfer Function) graph. Jaszczak phantom was used for SPECT image evaluation by CNR (Contrast to Noise to Ratio). Results: Radiation dose using the PMMA phantom was higher peripheral dose than center dose about 7%. SNRD were 7.8, 8.2, 8.3, 8.8, 8.8, 9.9, 9.8, 9.6 for 80 kVp 10, 15, 20, 25 mA, 100 kVp 10, 15, 20, 25 mA. We can distinguish 35, 45, 70, 71, 52, 58, 90, 110 linepair for 80 kVp 10, 15, 20, 25 mA, 100 kVp 10, 15, 20, 25 mA at resolution with MTF. CNR of SPECT images using CT attenuation map were 57.8, 57.7, 57.1, 56.7, 56.6, 56.7, 56.7, 56.7% for 80 kVp 10, 15, 20, 25 mA, 100 kVp 10, 15, 20, 25 mA. Conclusion: In this study, radiation dose for pediatric patients showed decreased low dose condition. And SNRD value was similar in all condition. Resolution showed higher value at 100kVp than 80kVp. for CNR, there was no significant difference. we should take additional study to prove better quality and dose reduction.