• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.101-108
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• 2024

The total number of railroad stations managed in Korea is 322 (including general and wide-area railways), and a considerable number of stations are aging. In terms of the size of the existing railway station and the number of entrances, it has not been possible to secure adequate service capacity, and the demand for station improvement is increasing due to changes in surrounding conditions such as urban development. In the past, railroad stations were focused on the simple function of a connection passage in terms of maintenance or management, but in recent years, railroad stations are also changing to an atmosphere that they should be reborn as a user-centered comfortable, convenient, and safe service provision space. In this study, a case study related to the improvement of the old railway station was conducted to derive an improvement plan that meets the improvement standard of the old station, and the service level evaluation standard was developed. By introducing the concept of service level (LOS) in the development model, station congestion, station movement convenience, and station safety were selected as evaluation indicators. In addition, this development model applied an analytical stratification technique to divide various evaluation elements of each indicator into major and detailed elements and derive the relative importance of the elements by class. Priority for improvement was derived using the ratio of the number of E and F on the LOS for each facility. Based on this study, it is expected to be helpful in using it as an evaluation criterion for improving objective and equitable railway station.

• Korean Chemical Engineering Research
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• v.62 no.1
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• pp.70-79
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• 2024

Raman analyzer is an analytical technique that utilizes the "Raman effect", which occurs when light is scattered by the inherent vibrations of molecules. It is used for molecular identification and composition analysis. In the natural gas industry, it is widely used in bunkering and tank lorry fields in addition to LNG export and import terminals. In this study, a LNG-specific Raman analyzer was installed and operated under actual field conditions to analyze the composition and principal properties (calorific value, reference density, etc.) of LNG. The measured LNG composition and calorific value were compared with those obtained by conventional gas chromatograph that are currently in operation and validated. The test results showed that the Raman analyzer provided rapid and stable measurements of LNG composition and calorific value. When comparing the calorific value, which serves as the basis for LNG transactions, with the results from conventional gas chromatograph, the Raman analyzer met the acceptable error criteria. Furthermore, the measurement results obtained in this study satisfied the accuracy criteria of relevant international standards (ASTM D7940-14) and demonstrated similar outcomes compared to large-scale international demonstration cases.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.315-323
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• 2023

Marine accidents due to loss of stability of small ships have continued to increase over the past decade. In particular, since sudden winds have been pointed out as main causes of most small ship accidents, safety measures have been established to prevent them. In this regard, to prevent accidents caused by sudden winds, a systematic analysis technique is required. The aim of the present study was to develop a probabilistic approach to estimate extreme value and evaluate effects of wind on motion characteristics of ships. The present study included studies of motion analysis, extraction of extreme values, and motion characteristics. A series analysis was conducted for three conditions: wave only, wave with uniform wind speed, and wave with the NPD wind model. Hysteresis filtering and Peak-Valley filtering techniques were applied to time-domain motion analysis results for extreme value extraction. Using extracted extreme values, the goodness of fit test was performed on four distribution functions to select the optimal distribution-function that best expressed extreme values. Motion characteristics of a fishing boat were evaluated for three periodic motion conditions (Heave, Roll, and Pitch) and results were compared. Numerical analysis was performed using a commercial solver, ANSYS-AQWA.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.41-51
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• 2024

In this paper, we explore the enhancement of target detection accuracy in the guided weapon using deep learning object detection on infrared (IR) images. Due to the characteristics of IR images being influenced by factors such as time and temperature, it's crucial to ensure a consistent representation of object features in various environments when training the model. A simple way to address this is by emphasizing the features of target objects and reducing noise within the infrared images through appropriate pre-processing techniques. However, in previous studies, there has not been sufficient discussion on pre-processing methods in learning deep learning models based on infrared images. In this paper, we aim to investigate the impact of image pre-processing techniques on infrared image-based training for object detection. To achieve this, we analyze the pre-processing results on infrared images that utilized global or local information from the video and the image. In addition, in order to confirm the impact of images converted by each pre-processing technique on object detector training, we learn the YOLOX target detector for images processed by various pre-processing methods and analyze them. In particular, the results of the experiments using the CLAHE (Contrast Limited Adaptive Histogram Equalization) shows the highest detection accuracy with a mean average precision (mAP) of 81.9%.

• Korean Journal of Radiology
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• v.25 no.2
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• pp.146-156
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• 2024

Objective: Automated breast ultrasound (ABUS) is a relevant imaging technique for early breast cancer diagnosis and is increasingly being used as a supplementary tool for mammography. This study compared the performance of ABUS and handheld ultrasound (HHUS) in detecting and characterizing the axillary lymph nodes (LNs) in patients with breast cancer. Materials and Methods: We retrospectively reviewed the medical records of women with recently diagnosed early breast cancer (≤ T2) who underwent both ABUS and HHUS examinations for axilla (September 2017-May 2018). ABUS and HHUS findings were compared using pathological outcomes as reference standards. Diagnostic performance in predicting any axillary LN metastasis and heavy nodal-burden metastases (i.e., ≥ 3 LNs) was evaluated. The ABUS-HHUS agreement for visibility and US findings was calculated. Results: The study included 377 women (53.1 ± 11.1 years). Among 385 breast cancers in 377 patients, 101 had axillary LN metastases and 30 had heavy nodal burden metastases. ABUS identified benign-looking or suspicious axillary LNs (average, 1.4 ± 0.8) in 246 axillae (63.9%, 246/385). According to the per-breast analysis, the sensitivity, specificity, positive and negative predictive values, and accuracy of ABUS in predicting axillary LN metastases were 43.6% (44/101), 95.1% (270/284), 75.9% (44/58), 82.6% (270/327), and 81.6% (314/385), respectively. The corresponding results for HHUS were 41.6% (42/101), 95.1% (270/284), 75.0% (42/56), 82.1% (270/329), and 81.0% (312/385), respectively, which were not significantly different from those of ABUS (P ≥ 0.53). The performance results for heavy nodal-burden metastases were 70.0% (21/30), 89.6% (318/355), 36.2% (21/58), 97.3% (318/327), and 88.1% (339/385), respectively, for ABUS and 66.7% (20/30), 89.9% (319/355), 35.7% (20/56), 97.0% (319/329), and 88.1% (339/385), respectively, for HHUS, also not showing significant difference (P ≥ 0.57). The ABUS-HHUS agreement was 95.9% (236/246; Cohen's kappa = 0.883). Conclusion: Although ABUS showed limited sensitivity in diagnosing axillary LN metastasis in early breast cancer, it was still useful as the performance was comparable to that of HHUS.

• Information Systems Review
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• v.21 no.1
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• pp.23-38
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• 2019

The social network service (SNS) is one of the important marketing channels, so many companies actively exploit SNSs by posting SNS messages with appropriate content and style for their customers. In this paper, we focused on the psychological distances embedded in the SNS messages and developed a method to measure the psychological distance in SNS message by mixing a traditional content analysis, natural language processing (NLP), and machine learning. Through a traditional content analysis by human coding, the psychological distance was extracted from the SNS message, and these coding results were used for input data for NLP and machine learning. With NLP, word embedding was executed and Bag of Word was created. The Support Vector Machine, one of machine learning techniques was performed to train and test the psychological distance in SNS message. As a result, sensitivity and precision of SVM prediction were significantly low because of the extreme skewness of dataset. We improved the performance of SVM by balancing the ratio of data by upsampling technique and using data coded with the same value in first content analysis. All performance index was more than 70%, which showed that psychological distance can be measured well.

• Animal Bioscience
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• v.37 no.8
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• pp.1398-1407
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• 2024

Objective: The objective of this study was to determine internal structure spectral profile of by-products from coffee processing that were affected by added-microorganism fermentation duration in relation to truly absorbed feed nutrient supply in ruminant system. Methods: The by-products from coffee processing were fermented using commercial fermentation product, consisting of various microorganisms: for 0 (control), 7, 14, 21, and 28 days. In this study, carbohydrate-related spectral profiles of coffee by-products were correlated with their chemical and nutritional properties (chemical composition, total digestible nutrient, bioenergy values, carbohydrate sub-fractions and predicted degradation and digestion parameters as well as milk value of feed). The vibrational spectra of coffee by-products samples after fermentation for 0 (control), 7, 14, 21, and 28 days were determined using a JASCO FT/IR-4200 spectroscopy coupled with accessory of attenuated total reflectance (ATR). The molecular spectral analyses with univariate approach were conducted with the OMNIC 7.3 software. Results: Molecular spectral analysis parameters in fermented and non-fermented by-products from coffee processing included structural carbohydrate, cellulosic compounds, non-structural carbohydrates, lignin compound, CH-bending, structural carbohydrate peak1, structural carbohydrate peak2, structural carbohydrate peak3, hemicellulosic compound, non-structural carbohydrate peak1, non-structural carbohydrate peak2, non-structural carbohydrate peak3. The study results show that added-microorganism fermentation induced chemical and nutritional changes of coffee by-products including carbohydrate chemical composition profiles, bioenergy value, feed milk value, carbohydrate subfractions, estimated degradable and undegradable fractions in the rumen, and intestinal digested nutrient supply in ruminant system. Conclusion: In conclusion, carbohydrate nutrition value changes by added-microorganism fermentation duration were in an agreement with the change of their spectral profile in the coffee by-products. The studies show that the vibrational ATR-FT/IR spectroscopic technique could be applied as a rapid analytical tool to evaluate fermented by-products and connect with truly digestible carbohydrate supply in ruminant system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.55-61
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• 2024

In a hybrid architecture that combines the technological advantages of P2P(peer-to-peer) and cloud computing, it is possible to efficiently supply resources and allocate loads. In other words, by appropriately utilizing the processing power of the players constituting P2P as well as the server in the cloud computing environment, MMOG(Massively Multiplayer Online Game) can be configured that considers the scale of economic cost and service quality. In fact, the computing power and communication bandwidth of servers in the cloud are important demand-based resources. The more it is used when renting, the higher the cost, while the quality of service improves. On the other hand, if the player's processing power is utilized a lot, the quality of service deteriorates relatively while the economic cost decreases. In this paper, a bandwidth adjustment technique between servers and players for MMOG based on this hybrid structure is described. When the number of players running at the same time increases, the players' actions are appropriately distributed to servers and players to effectively utilize the server's computing power and communication volume. Simulation results show that in the MMOG based on cloud and P2P hybrid architecture, the bandwidth of the server is proportionally decreased as the bandwidth directly handled by players is increased.

• Tunnel and Underground Space
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• v.34 no.2
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• pp.169-184
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• 2024

This study investigates acoustic emission (AE) and micro-deformation characteristics of circular openings through biaxial compression experiments. The experimental results showed a significant increase in the frequency, count, energy, and amplitude of AE signals immediately before damage occurred in the circular opening. The differences in frequency and count between before and after damage initiation were significantly pronounced, indicating suitable factors for identifying damage occurrence in circular openings. The results for digital image correlation (DIC) technique revealed that micro-deformation was concentrated around the openings, as evidenced by the spatial distribution of strain. In addition, spalling was observed at the end of the experiments. The AE and micro-deformation characteristics presented in this study are expected to serve as fundamental data for evaluating the stability of underground openings and boreholes for deep subsurface projects.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.314-323
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• 2024

Recently, a score-penalty method has been used for the acoustic passive tracking of marine mammals. The interesting aspect of this technique lies in the loss function, which has a penalty term representing the mismatch between the measured signal and the modeled signal, while the traditional time-domain matched-field processing is positively considering the match between them. In this study, we apply the score-penalty method into the depth estimation of a passive target with a known source waveform. Assuming deep ocean environments with uncertainties in the sound speed profile, we evaluate the score-penalty method, comparing it with the time-domain matched field processing method. We shows that the score-penalty method is more accurate than the time-domain matched field processing method in the ocean environment with weak mismatch of sound speed profile, and has better efficiency. However, in the ocean enviroment with strong mismatch of the sound speed profile, the score-penalty method also fails in the depth estimation of a target, similar to the time-domain matched-field processing method.