• Journal of Distribution Science
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• v.13 no.1
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• pp.93-103
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• 2015

Purpose - This study plans to adopt a more sophisticated approach toward service recognition by customers in general supermarkets in order to revise the service quality measurement methods that suit the context of Korean distribution channels. In particular, in general supermarkets, where much of the shopping process is in the form of self-service, there is high reliance on the service recognized by the consumers; therefore, it is highly likely that consumers would make their purchasing decisions based on their recognition of service quality or guarantees. It also utilized service quality elements of a basic level in the KD-SQS development model in order to indicate that the quality recognized by consumers impacts their loyalty to the stores with financial value and abstract value. Research design, data, and methodology - The study suggested a theoretical model comprising 13 hypotheses on relations between theoretic variables, and conducted surveys with consumers using discount stores in Seoul and Gyunggi Metropolitan area in order to verify the hypotheses, while using SPSS 20.0, AMOS 21.0 as the verification program. The survey sheets used amounted to 332, and a structural equation model was used to analyze the reliability and validity of constituent elements and to verify the suggested hypothesis. Therefore, this study analyzes the interrelations between service quality and guarantee factors in the distribution channel and their relations with the loyalty to stores as a dependent variable. Results - First, the results of the hypotheses tests helped identify the relations between service quality, service guarantees, service value, and customer loyalty, providing an opportunity to define the relations between constituent elements. In particular, service convenience in service quality has no impact on financial values. Further, stores' service policy had no impact on abstract values. Service recognition by service convenience has an impact on abstract values such as good image, comfort, and usability, while mileage systems promote financial values for consumers. In order to improve consumer values in service quality and values, general supermarkets should improve their service convenience, membership, and mileage programs using various strategies. Conclusion - In order to improve consumer values in service quality and values, general supermarkets should improve their service convenience, membership, and mileage programs using various strategies. Further, as service guarantee systems have a significant and direct impact on customer loyalty, rather than customer value recognition, service guarantees should be used to encourage customers to re-visit the stores. Finally, this study applied the findings of preceding studies in terms of service quality measurement; it had limitations in referencing preceding studies in a comprehensive manner. It also had limits in expanding upon various preceding studies because it was difficult to apply new measurement tools due to the lack of service quality measurement tools for general supermarkets. Therefore, it is necessary to conduct more studies on service quality to measure service quality and develop measurement tools by incorporating various industry characteristics.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.6
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• pp.760-767
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• 2014

An experimental study is carried out to investigate the effect of jet stream in the gab of rectangular cylinders with different length in a parallel arrangement by using PIV method in a circulating water channel. The height(h) of the rectangular cylinder and the gap between the cylinder is 10mm, and the width(B) which is 300mm. The length of the model for flow direction was applied to 30mm, 60mm, 90mm & 120mm, The aspect ratio of a model on the basis of height(H=30mm) is 1, 2, 3 and 4. Reynolds number $Re=1.4{\times}10^4$, $Re=2.0{\times}10^4$, $Re=2.9{\times}10^4$ based on the height(H) of model for the distance of tidal distributions as of water depth have been applied during the whole experiments. The measurement area was set to 5H rear of the cylinder. As a result, Vortex size in the wake area were increased as velocity increased. and high aspect ratio increased through-flow velocity component in the near wake. Velocity deficit increased highly after near-wake area and low aspect ratio.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.104-111
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• 2005

Dmitri Donskoi, the Russian cruiser launched in 1883, is known to have sunk near Ulleung Island (East Sea, Korea) on May 29, 1905, while it was participating in the Russo-Japanese War. In order to find this ship, information about its possible location was obtained from Russian and Japanese maritime historical records. The supposed location of the ship was identified, and we conducted a five-year geophysical survey from 1999 to 2003. A reconnaissance three-dimensional topographic survey of the sea floor was carried out using multi-beam echo sounder, marine magnetometer, and side-scan sonar. An anomalous body identified through the initial reconnaissance survey was identified by a detailed survey using a remotely operated vehicle, deep-sea camera, and the mini-submarine Pathfinder. Interpretation of the acquired data showed that the ship is hanging on the side of a channel, at the bottom of the sea 400 m below sea level. The location is about 2 km from Port Jeodong, Uleung Island. We discovered 152 mm naval guns and other war materiel still attached to the hull of the ship. In addition, the remnants of the steering gear and other machinery that were burnt during the final action were found near the hull. Strong magnetic fields, resulting from the presence of volcanic rocks in the survey area, affected the resolution of the magnetic data gathered; as a result, we could not locate the ship reliably using the magnetic method. Severe sea floor topography in the gully around the hull gave rise to diffuse reflections in the side-scan sonar data, and this prevented us from identifying the anomalous body with the side-scan sonar technique. However, the sea-floor image obtained from the multi-bean echo sounder was very useful in verifying the location of the ship.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.3
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• pp.11-20
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• 2022

The main purpose of this study is to investigate the applicability of the shear wave tomography technology as a non-destructive testing method to evaluate the debonding between the track concrete layer (TCL) and the hydraulically stabilized based course (HSB) of concrete slab tracks for the Korea high-speed railway system. A commercially available multi-channel shear wave measurement device (MIRA) is used to evaluate debonding defects in full-scaled mock-up test specimen that was designed and constructed according to the Rheda 200 system. A part of the mock-up specimen includes two artificial debonding defects with a length and a width of 400mm and thicknesses of 5mm and 10mm, respectively. The tomography images obtained by a MIRA on the surface of the concrete specimens are effective for visualizing the debonding defects in concrete. In this study, a simple image processing method is proposed to suppress the noisy signals reflected from the embedded items (reinforcing steel, precast sleeper, insert, etc.) in TCL, which significantly improves the readability of debonding defects in shear wave tomography images. Results show that debonding maps constructed in this study are effective for visualizing the spatial distribution and the depths of the debondiing defects in the railway concrete slab specimen.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.119-137
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• 2022

Recent recommendation system studies apply various deep learning models to represent user and item interactions better. One of the noteworthy studies is ONCF(Outer product-based Neural Collaborative Filtering) which builds a two-dimensional interaction map via outer product and employs CNN (Convolutional Neural Networks) to learn high-order correlations from the map. However, ONCF has limitations in recommendation performance due to the problems with CNN and the absence of side information. ONCF using CNN has an inductive bias problem that causes poor performances for data with a distribution that does not appear in the training data. This paper proposes to employ a Vision Transformer (ViT) instead of the vanilla CNN used in ONCF. The reason is that ViT showed better results than state-of-the-art CNN in many image classification cases. In addition, we propose a new architecture to reflect side information that ONCF did not consider. Unlike previous studies that reflect side information in a neural network using simple input combination methods, this study uses an independent auxiliary classifier to reflect side information more effectively in the recommender system. ONCF used a single latent vector for user and item, but in this study, a channel is constructed using multiple vectors to enable the model to learn more diverse expressions and to obtain an ensemble effect. The experiments showed our deep learning model improved performance in recommendation compared to ONCF.

• Smart Media Journal
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• v.11 no.10
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• pp.65-75
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• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.205-218
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• 2022

Recently, digital transformation in manufacturing has been accelerating. It results in that the data collection technologies from the shop-floor is becoming important. These approaches focus primarily on obtaining specific manufacturing data using various sensors and communication technologies. In order to expand the channel of field data collection, this study proposes a method to automatically collect manufacturing data based on vision-based artificial intelligence. This is to analyze real-time image information with the object detection and tracking technologies and to obtain manufacturing data. The research team collects object motion information for each frame by applying YOLO (You Only Look Once) and DeepSORT as object detection and tracking algorithms. Thereafter, the motion information is converted into two pieces of manufacturing data (production performance and time) through post-processing. A dynamically moving factory model is created to obtain training data for deep learning. In addition, operating scenarios are proposed to reproduce the shop-floor situation in the real world. The operating scenario assumes a flow-shop consisting of six facilities. As a result of collecting manufacturing data according to the operating scenarios, the accuracy was 96.3%.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.2
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• pp.28-35
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• 2024

Corrosion inside electronic packages significantly impacts the system performance and reliability, necessitating non-destructive diagnostic techniques for system health management. This study aims to present a non-destructive method for assessing corrosion in copper interconnects using the Smith chart, a tool that integrates the magnitude and phase of complex impedance for visualization. For the experiment, specimens simulating copper transmission lines were subjected to temperature and humidity cycles according to the MIL-STD-810G standard to induce corrosion. The corrosion level of the specimen was quantitatively assessed and labeled based on color changes in the R channel. S-parameters and Smith charts with progressing corrosion stages showed unique patterns corresponding to five levels of corrosion, confirming the effectiveness of the Smith chart as a tool for corrosion assessment. Furthermore, by employing data augmentation, 4,444 Smith charts representing various corrosion levels were obtained, and artificial intelligence models were trained to output the corrosion stages of copper interconnects based on the input Smith charts. Among image classification-specialized CNN and Transformer models, the ConvNeXt model achieved the highest diagnostic performance with an accuracy of 89.4%. When diagnosing the corrosion using the Smith chart, it is possible to perform a non-destructive evaluation using electronic signals. Additionally, by integrating and visualizing signal magnitude and phase information, it is expected to perform an intuitive and noise-robust diagnosis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.4
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• pp.875-884
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• 2000

Sea fog/stratus is very difficult to detect because of the characteristics of air-sea interaction and locality ,and the scantiness of the observed data from the oceans such as ships or ocean buoys. The aim of our study develops new algorism for sea fog detection by using Geostational Meteorological Satellite-5(GMS-5) and suggests the technics of its continuous detection. In this study, atmospheric synoptic patterns on sea fog day of May, 1999 are classified; cold air advection type(OOUTC, May 10, 1999) and warm air advection type(OOUTC, May 12, 1999), respectively, and we collected two case days in order to analyze variations of water vapor at Osan observation station during May 9-10, 1999.So as to detect daytime sea fog/stratus(OOUTC, May 10, 1999), composite image, visible accumulated histogram method and surface albedo method are used. The characteristic value during day showed A(min) .20% and DA < 10% when visible accumulated histogram method was applied. And the sea fog region which is detected is similar in composite image analysis and surface albedo method. Inland observation which visibility and relative humidity is beneath 1Km and 80%, respectively, at OOUTC, May 10,1999; Poryoung for visble accumulated histogram method and Poryoung, Mokp'o and Kangnung for surface albedo method. In case of nighttime sea fog(18UTC, May 10, 1999), IR accumulated histogram method and Maximum brightness temperature method are used, respectively. Maxium brightness temperature method dectected sea fog better than IR accumulated histogram method with the charateristic value that is T_max < T_max_trs, and then T_max is beneath 700hPa temperature of GDAPS(Global Data Assimilation and Prediction System). Sea fog region which is detected by Maxium brighness temperature method was similar to the result of National Oceanic and Atmosheric Administratio/Advanced Very High Resolution Radiometer (NOAA/AVHRR) DCD(Dual Channel Difference), but usually visibility and relative humidity are not agreed well in inland.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.179-193
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• 2021

This study examines the use of satellite images for river classification and determination of stream reach, which is the first priority in the river environment assessment system. In the river environment assessment system used in South Korea, it is proposed to set a stream reach by using 10 or 25 times the width of the river based on the result of river classification. First, river classification for the main stream section of Cheongmi stream was performed using various river-related data. The maximum likelihood method was applied for land cover classification. In this study, Sentinel-2 satellite imagery, which is an open data technology with a resolution of 10 m, was used. A total of four satellite images from 2018 was used to consider various flow conditions: February 2 (daily discharge = 2.39 m³/s), May 23 (daily discharge = 15.51 m³/s), June 2 (daily discharge = 3.88 m³/s), and July 7 (daily discharge = 33.61 m³/s). The river widths were estimated from the result of land cover classification to determine stream reach. The results of the assessment reach classification were evaluated using indicators of stream physical environments, including pool diversity, channel sinuosity, and river crossing shape and structure. It is concluded that appropriate flow conditions need to be considered when using satellite images to set up assessment segments for the river environment assessment system.