• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.383-384
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• 2022

Following the development of technologies such as digital twin, IoT, and AI after the 4th industrial revolution, decision-making problems are being solved based on high-dimensional data analysis. This has recently been applied to the port logistics sector, and a number of studies on big data analysis, deep learning predictions, and simulations have been conducted on container terminals to improve port productivity. These high-dimensional data analysis techniques generally require a large number of data. However, the global port environment has changed due to the COVID-19 pandemic in 2020. It is not appropriate to apply data before the COVID-19 outbreak to the current port environment, and the data after the outbreak was not sufficiently collected to apply it to data analysis such as deep learning. Therefore, this study intends to present a port data augmentation method for data analysis as one of these problem-solving methods. To this end, we generate the container stowage situation of the yard through a generative adversarial neural network model in terms of container terminal operation, and verify similarity through statistical distribution verification between real and augmented data.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.23-28
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• 2023

Windows operating system generates various logs with timestamps. Timestamp tampering is an act of anti-forensics in which a suspect manipulates the timestamps of data related to a crime to conceal traces, making it difficult for analysts to reconstruct the situation of the incident. This can delay investigations or lead to the failure of obtaining crucial digital evidence. Therefore, various techniques have been developed to detect timestamp tampering. However, there is a limitation in detection if a suspect is aware of timestamp patterns and manipulates timestamps skillfully or alters system artifacts used in timestamp tampering detection. In this paper, a method is designed to detect changes in timestamps, even if a suspect alters the timestamp of a file on a storage device, it is challenging to do so with precision beyond millisecond order. In the proposed detection method, the first step involves verifying the timestamp of a file suspected of tampering to determine its write time. Subsequently, the confirmed time is compared with the file size recorded within that time, taking into consideration the performance of the storage device. Finally, the total capacity of files written at a specific time is calculated, and this is compared with the maximum input and output performance of the storage device to detect any potential file tampering.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.4
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• pp.73-89
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• 2023

This study aims to analyze the frequency of keywords used in Korean abstracts, which are unstructured text data in the domestic record management research field, using text mining techniques to identify domestic record management research trends through distance analysis between keywords. To this end, 1,157 keywords of 77,578 journals were visualized by extracting 1,157 articles from 7 journal types (28 types) searched by major category (complex study) and middle category (literature informatics) from the institutional statistics (registered site, candidate site) of the Korean Citation Index (KCI). Analysis of t-Distributed Stochastic Neighbor Embedding (t-SNE) and Scattertext using Word2vec was performed. As a result of the analysis, first, it was confirmed that keywords such as "record management" (889 times), "analysis" (888 times), "archive" (742 times), "record" (562 times), and "utilization" (449 times) were treated as significant topics by researchers. Second, Word2vec analysis generated vector representations between keywords, and similarity distances were investigated and visualized using t-SNE and Scattertext. In the visualization results, the research area for record management was divided into two groups, with keywords such as "archiving," "national record management," "standardization," "official documents," and "record management systems" occurring frequently in the first group (past). On the other hand, keywords such as "community," "data," "record information service," "online," and "digital archives" in the second group (current) were garnering substantial focus.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.309-323
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• 2023

As the role of online reviews has become increasingly crucial, numerous studies have been conducted to utilize helpful reviews. Helpful reviews, perceived by customers, have been verified in various research studies to be influenced by factors such as ratings, review length, review content, and so on. The determination of a review's helpfulness is generally based on the number of 'helpful' votes from consumers, with more 'helpful' votes considered to have a more significant impact on consumers' purchasing decisions. However, recently written reviews that have not been exposed to many customers may have relatively few 'helpful' votes and may lack 'helpful' votes altogether due to a lack of participation. Therefore, rather than relying on the number of 'helpful' votes to assess the helpfulness of reviews, we aim to classify them based on review content. In addition, the text of the review emerges as the most influential factor in review helpfulness. This study employs text mining techniques, including topic modeling and sentiment analysis, to analyze the diverse impacts of content and emotions embedded in the review text. In this study, we propose a review helpfulness prediction model based on review content, utilizing movie reviews from IMDb, a global movie information site. We construct a review helpfulness prediction model by using an explainable Graph Neural Network (GNN), while addressing the interpretability limitations of the machine learning model. The explainable graph neural network is expected to provide more reliable information about helpful or non-helpful reviews as it can identify connections between reviews.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.392-399
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• 2023

This paper proposes a deep learning model to determine the region and depth of cabbage cores for robotic automation of the cabbage core removal process during the kimchi manufacturing process. In addition, rather than predicting the depth of the measured cabbage, a model was presented that simultaneously detects and classifies the area by converting it into a discrete class. For deep learning model learning and verification, RGB images of the harvested cabbage 522 were obtained. The core region and depth labeling and data augmentation techniques from the acquired images was processed. MAP, IoU, acuity, sensitivity, specificity, and F1-score were selected to evaluate the performance of the proposed YOLO-v4 deep learning model-based cabbage core area detection and classification model. As a result, the mAP and IoU values were 0.97 and 0.91, respectively, and the acuity and F1-score values were 96.2% and 95.5% for depth classification, respectively. Through the results of this study, it was confirmed that the depth information of cabbage can be classified, and that it can be used in the development of a robot-automation system for the cabbage core removal process in the future.

• Steel and Composite Structures
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• v.50 no.6
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• pp.705-720
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• 2024

Analyzing the collapse behavior of thin-walled steel structures holds significant importance in ensuring their safety and longevity. Geometric imperfections present on the surface of metal materials can diminish both the durability and mechanical integrity of steel shells. These imperfections, encompassing local geometric irregularities and deformations such as holes, cavities, notches, and cracks localized in specific regions of the shell surface, play a pivotal role in the assessment. They can induce stress concentration within the structure, thereby influencing its susceptibility to buckling. The intricate relationship between the buckling behavior of these structures and such imperfections is multifaceted, contingent upon a variety of factors. The buckling analysis of thin-walled steel shell structures, similar to other steel structures, commonly involves the determination of crucial material properties, including elastic modulus, shear modulus, tensile strength, and fracture toughness. An established method involves the emulation of distributed geometric imperfections, utilizing real test specimen data as a basis. This approach allows for the accurate representation and assessment of the diversity and distribution of imperfections encountered in real-world scenarios. Utilizing defect data obtained from actual test samples enhances the model's realism and applicability. The sizes and configurations of these defects are employed as inputs in the modeling process, aiding in the prediction of structural behavior. It's worth noting that there is a dearth of experimental studies addressing the influence of geometric defects on the buckling behavior of cylindrical steel shells. In this particular study, samples featuring geometric imperfections were subjected to experimental buckling tests. These same samples were also modeled using Finite Element Analysis (FEM), with results corroborating the experimental findings. Furthermore, the initial geometrical imperfections were measured using digital image correlation (DIC) techniques. In this way, the response of the test specimens can be estimated accurately by applying the initial imperfections to FE models. After validation of the test results with FEA, a numerical parametric study was conducted to develop more generalized design recommendations for the stainless-steel shell structures with the initial geometric imperfection. While the load-carrying capacity of samples with perfect surfaces was up to 140 kN, the load-carrying capacity of samples with 4 mm defects was around 130 kN. Likewise, while the load carrying capacity of samples with 10 mm defects was around 125 kN, the load carrying capacity of samples with 14 mm defects was measured around 120 kN.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.1
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• pp.10-20
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• 2024

RNA-sequencing (RNA-seq) is a technique used for providing global patterns of transcriptomes in samples. However, it can only provide the average gene expression across cells and does not address the heterogeneity within the samples. The advances in single-cell RNA sequencing (scRNA-seq) technology have revolutionized our understanding of heterogeneity and the dynamics of gene expression at the single-cell level. For example, scRNA-seq allows us to identify the cell types in complex tissues, which can provide information regarding the alteration of the cell population by perturbations, such as genetic modification. Since its initial introduction, scRNA-seq has rapidly become popular, leading to the development of a huge number of bioinformatic tools. However, the analysis of the big dataset generated from scRNA-seq requires a general understanding of the preprocessing of the dataset and a variety of analytical techniques. Here, we present an overview of the workflow involved in analyzing the scRNA-seq dataset. First, we describe the preprocessing of the dataset, including quality control, normalization, and dimensionality reduction. Then, we introduce the downstream analysis provided with the most commonly used computational packages. This review aims to provide a workflow guideline for new researchers interested in this field.

• Journal of Chest Surgery
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• v.41 no.4
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• pp.469-475
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• 2008

Background: Video-assisted thoracic sympathicotomy is a definitive minimally invasive treatment for axillary hyperhidrosis. Different techniques exist for controlling axillary hyperhidrosis, but they are temporary and expensive. We compared the results after using two different levels of sympathicotomy for treating axillary hyperhidrosis: T3-T4 and T4. Material and Method: Between June 2002 and May 2007, 30 patients with isolated axillary hyperhidrosis underwent either T3-T4 or T4 thoracoscopic sympathicotomy in the Department of Thoracic & Cardiovascular Surgery at Wonkwang University Hospital. The patients were divided into two groups. Group I (n=15) was composed of patients who underwent T3-T4 sympathicotomy (thermal ablation), and Group II (n=15) was composed of patients who underwent T4 sympathicotomy (thermal ablation). The procedures were bilateral and simultaneous, involving the use of two 2-mm trocars and a 0-degree 2-mm thoracoscope under general anesthesia with single endotracheal intubation. Outcome parameters included satisfaction rate of treatment, degree of compensatory sweating, and postoperative complications. Patients were interviewed by telephone regarding satisfaction and compensatory hyperhidrosis. Result: There were no differences in age between group I and group II. The mean follow-up for the T3-T4 group was $38.7{\pm}2.3$ months, and the mean follow-up for the T4 group was $18.7{\pm}3.6$ months. The immediate therapeutic success rate (within 2 weeks postoperative) was 100% in both groups, and there were no recurrences in either group during the long-term follow-up period. The satisfaction rate was higher (93.3%) in the T4 group than in the T3-T4 group (53.3%), and the incidence of compensatory hyperhidrosis was lower in the T4 group (6.7%) than in the T3-T4 group (46.7%). Postoperative complications included one mild pneumothorax and two instances of intercostal neuralgia. Digital infrared thermographic imaging (DITI) correlated well with postoperative satisfaction. Conclusion: Both techniques proved effective for controlling isolated axillary hyperhidrosis. The T4 group had a higher satisfaction rate and lower severity of compensatory hyperhidrosis. Hence, thermal ablation of the lower interganglionic fibers of the third thoracic sympathetic ganglion on the fourth rib is a more practical and minimally invasive treatment than is the T3-T4 surgical method, according to the degree of compensatory sweating in isolated axillary hyperhidrosis.

• Cartoon and Animation Studies
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• s.46
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• pp.85-106
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• 2017

With the media's shift into the digital era in the 2000s, comic book publishers attempted a transition into the new medium by establishing a distribution structure using internet networks. But that effort shied from escaping the parallel-page reading structure of traditional comics. On the other hand, webtoons are showing divers changes by redesigning the structure of traditional sequential art media; they tend to separate and allot spaces according to the vertical scroll reading method of the internet browser and include animations, sound effects and background music. This trend is also in accordance with the preferences of modern readers. Modern society has complicated social structures with the development of various media; the public is therefore exposed to different stimuli and shows characteristics of differentiated perceptions. In other words, webtoons display more relevant and entertaining characteristics by inserting sounds and using moving texts and characters in specific frames, while traditional comics require an appreciation of withdrawal and immersion like other published media. Motions in webtoons are partially applied for dramatic tension or to create an effective expression of action. For example, hand-drawn animation is adopted to express motions by dividing motion images into many layers. Sounds are also utilized, such as background music with episode-related lyrics, melodies, ambient sounds and motion-related sound effects. In addition, webtoons provide readers with new amusement by giving tactile stimuli via the vibration of a smart phone. As stated above, the vertical direction, time-based nature of animation motions and tactile stimuli used in webtoons are differentiated from published comics. However, webtoons' utilization of innovative techniques hasn't yet reached its full potential. In addition to the fact that the software used for webtoon effects is operationally complex, this is a transitional phenomenon since there is still a lack of technical understanding of animation and sound application amongst the general public. For example, a sound might be programmed to play when a specific frame scrolls into view on the monitor, but the frame may be scrolled faster or slower than the author intended; in this case, sound can end before or after a reader sees the whole image. The motion of each frame is also programmed to start in a similar fashion. Therefore, a reader's scroll speed is related to the motion's speed. For this reason, motions might miss the intended timing and be unnatural because they are played out of context. Also, finished sound effects can disturb the concentration of readers. These problems come from a shortage of continuity; to solve these, naturally activated consecutive sounds or animations, like the simple rotation of joints when a character moves, is required.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.1-14
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• 2017

In Korea, the soil series derived from sedimentary rocks are classified into seven soil series of coarse loamy soil such as Dain, Danbug, Dongam, Imdong, Jeomgog, Maryeong, and Yonggog; seventeen soil series of fine loamy soil such as Angye, Anmi, Banho, Bigog, Deoggog, Dogye, Dojeon, Gamgog, Gugog, Jincheon, Maji, Mungyeong, Oggye, Samam, Yanggog, Yeongwol, and Yulgog; six soil series of fine silty soil such as Goryeong, Bonggog, Juggog, Gyeongsan, Yuga, and Yugog; and four soil series of clayey soil such as Mitan, Pyeongan, Pyeongjeon, and Uji. All thirty-four soil series have different drainage rates and topography. However, the soil texture depends on the parent rock. The buffer functions in GIS (Geographic Information System) techniques were used to calculate adjacent soil series from a soil series. The length of the adjacent soil series was adjusted because a side of the buffer area was one meter long. The cluster analysis was conducted using the CCC (Cubic Clustering Criterion) method, in which the number of clusters is calculated based on the individual soil series ratio. Soil survey has been carried out since 1964 as "The reconnaissance soil survey", and 1:5,000 detailed soil survey was completed in 1999 with a five-years plan in Korea. Today, all the soil survey information has been computerized. GIS techniques were used to establish a digital soil map; however, there have not been any studies to interpret pedogenesis using the GIS technique. In this study, the area of the adjacent soil series were obtained using the GIS technique. The area of the adjacent soil series can be calculated based on the information area. The similarities of soil originated from sedimentary rocks were estimated using the length. As a result, the distribution of grain size was different based on the types of sedimentary rocks and the location. The clusters were distinguished into limestone, sandstone, and shale. In addition, the soil derived from shale was divided into red shale and gray shale. This means that quantitative interpretation of the catena and this established method can be used to interpret the relationship between soil series.