• The Transactions of the Korea Information Processing Society
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• v.13 no.8
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• pp.374-381
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• 2024

Documentation repositories on GitHub are used to share information that is helpful in performing various tasks. Popular documentation repositories have an advantage in attracting contributors who can help manage and extend documentation repository. Therefore, it is important to understand the characteristic of documentation repositories helpful to obtain popularity for developing strategies attracting attention of users. This paper presents a study on GitHub documentation repositories. To conduct the study, we collected 566 documentation repositories from GitHub and manually categorized their topic into 30 topics. Based on the stargazer score of the collected documentation repositories, we divided the collected documentation repositories into popular and unpopular documentation repository groups and investigated the topics in the popular documentation group. Then we statistically examined the differences in README characteristics of the popular and unpopular documentation repository groups. As a result, we found that the studied documentation repositories have 23 popular topics. We also found that the popular and unpopular documentation repository groups have differences in 5 README characteristics. The result of our study indicates that what documentation repository become popular in GitHub.

• Information Systems Review
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• v.26 no.2
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• pp.23-43
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• 2024

Nowadays, online reviews have become a common word of mouth that many users produce and consume. Posting online reviews is a kind of job that consumers do themselves. Since posting online reviews is not mandatory, it entirely relies on the consumer's voluntary willingness. In this respect, this study aims to describe the motivation for posting online reviews and their behavior processes, such as why online reviewers generate reviews and what types of reviews they create. In this study, we have conducted an in-depth study with 18 participants who have experience in posting reviews. By analyzing interview manuscripts from the grounded theory method approach, we have ultimately presented motivating factors for review posting (mutual reciprocity, material rewards), determinants of review browsing (trust toward review contents, preference for review format), and shadow work (a job that must be done, voluntary data production, consumer's share). We have also proposed the dynamics between core dimensions for theorizing a cycle process of review production and consumption. Our findings could bridge the gap in the existing online review research and offer practical implications for platform companies that need review management.

• Journal of Navigation and Port Research
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• v.48 no.4
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• pp.267-273
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• 2024

Bridge lanterns are installed on bridges or piers to signal the presence of these structures on navigational routes and navigable waters, and they fall under the category of light wave signals in Aids to Navigation. In Korea, medium to large bridges installed over major rivers and seas are equipped with bridge lanterns, which are necessary for routes frequented by ships and require periodic inspections on a monthly or multi-month basis. However, most bridge lanterns are mounted externally on bridge railings as fixed or manual rotary supports, posing a high risk of fatal falls during inspections. Furthermore, high -traffic bridges demand quick maintenance works due to complaints about traffic disruption, thus increasing work hazards. Consequently, this study introduced a tailored automatic bridge lantern support concept based on different types of bridge lantern installations, aiming for safe and rapid inspections. Additionally, the study sought to achieve full automation of the bridge lighting system by integrating it with a management program for monitoring and controlling bridge lanterns, utilizing both wired and wireless communication technologies. These findings provide foundational design data for new and refurbished bridges that will be installed in the future.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.21-34
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• 2024

In medical images such as MRI(Magnetic Resonance Imaging) and CT(Computed Tomography) images, noise removal has a significant impact on the performance of medical imaging systems. Recently, the introduction of deep learning in image processing technology has improved the performance of noise removal methods. However, there is a limit to removing only noise while preserving details in the image domain. In this paper, we propose a wavelet transform-based CNN(Convolutional Neural Network) model, namely the WT-DnCNN(Wavelet Transform-Denoising Convolutional Neural Network) model, to improve noise removal performance. This model first removes noise by dividing the noisy image into frequency bands using wavelet transform, and then applies the existing DnCNN model to the corresponding frequency bands to finally remove noise. In order to evaluate the performance of the WT-DnCNN model proposed in this paper, experiments were conducted on MRI and CT images damaged by various noises, namely Gaussian noise, Poisson noise, and speckle noise. The performance experiment results show that the WT-DnCNN model is superior to the traditional filter, i.e., the BM3D(Block-Matching and 3D Filtering) filter, as well as the existing deep learning models, DnCNN and CDAE(Convolution Denoising AutoEncoder) model in qualitative comparison, and in quantitative comparison, the PSNR(Peak Signal-to-Noise Ratio) and SSIM(Structural Similarity Index Measure) values were 36~43 and 0.93~0.98 for MRI images and 38~43 and 0.95~0.98 for CT images, respectively. In addition, in the comparison of the execution speed of the models, the DnCNN model was much less than the BM3D model, but it took a long time due to the addition of the wavelet transform in the comparison with the DnCNN model.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.69-75
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• 2024

Noise caused by adverse weather conditions in data collected during autonomous driving can lead to object recognition errors, potentially resulting in critical accidents. While this risk is widely acknowledged, there is a lack of research that quantitatively and systematically analyzes it. Therefore, this study aims to examine and quantify the extent to which noise affects object detection in autonomous driving environments. To this end, we utilized the YOLO v5 model trained on unprocessed datasets. The test data were divided into noise ratios of 0% (Original), 20%, 40%, 60%, and 80%, and the detection results were evaluated by constructing a Confusion Matrix. Experimental results show that as the noise ratio increases, the True Positive (TP) rate decreases, and the F1-score also significantly drops across all noise levels, specifically from 0.69 to 0.47, 0.29, 0.18, and 0.14. These findings are expected to contribute to enhancing the stability of autonomous driving technology. Future research will focus on collecting real datasets that include naturally occurring noise and developing more effective noise removal techniques.

• Journal of Naturopathy
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• v.13 no.1
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• pp.32-41
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• 2024

Background: With the advancement of various technologies and media, we have entered an era of music appreciation that transcends physical spaces and devices. Following these changes, research is needed to understand how listeners select and different parameters regarding their listening behaviors. Objective: This study aims to investigate the listening behaviors of listeners and the criteria for music selection. Method: A survey was conducted with 112 adults aged 18 and older to examine listening behaviors and selection criteria during music listening. The survey consisted of 29 items including multiple-choice and open-ended questions. Results: It was found that listeners regularly listen to newly updated music as they have more access to them via various streaming platforms. In terms of listening situations, the majority listened to music while commuting (35%) or exercising (29%), both define as energy-consuming activities. All music elements including rhythm/tempo(28%), melody(26%), timber(25%) and lyric(20%) were considered with similar proportion for music selection. In terms of music elements. Furthermore, three categories of non-musical factors influencing music selection were identified, which are relational, cultural, and emotional. Relational(41%) and cultural(41%) factors showed to have highest impact respectively. Conclusion: The results of this study provide basic data regarding music listening behaviors and what they consider when selecting music.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.5
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• pp.951-958
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• 2024

The public is requesting to view and receive copies of local government CCTV footage in order to deal with unauthorized dumping, loss, and other inconveniences related to their lives, and to confirm whether an incident or accident has occurred. However, due to the difficulty of identification and the privacy of others in the video, local governments cannot provide the original CCTV footage to the public, so they provide the footage after manual masking. As a result, the public is demanding local governments to resolve distrust and dissatisfaction, and secondary users of video information, such as police, fire, and courts, are demanding quick and efficient ways to improve video utilization. In this paper, we study how to make local government CCTV video information available to the public. To this end, we de-personalize the entire video by mosaicking it into a certain size. We automate and simplify the process of viewing and creating replicas. We apply artificial intelligence pattern technology to design measures against video misuse. If the government reflects these results in its policies, the public's right-to-know needs will be met, public trusted in the government will increase, and the government's administrative efficiency will be improved.

• Public Diplomacy: Theory and Practice
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• v.3 no.1
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• pp.21-42
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• 2023

Objective: To understand the contents and effects of public diplomacy by leaders, this paper throws out two questions: "To draw cooperation and support of international society in the middle of national crises, with what content do leaders conduct public diplomacy?" and "Through what mechanism, does leaders' public diplomacy promote cooperation and support of other countries?" Methods: To answer the research questions, this paper conducts a single case study with Ukrainian President Volodymyr Zelensky's public diplomacy in the Russia-Ukraine war in 2022. More specifically, the author collects text from Zelesky's Twitter and analyzes it in a descriptive manner. Results: When Russia invaded Ukraine in 2022, President Zelensky proactively utilized his SNS to communicate with people in other countries and thereby achieved the desired effect of public diplomacy. He has been delivering messages of 'appreciation of cooperation and support', 'situation of Ukraine', and 'congratulations or condolences', which could augment support, credibility, and audience cost. Conclusion: The effects of public diplomacy led to enhanced cooperation by alleviating problems within international cooperation and support. However, in the case of Ukraine, the patron's dilemma and commitment problem lasted, from which conducting public diplomacy has not been proven to be enough. The result of this paper provides lessons for the public diplomacy of the Republic of Korea in times of national crises in the future. In this regard, leaders should make efforts to promote the effectiveness of public diplomacy even in times of peace.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.5
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• pp.695-705
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• 2024

As a result of Typhoon Hinnamnoh, several slope failures occurred in the Pohang region, it is necessary to perform infiltration and slope stability analyses due to the actual rainfall. In the failed sites, samples were collected, and the hydro-mechanical properties of unsaturated soil were examined. Modeling the actual behavior using a single-mode function characteristic curve was found to be inadequate, leading to the adoption of a dual-mode function characteristic curve. The dual-mode function showed better agreement with the water retention test data. We calculated the unsaturated hydraulic conductivity for single and dual modes and performed rainfall-induced infiltration analysis. The variations in saturation and pore water pressure were calculated due to rainfall for three landslide-prone areas, Stability analysis based on effective stress of unsaturated soil was conducted, and safety factors were computed over time steps. The dual-mode model successfully reproduced landslides triggered by Typhoon Hinnamnoh, while the single-mode model exhibited a minimum safety factor of 1.2-1.3, making slope failure unpredictable. The dual-mode model accurately predicted instability in the slope by appropriately accounting for pore water pressure variations during Typhoon.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.5
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• pp.533-549
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• 2024

Soil conditioning is a critical process when tunneling with an earth pressure balance (EPB) shield tunnel boring machine (TBM) to enhance performance. To determine the optimal additive injection conditions, it is important to understand the rheological properties of conditioned soil, which is typically assessed using a rheometer. However, a rheometer cannot simulate the actual process of muck discharge in a TBM. Therefore, in this study, a scaled-down model of an 8-meter-class EPB shield TBM chamber and screw conveyor, reduced by a factor of 1:20, was fabricated and its applicability was evaluated through laboratory experiments. A lab-scale model experiment was conducted on artificial sandy soil using foam and polymer as additives. The experimental results confirmed that screw torque was consistent with trends observed in previous laboratory pressurized vane shear test data, establishing a positive proportional relationship between screw torque and yield stress. The muck discharge efficiency according to foam injection ratio (FIR) showed similar values overall, but decreased slightly at 60% of FIR and when the polymer was added. In addition, the pressure distribution generated along the chamber and screw conveyor was assessed in a manner similar to the actual EPB TBM. This study demonstrates that the lab-scale screw conveyor model can be used to evaluate the shear properties and muck discharge efficiency.