• The Journal of Information Systems
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• v.26 no.3
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• pp.273-293
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• 2017

Purpose The purpose of this study is to introduce a framework that helps Muslims to determine whether a food can be consumed. It can complement existing Halal food classification services having a difficulty of constructing Halal food database. Design/methodology/approach The proposed framework includes two components. First, OCR(Optical Character Recognition) technique is utilized to read the food additive information. Second, machine learning methods were used to trained and predicted to determine whether a food can be consumed using the provided information. Findings Among the compared machine learning methods, SVM(Support Vector Machine), DT(Decision Tree), and NB(Naive Bayes), SVM with linear kernel and DT had excellent performance in the Halal food classification. The framework which adopting the proposed framework will enhance the tourism experiences of Muslim tourists who consider keeping the Islamic law most importantly. Furthermore, it can eventually contribute to the enhancement of smart tourism ecosystem.

• Ecology and Resilient Infrastructure
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• v.8 no.2
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• pp.112-119
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• 2021

In 2012, the National Park Service conducted an ecological health assessment to efficiently preserve and manage the ecosystem. The need for improving pre-existing management indicators was recognized from the revised Natural Park Act because, while the indicators of the existing evaluation system focused on endangered species, ecosystem disturbance, diversity, water quality (BOD, DO), and habitat fragmentation, they did not reflect the lack of indicators for marine ecological assessment, policy changes, and the time demands. The evaluation results comprised a five-point grading system, which made the analysis of immediate changes, difficult. Therefore, the benthic pollution index (BPI) and habitat restoration indicators were added to improve the evaluation system. The National Park was assessed using 10 classifications, however, only four classifications were evaluated. The ratings were divided into five states, and ten classes were presented as pictograms. The assessment results showed a similar trend as the indicators were improved, increasing from level 3 to level 5. However, the results of the Wolaksan National Park after improvement in the indicators were lower than that before the improvement, whereas, for the Juwangsan National Park, it was higher. This study aims at contributing to the scientific and systematic management of the national park ecosystem by improving the ecological health assessment system.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.203-223
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• 2023

Recently, the platform industry is rapidly growing in the global market, and competition is intensifying at the same time. Therefore, in order for domestic platform companies to have global competitiveness in the platform market, it is necessary to study the platform business ecosystem and success factors. However, most of the recent platform-related studies have been theoretical studies on the characteristics of platform business status analysis, platform economy, and indirect network externalities of platforms. Therefore, this study comprehensively analyzed the success factors of Silicon Valley's business ecosystem proposed in previous studies, and at the same time analyzed the success factors extracted from stakeholders in the actual Silicon Valley platform business ecosystem. And based on these factors, an IPA analysis was conducted as a way to propose a success plan to stakeholders in the platform business ecosystem. As a result of the analysis, among the success factors collected through previous studies, manpower, capital, and challenge culture were identified as factors that are relatively well maintained in both importance and satisfaction in Silicon Valley. In the end, it can be seen that the creation of an environment and culture in which Silicon Valley can use it to challenge itself based on excellent human resources and abundant capital contributes the most to the success of Silicon Valley's platform business. On the other hand, although it is of high importance to Silicon Valley's platform corporate ecosystem, the factors that show relatively low satisfaction among stakeholders are 'learning and benchmarking among active companies' and 'strong ties and cooperation between members', and it is analyzed that interest and effort are needed to strengthen these factors in the future. Finally, the systems and policies necessary for market autonomous competition, 'business support service industry', 'name value', and 'spin-off start-up' were important factors in literature research, but the importance and satisfaction of these factors were lowered due to changes in the times and environment. This study has academic implications in that it comprehensively analyzes the success factors of Silicon Valley's business ecosystem proposed in previous studies, and at the same time analyzes the success factors extracted from stakeholders in the actual Silicon Valley platform business ecosystem. In addition, there is another academic implications that importance and satisfaction were simultaneously examined through IPA analysis based on these various extracted factors. As for academic implications, it is meaningful in that it contributed to the formation of the domestic platform ecosystem by providing the government and companies with concrete information on the success factors of the platform business ecosystem and the theoretical grounds for the growth of domestic platform businesses.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.35-41
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• 2018

The analysis of plankton species distribution in sea or fresh water is very important in preserving marine ecosystem health. Since manual analysis is infeasible, many automatic approaches were proposed. They usually use images from in situ towed underwater imaging sensor or specially designed, lab mounted microscopic imaging system. Normally they assume that only single plankton is present in an image so that, if there is a clumping among multiple plankton of same species (homogeneous clumping) or if there are multiple plankton of different species scattered in an image (heterogeneous interspersion), they have a difficulty in recognition. In this work, we propose a deep learning based method that can detect and recognize individual plankton in images with homogeneous clumping, heterogeneous interspersion, or combination of both.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.92-97
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• 2022

Plastics are classified into 7 types such as PET (PETE), HDPE, PVC, LDPE, PP, PS, and Other for separation and recycling. Recently, large corporations advocating ESG management are replacing them with bioplastics. Incineration and landfill of disposal of plastic waste are responsible for air pollution and destruction of the ecosystem. Because it is not easy to accurately classify plastic materials with the naked eye, automated system-based screening studies using various sensor technologies and AI-based software technologies have been conducted. In this paper, NIR scanning devices considering the NIR wavelength characteristics that appear differently for each plastic material and a system that can identify the type of plastic by learning the NIR spectrum data collected through it. The accuracy of plastic material identification was evaluated through a decision tree-based SVM model for multiclass classification on NIR spectral datasets for 8 types of plastic samples including biodegradable plastic.

• Journal of Integrative Natural Science
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• v.16 no.4
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• pp.111-122
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• 2023

Invasive species are organisms that are introduced into places outside of their natural distribution range. The global pet trade is facilitating the introduction of invasive species into new countries and areas. Among the introduced alien species, turtles are one of the most common animal groups whether lives in wetland ecosystems, such as wetlands or reservoirs. Like other countries around the world, exotic turtles is becoming a growing concern for the wetland ecosystem in South Korea. In this study, we report new reports of subspecies of Painted turtle (Chrysemys spp.): Chrysemys picta marginata, C. p. bellii and C. dorsalis, from the reservoirs in downtown Cheongju and Gwangju, South Korea. We used morphological features, such as the characteristics of the legs, plastron, and carapace, to identify the turtles. It is assumed that all turtles were artificially released into nature. Considering the increasing number of reports on the introduction of alien invasive turtles in Korean wetlands, we recommend the formulation of an immediate and systematic management plan for pet trades and organized continuous monitoring programs.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.909-919
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• 2023

Benthic marine invertebrates, the invertebrates living on the bottom of the ocean, are an essential component of the marine ecosystem, but excessive reproduction of invertebrate grazers or pirate creatures can cause damage to the coastal fishery ecosystem. In this study, we compared and evaluated You Only Look Once Version 7 (YOLOv7), the most widely used deep learning model for real-time object detection, and detection tansformer (DETR), a transformer-based model, using underwater images for benthic marine invertebratesin the coasts of South Korea. YOLOv7 showed a mean average precision at 0.5 (mAP@0.5) of 0.899, and DETR showed an mAP@0.5 of 0.862, which implies that YOLOv7 is more appropriate for object detection of various sizes. This is because YOLOv7 generates the bounding boxes at multiple scales that can help detect small objects. Both models had a processing speed of more than 30 frames persecond (FPS),so it is expected that real-time object detection from the images provided by divers and underwater drones will be possible. The proposed method can be used to prevent and restore damage to coastal fisheries ecosystems, such as rescuing invertebrate grazers and creating sea forests to prevent ocean desertification.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1145-1153
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• 2023

Urban trees play an important role in absorbing carbon dioxide from the atmosphere, improving air quality, mitigating the urban heat island effect, and providing ecosystem services. To effectively manage and conserve urban trees, accurate spatial information on their location, condition, species, and population is needed. In this study, we propose an algorithm that uses a high-resolution urban tree cover map constructed from deep learning approach to separate trees from the urban land surface and accurately detect tree locations through local maximum filtering. Instead of using a uniform filter size, we improved the tree detection performance by selecting the appropriate filter size according to the tree height in consideration of various urban growth environments. The research output, the location and height of individual trees in human settlement over Suwon, will serve as a basis for sustainable management of urban ecosystems and carbon reduction measures.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.1
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• pp.209-238
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• 2023

This study aims to propose the main learning contents, functions and activation plans for building an e-learning platform for libraries through a literature review, case analysis and expert survey. Through the literature review, it was found that libraries must play a role in providing high-quality online education for users in the e-learning ecosystem. Based on the previous studies, a learning function analysis tool was developed for the analysis of the library's e-learning platform. Based on this, the learning contents, learning functions and characteristics of library e-learning platforms were analyzed, and expert surveys and interviews were conducted. As a results, the construction of a platform for effectively applying learning processes and technology is essential for the library's sustainable e-learning services. The contents that should be provided for characteristics of library education, reading guidance, information literacy instruction, library usage instruction, and the latest IT technologies. And The main learning functions include the ability to conduct video lectures and real-time classes among learning types, and learning activity support functions, a cloud platform support function and a personalized environment support function. Additionally, suggested re-education for library staff to improve their technical skills and the formation of an e-learning team.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.328-331
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• 2013

As digital ecosystem has been rapidly transforming into the mobile based platform, several mobile operating system, which is in charge of user interface with mobile device has been appeared. This research suggest critical factors affecting success and failure of several commercial mobile operating systems from Palm OS appearing in 1996 to main mobile OSs appearing in 2013. For this, we analyse several mobile operating OS cases, elicit factors affecting success and failure of mobile OS, and conduct ID3 based inductive learning analyses based on elicted factors and values in case dataset. Through this, we draw rules in success and failure of mobile OS and suggest strategic implications for the commercial success of mobile OS.