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A Study on the Methods of Building Tools and Equipment for Digital Forensics Laboratory (디지털증거분석실의 도구·장비 구축 방안에 관한 연구)

  • Su-Min Shin;Hyeon-Min Park;Gi-Bum Kim
    • Convergence Security Journal
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    • v.22 no.5
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    • pp.21-35
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    • 2022
  • The use of digital information according to the development of information and communication technology and the 4th industrial revolution is continuously increasing and diversifying, and in proportion to this, crimes using digital information are also increasing. However, there are few cases of establishing an environment for processing and analysis of digital evidence in Korea. The budget allocated for each organization is different and the digital forensics laboratory built without solving the chronic problem of securing space has a problem in that there is no standard that can be referenced from the initial configuration stage. Based on this awareness of the problem, this thesis conducted an exploratory study focusing on tools and equipment necessary for building a digital forensics laboratory. As a research method, focus group interviews were conducted with 15 experts with extensive practical experience in the digital forensic laboratory or digital forensics field and experts' opinions were collected on the following 9 areas: network configuration, analyst computer, personal tools·equipment, imaging devices, dedicated software, open source software, common tools/equipment, accessories, and other considerations. As a result, a list of tools and equipment for digital forensic laboratories was derived.

Analysis of Review Data of 'Tamna' Franchisees to Promote Sustainable Travel in Jeju City (제주시의 지속가능한 여행 활성화를 위한 지역화폐 '탐나는전' 가맹점의 리뷰 데이터 분석)

  • Sehui Baek;Sehyoung Kim;Miran Bae;Juyoung Kang
    • The Journal of Bigdata
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    • v.7 no.2
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    • pp.113-128
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    • 2022
  • After COVID-19, interest in "sustainable tourism" increased, and the number of tourists who wanted to experience "sustainable tourism" also increased. However, there is a problem that the programs and methods for 'sustainable tourism' are not specific and diverse. In addition, since most of the interests of "sustainable tourism" focus on "environment" and "carbon neutrality," there are not many programs or government policies that can contribute to the community. Therefore, in this study, news data and review data were analyzed to suggest a method for promoting 'sustainable tourism'. First, in this study, major themes of sustainable travel were derived through news big data analysis. Through this analysis, policy themes and events of 'sustainable tourism' were derived. By analyzing news big data related to "sustainable tourism," we would like to analyze the reasons why sustainable travel has not been activated in Korea. Finally, in order to promote sustainable travel in Jeju island, we analyzed user review data of Jeju local currency, and propose a idea to coexist with the local community.

In-silico annotation of the chemical composition of Tibetan tea and its mechanism on antioxidant and lipid-lowering in mice

  • Ning Wang ;Linman Li ;Puyu Zhang;Muhammad Aamer Mehmood ;Chaohua Lan;Tian Gan ;Zaixin Li ;Zhi Zhang ;Kewei Xu ;Shan Mo ;Gang Xia ;Tao Wu ;Hui Zhu
    • Nutrition Research and Practice
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    • v.17 no.4
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    • pp.682-697
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    • 2023
  • BACKGROUND/OBJECTIVES: Tibetan tea is a kind of dark tea, due to the inherent complexity of natural products, the chemical composition and beneficial effects of Tibetan tea are not fully understood. The objective of this study was to unravel the composition of Tibetan tea using knowledge-guided multilayer network (KGMN) techniques and explore its potential antioxidant and hypolipidemic mechanisms in mice. MATERIALS/METHODS: The C57BL/6J mice were continuously gavaged with Tibetan tea extract (T group), green tea extract (G group) and ddH2O (H group) for 15 days. The activity of total antioxidant capacity (T-AOC) and superoxide dismutase (SOD) in mice was detected. Transcriptome sequencing technology was used to investigate the molecular mechanisms underlying the antioxidant and lipid-lowering effects of Tibetan tea in mice. Furthermore, the expression levels of liver antioxidant and lipid metabolism related genes in various groups were detected by the real-time quantitative polymerase chain reaction (qPCR) method. RESULTS: The results showed that a total of 42 flavonoids are provisionally annotated in Tibetan tea using KGMN strategies. Tibetan tea significantly reduced body weight gain and increased T-AOC and SOD activities in mice compared with the H group. Based on the results of transcriptome and qPCR, it was confirmed that Tibetan tea could play a key role in antioxidant and lipid lowering by regulating oxidative stress and lipid metabolism related pathways such as insulin resistance, P53 signaling pathway, insulin signaling pathway, fatty acid elongation and fatty acid metabolism. CONCLUSIONS: This study was the first to use computational tools to deeply explore the composition of Tibetan tea and revealed its potential antioxidant and hypolipidemic mechanisms, and it provides new insights into the composition and bioactivity of Tibetan tea.

Comparative analysis of water surface spectral characteristics based on hyperspectral images for chlorophyll-a estimation in Namyang estuarine reservoir and Baekje weir (남양호와 백제보의 Chlorophyll-a 산정을 위한 초분광 영상기반 수체분광특성 비교 분석)

  • Jang, Wonjin;Kim, Jinuk;Kim, Jinhwi;Nam, Guisook;Kang, Euetae;Park, Yongeun;Kim, Seongjoon
    • Journal of Korea Water Resources Association
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    • v.56 no.2
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    • pp.91-101
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    • 2023
  • In this study, we estimated the concentration of chlorophyll-a (Chl-a) using hyperspectral water surface reflectance in an inland weir (Baekjae weir) and estuarine reservoir (Namyang Reservoir) for monitoring the occurrence of algae in freshwater in South Korea. The hyperspectral reflectance was measured by aircraft in Baekjae Weir (BJW) from 2016 to 2017, and a drone in Namyang Reservoir (NYR) from 2020 to 2021. The 30 reflectance bands (BJW: 400-530, 620-680, 710-730, 760-790 nm, NYR: 400-430, 655-680, 740-800 nm) that were highly related to Chl-a concentration were selected using permutation importance. Artificial neural network based Chl-a estimation model was developed using the selected reflectance in both water bodies. And the performance of the model was evaluated with the coefficient of determination (R2), the root mean square error (RMSE), and the mean absolute error (MAE). The performance evaluation results of the Chl-a estimation model for each watershed was R2: 0.63, 0.82, RMSE: 9.67, 6.99, and MAE: 11.25, 8.48, respectively. The developed Chl-a model of this study may be used as foundation tool for the optimal management of freshwater algal blooms in the future.

A Research on the Development of Service Nature Measurement Items in the Sevice Economic Era (서비스 경제로의 전환에 따른 서비스본질 측정항목 개발 연구)

  • An Sehong;Kim Hyunsoo
    • Journal of Service Research and Studies
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    • v.11 no.1
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    • pp.59-79
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    • 2021
  • Service-related research in accordance with the transition to the service economy era has been conducted in a wide variety of ways, but the development of a service-related scale suitable for the present time is still insignificant. The purpose of this study is to define the nature of services and to develop measurement items for them. First, four categories of service nature were adopted in the previous study. The four categories are 'relationship', 'interactivity', 'horizontality', and 'harmony'. In this study, sub-factors and specific items of each of these four service essences were extracted and developed as measurable items. As a qualitative study, the four categories of sub-factors were extracted, and a mixed study was adopted to prove the reliability and validity of the extracted factors through quantitative studies. The scale items were identified through literature study, free response method, and Delphi technique, and the measurement items were refined through a second questionnaire of 30 Delphi panels composed of experts. As a result of the study, 15 out of 52 questions for relationship, 11 out of 45 questions for bilateral direction, 9 out of 33 questions for horizontality, and 17 out of 61 questions for harmonization were derived after secondary refining. Through this study, it was possible to uncover new essential items suitable for the service economy era. SNS, network, synergy, platform, system, real name, and breakthrough are concepts that have not been obtained in previous studies, and can be seen as contributions of this study. However, due to various limitations, this study did not cover all aspects of the service, but mainly dealt with people-centered services, which are part of the service. In the future, it is necessary to study the development of service essence measurement items for the overall aspect of services developed according to the evolution of the service economy era.

A Study about Learning Graph Representation on Farmhouse Apple Quality Images with Graph Transformer (그래프 트랜스포머 기반 농가 사과 품질 이미지의 그래프 표현 학습 연구)

  • Ji Hun Bae;Ju Hwan Lee;Gwang Hyun Yu;Gyeong Ju Kwon;Jin Young Kim
    • Smart Media Journal
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    • v.12 no.1
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    • pp.9-16
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    • 2023
  • Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.

On-site Inventory Management Plan for Construction Materials Considering Activity Float Time and Size of a Stock Yard (공정별 여유시간과 야적장 규모를 고려한 건설자재의 현장 재고관리 방안 연구)

  • Kim, Yong Hwan;Yoon, Hyeong Seok;Lee, Jae Hee;Kang, Leen Seok
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.1
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    • pp.79-89
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    • 2023
  • The inventory of many materials requires a large storage space, and the longer the storage period, the higher the potential maintenance cost. When materials are stored on a construction site, there are also concerns about safety due to the reduction of room for movement and working. On the other hand, construction sites that do not store materials have insufficient inventory, making it difficult to respond to demands such as sudden design changes. Ordering materials is then subject to delays and extra costs. Although securing an appropriate amount of inventory is important, in many cases, material management on a construction site depends on the experience of the site manager, so a reasonable material inventory management plan that reflects the construction conditions of a site is required. This study proposes an economical material management method by reflecting variables such as the status of the preceding and following activities, site size, material delivery cost, timing of an order, and quantity of orders. To this end, we set the appropriate inventory amount while adjusting related activities in the activity network, using float time for each activity, the size of the yard, and the order quantity as the main variables, and applied a genetic algorithm to this process to suggest the optimal order timing and order quantity. The material delivery cost derived from the results is set as a fitness index and the efficiency of inventory management was verified through a case application.

A study on the preparation and analysis of cordierite by sol-gel method (졸-겔법에 의한 코디어라이트 제조와 분석에 관한 연구)

  • Chun, Kyung Soo;Lee, Young Hwan
    • Analytical Science and Technology
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    • v.21 no.2
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    • pp.123-128
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    • 2008
  • The golden turbid solution of cordierite precursor was obtained by using magnesium ethoxide in sol-gel method, while the clear solution of cordierite precursor was obtained when 5%-$Zr(OC_3H_7)_4$ solution was used in the sol-gel reaction. $SiO_2$ component was confirmed by infrared spectra showing $1045cm^{-1}$ and the stretching vibration of gelish $SiO_4$ showed $1140cm^{-1}$ and $940cm^{-1}$. The component of $Al_2O_3$ showed at $580cm^{-1}$ and network structure of $Al_2O_6$ showed at $680cm^{-1}$. The component of MgO was confirmed at $575cm^{-1}$ as the stretching vibration. X-ray diffraction analysis showed ${\mu}$-cordierite crystal was showed up at temperature above $1000^{\circ}C$ at the mole ratio of cordierite precursor and water (1:5). ${\mu}$-Cordierite and ${\alpha}$-cordierite were coexisted at $1050^{\circ}C$ for the mole ratio of cordierite precursor and ammonia (1:5) while ${\alpha}$-cordierite was only existed at $1100^{\circ}C$ for the same mole ratio as mentioned above.

Context-Dependent Video Data Augmentation for Human Instance Segmentation (인물 개체 분할을 위한 맥락-의존적 비디오 데이터 보강)

  • HyunJin Chun;JongHun Lee;InCheol Kim
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.5
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    • pp.217-228
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    • 2023
  • Video instance segmentation is an intelligent visual task with high complexity because it not only requires object instance segmentation for each image frame constituting a video, but also requires accurate tracking of instances throughout the frame sequence of the video. In special, human instance segmentation in drama videos has an unique characteristic that requires accurate tracking of several main characters interacting in various places and times. Also, it is also characterized by a kind of the class imbalance problem because there is a significant difference between the frequency of main characters and that of supporting or auxiliary characters in drama videos. In this paper, we introduce a new human instance datatset called MHIS, which is built upon drama videos, Miseang, and then propose a novel video data augmentation method, CDVA, in order to overcome the data imbalance problem between character classes. Different from the previous video data augmentation methods, the proposed CDVA generates more realistic augmented videos by deciding the optimal location within the background clip for a target human instance to be inserted with taking rich spatio-temporal context embedded in videos into account. Therefore, the proposed augmentation method, CDVA, can improve the performance of a deep neural network model for video instance segmentation. Conducting both quantitative and qualitative experiments using the MHIS dataset, we prove the usefulness and effectiveness of the proposed video data augmentation method.

Analysis for Circumstance of Maritime Transport in the Chinese northeastern three provinces towards Sustainable New Northern Policy

  • Junghwan Choi;Sangseop Lim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.4
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    • pp.121-131
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    • 2023
  • The Chinese three northeastern three provinces - Heilongjiang, Liaoning, and Jilin - hold significant geographical, geopolitical, and commercial importance due to their location allowing for cross-border trade and transportation with North Korea. These provinces are crucial for establishing a complex Eurasian logistics network in line with South Korea's new northern policy. The Chinese three northeastern three provinces, as this region is known, boasts excellent maritime transportation links between South Korea, China, and North Korea, making it an logistics hub for transporting goods to Eurasia and Europe through multimodal transport. This study highlights the importance of securing a logistics hub area by fostering cooperation and friendly relations with China's three northeastern three provinces, which are crucial to the success of the New Northern Policy. In particular, the study aims to analyze current status of trade with these region and freight volume transported by ships and recommend political advice for securing logistics hub and revitalizing maritime transport. As the policy suggestion, this study is to establish a logistics hub by implementing joint port operations, constructing port infrastructure jointly, and operating shipping companies together. Additionally, we propose ways to revitalize the maritime passenger transport business between Korea and China, which involves expanding cultural exchanges and developing content.