• Asia pacific journal of information systems
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• v.30 no.2
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• pp.397-419
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• 2020

Business analytics is a management tool for achieving significant business performance improvements. Many organizations fail to or only partially achieve their business objectives and goals from business analytics. Business analytics adoption is a multi-stage complex activity consisting of evaluation, adoption, and assimilation stages. Several research papers have been published in the field of business analytics, but the research on multi-stage BA adoption is fewer in number. This study contributes to the scant literature on the multi-stage adoption model by identifying the critical themes for evaluation, adoption, and assimilation stages of business analytics. This study uses the thematic content analysis of peer-reviewed published academic papers as a research technique to explore the key themes of business analytics adoption. This study links the critical themes with the popular theoretical foundations: Resource-Based View (RBV), Dynamic Capabilities, Diffusion of Innovations, and Technology-Organizational-Environmental (TOE) framework. The study identifies twelve major factors categorized into three key themes: organizational characteristics, innovation characteristics, and environmental characteristics. The main organizational factors are top management support, organization data environment, centralized analytics structure, perceived cost, employee skills, and data-based decision making culture. The major innovation characteristics are perceived benefits, complexity, and compatibility, and information technology assets. The environmental factors influencing BA adoption stages are competition and industry pressure. A conceptual framework for the multi-stage BA adoption model is proposed in this study. The findings of this study can assist the practicing managers in developing a stage-wise operational strategy for business analytics adoption. Future research can also attempt to validate the conceptual model proposed in this study.

• Information Systems Review
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• v.22 no.4
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• pp.115-134
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• 2020

Previous studies on willingness to pay for digital content have mainly focused on audience factors and individual level. To complement the limitation of previous research, this study conducts a multilevel analysis to find the factors influence digital content purchases considering two axes: audience/media factors and individual/household levels. Using a sample of 10,172 individuals within 4,313 households, the analysis results show individual media factors including theater-going, experience with cloud services, and multi-screen service usage have the greatest effects on digital content purchases. At the household level, the media ownership factors that the number of laptops, wireless routers, and tablets have a greater influence than audience factors such as household size or household income. Our findings help scholars to enhance the understanding of individuals' media use considering household environmental factors and shed light on the importance of multi-screen service usage, and content providers to improve their digital content sales using multi-screen environment.

• Convergence Security Journal
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• v.24 no.1
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• pp.35-42
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• 2024

Multi-tenancy architecture plays a crucial role in cloud-based services and applications, and data isolation within such environments has emerged as a significant security challenge. This paper investigates various data isolation methods including schema-based isolation, logical isolation, and physical isolation, and compares their respective advantages and disadvantages. It evaluates the practical application and effectiveness of these data isolation methods, proposing security considerations and selection criteria for data isolation in the development of multi-tenant websites. This paper offers important guidance for developers, architects, and system administrators aiming to enhance data security in multi-tenancy environments. It suggests a foundational framework for the design and implementation of efficient and secure multi-tenant websites. Additionally, it provides insights into how the choice of data isolation methods impacts system performance, scalability, maintenance ease, and overall security, exploring ways to improve the security and stability of multi-tenant systems.

• Journal of Information Technology Services
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• v.23 no.1
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• pp.1-10
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• 2024

The IT environment is changing due to the acceleration of digital transformation in enterprises and organizations. This expansion of the digital space makes centralized cybersecurity controls more difficult. For this reason, cyberattacks are increasing in frequency and severity and are becoming more sophisticated, such as ransomware and digital supply chain attacks. Even in large organizations with numerous security personnel and systems, security incidents continue to occur due to unmanaged and unknown threats and vulnerabilities to IT assets. It's time to move beyond the current focus on detecting and responding to security threats to managing the full range of cyber risks. This requires the implementation of asset Inventory for comprehensive management by collecting and integrating all IT assets of the enterprise and organization in a wide range. IT Asset Management(ITAM) systems exist to identify and manage various assets from a financial and administrative perspective. However, the asset information managed in this way is not complete, and there are problems with duplication of data. Also, it is insufficient to update of data-set, including Network Infrastructure, Active Directory, Virtualization Management, and Cloud Platforms. In this study, we, the researcher group propose a new framework for automated 'Comprehensive IT Asset Management(CITAM)' required for security operations by designing a process to automatically collect asset data-set. Such as the Hostname, IP, MAC address, Serial, OS, installed software information, last seen time, those are already distributed and stored in operating IT security systems. CITAM framwork could classify them into unique device units through analysis processes in term of aggregation, normalization, deduplication, validation, and integration.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.99-107
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• 2024

In an environment where computer-related technologies are rapidly changing, cyber threats continue to emerge as they are advanced and diversified along with new technologies. Therefore, in this study, we would like to collect security-related news articles, conduct LDA topic modeling, and examine trends. To that end, news articles from January 2020 to August 2023 were collected and major topics were derived through LDA analysis. After that, the flow by topic was grasped and the main origin was analyzed. The analysis results show that ransomware attacks in 2021 and hacking of virtual asset exchanges in 2023 are major issues in the recent security sector. This allows you to check trends in security issues and see what research should be focused on in the future. It is also expected to be able to recognize the latest threats and support appropriate response strategies, contributing to the development of effective security measures.

• Journal of Practical Engineering Education
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• v.16 no.4
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• pp.481-489
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• 2024

The purpose of this study is to propose a new teaching method of the digital logic circuit so that students can cultivate digital literacy in diversifying future educational environments. In this paper, we analyzed the previous studies related to teaching methods for Tinkercad and digital logic circuits and suggested how to apply Tinkercad to the specific instruction design of the digital logic circuit. In addition, after showing the class design using Tinkercad to the actual lessons, It turns out two significant facts in a survey: to create a circuit that can implement the operation of the basic gate and to make it easier to understand the principles of the basic gate. The teaching method suggested in this study can be informative for students to acquire basic knowledge of electricity and electronics. Since Tinkercad is an open software based on cloud systems that are used not only in Korea but also foreign countries, it can be utilized in the lessons of digital logic circuits in the near future.

• Journal of Ecology and Environment
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• v.43 no.2
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• pp.226-245
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• 2019

To understand the dynamics of radial growth of trees and micro-climate at a site of Korean fir (Abies koreana Wilson) forest on high-altitude area of Mt. Hallasan National Park, Jeju Island, Korea, high precision dendrometers were installed on the stems of Korean fir trees, and the sensors for measuring micro-climate of the forest at 10 minutes interval were also installed at the forest. Data from the sensors were sent to nodes, collected to a gateway wireless, and transmitted to a data server using mobile phone communication system. By analyzing the radial growth data for the trees during the growing season in 2016, we can estimate that the radial growth of Korean fir trees initiated in late April to early May and ceased in late August to early September, which indicates that period for the radial growth was about 4 months in 2016. It is interesting to observe that the daily ambient temperature and the daily soil temperature at the depth of 20 cm coincided with the values of about 10 ℃ when the radial growth of the trees initiated in 2016. When the radial growth ceased, the values of the ambient temperature went down below about 15 ℃ and 16 ℃, respectively. While the ambient temperature and the soil temperature are evaluated to be the good indicators for the initiation and the cessation of radial growth, it becomes clear that radii of tree stems showed diurnal growth patterns affected by diurnal change of ambient temperature. In addition, the wetting and drying of the surface of the tree stems affected by precipitation became the additional factors that affect the expansion and shrinkage of the tree stems at the forest site. While it is interesting to note that the interrelationships among the micro-climatic factors at the forest site were well explained through this study, it should be recognized that the precision monitoring made possible with the application of high resolution sensors in the measurement of the radial increment combined with the observation of 10 minutes interval with aids of information and communication technology in the ecosystem observation.

• Korean Journal of Environment and Ecology
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• v.28 no.4
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• pp.484-489
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• 2014

In this paper, we examined factors that influenced light pollution in Korean national parks during peak and off-peak tourist seasons. Cloud-and moonlight-free nighttime satellite images that were collected during October 2012(for peak season) and January 2013(for off-peak season) by the Day and Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor were used to estimate the levels of light pollution in 19 national parks (excluding the Bukhansan and Mudeungsan National Parks). Bootstrapping regression analyses were conducted to examine the effects of socioeconomic and policy factors on light pollution in the study national parks for peak and off-peak tourist seasons, separately. The characteristics of light pollution in the national parks varied by season. During the peak tourist season, light pollution in the national parks were affected more by night lights nearby the parks than those within in the parks, while in the off-peak season, light sources in the parks were more important. Scattering of light emitted from hotels and other recreational facilities outside the parks that led to the sky glow effect can be attributed to the greater impact of night lights nearby the parks during the peak season. This result suggests that regulating light pollution nearby the park areas is needed to mitigate light pollution in the national parks, especially in a peak tourist season.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.9
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• pp.794-806
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• 2017

It is essential to protect the national space assets and space environment safely as a space development country from the continuously increasing space debris. And Active Debris Removal(ADR) is the most active way to solve this problem. In this paper, we studied the Artificial Neural Network(ANN) for a stable recognition model of vision-based space debris tracking system. We obtained the simulated image of the space environment by the KARICAT which is the ground-based space debris clearing satellite testbed developed by the Korea Aerospace Research Institute, and created the vector which encodes structure and color-based features of each object after image segmentation by depth discontinuity. The Feature Vector consists of 3D surface area, principle vector of point cloud, 2D shape and color information. We designed artificial neural network model based on the separated Feature Vector. In order to improve the performance of the artificial neural network, the model is divided according to the categories of the input feature vectors, and the ensemble technique is applied to each model. As a result, we confirmed the performance improvement of recognition model by ensemble technique.

• Journal of Plant Biotechnology
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• v.43 no.1
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• pp.21-29
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• 2016

Remote Sensing (RS) is a technique to obtain necessary information in a non-contact and non-destructive method by using various sensors on the surface, water or atmospheric phenomena. These techniques combine elements such as sensors, and platform and information communication technology (ICT) for mounting the sensor. ICT has contributed significantly to the success of smart agriculture through quantification and measurement of environmental factors and information such as weather, crop and soil management to distribution and consumption stage, as well as the production stage by the cloud computer. Remote sensing techniques, including non-destructive non-contact bioimaging (remote imaging) is required to measure the plant function. In addition, bioimaging study in plant science is performed at the gene, cellular and individual plant level. Recently, bioimaging technology is considered the latest phenomics that identifies the relationship between the genotype and environment for distinguishing phenotypes. In this review, trends in remote sensing in plants, plants diagnostics and response to environment and status of plants phonemics research were presented.