• Explosives and Blasting
• /
• v.40 no.4
• /
• pp.15-26
• /
• 2022

With the recent increase in old and dangerous buildings, the demand for technology in the field of structure demolition is rapidly increasing. In particular, in the case of structures with severe deformation of damage, there is a risk of deterioration in stability and disaster due to changes in the load distribution characteristics in the structure, so rapid structure demolition technology that can be efficiently dismantled in a short period of time is drawing attention. However, structural deformation such as unauthorized extension or illegal remodeling occurs frequently in many old structures, which is not reflected in structural information such as building drawings, and acts as an obstacle in the demolition design process. In this study, as an effective way to overcome the discrepancy between the structural information of old structures and the actual structure, access to actual structures through 3D modeling was considered. 3D point cloud data inside and outside the building were obtained through LiDAR and drone photography for buildings scheduled to be blasting demolition, and precision matching between the two spatial data groups was performed using an open-source based spatial information construction system. The 3D structure model was completed by importing point cloud data matched with 3D modeling software to create structural drawings for each layer and forming each member along the structure slab, pillar, beam, and ceiling boundary. In addition, the modeling technique proposed in this study was verified by comparing it with the actual measurement value for selected structure member.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.4
• /
• pp.173-179
• /
• 2023

This paper analyzes the time-dependent dielectric breakdown(TDDB) degradation mechanism for each stress region of Peri devices manufactured by 4th generation VNAND process, and presents a complementary lifetime prediction model that improves speed and accuracy in a wider reliability evaluation region compared to the conventional model presented. SiON dielectric nMOSFETs were measured 10 times each under 5 constant voltage stress(CVS) conditions. The analysis of stress-induced leakage current(SILC) confirmed the significance of the field-based degradation mechanism in the low electric field region and the current-based degradation mechanism in the high field region. Time-to-failure(TF) was extracted from Weibull distribution to ascertain the lifetime prediction limitations of the conventional E-model and 1/E-model, and a parallel complementary model including both electric field and current based degradation mechanisms was proposed by extracting and combining the thermal bond breakage rate constant(k) of each model. Finally, when predicting the lifetime of the measured TDDB data, the proposed complementary model predicts lifetime faster and more accurately, even in the wider electric field region, compared to the conventional E-model and 1/E-model.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.26 no.1
• /
• pp.132-144
• /
• 2023

Recently, the frequency and intensity of heat waves due to the increase in climate change temperature are increasing. Therefore, this study tried to compare the evaluation process and evaluation results of the heat wave disaster evaluation, which is the government's analysis of the heat wave disaster vulnerability and the risk evaluation method recently emphasized by the IPCC. The analysis of climate change disaster vulnerability is evaluated based on manuals and guidelines prepared by the government. Risk evaluation can be evaluated as the product of the possibility of a disaster and its impact, and it is evaluated using the Markov chain Monte Carlo simulation based on Bayesian estimation method, which uses prior information to infer posterior probability. As a result of the analysis, the two evaluation results for Busan Metropolitan City differed slightly in the spatial distribution of areas vulnerable to heat waves. In order to properly evaluate disaster vulnerable areas due to climate change, the process and results of climate change disaster vulnerability analysis and risk assessment must be reviewed, and consider each methodology and countermeasures must be prepared.

• Journal of Internet Computing and Services
• /
• v.24 no.5
• /
• pp.17-27
• /
• 2023

Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.

• Korean Journal of Plant Resources
• /
• v.37 no.2
• /
• pp.171-202
• /
• 2024

If the plant genetic resources and information-sharing systems held by arboretums worldwide are effectively utilized, it is believed that a conservation system for plant diversity in the currently inaccessible North Korean region could be established. This study was conducted to review the scientific names of plants native to North Korea but not to South Korea and to assess the status of genetic resources held in domestic and international arboretums. To compile a list and status of North Korean plant's genetic resources, updated checklists of vascular plants in Korean Peninsula and online plant information databases were consulted to compile synonym, distribution range, and other related information. A total of 486 taxa (449 species, 13 subspecies, 21 varieties, 1 forma and 2 hybrids) from 236 genera and 64 families, representing 12.34% of the total native flora of the Korean Peninsular were presented in the North Korea plant list, and the presence of rare, endemic and northern lineage species was confirmed. It was found that 384 taxa from 190 genera, 53 families of North Korean plants are held as genetic resources in 333 arboretums and plant research institutions across 46 countries and 5 continents worldwide. This study is expected to contribute to the construction and application of a species list for plants native to the Korean Peninsula.

• Asia-Pacific Journal of Business
• /
• v.15 no.1
• /
• pp.193-207
• /
• 2024

Purpose - With the increase of non-face-to-face activities due to the spread of COVID-19, O2O industry has grown rapidly which reduces contact points between suppliers and consumers. O2O platform is now recognized as an indispensable channel of distribution, but the voice is getting louder that it is necessary to check how it contributes to the performance of suppliers or how its fee system or contract terms affects the expansion of O2O industry as the leading companies tend to monopolize the market. Design/methodology/approach - In this study, the scope was limited to the restaurant industry in which transactions are the most active among the O2O industry and a regression analysis was done on 775 businesses that had used guarantor service from the Seoul Credit Guarantee Foundation. Findings - Analysis on the impact of O2O platform system, information, and service quality on the business performance of the sole proprietors revealed that the system quality represented by ease of use and the information quality determined by level of timely, accurate and reliable information provided to the consumers have a statistically significant effect on the improvement of business performance. In addition, the effect of business performance on the loyalty measured by the likelihood of users continuing to use the service as well as recommending it to others was moderated by the satisfaction with contract terms, not by the fee system. Research implications or Originality - Although the number of O2O platform providers has increased manyfold, the membership rate is no more than 20%, which means that the small business owners are still struggling with digital transformation. In order for the O2O industry, which is now commonplace, to form a healthy ecosystem that satisfies both suppliers and consumers, the standard contract guidelines that are acceptable to both parties must be established and the O2O providers must offer services that help suppliers to improve performance.

• Information Systems Review
• /
• v.21 no.2
• /
• pp.117-137
• /
• 2019

In the Big Data era, data science has become popular with the production of numerous data in various domains, and the power of data has become a competitive power. There is a growing interest in unstructured data, which accounts for more than 80% of the world's data. Along with the everyday use of social media, most of the unstructured data is in the form of text data and plays an important role in various areas such as marketing, finance, and distribution. However, text mining using social media is difficult to access and difficult to use compared to data mining using numerical data. Thus, this study aims to develop Korean Natural Language Application (KoALA) as an integrated application for easy and handy social media text mining without relying on programming language or high-level hardware or solution. KoALA is a specialized application for social media text mining. It is an integrated application that can analyze both Korean and English. KoALA handles the entire process from data collection to preprocessing, analysis and visualization. This paper describes the process of designing, implementing, and applying KoALA applications using the design science methodology. Lastly, we will discuss practical use of KoALA through a block-chain business case. Through this paper, we hope to popularize social media text mining and utilize it for practical and academic use in various domains.

• Journal of the Korean Society for information Management
• /
• v.41 no.3
• /
• pp.269-288
• /
• 2024

In the era of digital transformation, discussions about digital curation have become increasingly active not only in academia but also in various fields. The primary purpose of this study is to analyze the conceptual changes in digital curation over time, particularly by examining the definition statements related to digital curation as described in academic literature. To achieve this, academic research papers from 2009, when the term "digital curation" was first mentioned, to 2023 were collected, and definition statements that explained relevant concepts were extracted. Basic statistical analyses were conducted. Using DMR topic modeling and word networks, the relationships among keywords and the changes in their importance over time were examined, and a conceptual map of digital curation was made focusing on the main topics. The results revealed that the concept of digital curation is primarily centered around the themes of "data preservation," "traditional curator roles," and "product recommendation curation." Depending on the researchers' intentions for utilizing digital curation, the concept was expanded to include topics such as "content distribution and classification," "information usage," and "curation models." This study is significant in that it analyzed the concept of digital curation through definition statements reflecting the perspectives of researchers. Additionally, the study holds value in explicitly identifying changes in the concepts that researchers emphasize over time through the trends in topic prevalence.

• Research in Plant Disease
• /
• v.30 no.3
• /
• pp.256-267
• /
• 2024

We have developed FBcastS (Fire Blight Forecasting System), a cloud-based information system that leverages the K-Maryblyt forecasting model. The FBcastS provides an optimal timing for spraying antibiotics to prevent flower infection caused by Erwinia amylovora and forecasts the onset of disease symptoms to assist in scheduling field scouting activities. FBcastS comprises four discrete subsystems tailored to specific functionalities: meteorological data acquisition and processing, execution of the K-Maryblyt model, distribution of web-based information, and dissemination of spray timing notifications. The meteorological data acquisition subsystem gathers both observed and forecasted weather data from 1,583 sites across South Korea, including 761 apple or pear orchards where automated weather stations are installed for fire blight forecast. This subsystem also performs post-processing tasks such as quality control and data conversion. The model execution subsystem operates the K-Maryblyt model and stores its results in a database. The web-based service subsystem offers an array of internet-based services, including weather monitoring, mobile services for forecasting fire blight infection and symptoms, and nationwide fire blight monitoring. The final subsystem issues timely notifications of fire blight spray timing alert to growers based on forecasts from the K-Maryblyt model, blossom status, pesticide types, and field conditions, following guidelines set by the Rural Development Administration. FBcastS epitomizes a smart agriculture internet of things (IoT) by utilizing densely collected data with a spatial resolution of approximately 4.25 km to improve the accuracy of fire blight forecasts. The system's internet-based services ensure high accessibility and utility, making it a vital tool in data-driven smart agricultural practices.

• The Korean Journal of Archival Studies
• /
• no.79
• /
• pp.5-32
• /
• 2024

The Korean government ranked 3rd among 193 UN member countries in the UN's 2022 e-Government Development Index. Korea, which has consistently been evaluated as a top country, can clearly be said to be a leading country in the world of e-government. The lubricant of e-government is data. Data itself is neither information nor a record, but it is a source of information and records and a resource of knowledge. Since administrative actions through electronic systems have become widespread, the production and technology of data-based records have naturally expanded and evolved. Technology may seem value-neutral, but in fact, technology itself reflects a specific worldview. The digital order of new technologies, armed with hyper-connectivity and super-intelligence, not only has a profound influence on traditional power structures, but also has an a similar influence on existing information and knowledge transmission media. Moreover, new technologies and media, including data-based generative artificial intelligence, are by far the hot topic. It can be seen that the all-round growth and spread of digital technology has led to the augmentation of human capabilities and the outsourcing of thinking. This also involves a variety of problems, ranging from deep fakes and other fake images, auto profiling, AI lies hallucination that creates them as if they were real, and copyright infringement of machine learning data. Moreover, radical connectivity capabilities enable the instantaneous sharing of vast amounts of data and rely on the technological unconscious to generate actions without awareness. Another irony of the digital world and online network, which is based on immaterial distribution and logical existence, is that access and contact can only be made through physical tools. Digital information is a logical object, but digital resources cannot be read or utilized without some type of device to relay it. In that respect, machines in today's technological society have gone beyond the level of simple assistance, and there are points at which it is difficult to say that the entry of machines into human society is a natural change pattern due to advanced technological development. This is because perspectives on machines will change over time. Important is the social and cultural implications of changes in the way records are produced as a result of communication and actions through machines. Even in the archive field, what problems will a data-based archive society face due to technological changes toward a hyper-intelligence and hyper-connected society, and who will prove the continuous activity of records and data and what will be the main drivers of media change? It is time to research whether this will happen. This study began with the need to recognize that archives are not only records that are the result of actions, but also data as strategic assets. Through this, author considered how to expand traditional boundaries and achieves reterritorialization in a data-driven society.