Recently, with the development of artificial intelligence technology, many technologies for user convenience are being developed. Among them, interest in autonomous vehicles is increasing day by day. Currently, many automobile companies are aiming to commercialize autonomous vehicles. In order to lay the foundation for the government's new and reasonable policy establishment to support commercialization, we tried to analyze changes and perceptions of public opinion through news article data. Therefore, in this paper, 35,891 news article data mentioning terms similar to 'autonomous vehicles' over the past three years were collected and network analyzed. As a result of the analysis, major keywords such as 'autonomous driving', 'AI', 'future', 'Hyundai Motor', 'autonomous driving vehicle', 'automobile', 'industrial', and 'electric vehicle' were derived. In addition, the autonomous vehicle industry is developing into a faster and more diverse platform and service industry by converging with various industries such as semiconductor companies and big tech companies as well as automobile companies and is paying attention to the convergence of industries. To continuously confirm changes and perceptions in public opinion, it is necessary to analyze perceptions through continuous analysis of SNS data or technology trends.
Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.
In recent times, with the development of virtual convergence technologies, the market for the Metaverse, a digitally virtual space that combines virtuality and reality, is experiencing significant growth. These Metaverses are realizing new value in both reality and virtual spaces through the development of diverse services and content. However, existing research on the Metaverse mostly revolves around its conceptualization and categorization, with limited exploration of intentions to use the Metaverse. Consequently, this study examined the impact of Metaverse service characteristic factors on trust and intention to use within the Metaverse. The results of this study are as follows. First, among the service characteristic factors of the Metaverse, presence, interactivity, and playfulness were found to have a positive impact on Metaverse trust. On the other hand, informativeness was found not to have a significant influence on trust in the Metaverse. Second, Metaverse trust was found to have a positive impact on intention to use the Metaverse. Based on the research results above, this study aims to propose effective communication strategies for activating the Metaverse and developing services within the Metaverse platform.
Byeonghan Lee;Deok-Gyeong Seong;Young Min Jin;Yeon-Hyeon Hwang;Young-Gwang Kim
Journal of Internet of Things and Convergence
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v.9
no.6
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pp.93-98
/
2023
In paddy rice farming, water management is a critical task. To suppress weed emergence during the early stages of growth, fields are deeply flooded, and after transplantation, the water level is reduced to promote rooting and stimulate stem generation. Later, water is drained to prevent the production of sterile tillers. The adequacy of water supply is influenced by various factors such as field location, irrigation channels, soil conditions, and weather, requiring farmers to frequently check water levels and control the ingress and egress of water. This effort increases if the fields are scattered in remote locations. Automated irrigation systems have been considered to reduce labor and improve productivity. However, the net income from rice production in 2022 was about KRW 320,000/10a on average, making it financially unfeasible to implement high-cost devices or construct new infrastructure. This study focused on developing an IoT-Based irrigation valve that can be easily integrated into existing agricultural infrastructure without additional construction. The research was carried out in three main areas: Firstly, an irrigation valve was designed for quick and easy installation on existing agricultural pipes. Secondly, a power circuit was developed to connect a low-power Cat M1 communication modem with an Arduino Nano board for remote operation. Thirdly, a cloud-based platform was used to set up a server and database environment and create a web interface that users can easily access.
Yong-Soo, Gang;Jong-Kyu, Kim;Baek-Bum, Lee;Su-In, Yang;Jong-Wook, Kim
Journal of Navigation and Port Research
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v.46
no.6
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pp.483-490
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2022
Floating LiDAR is a system that provides a new paradigm for wind condition observation, which is essential when creating an offshore wind farm. As it can save time and money, minimize environmental impact, and even reduce backlash from local communities, it is emerging as the industry standard. However, the design and verification of a stable platform is very important, as disturbance factors caused by fluctuations of the buoy affect the reliability of observation data. In Korea, due to the nation's late entry into the technology, a number of foreign equipment manufacturers are dominating the domestic market. The west coast of Korea is a shallow sea environment with a very large tidal difference, so strong currents repeatedly appear depending on the region, and waves of strong energy that differ by season are formed. This paper conducted a study examining buoys suitable for LiDAR operation in the waters of Korea, which have such complex environmental characteristics. In this paper, we will introduce examples of optimized design and verification of ship-type buoys, which were applied first, and derive important concepts that will serve as the basis for the development of various platforms in the future.
Younghee Noh;Inho Chang;Youngmi Jung;Aekyoung Son;Kyungsun Lee;Hyunju Cha
Journal of the Korean BIBLIA Society for library and Information Science
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v.35
no.2
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pp.5-23
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2024
The seventh year of implementing online material deposit demands a systematic collection, legal and regulatory improvements, and the establishment of a long-term strategic plan for online material collection. In this study, we aimed to propose an online material collection strategy and a long-term roadmap for preserving online resources as national intellectual and cultural heritage for future generations. To achieve this, we analyzed the status of domestic and foreign libraries, related laws and regulations, and the types and collection status of online materials. Based on this analysis, we proposed practical collection standards and methods. Ultimately, a long-term roadmap and implementation plan were suggested. The long-term development plan for online material collection established a phased, concrete implementation strategy. This includes the foundation-building phase of online material collection, followed by the expansion phase, and finally reaching the maturity phase.
Global e-commerce websites offer personalized recommendation services to gain sustainable competitiveness. Existing studies have offered personalized recommendation services using quantitative preferences such as ratings. However, offering personalized recommendation services using only quantitative data has raised the problem of decreasing recommendation performance. For example, a user gave a five-star rating but wrote a review that the user was unsatisfied with hotel service and cleanliness. In such cases, has problems where quantitative and qualitative preferences are inconsistent. Recently, a growing number of studies have considered review data simultaneously to improve the limitations of existing personalized recommendation service studies. Therefore, in this study, we identify review and rating mismatches and build a new user profile to offer personalized recommendation services. To this end, we use deep learning algorithms such as CNN, LSTM, CNN + LSTM, which have been widely used in sentiment analysis studies. And extract sentiment features from reviews and compare with quantitative preferences. To evaluate the performance of the proposed methodology in this study, we collect user preference information using real-world hotel data from the world's largest travel platform TripAdvisor. Experiments show that the proposed methodology in this study outperforms the existing other methodologies, using only existing quantitative preferences.
Younghee Noh;Youngmi Jung;Aekyoung Son;Inho Chang;Kyung Sun Lee;Hyunju Cha
Journal of Korean Library and Information Science Society
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v.55
no.2
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pp.1-28
/
2024
This study aimed to present practical strategies for libraries in South Korea, including the National Central Library, to effectively respond to the new challenges of the digital era by systematically comparing and analyzing the status of online material collection and services of libraries both domestically and abroad. To achieve this, we sought to understand the cases and service status of online material collection in major foreign libraries and to derive directions and usage plans for our libraries based on the analysis of these foreign libraries' online material collection status. As a result of this research, it was found that the National Central Library needs to explore various strategies for expanding online material collection, including the proper collection and preservation of web resources that are being created and deleted, as well as expanding openness and utilizing archives. Secondly, as a central institution for future national information resources, it is necessary to establish a strategy for smoothly collecting, preserving, and servicing vast and complex web resources. Thirdly, there is a need to explore ways to implement a national-level web archive that can systematically collect, preserve, and utilize all web resources in our country. In the long term, it should be improved into a national platform capable of systematically collecting, preserving, and utilizing various types of web resources.
Diverse research topics relating to Social Network Services (SNS) such as, social affective factors in relationships among internet users, social capital value of SNS, comparing attributes why users are intending to participate in SNS, user's lifestyle and their preferences, and the exploratory seeking potential of SNS as a social capital need to be focused on. However, these researches that have been undertaken only consider facts at a particular period of the changing computing environment. In accordance with this indispensability, the integrated view on what technical, social and business characteristics and attributes need to be acknowledged. The purpose of this study is to analyze the evolving attributes and characteristics of SNS from Web 1.0 to Mobile web 2.0 through the Web 2.0 and Mobile 1.0 period. Based on the relevant literature, the attributes that drive the changing technological, social and business aspects of SNS have been developed and analyzed. This exploratory study analyzed major attributes and relationships between SNS and users by changing the paradigms which represented each period. It classified and chronicled each period by representing paradigms and deducted the attributes by considering three aspects such as technological, social and business administration. The major findings of this study are, firstly, the web based computing environment has been changed into the platform attribute for users in the aspect of technology. Users can only read, listen and view information through the web site in the early stages, but now it is possible that users can create, modify and distribute all kinds of information. Secondly, the few knowledge producers of web services have been changed into a collective intelligence by groups of people in the aspect of society. Information authority has been distributed and there is no limit to its spread. Many businesses recognized the potential of the SNS and they are considering how to utilize these advantages toward channel of promotion and marketing. Thirdly, the conventional marketing channel has been changed into oral transmission by using SNS. The market of innovative mobile technology such as smart phones, which provide convenience and access-ability toward customers, has been enlarged. New opportunities to build friendly relationship between business and customers as a new marketing chance have been created. Finally, the role of the consumer has been changed into the leading role of a prosumer. Users can create, modify and distribute information, and are performing the dual role of customer and producer.
R programming is free and open source system associated with a rich and ever-growing set of libraries of functions developed and submitted by independent end-users. It is recognized as a popular tool for handling big data sets and analyzing them. Reflecting these characteristics, R has been gaining popularity from data analysts. However, the antecedents of R technology acceptance has not been studied yet. In this study we identify and investigates cognitive factors contributing to build user acceptance toward R in education environment. We extend the existing technology acceptance model by incorporating social norms and software capability. It was found that the factors of subjective norm, perceived usefulness, ease of use affect positively on the intention of acceptance R programming. In addition, perceived usefulness is related to subjective norms, perceived ease of use, and software capability. The main difference of this research from the previous ones is that the target system is not a stand-alone. In addition, the system is not static in the sense that the system is not a final version. Instead, R system is evolving and open source system. We applied the Technology Acceptance Model (TAM) to the target system which is a platform where diverse applications such as statistical, big data analyses, and visual rendering can be performed. The model presented in this work can be useful for both colleges that plan to invest in new statistical software and for companies that need to pursue future installations of new technologies. In addition, we identified a modified version of the TAM model which is extended by the constructs such as subjective norm and software capability to the original TAM model. However one of the weak aspects that might inhibit the reliability and validity of the model is that small number of sample size.
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