• Journal of the Korea Computer Industry Society
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• v.3 no.3
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• pp.331-340
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• 2002

The web world is getting so huge and untractable that without an intelligent information extractor we would get more and more helpless. Conventional web spidering techniques for general purpose search engine may be too slow for the specific search engines, which concentrate only on specific areas or keywords. In this paper a new model for improving web spidering capabilities is suggested and experimented. How to select adequate reference web pages from the initial web Page set relevant to a given specific area (or keywords) can be very important to reduce the spidering speed. Our reference web page selection method DOPS dynamically and orthogonally selects web pages, and it can also decide the appropriate number of reference pages, using a newly defined measure. Even for a very specific area, this method worked comparably well almost at the level of experts. If we consider that experts cannot work on a huge initial page set, and they still have difficulty in deciding the optimal number of the reference web pages, this method seems to be very promising. We also applied reinforcement learning to web environment, and DOPS-based reinforcement learning experiments shows that our method works quite favorably in terms of both the number of hyper links and time.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.2
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• pp.161-172
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• 2021

Along with the emergence of technologies related to the 4th industrial revolution, all industry sectors are making efforts to dramatically increase productivity by actively introducing high-tech technologies. Recently, the MLIT (Ministry of Land, Infrastructure and Transport) is trying to solve problems related to low productivity and high accident rate in the construction industry by applying the 4th industrial revolution technologies to infrastructure construction through smart construction R&D projects. This research was performed as part of the smart construction R&D project supported by MLIT, and the purpose is to develop a module that automatically generates moving paths for construction equipment based on the earthwork plan for road construction. The generated moving path can be used to provide safe and efficient paths for construction equipment and to support MC and MG to work efficiently. The moving paths for construction equipment are created based on the Visibility Graph and a case study is performed to show how the paths are generated based on a given construction site.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.35-40
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• 2022

In the agricultural environment, pesticide control requires a high risk of work and a high labor force for farmers. The effectiveness of pesticide control using unmanned aerial vehicles varies according to climate, land type, and characteristics of unmanned aerial vehicles. Therefore, an effective method for pesticide control by unmanned aerial vehicles considering the spraying conditions and environmental conditions is required. In this paper, we propose an efficient pesticide control system based on agricultural unmanned aerial vehicles considering the application conditions and environmental information for each crop. The effectiveness of the proposed model was demonstrated by measuring the drop uniformity of pesticides according to the change in altitude and speed after attaching the sensory paper and measuring the penetration rate of the drug inside the canopy according to the change in crop growth conditions. Experiment result, the closer the height of the UAV is to the ground, the more evenly the crops are sprayed, but for safety reasons, 2m more is suitable, and on average a speed of 2m/s is most suitable for control. The proposed control system is expected to help develop intelligent services based on the use of various unmanned aerial vehicles in agricultural environments.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.524-539
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• 2022

With the advent of generative artificial intelligence technology, it became possible to create a virtual human, and produce a lecture video only with textual information. It is expected that the virtual human will enhance the efficient production of educational contents and the student's entertainment experience and satisfaction. However, there have been still few studies that have demonstrated the process of how virtual human technology reaches students' satisfaction. Therefore, the purpose of this study is to empirically examine whether the human likeness, which is the main characteristic of a virtual human based on Uncanny Valley theory, affects human experience and satisfaction. In particular, human likeness of the Uncanny Valley theory was subdivided into human likeness in the visual and verbal dimensions, and the process of reaching satisfaction was understood based on the experience economy model. In particular, human similarity in Uncanny Valley theory was classified as similarity in the visual and language levels, and the process of reaching satisfaction based on the experiential economic model was analyzed with a partial least squares structure model equation (PLS-SEM). The survey was conducted online for a panel of office workers at a specialized research institution in China. The results indicate that both the visual and verbal human likeness had a positive effect on experience economy factors (education, entertainment, esthetic, escape), and then these experiential factors had a significant effect on satisfaction. The results also provide some suggestions to consider when designing educational contents by virtual human.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.555-562
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• 2022

This study measured and analyzed the propagation characteristics at frequencies 6, 10, and 17 GHz to discover the new propagation demands in a semi-basement indoor corridor environment for meeting the 4th industrial revolution requirements. The measured indoor environment is a straight corridor consisting of three lecture rooms and glass windows on the outside. The measurement scenario development and measurement system were constructed to match this environment. The transmitting antenna was fixed, and the frequency domain and time domain propagation characteristics were measured and analyzed in the line-of-sight environment based on the distance of the receiving antenna location. In the frequency domain, reliability was determined by the parameters of the floating intercept (FI) path loss model and an R-squared value of 0.5 or more. In the time domain, the root mean square (RMS) delay spread and the cumulative probability of K-factor were used to determine that 6 GHz had high propagation power and 17 GHz had low propagation power. These research results will be effective in providing ultra-connection and ultra-delay artificial intelligence services for WIFI 6, 5G, and future systems in a semi-basement indoor corridor environment.

• Convergence Security Journal
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• v.22 no.5
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• pp.69-80
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• 2022

Now that climate change and food resource security are becoming issues around the world, smart farms are emerging as an alternative to solve them. In addition, changes in the production environment in the primary industry are a major concern for people engaged in all primary industries (agriculture, livestock, fishery), and the resulting food shortage problem is an important problem that we all need to solve. In order to solve this problem, in the primary industry, efforts are made to solve the food shortage problem through productivity improvement by introducing smart farms using the 4th industrial revolution such as ICT and BT and IoT big data and artificial intelligence technologies. This is done through the public and private sectors.This paper intends to consider the minimum requirements for the smart farm data collection system for the development and utilization of smart farms, the establishment of a sustainable agricultural management system, the sequential system construction method, and the purposeful, efficient and usable data collection system. In particular, we analyze and improve the problems of the data collection system for building a Korean smart farm standard model, which is facing limitations, based on in-depth investigations in the field of livestock and livestock (pig farming) and analysis of various cases, to establish an efficient and usable big data collection system. The goal is to propose a method for collecting big data.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.45-52
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• 2023

Recently, as climate change caused by greenhouse gases is intensifying, the international community has committed to reduce greenhouse gas emissions. The purpose of this study is to present the methodology and major considerations for investment judgment. Two actual cases of overseas projects were selected as study subjects. As an analysis method, the major risk factors were defined as a probability distribution, and the NPV was stochastically estimated using the Monte Carlo simulation method. In addition, assuming a policy change, the range of NPV change was analyzed. As a result, the average NPV of project A was lowered by 19%, and the probability of showing a negative NPV was 12.2%. The average value of project B was lowered by 12.5%. Considering the policy change, project A can obtain economic benefits only when it obtains 72.9% or more of the total amount of carbon credits generated, and project B is economically feasible when it acquires 49.5% or more. As a result, the average value of project A is lower than the net present value under basic assumptions, so caution is needed in investment decisions depending on changes in major risk factors. Additionally, considering policy changes, the carbon credit distribution ratio should be differentially applied depending on the project size, and this was presented as a specific figure.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.79-92
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• 2024

ChatGPT, as a representative chatbot leveraging generative artificial intelligence technology, is used valuable not only in scientific and technological domains but also across diverse sectors such as society, economy, industry, and culture. This study conducts an explorative analysis of user sentiments and needs for ChatGPT by examining global social media discourse on Reddit. We collected 10,796 comments on Reddit from December 2022 to August 2023 and then employed keyword analysis, sentiment analysis, and need-mining-based topic modeling to derive insights. The analysis reveals several key findings. The most frequently mentioned term in ChatGPT-related comments is "time," indicative of users' emphasis on prompt responses, time efficiency, and enhanced productivity. Users express sentiments of trust and anticipation in ChatGPT, yet simultaneously articulate concerns and frustrations regarding its societal impact, including fears and anger. In addition, the topic modeling analysis identifies 14 topics, shedding light on potential user needs. Notably, users exhibit a keen interest in the educational applications of ChatGPT and its societal implications. Moreover, our investigation uncovers various user-driven topics related to ChatGPT, encompassing language models, jobs, information retrieval, healthcare applications, services, gaming, regulations, energy, and ethical concerns. In conclusion, this analysis provides insights into user perspectives, emphasizing the significance of understanding and addressing user needs. The identified application directions offer valuable guidance for enhancing existing products and services or planning the development of new service platforms.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.217-225
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• 2024

To foster the core talents of the future, the development of diverse and substantial SW·AI education programs is required, and a systematic system that can assist public education in SW and AI must be established. In this study, we develop and combine SW·AI education modules to construct a SW and AI education program applicable to public education. We also establish a systematic education system and provide sustainable SW·AI education to elementary, middle, and high school students through 'Job's Garage Camp' based on various sharing platforms. By creating a sustainable follow-up educational environment, students are encouraged to continue their self-directed learning of SW and AI. As a result of conducting a pre-post survey of students participating in the 'Job's Garage Camp', the post-survey values improved compared to the pre-survey values in all areas of 'interest', 'understanding and confidence', and 'career aspirations'. Based on these results, it can be confirmed that students had a universal positive perception and influence on SW and AI. Therefore, if the operation case of 'Job's Garage Camp' is improved and expanded, it can be presented as a standard model applicable to other SW and AI education programs in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.77-85
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• 2024

In this dissertation, a we designed and implemented a patrol robot that integrates a thermal imaging camera, speed dome camera, PTZ camera, radar, lidar sensor, and smartphone. This robot has the ability to monitor and respond efficiently even in complex environments, and is especially designed to demonstrate high performance even at night or in low visibility conditions. An orbital movement system was selected for the robot's mobility, and a smartphone-based control system was developed for real-time data processing and decision-making. The combination of various sensors allows the robot to comprehensively perceive the environment and quickly detect hazards. Thermal imaging cameras are used for night surveillance, speed domes and PTZ cameras are used for wide-area monitoring, and radar and LIDAR are used for obstacle detection and avoidance. The smartphone-based control system provides a user-friendly interface. The proposed robot system can be used in various fields such as security, surveillance, and disaster response. Future research should include improving the robot's autonomous patrol algorithm, developing a multi-robot collaboration system, and long-term testing in a real environment. This study is expected to contribute to the development of the field of intelligent surveillance robots.