• Journal of IKEEE
• /
• v.27 no.1
• /
• pp.1-11
• /
• 2023

Path driving tests are necessary for the development of self-driving cars or robots. These tests are being conducted in simulation as well as real environments. In particular, for development using reinforcement learning and deep learning, development through simulators is also being carried out when data of various environments are needed. To this end, it is necessary to utilize not only manually designed paths but also various randomly and automatically designed paths. This test site design can be used for actual construction and manufacturing. In this paper, we introduce a method for randomly generating a driving test path consisting of a combination of arcs and segments. This consists of a method of determining whether there is a collision by obtaining the distance between an arc and a line segment, and an algorithm that deletes part of the path and recreates an appropriate path if it is impossible to continue the path.

• Journal of the Korean School Mathematics Society
• /
• v.26 no.1
• /
• pp.1-19
• /
• 2023

This study analyzed the international trends of research concerning artificial intelligence in education by examining 352 papers recently published in the International Journal of Artificial Intelligence in Education(IJAIED) with the topic modeling method. The IJAIED is the official, SCOPUS-indexed journal of the International AIED Society. The analysis revealed that international AIED research trends could be categorized into eight topics with topics such as analyzing student behavior model in learning systems and designing feedback to student solutions being increased over time, whereas research focusing on data handling methods was decreased over time. Based on the findings implications and suggestions for the research and development of the applications of AIED were provided.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.3
• /
• pp.421-426
• /
• 2023

Among artificial intelligence convergence technologies, Chatbot is an artificial intelligence-based interactive system and refers to a system that can provide interaction with humans. Chatbots are being re-examined as chatbots develop into NLP, NLU, and NLG. However, artificial intelligence chatbots can provide biased information based on learned data and cause serious damage such as privacy infringement and cybersecurity concerns, and it is essential to understand artificial intelligence technology and foster AI literacy. With the continued evolution and universalization of artificial intelligence, AI Literacy will also expand its scope and include new areas. This study is meaningful in raising awareness of artificial intelligence technology and proposing the use of human respect technology that is not buried in technology by cultivating human AI literacy capabilities.

• Knowledge Management Research
• /
• v.24 no.1
• /
• pp.223-243
• /
• 2023

RPA is implemented through management policy and enforced in mandatory environments to enhance performance and efficiency in various fields. However, the success of RPA implementation depends on the level of active engagement from organization members, even in a mandatory setting. This study identifies perceived ease of use, usefulness, accountability, perceived risk, and self-efficacy as variables that influence conative use behavior, which consists of reflective secondary factors such as immersion, reinvention, and learning. Data was collected from 207 office workers in various industries who have experience with RPA to test the proposed research model. The structural equation was verified using SPSS 20.0 and SmartPLS 4.0, and the analysis showed that all the proposed variables had a significant impact on conative use behavior. Our research findings provide theoretical and practical implications in knowledge management, enabling companies that implement RPA to recognize and address factors that encourage their members to actively use RPA.

• Smart Media Journal
• /
• v.11 no.2
• /
• pp.18-24
• /
• 2022

Problems caused by malicious comments occur on many social media. In particular, YouTube, which has a strong character as a medium, is getting more and more harmful from malicious comments due to its easy accessibility using mobile devices. In this paper, we designed and implemented a YouTube malicious comment detection system to identify malicious comments in YouTube contents through LSTM-based natural language processing and to visually display the percentage of malicious comments, such commentors' nicknames and their frequency, and we evaluated the performance of the system. By using a dataset of about 50,000 comments, malicious comments could be detected with an accuracy of about 92%. Therefore, it is expected that this system can solve the social problems caused by malicious comments that many YouTubers faced by automatically generating malicious comments statistics.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.1
• /
• pp.23-30
• /
• 2022

Recently, there are various studies underway on the deep learning-used image matting methods. Even in the field of photogrammetry, a process of extracting information about relics from images photographed is essential to produce a high-quality realistic model. Such a process requires a great deal of time and manpower, so chroma-key has been used for extraction so far. This method is low in accuracy of sub-classification, however, it is difficult to apply the existing method to high-quality realistic models. Thus, this study attempted to remove background information from high-resolution relic images by using prior background information and trained learning data and evaluate both qualitative and quantitative results of the relic images extracted. As a result, this proposed method with FBA(manual trimap) showed quantitatively better results, and even in the qualitative evaluation, it was high in accuracy of classification around relics. Accordingly, this study confirmed the applicability of the proposed method in the indoor relic photography since it showed high accuracy and fast processing speed by acquiring prior background information when classifying high-resolution relic images.

• Korean Educational Research Journal
• /
• v.43 no.1
• /
• pp.183-213
• /
• 2022

The purpose of this study is to examine the implications of Deleuze and Guattari's Machinism and Pedagogy of Assemblages. A slow, empirical process offered by Deleuze and Guattari is possible only if they experience a repetition of the duration in time. The identity of this world, a combination of potential and reality, is expressed as a machine. The identity of the 'machine' is the generation. The identity of the information society that exists everywhere in the cloud and unconsciously collects big data is also the information society. The information society is at risk of leaning toward a society in which individual desires are managed prior to the manifestation of a self-reliance a machine consisting of unmarked and mechanical arrangements. Social science based on the theory of layout shares the characteristics of repetition patterns, coexistence of linguistic and materiality, attention to boundary and negation to total whole. The pedagogy of layout, in which the collective pattern is structurally deformed in time, conforms to the original problem consciousness of Deleuze and Guattari, slow and empirical education. In addition, the work of examining the materiality and expression of the education-machine will contribute to the establishment of a new learning theory, an educational theory in the era of trans-human.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.6
• /
• pp.51-56
• /
• 2022

With the development of industrialization, the amount of food and waste is rapidly increasing. Accordingly, the government is aware of the seriousness and is making efforts in various ways to reduce it. As a part of that, the volume-based food system was introduced, and although there were several trials and errors at the beginning of the introduction, it shows a reduction effect of 20 to 30%. These results suggest that the volume-based food system is being established. However, the waste is caused by foreign substances in the process of recycling resources by collecting them from the 1st collection to the 2nd collection process. Therefore, in this study, to solve these problems fundamentally, artificial intelligence is applied to classify foreign substances and improve them. Due to the nature of food waste, there is a limit to obtaining many images, so we compare several models based on CNNs and classify them as abnormal data, that is, CNN-based models are trained on various types of foreign substances, and then models with high accuracy are selected. We intend to prepare improvement measures for maintenance, such as manpower input to protect equipment and classify foreign substances by applying it.

• Journal of Broadcast Engineering
• /
• v.27 no.1
• /
• pp.20-30
• /
• 2022

Recently, as VR (Virtual Reality) technology has been in the spotlight, 360° panoramic images that can view lively VR contents are attracting a lot of attention. Image stitching technology is a major technology for producing 360° panorama images, and many studies are being actively conducted. Typical stitching algorithms are based on feature point-based image stitching. However, conventional feature point-based image stitching methods have a problem that stitching results are intensely affected by feature points. To solve this problem, deep learning-based image stitching technologies have recently been studied, but there are still many problems when there are few overlapping areas between images or large parallax. In addition, there is a limit to complete supervised learning because labeled ground-truth panorama images cannot be obtained in a real environment. Therefore, we produced three fisheye images with different camera centers and corresponding ground truth image through carla simulator that is widely used in the autonomous driving field. We propose image stitching model that creates a 360° panorama image with the produced fisheye image. The final experimental results are virtual datasets configured similar to the actual environment, verifying stitching results that are strong against various environments and large parallax.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.7 no.6
• /
• pp.839-849
• /
• 2017

Recently, the role of the kitchen has evolved from the space for previous survival to the space that shows the present life and culture. Along with these changes, the use of IoT technology is spreading. As a result, the development and diffusion of new smart devices in the kitchen is being achieved. The user experience for using these smart devices is also becoming important. For a natural interaction between a user and a computer, better interactions can be expected based on context awareness. This paper examines the Natural User Interface (NUI) that does not touch the device based on the user interface (UI) of the smart device used in the kitchen. In this method, we use the image processing technology to recognize the user's hand gesture using the camera attached to the device and apply the recognized hand shape to the interface. The gestures used in this study are proposed to gesture according to the user's context and situation, and 5 kinds of gestures are classified and used in the interface.