• Journal of the Korea Institute of Building Construction
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• v.23 no.5
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• pp.629-638
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• 2023

This study introduces an innovative approach to monitor the whereabouts of workers within indoor construction settings. While traditional modalities such as GPS and NTRIP have demonstrated efficacy for outdoor localizations, their precision dwindles in indoor environments. In response, this research advocates for the adoption of Aruco markers. Leveraging computer vision technology, these markers facilitate the quantification of the distance between a worker and the marker, subsequently pinpointing the worker's instantaneous location with heightened accuracy. The methodology's efficacy was rigorously evaluated in a real-world construction scenario. Parameters including system stability, the influence of lighting conditions, the extremity of measurable distances, and the breadth of recognition angles were methodically appraised. System stability was ascertained by maneuvering the camera at a uniform velocity, gauging its marker recognition prowess. The impact of varying luminosity on marker discernibility was scrutinized by modulating the ambient lighting. Furthermore, the camera's spatial movement ascertained both the upper threshold of distance until marker recognition waned and the maximal angle at which markers remained discernible.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.57-84
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• 2023

With the development of information and communications technology (ICT) and big data technology, anyone can easily obtain and utilize vast amounts of data through the Internet. Therefore, the capability of selecting high-quality data from a large amount of information is becoming more important than the capability of just collecting them. This trend continues in academia; literature reviews, such as systematic and non-systematic reviews, have been conducted in various research fields to construct a healthy knowledge structure by selecting high-quality research from accumulated research materials. Meanwhile, after the COVID-19 pandemic, remote healthcare services, which have not been agreed upon, are allowed to a limited extent, and new healthcare services such as health recommender systems (HRS) equipped with artificial intelligence (AI) and big data technologies are in the spotlight. Although, in practice, HRS are considered one of the most important technologies to lead the future healthcare industry, literature review on HRS is relatively rare compared to other fields. In addition, although HRS are fields of convergence with a strong interdisciplinary nature, prior literature review studies have mainly applied either systematic or non-systematic review methods; hence, there are limitations in analyzing interactions or dynamic relationships with other research fields. Therefore, in this study, the overall network structure of HRS and surrounding research fields were identified using citation network analysis (CNA). Additionally, in this process, in order to address the problem that the latest papers are underestimated in their citation relationships, the GraphSAGE algorithm was applied. As a result, this study identified 'recommender system', 'wireless & IoT', 'computer vision', and 'text mining' as increasingly important research fields related to HRS research, and confirmed that 'personalization' and 'privacy' are emerging issues in HRS research. The study findings would provide both academic and practical insights into identifying the structure of the HRS research community, examining related research trends, and designing future HRS research directions.

• The Journal of Art Theory & Practice
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• no.14
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• pp.87-124
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• 2012

This paper focuses on the social implication of new media art, which has evolved with the advance of technology. To understand the notion of human-computer interactivity in media art, it examines the meaning of "cybernetics" theory invented by Norbert Wiener just after WWII, who provided "control and communication" as central components of his theory of messages. It goes on to investigate the application of cybernetics theory onto art since the 1960s, to which Roy Ascott made a significant contribution by developing telematic art, utilizing the network of telecommunication. This paper underlines the significance of the relationship between human and machine, art and technology in transforming the work of art as a site of communication and experience. The interactivity in new media art transforms the viewer into the user of the work, who is now provided free will to make decisions on his or her action with the work. The artist is no longer a godlike figure who determines the meaning of the work, yet becomes another user of his or her own work, with which to interact. This paper believes that the interaction between man and machine, art and technology can lead to various ways of interaction between humans, thereby restoring a sense of community while liberating humans from conventional limitations on their creativity. This paper considers the development of new media art more than a mere invention of new aesthetic styles employing advanced technology. Rather, new media art provides a critical shift in subverting the modernist autonomy that advocates the medium specificity. New media art envisions a new art, which would embrace impurity into art, allowing the coexistence of autonomy and heteronomy, embracing a technological other, thereby expanding human relations. By enabling the birth of the user in experiencing the work, interactive new media art produces an open arena, in which the user can create the work while communicating with the work and other users. The user now has freedom to visit the work, to take a journey on his or her own, and to make decisions on what to choose and what to do with the work. This paper contends that there is a significant parallel between new media artists' interest in creating new experiences of the art and Jacques Ranci$\grave{e}$re's concept of the aesthetic regime of art. In his argument for eliminating hierarchy in art and for embracing impurity, Ranci$\grave{e}$re provides a vision for art, which is related to life and ultimately reshapes life. Ranci$\grave{e}$re's critique of both formalist modernism and Jean-Francois Lyotard's postmodern view underlines the social implication of new media art practices, which seek to form "the common of a community."

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.6
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• pp.599-609
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• 2008

Development of computer and electronic technology leads innovative progress in spatial informatics and successful commercialization. Geospatial information technology plays an important role in decision making in various applications. However, information display media are two-dimensional plane that limits visual perception. Understanding human visual processing mechanism to percept stereo vision makes possible to implement three-dimensional stereo image display. This paper proposes on-the-fly stereo image generation methods that are involved with various exterior and camera parameters including exposure station, viewing direction, image size, overlap and focal length. Collinearity equations and parameters related with stereo viewing conditions were solved to generate realisitc stereo imagery. In addition stereo flying simulation scenery was generated with different viewing locations and directions. The stereo viewing is based on the parallax principle of two veiwing locations. This study implemented anaglyphic stereogram, polarization and lenticular stereo display methods. Existing display technology has limitation to provide visual information of three-dimensional and dynamic nature of the real world because the 3D spatial information is projected into 2D plane. Therefore, stereo display methods developed in this study improves geospatial information and applications of GIS by realistic stereo visualization.

• Journal of the Korean Wood Science and Technology
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• v.47 no.2
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• pp.229-238
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• 2019

Various wood defects occur during tree growing or wood processing. Thus, to use wood practically, it is necessary to objectively assess their quality based on the usage requirement by accurately classifying their defects. However, manual visual grading and species classification may result in differences due to subjective decisions; therefore, computer-vision-based image analysis is required for the objective evaluation of wood quality and the speeding up of wood production. In this study, the SIFT+k-NN and CNN models were used to implement a model that automatically classifies knots and analyze its accuracy. Toward this end, a total of 1,172 knot images in various shapes from five domestic conifers were used for learning and validation. For the SIFT+k-NN model, SIFT technology was used to extract properties from the knot images and k-NN was used for the classification, resulting in the classification with an accuracy of up to 60.53% when k-index was 17. The CNN model comprised 8 convolution layers and 3 hidden layers, and its maximum accuracy was 88.09% after 1205 epoch, which was higher than that of the SIFT+k-NN model. Moreover, if there is a large difference in the number of images by knot types, the SIFT+k-NN tended to show a learning biased toward the knot type with a higher number of images, whereas the CNN model did not show a drastic bias regardless of the difference in the number of images. Therefore, the CNN model showed better performance in knot classification. It is determined that the wood knot classification by the CNN model will show a sufficient accuracy in its practical applicability.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.143-149
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• 2018

Recently, due to the large-scale damage of natural disasters caused by global climate change, a monitoring system applying remote sensing technology is being constructed in disaster areas. Among remote sensing platforms, the drone has been actively used in the private sector due to recent technological developments, and has been applied in the disaster areas owing to advantages such as timeliness and economical efficiency. This paper deals with the development of a preprocessing system that can map the drone image data in a near-real time manner as a basis for constructing the disaster monitoring system using the drones. For the research purpose, our system is based on the SURF algorithm which is one of the computer vision technologies. This system aims to performs the desired correction through the feature point matching technique between reference images and shot images. The study area is selected as the lower part of the Gahwa River and the Daecheong dam basin. The former area has many characteristic points for matching whereas the latter area has a relatively low number of difference, so it is possible to effectively test whether the system can be applied in various environments. The results show that the accuracy of the geometric correction is 0.6m and 1.7m respectively, in both areas, and the processing time is about 30 seconds per 1 scene. This indicates that the applicability of this study may be high in disaster areas requiring timeliness. However, in case of no reference image or low-level accuracy, the results entail the limit of the decreased calibration.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.143-149
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• 2019

This study investigates the satisfaction of students who participated in 'Disaster Safety and On-Site Emergency Management' weekend course, the high school-university affiliated program, to provide the basic data on university's major linked program developing and teaching methods. 98 high school students attended the courses at D General high school and B University in North Jeonlla Province. Among the participants, 52%(51 students) were sophomores, while 56.1%(55 students) were male and 43.9%(43 students) were female. The collected data was analyzed by using the SPSS statistics version 21.0 program. 80.6%(79 students) among the participants chose the weekend course program by themselves, 85.7%(84 students) were with clear motivation and goal, and 42.9%(42 students) answered "so interested studying Emergency at a college in the future" The most important reasons to choose this program are as follows: score 4.68 for 'the degree to which the useful program for youth', score 4.58 for 'the leader's expertise', and score 4.53 for 'reflecting the opinion of youth.' After the program's experience, the 'certificate for cardiopulmonary resuscitation' was the most important and the most satisfactory with score 4.78 and score 4.83 respectively. As the university career program using various job experience can be a meaningful experience that enhance the level of career status and career decisions of high school students, this program will strengthen the affiliation between high school and university curriculum and establish the sufficient national social system environment.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.183-190
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• 2022

The article analyzes the features of the formation of a person's value attitude to the worldview by means of information technologies. The present considers it necessary to form a person's value attitude to the perception of the world by means of information technologies. The explosive development of information and telecommunications technologies has become a determining factor in the development of modern society, which is called the information or Global Information Society. It is not yet fully formed, and we are all participants in the development of the Global Information Society. The article considers the basics of a harmonious worldview of a person, which is the basis for the formation of outlook ideas, views, knowledge, beliefs about the surrounding world, which determine the place and role and motivate actions in relation to the surrounding reality through the prism of value orientations. Worldview is considered as an integrity of relatively stable schemes, behaviors, feelings, thinking, vision of the surrounding world, inherent in an individual child, ethno-cultural and socio-cultural groups. The concept of "worldview" as a component of the multi-level structure of the individual's outlook is defined. The features that characterize a person's perception of the world are revealed. The main educational value of information technologies in the formation of a person's value attitude to the perception of the world is highlighted, which consists in the fact that they allow you to create an immeasurable brighter multi-sensory interactive learning environment with almost unlimited potential opportunities that fall at the disposal of both the teacher and the student. The trend of forming a person's value attitude to the perception of the world is clearly developing in the direction of mixed learning as a process that creates a comfortable information educational environment, communication systems that provide all the necessary educational information. The approach to student development by means of the educational environment and the formation, while in the person of a value attitude to the perception of the world by means of Information Technologies, has many pedagogical advantages, which is considered in the article.

• Informatization Policy
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• v.31 no.2
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• pp.3-38
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• 2024

Hallucination is a significant barrier to the utilization of large-scale language models or multimodal models. In this study, we collected 654 computer science papers with "hallucination" in the abstract from arXiv from December 2022 to January 2024 following the advent of Chat GPT and conducted frequency analysis, knowledge network analysis, and literature review to explore the latest trends in hallucination research. The results showed that research in the fields of "Computation and Language," "Artificial Intelligence," "Computer Vision and Pattern Recognition," and "Machine Learning" were active. We then analyzed the research trends in the four major fields by focusing on the main authors and dividing them into data, hallucination detection, and hallucination mitigation. The main research trends included hallucination mitigation through supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF), inference enhancement via "chain of thought" (CoT), and growing interest in hallucination mitigation within the domain of multimodal AI. This study provides insights into the latest developments in hallucination research through a technology-oriented literature review. This study is expected to help subsequent research in both engineering and humanities and social sciences fields by understanding the latest trends in hallucination research.