• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.2
• /
• pp.93-98
• /
• 2024

With the rapid advance in AI (artificial intelligence) and high-performance computing technologies, deep learning is being used in various fields. Deep learning proceeds training by randomly reading a large amount of data and repeats this process. A large number of files are randomly repeatedly referenced during deep learning, which shows different access characteristics from traditional workloads with temporal locality. In order to cope with the difficulty in caching caused by deep learning, we propose a new sampling method that aims at reducing the randomness of dataset reading and adaptively operating on existing buffer cache algorithms. We show that the proposed policy reduces the miss rate of the buffer cache by 16% on average and up to 33% compared to the existing method, and improves the execution time by up to 24%.

• Journal of KIBIM
• /
• v.14 no.2
• /
• pp.25-34
• /
• 2024

This study proposes a new methodology to increase the flexibility and efficiency of the design data evaluation system by combining Building Information Modeling (BIM) technology in the architectural industry, OpenAI's interactive artificial intelligence, and ChatGPT. BIM technology plays an important role in digitally modeling and managing architectural information. Since architectural information is included, research and development are underway to review and evaluate BIM data according to conditions through program development. However, in the process of reviewing BIM design data, if the review criteria or evaluation criteria according to design change occur frequently, it is necessary to update the program anew. In order for designers or reviewers to apply the changed criteria, requesting a program developer will delay time. This problem was studied by using ChatGPT to modify and update the design data evaluation program code in real time. In this study, it is aimed to improve the changing standards and accuracy by enabling programming non-professionals to change the design regulations and calculation standards of the BIM evaluation program system using ChatGPT. In this study, in the BIM-based design certification automation evaluation program, a program in which the automation evaluation method is being studied based on the design certification evaluation manual was first used. In the design certification automation evaluation program, the programming non-majors checked the automation evaluation code by linking ChatGPT, and the changed calculation criteria were created and modified interactively. As a result of the evaluation, the change in the calculation standard was explained to ChatGPT and the applied result was confirmed.

• Journal of Korean Clinical Health Science
• /
• v.12 no.1
• /
• pp.1668-1677
• /
• 2024

Objective: This study investigated the awareness of occupational therapy in the community in occupational therapy majors through a survey. This purpose is to investigate the awareness of occupational therapy in the community among occupational therapy majors and establish a theoretical foundation. Methods: The research subjects were surveyed among occupational therapy majors at M University living in Gyeongsangnam-do, and analyzed 141 questionnaires from September 2023 to December 2023. Results: The results of this study that education and awareness improvement are needed to increase awareness of occupational therapy in the community, and it was found that continuing education and case sharing are effective. Activation of home rehabilitation and continuous health management. This institutional development can induce employment activity through community rehabilitation, and activate programs in connection with adult day care centers. For the development of community occupational therapy, participation in education and development of customized treatment are necessary, and patient It should be developed to help with movement and movement, and it has been shown that it can also affect the quality of life of patients. In addition, cutting-edge technologies such as artificial intelligence are expected to be applied to remote support, telemedicine, etc., and are applied to dementia, cognitive patients, and central nervous system patients. In order to institutionalize occupational therapy in the community, it is helpful in daily life, nursing, and management. It was said that this would be helpful for community participation. Conclusion: This study investigated the awareness of occupational therapy in the community among occupational therapy majors. Education and awareness improvement are needed to increase awareness of occupational therapy in the community. Education to improve the professionalism of occupational therapists, strengthening connectivity with other majors, and local organizations. It is believed that collaboration with the local community and institutional supplementation tailored to the needs of the local community were necessary.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.3
• /
• pp.147-156
• /
• 2024

This paper introduces the design of a turtle neck posture correction and prevention system for users of digital devices for a long time. The number of forward head posture patients in Korea increased by 13% from 2018 to 2021, and has not yet improved according to the latest statistics at the present time. Because of the nature of the disease, prevention is more important than treatment. Therefore, in this paper, we designed a system based on built-camera in most laptops to increase the accessiblility of the system, and utilize the features such as Pose Estimation, Face Landmarks Detection, Iris Tracking, and Depth Estimation of Google Mediapipe to prevent the need to produce artificial intelligence models and allow users to easily prevent forward head posture.

• Geomechanics and Engineering
• /
• v.36 no.2
• /
• pp.183-204
• /
• 2024

In current investigation, a novel beam finite element model is formulated to analyze the buckling and free vibration responses of functionally graded porous beams resting on Winkler-Pasternak elastic foundations. The novelty lies in the formulation of a simplified finite element model with only three degrees of freedom per node, integrating both C⁰ and C¹ continuity requirements according to Lagrange and Hermite interpolations, respectively, in isoparametric coordinate while emphasizing the impact of z-coordinate-dependent porosity on vibration and buckling responses. The proposed model has been validated and demonstrating high accuracy when compared to previously published solutions. A detailed parametric examination is performed, highlighting the influence of porosity distribution, foundation parameters, slenderness ratio, and boundary conditions. Unlike existing numerical techniques, the proposed element achieves a high rate of convergence with reduced computational complexity. Additionally, the model's adaptability to various mechanical problems and structural geometries is showcased through the numerical evaluation of elastic foundations, with results in strong agreement with the theoretical formulation. In light of the findings, porosity significantly affects the mechanical integrity of FGP beams on elastic foundations, with the advanced beam element offering a stable, efficient model for future research and this in-depth investigation enriches porous structure simulations in a field with limited current research, necessitating additional exploration and investigation.

• Smart Media Journal
• /
• v.13 no.1
• /
• pp.60-66
• /
• 2024

The Internet of Things, which began by connecting sensors through a network, is developing into an intelligent IoT by combining it with artificial intelligence technology. Elevators are essential for high-rise buildings in the city, and elevators move from floor to floor and perform the functions of transporting goods and moving users. It is necessary to provide safe and convenient services for elevator users in high-rise buildings or special environments (hospitals, etc.). In an environment where rapid patient transportation is important, such as large hospitals, there is a problem that hospital staff and the general public often use the elevator for patients. In particular, when moving patients where golden time is important, the waiting time to board the elevator is a major hindrance. In order to solve this problem, this study proposes an intelligent IoT system for elevator calling using smartphone Bluetooth. First, we experimented with the elevator calling IoT system using smartphone Bluetooth, and as a result of the experiment, it was confirmed that it can authenticate elevator users and reduce unnecessary waiting time for boarding. In addition, we propose an intelligent IoT system that connects with intelligent IoT.

• Smart Media Journal
• /
• v.13 no.1
• /
• pp.9-17
• /
• 2024

This study aims to develop an integrated agricultural distribution network management system to improve the quality, profit, and decision-making efficiency of agricultural products. We adopt two key techniques: crop maturity detection based on the YOLOX target detection algorithm and market price prediction based on the Prophet model. By training the target detection model, it was possible to accurately identify crops of various maturity stages, thereby optimizing the shipment timing. At the same time, by collecting historical market price data and predicting prices using the Prophet model, we provided reliable price trend information to shipping decision makers. According to the results of the study, it was found that the performance of the model considering the holiday factor was significantly superior to that of the model that did not, proving that the effect of the holiday on the price was strong. The system provides strong tools and decision support to farmers and agricultural distribution managers, helping them make smart decisions during various seasons and holidays. In addition, it is possible to optimize the distribution network of agricultural products and improve the quality and profit of agricultural products.

• Advanced Industrial SCIence
• /
• v.3 no.1
• /
• pp.1-16
• /
• 2024

The purpose of this study is to develop a machine learning-based AI convergence class model and class design principles that can foster data literacy in high school students, and to develop detailed guidelines accordingly. We developed a machine learning-based teaching model, design principles, and detailed guidelines through research on prior literature, and applied them to 15 students at a specialized high school in Seoul. As a result of the study, students' data literacy improved statistically significantly (p<.001), so we confirmed that the model of this study has a positive effect on improving learners' data literacy, and it is expected that it will lead to related research in the future.

• Information Systems Review
• /
• v.25 no.2
• /
• pp.125-144
• /
• 2023

Generative Artificial Intelligence (AI) technology is gaining global attention as it can automatically generate sentences, images, and voices that humans previously generated. In particular, ChatGPT, a representative generative AI service, shows proactivity and accuracy differentiated from existing chatbot services, and the number of users is rapidly increasing in a short period of time. Despite this growing interest in generative AI services, most preceding studies are still in their infancy. Therefore, this study utilized LDA topic modeling and keyword network diagrams to derive success factors for generative AI services and to propose successful business strategies based on them. In addition, using ChatGPT, a new research methodology that complements the existing text-mining method, was presented. This study overcomes the limitations of previous research that relied on qualitative methods and makes academic and practical contributions to the future development of generative AI services.

• Advances in nano research
• /
• v.16 no.3
• /
• pp.289-301
• /
• 2024

In this work, an analytical model employing a new higher-order shear deformation beam theory is utilized to investigate the bending behavior of axially randomly oriented functionally graded carbon nanotubes reinforced composite nanobeams. A modified continuum nonlocal strain gradient theory is employed to incorporate both microstructural effects and geometric nano-scale length scales. The extended rule of mixture, along with molecular dynamics simulations, is used to assess the equivalent mechanical properties of functionally graded carbon nanotubes reinforced composite (FG-CNTRC) beams. Carbon nanotube reinforcements are randomly distributed axially along the length of the beam. The equilibrium equations, accompanied by nonclassical boundary conditions, are formulated, and Navier's procedure is used to solve the resulting differential equation, yielding the response of the nanobeam under various mechanical loadings, including uniform, linear, and sinusoidal loads. Numerical analysis is conducted to examine the influence of inhomogeneity parameters, geometric parameters, types of loading, as well as nonlocal and length scale parameters on the deflections and stresses of axially functionally graded carbon nanotubes reinforced composite (AFG CNTRC) nanobeams. The results indicate that, in contrast to the nonlocal parameter, the beam stiffness is increased by both the CNTs volume fraction and the length-scale parameter. The presented model is applicable for designing and analyzing microelectromechanical systems (MEMS) and nanoelectromechanical systems (NEMS) constructed from carbon nanotubes reinforced composite nanobeams.