• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.7 no.2
• /
• pp.331-339
• /
• 2017

This paper proposes a thread pool management technique of an websocket server that is applicable to embedded systems. WebSocket is a proposed technique for consisting a dynamic web, and is constructed using HTML5 and jQuery. Various studies have been progressing to construct a dynamic web by Apache, Oracle and etc. Previous web service systems require high-capacity, high-performance hardware specifications and are not suitable for embedded systems. The node.js which is consist of HTML5 and jQuery is a typical websocket server which is made by open sources, and is a java script based web application which is composed of a single thread. The node.js has a limitation on the performance for processing a high velocity data on the embedded system. We make up a multi-thread based websoket server which can solve the mentioned problem. The thread pool is managed by a bit register and suitable for embedded systems. To evaluate the performance of the proposed algorithm, we uses JMeter that is a network test tool.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.5 no.3
• /
• pp.27-36
• /
• 2015

Electronic cultural atlases based on a variety of topics have been studied because of recently increased interest about them. Existing cultural atlases are difficult to analyze the correlation between the subjects and to make utilization based on the various points of view since they are implemented mostly by a single theme. To solve these problems, we propose a method that express a variety of themes by using layer functions of electronic cultural atlases. Using thematic overlay functions, also, application plans are suggested to analyze the relationship between subjects and to derive new knowledge through the association of various themes.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.253-259
• /
• 2021

In line with the modern society where artificial intelligence has spread throughout society, the Ministry of Education decided to provide AI education in kindergartens, elementary, middle and high school classes in 2025, and develop related learning materials and textbooks from 2021. Korea currently does not have state-led AI education for kindergarten and elementary school, so there is no systematic teaching material. Therefore, this study designed and presented textbooks for pattern analysis-based computational thinking development based on the GPS curriculum, a kindergarten SW curriculum studied by Y. S. Jeong and S. E. Lim (2020). Class procedures for using the textbooks were classified as introduction activities, development activities, and organization activities. Supplementary explanations were presented by presenting textbooks and teaching aids along with explanations of each activity. In order for this study to help AI education conducted in 2025, research must be conducted to demonstrate its effectiveness through actual application in the future.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.385-391
• /
• 2021

In this paper, a case of deep learning artificial neural network education was studied for artificial intelligence literacy education for preservice teachers and incumbent teachers. In addition, through the proposed educational case, we tried to explore the contents of artificial neural network principle education that elementary, middle and high school students can experience. To this end, first, an example of training on the principle of operation of an artificial neural network that recognizes two types of images is presented. And as an artificial neural network extension application education case, an artificial neural network education case for recognizing three types of images was presented. The number of output layers was changed according to the number of images to be recognized by the artificial neural network, and the cases implemented in a spreadsheet were divided and explained. In addition, in order to experience the operation results of the artificial neural network, we presented the educational contents to directly write the learning data necessary for the artificial neural network of the supervised learning method. In this paper, the implementation of the artificial neural network and the recognition test results are visually presented using a spreadsheet.

• 한국정보교육학회:학술대회논문집
• /
• 2021.08a
• /
• pp.131-139
• /
• 2021

In the newly revised curriculum, it is aimed to raise student who has creativity and convergence ability with computational thinking. Based on the analysis of revised curriculum including software education in elementary school, this study proposed educational program that can be applied in actual school field, considering various factors. This educational program using Bitbrick was conducted by 50 students in fifth grade that consist of 23 students in Seoul and 27 students in Gyeonggido during five weeks in 17 periods. The purpose of this study is to verify the effect of application of software education program in terms of computational thinking ability and problem solving ability. The effect was verified after comparing the result of pre-test and post-test through T-test. So, this study obtained improvement of computational thinking and problem solving ability.

• Journal of Gastric Cancer
• /
• v.23 no.3
• /
• pp.388-399
• /
• 2023

Gastric cancer remains a significant global health concern, coercing the need for advancements in imaging techniques for ensuring accurate diagnosis and effective treatment planning. Artificial intelligence (AI) has emerged as a potent tool for gastric-cancer imaging, particularly for diagnostic imaging and body morphometry. This review article offers a comprehensive overview of the recent developments and applications of AI in gastric cancer imaging. We investigated the role of AI imaging in gastric cancer diagnosis and staging, showcasing its potential to enhance the accuracy and efficiency of these crucial aspects of patient management. Additionally, we explored the application of AI body morphometry specifically for assessing the clinical impact of gastrectomy. This aspect of AI utilization holds significant promise for understanding postoperative changes and optimizing patient outcomes. Furthermore, we examine the current state of AI techniques for the prognosis of patients with gastric cancer. These prognostic models leverage AI algorithms to predict long-term survival outcomes and assist clinicians in making informed treatment decisions. However, the implementation of AI techniques for gastric cancer imaging has several limitations. As AI continues to evolve, we hope to witness the translation of cutting-edge technologies into routine clinical practice, ultimately improving patient care and outcomes in the fight against gastric cancer.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.3A
• /
• pp.411-419
• /
• 2006

In this study, a new approach employing 3-dimensional strut-tie models for analysis and design of 3-dimensional structural concrete with disturbed regions that are not properly occupied by current design codes is proposed. In addition, a computer graphics program for the practical application of the approach is developed. The approach adopts a grid strut-tie model to exclude the subjectivity in the selection of strut-tie model and evaluates the effective strength of concrete strut by considering the 3-dimensional failure criteria of concrete and the deviation angles between the struts and compressive principal stress trajectories. To verify the appropriateness of the approach, nine pile caps tested to failure are analyzed and a bridge pier is designed. The analysis and design results are compared with those obtained by several different methods.

• Journal of IKEEE
• /
• v.27 no.4
• /
• pp.624-629
• /
• 2023

Estimation of signal parameters via rotational invariance techniques (ESPRIT) is an algorithm that estimates the angle of a signal arriving at an array antenna using the shift invariance property of an array antenna. ESPRIT offers the good trade-off between performance and complexity. However, the ESPRIT algorithm still requires high-complexity operations such as covariance matrix and eigenvalue decomposition, so implementation with a hardware processor is essential to estimate the angle of arrival in real time. In addition, ESPRIT processors should have high performance. The performance is related to the number of antennas, and the number of antennas required for each application are different. Therefore, we proposed an ESPRIT processor that provides 2 to 8 variable antenna configurations to meet the performance and complexity requirements according to the applied field. The proposed ESPRIT processor was designed using the Verilog-HDL and implemented on a field programmable gate array (FPGA).

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.5
• /
• pp.307-314
• /
• 2023

As supercomputing and hardware technology advances, climate prediction models are improving. The Korean Meteorological Administration adopted GloSea5 from the UK Met Office and now operates an updated GloSea6 tailored to Korean weather. Universities and research institutions use Low-GloSea6 on smaller servers, improving accessibility and research efficiency. In this paper, profiling Low-GloSea6 on smaller servers identified the tri_sor_dp_dp subroutine in the tri_sor.F90 atmospheric model as a CPU-intensive hotspot. Applying linear regression, a type of machine learning, to this function showed promise. After removing outliers, the linear regression model achieved an RMSE of 2.7665e-08 and an MAE of 1.4958e-08, outperforming Lasso and ElasticNet regression methods. This suggests the potential for machine learning in optimizing identified hotspots during Low-GloSea6 execution.

• Advances in nano research
• /
• v.15 no.5
• /
• pp.401-410
• /
• 2023

Vibration investigation of fluid-filled three layered cylindrical shells is studied here. A cylindrical shell is immersed in a fluid which is a non-viscous one. Shell motion equations are framed first order shell theory due to Love. These equations are partial differential equations which are usually solved by approximate technique. Robust and efficient techniques are favored to get precise results. Employment of the wave propagation approach procedure gives birth to the shell frequency equation. Use of acoustic wave equation is done to incorporate the sound pressure produced in a fluid. Hankel's functions of second kind designate the fluid influence. Mathematically the integral form of the Lagrange energy functional is converted into a set of three partial differential equations. It is also exhibited that the effect of frequencies is investigated by varying the different layers with constituent material. The coupled frequencies changes with these layers according to the material formation of fluid-filled FG-CSs. Throughout the computation, it is observed that the frequency behavior for the boundary conditions follow as; clamped-clamped (C-C), simply supported-simply supported (SS-SS) frequency curves are higher than that of clamped-simply (C-S) curves. Expressions for modal displacement functions, the three unknown functions are supposed in such way that the axial, circumferential and time variables are separated by the product method. Computer software MATLAB codes are used to solve the frequency equation for extracting vibrations of fluid-filled.