• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.275-285
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• 2021

Ministries of Education are integrating different Learning Management Systems (LMS) to enhance teaching and learning during the lockdown to avoid academic loss. The key factor for delivering a high-quality education through LMS platforms is teachers' acceptance and adoption of the platform. Madrasati platform (which means My school) was introduced by Saudi Arabian Ministry of education as the formal teaching and learning for distance education for public education levels. This study aims to examine the effectiveness, usability and adoption of "Madrasati" platform from teachers' perspectives in Saudi Arabia. "SUS, CSUQ" tests were used to test the usability of the new platform. Using quantitative research design, data were collected using questionnaire. 200 teachers were selected randomly answered the survey. Data was analysed descriptively and inferentially using SPSS (25). The results obtained indicate that the teachers are highly satisfied using Madrasati platform and technically it is well designed. Also, Madrasati has positive effect on teaching quality. Moreover, Madrasati has high usability in teaching. One of the key findings were that the quality of the information content in Madrasati has a strong effect on teachers' perception of the Madrasati usefulness that led to a positive attitude towards Madrasati. These findings would be useful to the ministry of education and institutions trying to integrate technology in their teaching and learning processes. Thus, this paper contributes towards more effective utilisation of the extensive functionalities that Madrasati have to offer, which will contribute toward the development of pedagogy in Saudi Arabia.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.18-23
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• 2021

There has been demand for many magnetic sensor applications, and to develop low-cost devices, it is critical to accurately understand the behavior of the magnetic field and the characteristics of magnetic sensors and target devices during initial development phase. The magnetic field has been known to have very complicated nonlinear data to calculate, so it has required expensive computing machines or research to accurately calculate the magnetic sensor values. However, this paper introduces a characteristic of a magnetic sensor called the giant magnetoresistance (GMR) and proposes simple and sufficient approaches to develop a wearable joystick device using a magnetic sensor. Particularly, this paper introduces the design factors for how to properly develop a low-cost wearable joystick device using magnetic sensors after carefully considering the mechanism of a real joystick and the characteristics of magnetic sensors. As a result, user test results are provided to show how users can operate this new wearable joystick device.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1279-1289
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• 2020

To securely protect users' sensitive information and national secrets, the importance of cryptographic modules has been emphasized. Currently, many companies and national organizations are actively using cryptographic modules. In Korea, To ensure the security of these cryptographic modules, the cryptographic module has been verified through the Korea Certificate Module Validation Program(KCMVP). Most of the domestic cryptographic modules are CPU-based software (S/W). However, CPU-based cryptographic modules are difficult to use in servers that need to process large amounts of data. In this paper, we propose an S/W cryptographic module that provides a high-speed operation using GPU. We describe the configuration and operation of the S/W cryptographic module using GPU and present the changes in the cryptographic module security requirements by using GPU. In addition, we present the performance improvement compared to the existing CPU S/W cryptographic module. The results of this paper can be used for cryptographic modules that provide cryptography in servers that manage IoT (Internet of Things) or provide cloud computing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1500-1505
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• 2019

Currently, as part of the ICT Smart City, the company is building C-ITS(Cooperative-Intelligent Transport Systems) for solving urban traffic problems. In order to realize autonomous driving service with C-ITS, the role of advanced road infrastructure is important. In addition to the study of mid- to long-term C-ITS and autonomous driving services, it is necessary to present more realistic solutions for road traffic safety in the short term. Therefore, in this paper, we propose a highway accident detection alarm system that can detect and analyze traffic flow and risk information, which are essential information of C-ITS, based on IoT guard rail and provide immediate alarm and remote control. Intelligent IoT guard rail is expected to be used as an intelligent advanced road infrastructure that provides data at actual road sites that are required by C-ITS and self-driving services in the long term.

• Smart Media Journal
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• v.10 no.1
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• pp.99-107
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• 2021

In addition to the 4th Industrial Revolution and Industry 4.0, the recent megatrends in the ICT field are Big-data, IoT, Cloud Computing, and Artificial Intelligence. Therefore, rapid digital transformation according to the convergence of various industrial areas and ICT fields is an ongoing trend that is due to the development of technology of AI services suitable for the era of the 4th industrial revolution and the development of subdivided technologies such as (Business Intelligence), IA (Intelligent Analytics, BI + AI), AIoT (Artificial Intelligence of Things), AIOPS (Artificial Intelligence for IT Operations), and RPA 2.0 (Robotic Process Automation + AI). This study aims to integrate and advance various machine learning services of infrastructure-side GPU, CDA (Connected Data Architecture) framework, and AI based on mass distributed Abyss storage in accordance with these technical situations. Also, we want to utilize AI business revenue model in various industries.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.307-313
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• 2021

Most of the stores of small business owners are those that use a large number of electrical devices, and in particular, there are many stores that use a cold storage system. In severe cases, there is a lot of power load on the store, which can cause a loss to the assets in the store as the power supply is cut off. Accordingly, in this paper, an LSTM-based power load prediction system was designed to measure the energy demand rate of stores and to save energy. Since it can be used as a data-based power saving system for small and medium-sized stores, it is expected to be used as a data-based power demand prediction system for small businesses in the future, and to be used in the field of preventing damage due to power load.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.4
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• pp.199-204
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• 2021

In this study, an isogoemetric analysis (IGA) method that uses NURBS (Non-Uniform Rational B-Spline) basis functions in computer-aided design (CAD) systems is employed to account for the geometric exactness of curved electrodes constituting an electro-adhesive pad in electrostatic problems. The IGA is advantageous for obtaining precise normal vectors when computing the electro-adhesive forces on curved surfaces. By performing parametric studies using numerical examples, we demonstrate the superior performance of the curved electrodes, which is attributed to the increase in the normal component of the electro-adhesive forces. In addition, concave curved electrodes exhibit better performance than their convex counterparts.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.123-127
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• 2021

Millimeter-wave tracking radars should be operated in various environmental restrictions, thus they demand more computing power and smaller size compared to conventional tracking radars. This paper presents the design and implementation of the compact power supply for millimeter-wave tracking radar applications. To meet requirements of low voltage/high current and voltage accuracy for FPGA/DSP digital circuits, Point of Load (POL) converters are used in order to enhance power density and system efficiency. LDO (Low Dropout) is applied for the output voltage under the light load condition, then the single-input-multi-output power supply with max power of 375 W and 8 outputs is developed. The proposed power supply achieves output voltage accuracy of ±2 % and noise level of <50 mVpp % under full load conditions.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.159-166
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• 2022

Artificial Intelligence has stimulated every aspect of today's life. Human thinking quality is trying to be involved through digital tools in all research areas of the modern era. The education industry is also leveraging artificial intelligence magical power. Uses of digital technologies in pedagogical paradigms are being observed from the last century. The widespread involvement of artificial intelligence starts reshaping the educational landscape. Adaptive learning is an emerging pedagogical technique that uses computer-based algorithms, tools, and technologies for the learning process. These intelligent practices help at each learning curve stage, from content development to student's exam evaluation. The quality of information technology students and professionals training has also improved drastically with the involvement of artificial intelligence systems. In this paper, we will investigate adopted digital methods in the education sector so far. We will focus on intelligent techniques adopted for information technology students and professionals. Our literature review works on our proposed framework that entails four categories. These categories are communication between teacher and student, improved content design for computing course, evaluation of student's performance and intelligent agent. Our research will present the role of artificial intelligence in reshaping the educational process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.850-858
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• 2022

To deploy Gate Recurrent Units (GRU) on resource-constrained embedded devices, this paper presents a reconfigurable FPGA-based GRU accelerator that enables structured compression. Firstly, a dense GRU model is significantly reduced in size by hybrid quantization and structured top-k pruning. Secondly, the energy consumption on external memory access is greatly reduced by the proposed reuse computing pattern. Finally, the accelerator can handle a structured sparse model that benefits from the algorithm-hardware co-design workflows. Moreover, inference tasks can be flexibly performed using all functional dimensions, sequence length, and number of layers. Implemented on the Intel DE1-SoC FPGA, the proposed accelerator achieves 45.01 GOPs in a structured sparse GRU network without batching. Compared to the implementation of CPU and GPU, low-cost FPGA accelerator achieves 57 and 30x improvements in latency, 300 and 23.44x improvements in energy efficiency, respectively. Thus, the proposed accelerator is utilized as an early study of real-time embedded applications, demonstrating the potential for further development in the future.