• International journal of advanced smart convergence
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• v.11 no.4
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• pp.96-103
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• 2022

This paper presents the analysis of increasing the resolution of True-Time-Delay (TTD) by 0.5-bit for phased-array antenna system which is one of the Multiple-Input and Multiple Output (MIMO) technologies. For the analysis, a 5.5-bit True-Time Delay (TTD) integrated circuit is designed and analyzed in terms of beam steering performance. In order to increase the number of effective bits, the designed 5.5-bit TTD uses Single Pole Triple Throw (SP3T) and Double Pole Triple Throw (DP3T) switches, and this method can minimize the circuit area by inserting the minimum time delay of 0.5-bit. Furthermore, the circuit mostly maintains the performance of the circuit with the fully added bits. The idea of adding 0.5-bit is verified by analyzing the relation between the number of bits and array elements. The 5.5-bit TTD is designed using 0.18 ㎛ RF CMOS process and the estimated size of the designed circuit excluding the pad is 0.57×1.53 mm². In contrast to the conventional phase shifter which has distortion of scanning angle known as beam squint phenomenon, the proposed TTD circuit has constant time delays for all states across a wide frequency range of 4 - 20 GHz with minimized power consumption. The minimum time delay is designed to have 1.1 ps and 2.2 ps for the 0.5-bit option and the normal 1-bit option, respectively. A simulation for beam patterns where the 10 phased-array antenna is assumed at 10 GHz confirms that the 0.5-bit concept suppresses the pointing error and the relative power error by up to 1.5 degrees and 80 mW, respectively, compared to the conventional 5-bit TTD circuit.

• Journal of Aerospace System Engineering
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• v.17 no.2
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• pp.111-119
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• 2023

Internal storage state, weight data, and weight-centered calculation values for overhead bin can all be seen in this paper's real-time internal status identification system. The suggested system offers such valuable data via a range of sensors, including load cells and switch arrays. The proposed system could locate internal free space, locate the center of gravity, and give real-time visual information. It was developed utilizing an embedded system and the C programming language. These features led to the creation of smart overhead bins and real-time cargo loading monitoring technologies, both of which could one day aid in the creation of a cargo loading automation system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.469-472
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• 2022

With the recent development of intelligent transportation systems, various technologies applying deep learning technology are being used. To crackdown on illegal vehicles and criminal vehicles driving on the road, a vehicle type classification system capable of accurately determining the type of vehicle is required. This study proposes a vehicle type classification system optimized for mobile traffic control systems using YOLO(You Only Look Once). The system uses a one-stage object detection algorithm YOLOv5 to detect vehicles into six classes: passenger cars, subcompact, compact, and midsize vans, full-size vans, trucks, motorcycles, special vehicles, and construction machinery. About 5,000 pieces of domestic vehicle image data built by the Korea Institute of Science and Technology for the development of artificial intelligence technology were used as learning data. It proposes a lane designation control system that applies a vehicle type classification algorithm capable of recognizing both front and side angles with one camera.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.272-275
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• 2022

Large-scale online platforms such as MOOCs-Massive Open Online Courses, which provide a variety of educational contents, have provided a learning environment that allows students to freely access and learn anytime and anywhere. Currently, the proportion of online lectures and home-based learning is increasing, and portfolio or experience-based learning such as bootcamp, field activities, and team project-based group learning are also being actively carried out for educational outcomes. At present, interest in nano or microdegree focused on core technology in units of hours or credits is increasing significantly because such strategic intensive education enables effective learning in terms of continuity and efficiency of education. In an era of large changes in job market due to the reorganization of the industrial structure by new technologies, intensive education in specialized new technology fields such as smart mobility, big data, and artificial intelligence is much more conducive to finding a job. With this reason it is attracting attention as an alternative to lifelong learning are receiving In this paper we propose an educational platform that can efficiently and effectively support the purpose learning for the personalized microdegree education in the online learning era.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.357-359
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• 2022

The market for eco-friendly food materials by online distribution is rapidly growing due to major environmental pollution such as air, soil, and water quality, and radical changes in living patterns caused by COVID-19. In addition, because of the aging population and the decrease in agricultural-related population due to social structural changes, aquaponics is emerging as a system that can solve problems such as independence of old economic activities, environmental protection, and securing healthy and safe food. This paper aims to design an intelligent plant growth measurement system among intelligent aquaponics production management modules for optimal growth environment derivation and quantitative production prediction by converging various ICT technologies into existing aquaponics systems. In particular, the focus is on designing systems suitable for production sites that do not have high-performance processing resources, and we propose a module configuration plan for production environments and training data and prediction systems.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.385-386
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• 2022

Currently, global developed countries in shipping and logistics establish smart ports by introducing various digital technologies such as automated terminals and sharing platforms. This means that the importance of efficiency throughout the port by improving resource utilization efficiency and minimizing work idle time is increasing. Therefore, this study proposes a yard truck dispatching method of improving resource utilization efficiency. And we analyze the problems of the existing dispatching rules and develop Y/T dispatching algorithm that comprehensively considers related constraints. In addition, the simulation takes into account the terminal congestion based on the operation data of the Busan New Port, it is conducted using the existing dispatch method and developed Y/T dispatching algorithm. And the operational effects of analysis result are evaluated.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.388-389
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• 2022

Recently, AI (Artificial Intelligence) has been applied to various technologies such as automatic driving, robot and smart communication. Currently, AI system is developed by software-based method using tensor flow, and GPU (Graphic Processing Unit) is employed for processing unit. However, if software-based method employing GPU is used for AI applications, there is a problem that we can not change the internal circuit of processing unit. In this method, if high-level jobs are required for AI system, we need high-performance GPU, therefore, we have to change GPU or graphic card to perform the jobs. In this work, we developed a CNN-based FPGA (Field Programmable Gate Array) chip to solve this problem.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.2
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• pp.155-168
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• 2023

Health geography has gained importance due to healthy smart cities, regions, and the integration of geo-internet and blockchain technologies. This study explores the intersection of geography and health, focusing on specific health challenges faced by individuals and groups. Using observational and descriptive methods, the study takes a regional approach to illuminate the socio-economic factors that are critical to addressing global health challenges. Drawing on academic literature and practical research, a concise case study of health challenges in Uzbekistan is presented, offering valuable insights. The analysis of data from informative articles and UN publications highlights the interdisciplinary nature of health geography and its practical applicability for researchers and policymakers. The findings underscore the important role of geography and health sciences in addressing region-specific diseases while highlighting the importance of spatial analysis in understanding environmental hazards and health impacts, including disease outbreaks.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.1-7
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• 2023

The advent of deep learning technologies has led to the development of various medical applications, making healthcare services more convenient and effective. Among these applications, heart rate estimation is considered a vital method for assessing an individual's health. Traditional methods, such as photoplethysmography through smart watches, have been widely used but are invasive and require additional hardware. Recent advancements allow for contactless heart rate estimation through facial image analysis, providing a more hygienic and convenient approach. In this paper, we propose a lightweight methodology capable of accurately estimating heart rate in mobile environments, using a specialized 2-channel network structure based on 2D convolution. Our method considers both subtle facial movements and color changes resulting from blood flow and muscle contractions. The approach comprises two major components: an Encoder for analyzing image features and a regression layer for evaluating Blood Volume Pulse. By incorporating both features simultaneously our methodology delivers more accurate results even in computing environments with limited resources. The proposed approach is expected to offer a more efficient way to monitor heart rate without invasive technology, particularly well-suited for mobile devices.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.5
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• pp.367-374
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• 2023

As the Fourth Industrial Revolution accelerating, countries worldwide are developing technologies to digitize and automate various industrial sectors. Building smart factories not only reduces costs through improved process productivity but also allows for preemptive identification and removal of risk factors through the practice of Health, Safety, and Environment (HSE) management, thereby reducing industrial accident risks. In this study, we visualized pressure, temperature, power, and wind speed data measured in real-time via a monitoring GUI, enabling field managers and workers to easily access related information. Through the work environment monitoring system developed in this study, it is possible to conduct economic analysis on per-unit basis, based on the digitization of production management elements and the tracking of required resources. By implementing HSE in shipyards, potential risk factors can be improved, and gas and electrical leaks can be identified, which are expected to reduce production costs.