• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.441-446
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• 2023

Electrical and optical characteristics of the GaN-based light-emitting diode (LED) with the improved multi-quantum well (MQW) structure have been studied for light source in bio-sensing systems. Novel GaN/In_0.1GaN/In_0.2GaN/In_0.1GaN/GaN and Al_0.1GaN/GaN/In_0.2GaN/GaN/Al_0.1GaN (MQW) structures were suggested, and their radiative recombination rate, light output power, electroluminescence, and external quantum efficiency were compared with those of the conventional GaN/In_0.2GaN/GaN MQW structure using device simulation. The LED with the GaN/In_0.1GaN/In_0.2GaN/In_0.1GaN/GaN MQW structure showed an excellent recombination rate of 5.57 × 10²⁸ cm^-3·s^-1 that was more than one order improvement over that of the conventional LED. In addition, the efficiency droop was relieved by the suggested stepped MQW structure.

• Journal of Aerospace System Engineering
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• v.17 no.5
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• pp.42-57
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• 2023

In this paper, to increase the research capability of flight missions and maintenance in operating military aircraft, we studied the requirements for additional mounting of flight video and data recorders and safety verification methods. The verification process of the recorder equipment itself, structural safety in the aircraft system, power and electrical safety, electromagnetic compatibility, and impact of airworthiness are described in accordance with military standards and operating environment requirements. In addition, through ground/flight tests, the results of functional operation suitable for the influence and demand of interference between the flight video and data recorder and other systems are also presented.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.569-575
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• 2021

Deep learning shows differences in prediction performance depending on data quality and model. This study uses various input data and multiple deep learning models to build an optimal deep learning model for predicting solar radiation, which has the most influence on power generation prediction. did. As the input data, the weather data of the Korea Meteorological Administration and the clairvoyant meteorological image were used by segmenting the image of the Korea Meteorological Agency. , comparative evaluation, and predicting solar radiation by constructing multiple deep learning models connecting the models with the best error rate in each model. As an experimental result, the RMSE of model A, which is a multiple deep learning model, was 0.0637, the RMSE of model B was 0.07062, and the RMSE of model C was 0.06052, so the error rate of model A and model C was better than that of a single model. In this study, the model that connected two or more models through experiments showed improved prediction rates and stable learning results.

• 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.

• Journal of the Korean Society of Safety
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• v.38 no.5
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• pp.1-7
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• 2023

This study analyzes the operational characteristics of 311 aged and non-aged residual current circuit breakers (RCCBs) in low-voltage consumer contexts. It investigates the influence of external temperature and harmonics based on the rated current multiples. To simulate temperature variations, a convectional oven was used around the circuit breakers. Additionally, the generation of harmonic reference signals and data measurement for overcurrent experiments were conducted using NI SCXI, myDAQ, and LabVIEW. An observation revealed that as the ambient temperature increased, the operating time of RCCBs decreased in the time delay region. This was attributed to the faster response or bending of the bimetal, which is the tripping element. However, aged RCCBs encountered challenges with tripping outside the protective curve. The operating time of the circuit breakers exhibited an acceleration influenced by the order and content of harmonic currents, potentially leading to malfunctions. Aged RCCBs demonstrated faster operating times than their non-aged counterparts. However, the difference in operating time varied based on the manufacturer's and operating environment of the RCCBs. Frequent malfunctions of RCCBs can result in power outages. In cases where these circuit breakers fail to operate, they can lead to secondary damages, including electrical fires and shocks. Consequently, it is imperative to consider the operating environment of RCCBs and provide appropriate replacement cycles to mitigate these risks.

• Journal of Advanced Technology Convergence
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• v.3 no.2
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• pp.9-15
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• 2024

Due to the high inflation rate of dining out, along with changes in group meals or cafeteria services, office workers are increasingly using workplace cafeterias to reduce their meal expenses even slightly. With the recent development of ICT technology, various fields are realizing that not only are smartphones becoming more popular, but they are also becoming an integration of the latest technologies. In this paper, we analyze the current status of cafeterias with a large number of customers and propose ways to improve problems or difficulties. Since most people always carry their smartphones for urgent communication or work tasks, we aim to develop a cafeteria management system that utilizes the NFC function of smartphones. By presenting the process from customer entry to menu selection, it will enable more efficient use of the cafeteria.

• Journal of IKEEE
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• v.28 no.1
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• pp.116-122
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• 2024

AMBA AHB-Lite bus is widely used in on-chip bus protocol for low-power and cost-effective SoC. However, it lacks built-in error detection and correction for end-to-end data integrity. This can lead to data corruption and system instability, particularly in harsh environments like automotive applications. To mitigate this problem, this paper proposes the application of SEC-DED (Single Error Correction-Double Error Detection) to AMBA AHB-Lite bus. It aims not only to detect errors in real-time but also to correct them, thereby enhancing end-to-end data integrity. Simulation results demonstrate real-time error detection and correction when errors occur, which bolsters end-to-end data integrity of automotive on-chip bus.

• Journal of IKEEE
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• v.28 no.1
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• pp.33-37
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• 2024

In this paper, we report the design and the measurement of a X-band low noise amplifier (LNA) monolithic microwave integrated circuit (MMIC) using a 0.25 ㎛ gate length microstrip GaN-on-SiC high electron mobility transistor (HEMT) technology. The developed X-band GaN-based LNA MMIC achieves small signal gain of 22.75 dB ~ 25.14 dB and noise figure of 1.84 dB ~ 1.94 dB in the desired band of 9 GHz to 10 GHz. Input and output return loss values are -11.36 dB ~ -24.49 dB and -11.11 dB ~ -17.68 dB, respectively. The LNA MMIC can withstand 40 dBm (10 W) input power without performance degradation. The chip dimensions are 3.67 mm × 1.15 mm. The developed GaN-based LNA MMIC is applicable to various X-band applications.

• Journal of IKEEE
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• v.28 no.1
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• pp.53-64
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• 2024

With the advancement of NLP(Natural Language Processing) models, conversational AI such as ChatGPT is becoming increasingly popular. To enhance processing speed and reduce power consumption, it is important to implement the Transformer algorithm, which forms the basis of the latest natural language processing models, in hardware. In particular, the multi-head attention and feed-forward network, which analyze the relationships between different words in a sentence through matrix multiplication, are the most computationally intensive core algorithms in the Transformer. In this paper, we propose a new variable systolic array based on the number of input words to enhance matrix multiplication speed. Quantization maintains Transformer accuracy, boosting memory efficiency and speed. For evaluation purposes, this paper verifies the clock cycles required in multi-head attention and feed-forward network and compares the performance with other multipliers.

• Korean Journal of Materials Research
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• v.34 no.3
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• pp.152-162
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• 2024

In this study, we introduce a novel TiN/Ag embedded TiO₂/FTO resistive random-access memory (RRAM) device. This distinctive device was fabricated using an environmentally sustainable, solution-based thin film manufacturing process. Utilizing the peroxo titanium complex (PTC) method, we successfully incorporated Ag precursors into the device architecture, markedly enhancing its performance. This innovative approach effectively mitigates the random filament formation typically observed in RRAM devices, and leverages the seed effect to guide filament growth. As a result, the device demonstrates switching behavior at substantially reduced voltage and current levels, heralding a new era of low-power RRAM operation. The changes occurring within the insulator depending on Ag contents were confirmed by X-ray photoelectron spectroscopy (XPS) analysis. Additionally, we confirmed the correlation between Ag and oxygen vacancies (V_o). The current-voltage (I-V) curves obtained suggest that as the Ag content increases there is a change in the operating mechanism, from the space charge limited conduction (SCLC) model to ionic conduction mechanism. We propose a new filament model based on changes in filament configuration and the change in conduction mechanisms. Further, we propose a novel filament model that encapsulates this shift in conduction behavior. This model illustrates how introducing Ag alters the filament configuration within the device, leading to a more efficient and controlled resistive switching process.