• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1477-1485
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• 2021

Recently, super-resolution has been intensively studied only on upscaling models with integer magnification. However, the need to expand arbitrary magnification is emerging in representative application fields of actual super-resolution, such as object recognition and display image quality improvement. In this paper, we propose a model that can support arbitrary magnification by using the weights of the existing integer magnification model. This model converts super-resolution results into the DCT spectral domain to expand the space for arbitrary magnification. To reduce the loss of high-frequency information in the image caused by the expansion by the DCT spectral domain, we propose a high-frequency attention network for arbitrary magnification so that this model can properly restore high-frequency spectral information. To recover high-frequency information properly, the proposed network utilizes channel attention layers. This layer can learn correlations between RGB channels, and it can deepen the model through residual structures.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.175-186
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• 2023

This study was conducted to explore the necessary conditions and support for stable operation of an expanded AI curriculum in education. A high school that has implemented an AI curriculum since 2020 was targeted, and students and teachers were surveyed on their perceptions of the AI curriculum, implementation and support strategies. The survey items were categorized into 1) experience with AI education, 2) implementation direction of AI education, and 3) expected effects through AI education, and the results were derived focusing on frequency analysis to identify trends. The analysis resulted in three implications. First, it was suggested that the activation of AI education. Second, the need to develop a hands-on AI curriculum and incorporate AI throughout the entire curriculum was highlighted. Third, it was emphasized that efforts to enhance the capabilities of teachers to implement AI teaching and learning, along with the expansion of physical infrastructure for hands-on education, are necessary.

• ETRI Journal
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• v.42 no.4
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• pp.468-479
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• 2020

The proposed AI processor architecture has high throughput for accelerating the neural network and reduces the external memory bandwidth required for processing the neural network. For achieving high throughput, the proposed super thread core (STC) includes 128 × 128 nano cores operating at the clock frequency of 1.2 GHz. The function-safe architecture is proposed for a fault-tolerance system such as an electronics system for autonomous cars. The general-purpose processor (GPP) core is integrated with STC for controlling the STC and processing the AI algorithm. It has a self-recovering cache and dynamic lockstep function. The function-safe design has proved the fault performance has ASIL D of ISO26262 standard fault tolerance levels. Therefore, the entire AI processor is fabricated via the 28-nm CMOS process as a prototype chip. Its peak computing performance is 40 TFLOPS at 1.2 GHz with the supply voltage of 1.1 V. The measured energy efficiency is 1.3 TOPS/W. A GPP for control with a function-safe design can have ISO26262 ASIL-D with the single-point fault-tolerance rate of 99.64%.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.244-247
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• 2022

In this paper, the performance of the decoding schemes using linear MMSE filters in the frequency and time domains and the reinforcement Gauss-Seidel algorithm for the orthogonal time frequency space (OTFS) system that can improve robustness under high-speed mobile environments are compared. The reinforcement Gauss-Seidel algorithm can improve the bit error rate performance by suppressing the noise enhancement. The simulation results show that the performance of the decoding scheme using the linear MMSE filter in the frequency domain is severely degraded due to the effect of Doppler shift as the mobile speed increases. In addition, the decoding scheme using the reinforcement Gauss-Seidel algorithm under the channel environment with 120 km/h and 500 km/h speeds outperforms the decoding schemes using linear MMSE filters in the frequency and time domains.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.4
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• pp.39-50
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• 2011

In this paper, we presents a CDR circuit for $2^{nd}$-generation AiPi+, one of the Intra-panel Interface. The speed of the proposed clock and data recovery is increased to 1.25 Gbps compared with that of AiPi+. The DLL-based CDR architecture is used to generate the multi-phase clocks. We propose the simple scheme for frequency detector (FD) to mitigate the harmonic-locking and reduce the complexity. In addition, the duty cycle corrector that limits the maximum pulse width is used to avoid the problem of missing clock edges due to the mismatch between rising and falling time of VCDL's delay cells. The proposed CDR is implemented in 0.18 um technology with the supply voltage of 1.8 V. The active die area is $660\;{\mu}m\;{\times}\;250\;{\mu}m$, and supply voltage is 1.8 V. Peak-to-Peak jitter is less than 15 ps and the power consumption of the CDR except input buffer, equalizer, and de-serializer is 5.94 mW.

• Journal of dental hygiene science
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• v.24 no.3
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• pp.171-180
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• 2024

Background: The Fourth Industrial Revolution highlights the importance of artificial intelligence (AI) and digital literacy in dental hygiene education. However, research on students' attitudes toward AI and their digital literacy levels is limited. Therefore, this study investigated the attitudes of dental hygiene students toward AI and digital literacy levels. Methods: In total, 167 dental hygiene students in Baekseok University participated in the study and provided informed consent. The survey tool included general characteristics, smartphone usage patterns, attitudes toward AI, and digital literacy levels. Attitudes toward AI and digital literacy based on general characteristics and smart device usage were analyzed using t-tests and one-way ANOVA. Correlations among attitudes toward AI, digital literacy awareness, and digital literacy behaviors were analyzed using Pearson's correlation analysis. The impact of AI attitudes and digital literacy awareness on digital literacy behavior was examined using linear regression analysis. Results: Students with higher interest in their major had more positive attitudes toward AI, and those with higher smart device usage showed increased AI attitudes and digital literacy (p<0.05). Simple frequency or duration of smartphone use did not affect digital literacy, but students who perceived their smart device usage positively and believed that they used smart devices effectively in their studies exhibited higher levels of digital literacy (p<0.05). A positive attitude toward AI is associated with higher levels of digital literacy (p<0.05). Digital literacy awareness and attitudes toward AI influenced digital literacy behavior (p<0.05). Conclusion: These results suggest that the qualified utilization and application of digital devices in dental hygiene education are important. Improving the educational curriculum is necessary; as a result, digital technology can be effectively utilized, and various educational programs should be introduced to enhance digital literacy.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.4
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• pp.393-402
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• 1999

Precipitation samples were collected by the wet-only sampling method in Iksan in the northwest of Chonbuk from March 1995 to February 1997. These samples were analyzed for the concentration of ion components, in addition to pH and electrical conductivity. The annual mean pH of precipitation was 4.8 and the seasonal trend of pH was shown to be low in Fall and Winter(4.5), middle-ranged in Spring(4.7) and high in Summer(5.0). The frequency of pH below 5.6 was about 71%. The seasonal pattern of pH frequency was found to be different in each season. In the case of the pH less than 5.0, the frequency was higher in Spring, Fall and Winter than in Summer, especially higher in Fall than in other seasons. The concentrations of analysed ions showed a pronounced seasonal pattern. However, major ion species for all seasons were $NH^+_4,;Ca^{2+};and;Na^+$ among cations and $SO^{2-}_4,;Cl^-;and;NO^-_3$ among anions. The major acidifying species appeared to be $nss-SO^{2-}_4;and;NO^-_3$, and the main bases responsible for the neutralization of precipitation acidity were $nss-Ca^{2+};and;NH^+_4$. The potential acidity of precipitation, pAi, was found to be between 3.0 and 5.0 for total samples, while the measured pH was approximately between 3.9 and 7.8. The seasonal trend of pAi showed a decreasing order: Summer (4.3), Winter(4.0), Spring and Fall(3.8). During the Fall, both pAi and pH were especially very low, which indicated that during this period the potential acidity of precipitation was high but the neutralizing capacity was low. For Spring, pAi was very low but pH was slightly high. This was likely due to the large amount of $CaCO_3$ in the soil particles transported over a long range from the Chinese continent that were incorporated into the precipitation, and then neutralized the acidifying species with its high concentraton.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.137-142
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• 2022

Every year, the number of wild animals appearing in human settlements increases, resulting in increased damage to property and human life. In particular, the damage is more severe when wild animals appear on highways or farmhouses. To solve this problem, ecological pathways and guide fences are being installed on highways. In addition, in order to solve the problem in farms, horn repelling using sensors, installing a net, and repelling by smell of excrement are being used. However, these methods are expensive and their effectiveness is not high. In this paper, we used YOLO (You Only Look Once), an AI-based image analysis method, to analyze harmful animals in real time to reduce malfunctions, and high-brightness LEDs and ultrasonic frequency speakers were used as extermination devices. The speaker outputs an audible frequency that only animals can hear, increasing the efficiency to only exterminate wild animals. The proposed system is designed using a general-purpose board so that it can be installed economically, and the detection performance is higher than that of the devices using the existing sensor.

• The Research Journal of the Costume Culture
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• v.31 no.5
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• pp.651-668
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• 2023

This study aims to help companies with efficient investment and marketing strategies by empirically verifying the impact on satisfaction and purchase intention for artificial intelligence-based digital technology supported shopping assistants introduced in e-commerce. Frequency, factor, SEM, and multiple group analysises were conducted using SPSS 26.0 and Amos 26.0. As a result, first, motivated consumer innovativeness elements of AI shopping assistant were derived into a total of four categories: functional, hedonic, rational, and reliable. Second, in the order of hedonic and rational, satisfaction with the AI shopping assistant was significantly affected, and in the order of rational and functional, purchase intention was significantly affected. The satisfaction with the AI shopping assistant did not affect the purchase intention. Third, in the case of hedonic, the AI-preferred group had a more significant effect on satisfaction than the human-preferred group, and in the case of rational, there was no difference by group in purchase intention. Thus, it was found that consumers prefer AI shopping helpers for e-commerce because they can shop reasonably and are functionally convenient. Therefore, when introducing AI shopping assistants, it is essential to include content that can compare and analyze fundamental information, such as product prices, as well as search functions and payment system compatibility that facilitate shopping.

• Korean Journal of Radiology
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• v.24 no.9
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• pp.890-902
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• 2023

Objective: The clinical impact of artificial intelligence-based computer-aided detection (AI-CAD) beyond diagnostic accuracy remains uncertain. We aimed to investigate the influence of the clinical implementation of AI-CAD for chest radiograph (CR) interpretation in daily practice on the rate of referral for chest computed tomography (CT). Materials and Methods: AI-CAD was implemented in clinical practice at the Seoul National University Hospital. CRs obtained from patients who visited the pulmonology outpatient clinics before (January-December 2019) and after (January-December 2020) implementation were included in this study. After implementation, the referring pulmonologist requested CRs with or without AI-CAD analysis. We conducted multivariable logistic regression analyses to evaluate the associations between using AI-CAD and the following study outcomes: the rate of chest CT referral, defined as request and actual acquisition of chest CT within 30 days after CR acquisition, and the CT referral rates separately for subsequent positive and negative CT results. Multivariable analyses included various covariates such as patient age and sex, time of CR acquisition (before versus after AI-CAD implementation), referring pulmonologist, nature of the CR examination (baseline versus follow-up examination), and radiology reports presence at the time of the pulmonology visit. Results: A total of 28546 CRs from 14565 patients (mean age: 67 years; 7130 males) and 25888 CRs from 12929 patients (mean age: 67 years; 6435 males) before and after AI-CAD implementation were included. The use of AI-CAD was independently associated with increased chest CT referrals (odds ratio [OR], 1.33; P = 0.008) and referrals with subsequent negative chest CT results (OR, 1.46; P = 0.005). Meanwhile, referrals with positive chest CT results were not significantly associated with AI-CAD use (OR, 1.08; P = 0.647). Conclusion: The use of AI-CAD for CR interpretation in pulmonology outpatients was independently associated with an increased frequency of overall referrals for chest CT scans and referrals with subsequent negative results.