• Korean Journal of Remote Sensing
• /
• v.38 no.5_1
• /
• pp.647-660
• /
• 2022

To prepare an atmospheric correction model suitable for CAS500-4 (Compact Advanced Satellite 500-4), this letter examined an atmospheric correction experiment using Sentinel-2 images having similar spectral characteristics to CAS500-4. Studies to compare the atmospheric correction results depending on different Aerosol Optical Depth (AOD) data are rarely found. We conducted a comparison of Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), Sen2Cor, and Second Simulation of the Satellite Signal in the Solar Spectrum - Vector (6SV) version 1.1 and 2.1, using Geo-Kompsat 2A (GK2A) Advanced Meteorological Imager (AMI) and Aerosol Robotic Network (AERONET) AOD data. In this experiment, 6SV2.1 seemed more stable than others when considering the correlation matrices and the output images for each band and Normalized Difference Vegetation Index (NDVI).

• Korean Journal of Head & Neck Oncology
• /
• v.37 no.2
• /
• pp.43-50
• /
• 2021

Background/Objectives: Shoulder function is an important aspect of health related quality of life (QOL). Neck dissection impairment index (NDII) is a simple shoulder-specific questionnaire. This study aimed to evaluate the association between QOL and NDII in patients who underwent neck dissection to validate the Korean version of NDII. Materials & Methods: This study enrolled 74 patients with head and neck cancer who underwent neck dissection from December 2013 to April 2014. Patients completed questionnaires on QOL including the European Organization of Research and Treatment of Cancer 30-item Core QOL questionnaire (EORTC QLQ-C30) and NDII which was translated into Korean. Validity was evaluated by calculating the Pearson correlation coefficient between NDII and EORTC QLQ-C30. Results: We compared preoperative, postoperative within a week, 1st and 3rd months NDII scores. The total NDII scores were 14.7, 47.4, 33.7 and 34.3 each. Clinical variables including gender, site of primary tumor, performing revision neck dissection, radiotherapy and flap reconstruction were not significantly associated with NDII. However NDII mean score of patients who underwent unilateral neck dissection over 3 levels is most increased after operation. During all periods NDII scores were significantly associated with functioning score. Although other scores are lower correlation than function scores, global health status scores and symptom scores are also correlation with NDII. Conclusion: NDII was valid instrument and can be used not only in the clinical practice to assess shoulder dysfunction but also in the simple instrument to evaluate global QOL in Korea patients with having neck dissection.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.9
• /
• pp.1266-1271
• /
• 2022

Cats have strong wildness so they have a characteristic of hiding diseases well. The disease may have already worsened when the guardian finds out that the cat has a disease. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia, polyuria, and frequent urination more quickly. In this paper, 1) Efficient version of DeepLabCut for pose estimation, 2) YOLO v4 for object detection, 3) LSTM is used for behavior prediction, and 4) BoT-SORT is used for object tracking running on an artificial intelligence device. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the server system.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.5
• /
• pp.161-169
• /
• 2022

The purpose of this study performed to confirm the effect of caffeine intake and stress on sleep quality of college students. Research respondents and data collection were conducted on 269 college students through Google questionnaires from February 14 to March 13, 2022, and the research design is a descriptive survey study. Statistical analysis was performed using the SPSS 27.0 version as t-test and one way ANOVA. As a result of the study, it was found that most college students consume more caffeine than the average daily caffeine intake of Korean adults, although it is far below the recommended daily caffeine intake of Korean adults. The quality of sleep of college students is stress (r=.32, p=<).001) and caffeine intake (r=.204, p=.001). It was found that there was a positive correlation. Factors affecting sleep quality are body mass index (β=.1.19, p<.001) Stress (β=.3.37, p<.001), smoking (β=-.18, p=.001), caffeine intake (β=.15, p=.005) It was in order, and the explanatory power of the model was 24.8%.

• Journal of Internet Computing and Services
• /
• v.24 no.1
• /
• pp.71-86
• /
• 2023

The purpose of this exploratory study is to compare the differences in public perceptual characteristics of Korean and Chinese societies regarding the metaverse using big data analysis. Due to the environmental impact of the COVID-19 pandemic, technological progress, and the expansion of new consumer bases such as generation Z and Alpha, the world's interest in the metaverse is drawing attention, and related academic studies have been also in full swing from 2021. In particular, Korea and China have emerged as major leading countries in the metaverse industry. It is a timely research question to discover the difference in social awareness using big data accumulated in both countries at a time when the amount of mentions on the metaverse has skyrocketed. The analysis technique identifies the importance of key words by analyzing word frequency, N-gram, and TF-IDF of clean data through text mining analysis, and analyzes the density and centrality of semantic networks to determine the strength of connection between words and their semantic relevance. Python 3.9 Anaconda data science platform 3 and Textom 6 versions were used, and UCINET 6.759 analysis and visualization were performed for semantic network analysis and structural CONCOR analysis. As a result, four blocks, each of which are similar word groups, were driven. These blocks represent different perspectives that reflect the types of social perceptions of the metaverse in both countries. Studies on the metaverse are increasing, but studies on comparative research approaches between countries from a cross-cultural aspect have not yet been conducted. At this point, as a preceding study, this study will be able to provide theoretical grounds and meaningful insights to future studies.

• Journal of Nutrition and Health
• /
• v.56 no.4
• /
• pp.391-403
• /
• 2023

Purpose: This study evaluated the validity of a physical activity classification table (PACT) based on total energy expenditure (TEE) and physical activity level (PAL) measured using the doubly labeled water (DLW) method in Korean adults and the elderly. Methods: A total of 141 (male 70, female 71) adults and elderly were included. The reference standards TEE_DLW, PAL_DLW were measured over a 14-day period using DLW. A 24-hour physical activity diary was kept for three days (two days during the week and one day on the weekend). PAL_PACT was calculated by classifying the activity type and intensity using the PACT. PAL_PACT was multiplied by resting energy expenditure measured by indirect calorimetry to estimate TEE_PACT. Results: The mean age of the study participants was 50.5 ± 18.8 years, and the mean body mass index was 23.4 ± 3.3 kg/m². A comparison of TEE_DLW and TEE_PACT by sex and age showed no significant differences. The bias, the difference between TEE_DLW and TEE_PACT, was male 17.3 kcal/day and female -4.5 kcal/day. The percentage of accurate predictions (values within ± 10% of the TEE_DLW) of TEE_PACT was 58.6% in males and 54.9% in females, with the highest prediction values in the age group 40-64 years (70.9%) in males and over 65 years (73.9%) in females. The spearman correlation coefficient (r) between TEE_PACT and TEE_DLW was 0.769, indicating a significant positive correlation (p < 0.001). Conclusion: In this study, the use of a new PACT for calculating TEE and PAL was evaluated as valid. A web version of the software program and a smartphone application need to be developed using PACT to make it easier to apply for research purposes.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.4
• /
• pp.41-46
• /
• 2023

Human urine is a process of excreting waste products in the blood, and it is easy to collect and contains various substances. Urinalysis is used to check for diseases, health conditions, and urinary tract infections. There are three methods of urinalysis: physical property test, chemical test, and microscopic test, and chemical test results can be easily confirmed using urine test strips. A variety of items can be tested on the urine test strip, through which various diseases can be identified. Recently, with the spread of smart phones, research on reading urine test strips using smart phones is being conducted. There is a method of detecting and reading the color change of a urine test strip using a smartphone. This method uses the RGB values and the color difference formula to discriminate. However, there is a problem in that accuracy is lowered due to various environmental factors. This paper applies a deep learning model to solve this problem. In particular, color discrimination of a urine test strip is improved in a smartphone using a lightweight CNN (Convolutional Neural Networks) model. CNN is a useful model for image recognition and pattern finding, and a lightweight version is also available. Through this, it is possible to operate a deep learning model on a smartphone and extract accurate urine test results. Urine test strips were taken in various environments to prepare deep learning model training images, and a urine test service application was designed using MobileNet V3.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.165-167
• /
• 2022

The proportion of cat cats among companion animals has been increasing at an average annual rate of 25.4% since 2012. Cats have strong wildness compared to dogs, so they have a characteristic of hiding diseases well. Therefore, when the guardian finds out that the cat has a disease, the disease may have already worsened. Symptoms such as anorexia (eating avoidance), vomiting, diarrhea, polydipsia, and polyuria in cats are some of the symptoms that appear in cat diseases such as diabetes, hyperthyroidism, renal failure, and panleukopenia. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia (drinking a lot of water), polyuria (a large amount of urine), and frequent urination (urinating frequently) more quickly. In this paper, 1) Efficient version of DeepLabCut for posture prediction running on an artificial intelligence server, 2) yolov4 for object detection, and 3) LSTM are used for behavior prediction. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the main server system.

• Phonetics and Speech Sciences
• /
• v.15 no.1
• /
• pp.55-64
• /
• 2023

This study investigated the factors influencing the perceptions that military officers can harbor regarding persons who stutter in terms of how well they can adapt to the army. In total, 89 participants were randomly assigned to each of the three different conditions ("fluent speech"=23, "mildly stuttered speech"=34, and "severely stuttered speech"=32). Subsequently, the participants were asked to listen and rate each sample in terms of "the speaker's communicative functioning (i.e., speech fluency, intelligibility, naturalness, speech rate), personal traits (i.e., likeability, anxiety level, intellectual level, and sociability), and the perceived degree of the adaptability to the army." The results showed that significant differences were found between "fluent speech" and "severely stuttered speech" in the perceived communicative functionings and the perceived adaptability to the army. Moreover, there were significant differences in the same variables between "mildly stuttered speech" and "severely stuttered speech." However, there were no significant differences between "mildly stuttered speech" and "fluent speech." Following the conducting of the Pearson correlation test, strong correlations were also found between the perceived communicative functionings, in particular "speech fluency," and the perceived adaptability to the army. Those results can be employed to argue that the communicative functionings can serve as factors which influence the perceptions of persons who stutter in terms of how well they can adapt to the army. Further discussion has taken place regarding the relationship between the perceived communicative functionings and the perceived adaptability to the army.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.2
• /
• pp.193-200
• /
• 2023

Cryptanalysis can be performed by various techniques such as known plaintext attack, differential attack, side-channel analysis, and the like. Recently, many studies have been conducted on cryptanalysis using deep learning. A known-plaintext attack is a technique that uses a known plaintext and ciphertext pair to find a key. In this paper, we use deep learning technology to perform a known-plaintext attack against S-PRESENT, a reduced version of the lightweight block cipher PRESENT. This paper is significant in that it is the first known-plaintext attack based on deep learning performed on a reduced lightweight block cipher. For cryptanalysis, MLP (Multi-Layer Perceptron) and 1D and 2D CNN(Convolutional Neural Network) models are used and optimized, and the performance of the three models is compared. It showed the highest performance in 2D convolutional neural networks, but it was possible to attack only up to some key spaces. From this, it can be seen that the known-plaintext attack through the MLP model and the convolutional neural network is limited in attackable key bits.