• Korean Journal of Materials Research
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• v.33 no.11
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• pp.465-474
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• 2023

The effects of La³⁺ substitution for Sr²⁺-site on the crystal structure and the dielectric properties of (Ba_0.7Sr_0.3-3x/2La_x) (Ti_0.9Zr_0.1)O₃ (BSLTZ) (0.005 ≤ x ≤ 0.02) ceramics were investigated. The structural characteristics of the BSLTZ ceramics were quantitatively evaluated using the Rietveld refinement method from X-ray diffraction (XRD) data. For the specimens sintered at 1,550 ℃ for 6 h, a single phase with a perovskite structure and homogeneous microstructure were observed for the entire range of compositions. With increasing La³⁺ substitution (x), the unit cell volume decreased because the ionic size of La³⁺ (1.36 Å) ions is smaller than that of Sr²⁺ (1.44 Å) ions. With increasing La³⁺ substitution (x), the tetragonal phase fraction increased due to the A-site cation size mismatch effect. Dielectric constant (ε_r) increased with the La³⁺ substitution (x) due to the increase in tetragonality (c/a) and the average B-site bond valence of the ABO₃ perovskite. The BSLTZ ceramics showed a higher dielectric loss due to the smaller grain size than that of (Ba_0.7Sr_0.3)(Ti_0.9Zr_0.1)O₃ ceramics. BSLTZ (x = 0.02) ceramics met the X7R specification proposed by the Electronic Industries Association (EIA).

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.671-679
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• 2023

This study aims to establish an evaluation model by quantifying the evaluation index as a follow-up study to the development of evaluation index for work-study parallel learning companies. An evaluation model was established by verifying the 2nd level components based on the quantitative factors of the learning company, the qualitative factors, the competency factors of the person in charge, and the competency factors of the learning workers, which are the highest-level components derived from previous study. For the evaluation of a learning company, an AHP survey was conducted with experts in charge of the company consulting to derive important factors that determine the quality of on-site education and training, and the evaluation model of the learning company was completed and grouped by calculating the weight between evaluation items proceeded. Work-study parallel program was promoted as a key policy to resolve the mismatch between industrial sites and school education and realize a competency-centered society, and as of December 2022, 16,664 companies participated in the training. Learning companies play a very important role as education and training supply organizations that conduct field training. It is expected that the support and consulting plan for each level of learning companies according to the evaluation model presented in this study will be used as basic data to improve the quality of work-study parallel program.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1321-1330
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• 2023

This study attempts to address the problem of 3D pose estimation for multiple human objects through a single image generated during the character development process that can be used in augmented reality. In the existing top-down method, all objects in the image are first detected, and then each is reconstructed independently. The problem is that inconsistent results may occur due to overlap or depth order mismatch between the reconstructed objects. The goal of this study is to solve these problems and develop a single network that provides consistent 3D reconstruction of all humans in a scene. Integrating a human body model based on the SMPL parametric system into a top-down framework became an important choice. Through this, two types of collision loss based on distance field and loss that considers depth order were introduced. The first loss prevents overlap between reconstructed people, and the second loss adjusts the depth ordering of people to render occlusion inference and annotated instance segmentation consistently. This method allows depth information to be provided to the network without explicit 3D annotation of the image. Experimental results show that this study's methodology performs better than existing methods on standard 3D pose benchmarks, and the proposed losses enable more consistent reconstruction from natural images.

• Information Systems Review
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• v.23 no.3
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• pp.51-75
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• 2021

Global e-commerce websites offer personalized recommendation services to gain sustainable competitiveness. Existing studies have offered personalized recommendation services using quantitative preferences such as ratings. However, offering personalized recommendation services using only quantitative data has raised the problem of decreasing recommendation performance. For example, a user gave a five-star rating but wrote a review that the user was unsatisfied with hotel service and cleanliness. In such cases, has problems where quantitative and qualitative preferences are inconsistent. Recently, a growing number of studies have considered review data simultaneously to improve the limitations of existing personalized recommendation service studies. Therefore, in this study, we identify review and rating mismatches and build a new user profile to offer personalized recommendation services. To this end, we use deep learning algorithms such as CNN, LSTM, CNN + LSTM, which have been widely used in sentiment analysis studies. And extract sentiment features from reviews and compare with quantitative preferences. To evaluate the performance of the proposed methodology in this study, we collect user preference information using real-world hotel data from the world's largest travel platform TripAdvisor. Experiments show that the proposed methodology in this study outperforms the existing other methodologies, using only existing quantitative preferences.

• Pediatric Infection and Vaccine
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• v.31 no.1
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• pp.46-54
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• 2024

Purpose: This study aimed to identify the pathogens of bloodstream infection in children with underlying hemato-oncologic diseases, analyze susceptibility patterns, compare temporal trends with those of previous studies, and assess empirical antimicrobial therapy. Methods: Retrospective review study of children bacteremia in hemato-oncologic diseases was conducted at Seoul National University Bundang Hospital from January 2013 to July 2023. Results: Overall, 98 episodes of bacteremia were observed in 74 patients. Among pathogens isolated, 57.1% (n=56) were Gram-positive bacteria, 38.8% (n=38) were Gram-negative bacteria, and 4.1% (n=4) were Candida spp. The most common Gram-positive bacteria were coagulase-negative staphylococci (n=21, 21.4%) and Staphylococcus aureus, (n=14, 14.3%) whereas the most common Gram-negative bacteria were Klebsiella pneumoniae (n=16, 16.3%) and Escherichia coli (n=10, 10.2%). The susceptibility of Gram-positive bacteria to penicillin, oxacillin, and vancomycin was 11.5%, 32.7%, and 94.2%, respectively and the susceptibility of Gram-negative bacteria to cefotaxime, piperacillin/tazobactam, imipenem, gentamicin, and amikacin was 68.6%, 80%, 97.1%, 82.9%, and 91.4%, respectively. Methicillin-resistant S. aureus was detected in 1 strain and among Gram-negative strains, extended spectrum β-lactamase accounted for 28.9% (12/38). When analyzing the antibiotic susceptibility and empirical antibiotics, the mismatch rate was 25.5% (n=25). The mortality rate of children within 30 days of bacteremia was 7.1% (n=7). Conclusions: Empirical antibiotic therapy for bacteremia in children with hemato-oncologic diseases should be based on the local antibiogram in each institution and continuous monitoring is necessary.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.284-290
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• 2024

Speech emotion recognition (SER) is a technique that is used to analyze the speaker's voice patterns, including vibration, intensity, and tone, to determine their emotional state. There has been an increase in interest in artificial intelligence (AI) techniques, which are now widely used in medicine, education, industry, and the military. Nevertheless, existing researchers have attained impressive results by utilizing acted-out speech from skilled actors in a controlled environment for various scenarios. In particular, there is a mismatch between acted and spontaneous speech since acted speech includes more explicit emotional expressions than spontaneous speech. For this reason, spontaneous speech-emotion recognition remains a challenging task. This paper aims to conduct emotion recognition and improve performance using spontaneous speech data. To this end, we implement deep learning-based speech emotion recognition using the VGG (Visual Geometry Group) after converting 1-dimensional audio signals into a 2-dimensional spectrogram image. The experimental evaluations are performed on the Korean spontaneous emotional speech database from AI-Hub, consisting of 7 emotions, i.e., joy, love, anger, fear, sadness, surprise, and neutral. As a result, we achieved an average accuracy of 83.5% and 73.0% for adults and young people using a time-frequency 2-dimension spectrogram, respectively. In conclusion, our findings demonstrated that the suggested framework outperformed current state-of-the-art techniques for spontaneous speech and showed a promising performance despite the difficulty in quantifying spontaneous speech emotional expression.

• The Journal of the Acoustical Society of Korea
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• v.26 no.4
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• pp.159-165
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• 2007

In this paper, we propose a new pre-selection of candidate units that is suitable for the unit selection based Japanese TTS system. General pre-selection method performed by calculating a context-dependent cost within IP (Intonation Phrase). Different from other languages, however. Japanese has an accent represented as the height of a relative pitch, and several words form a single accentual phrase. Also. the prosody in Japanese changes in accentual phrase units. By reflecting such prosodic change in pre-selection. the qualify of synthesized speech can be improved. Furthermore, by calculating a context-dependent cost within accentual phrase, synthesis speed can be improved than calculating within intonation phrase. The proposed method defines AP. analyzes AP in context and performs pre-selection using accentual phrase matching which calculates CCL (connected context length) of the Phoneme's candidates that should be synthesized in each accentual phrase. The baseline system used in the proposed method is VoiceText, which is a synthesizer of Voiceware. Evaluations were made on perceptual error (intonation error, concatenation mismatch error) and synthesis time. Experimental result showed that the proposed method improved the qualify of synthesized speech. as well as shortened the synthesis time.

• Korean Journal of Radiology
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• v.24 no.8
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• pp.772-783
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• 2023

Objective: Imaging-based survival stratification of patients with gliomas is important for their management, and the 2021 WHO classification system must be clinically tested. The aim of this study was to compare integrative imaging- and pathology-based methods for survival stratification of patients with diffuse glioma. Materials and Methods: This study included diffuse glioma cases from The Cancer Genome Atlas (training set: 141 patients) and Asan Medical Center (validation set: 131 patients). Two neuroradiologists analyzed presurgical CT and MRI to assign gliomas to five imaging-based risk subgroups (1 to 5) according to well-known imaging phenotypes (e.g., T2/FLAIR mismatch) and recategorized them into three imaging-based risk groups, according to the 2021 WHO classification: group 1 (corresponding to risk subgroup 1, indicating oligodendroglioma, isocitrate dehydrogenase [IDH]-mutant, and 1p19q-codeleted), group 2 (risk subgroups 2 and 3, indicating astrocytoma, IDH-mutant), and group 3 (risk subgroups 4 and 5, indicating glioblastoma, IDHwt). The progression-free survival (PFS) and overall survival (OS) were estimated for each imaging risk group, subgroup, and pathological diagnosis. Time-dependent area-under-the receiver operating characteristic analysis (AUC) was used to compare the performance between imaging-based and pathology-based survival model. Results: Both OS and PFS were stratified according to the five imaging-based risk subgroups (P < 0.001) and three imaging-based risk groups (P < 0.001). The three imaging-based groups showed high performance in predicting PFS at one-year (AUC, 0.787) and five-years (AUC, 0.823), which was similar to that of the pathology-based prediction of PFS (AUC of 0.785 and 0.837). Combined with clinical predictors, the performance of the imaging-based survival model for 1- and 3-year PFS (AUC 0.813 and 0.921) was similar to that of the pathology-based survival model (AUC 0.839 and 0.889). Conclusion: Imaging-based survival stratification according to the 2021 WHO classification demonstrated a performance similar to that of pathology-based survival stratification, especially in predicting PFS.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.135-140
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• 2024

It is said that PV power generation systems have a long lifespan compared to other renewable energy sources and require little maintenance. However, there are cases where the performance expected during initial design is not achieved due to shading, temperature rise, mismatch, contamination/deterioration of PV modules, failure of inverter, leakage current, and arc generation. Therefore, in order to solve the problems of these systems, the power generation amount and operation status are investigated qualitatively, or the performance is comparatively analyzed based on the performance ratio (PR), which is the performance index of the solar power generation system. However, because it includes large losses, it is difficult to accurately determine whether there are any abnormalities such as performance degradation, failure, or defects in the PV power generation system using only the performance coefficient. In this paper, we studied a status diagnosis algorithm for shading, inverter failure, leakage, and arcing of PV modules to optimize the power generation of PV power generation systems according to changes in the surrounding environment. In addition, using the studied algorithm, we examined the results of an empirical test on condition diagnosis for each area and the resulting optimized operation of power generation.

• Journal of the Korean Vacuum Society
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• v.22 no.6
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• pp.313-320
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• 2013

The $AlAs_xSb_{1-x}$ step-graded buffer (SGB) layer was grown on the Silicon (Si) substrate to overcome lattice mismatch between Si substrate and $Al_{0.3}Ga_{0.7}As$/GaAs multiple quantum wells (MQWs). The value of root-mean-square (RMS) surface roughness for 5 nm-thick GaAs grown on $AlAs_xSb_{1-x}$ step-graded buffer layer was ~1.7 nm. $Al_{0.3}Ga_{0.7}As$/GaAs MQWs with AlAs/GaAs short period superlattice (SPS) were formed on the $AlAs_xSb_{1-x}$/Si substrate. Photoluminescence (PL) peak at 10 K for the $Al_{0.3}Ga_{0.7}As$/GaAs MQW structure showed relatively low intensity at ~813 nm. The RMS surface roughness of the $Al_{0.3}Ga_{0.7}As$/GaAs MQW structure was ~42.9 nm. The crystal defects were observed on the cross-sectional transmission electron microscope (TEM) images of the $Al_{0.3}Ga_{0.7}As$/GaAs MQW structure. The decrease of PL intensity and increase of RMS surface roughness would be due to the formation of the crystal defects.