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User Experience Analysis and Management Based on Text Mining: A Smart Speaker Case (텍스트 마이닝 기반 사용자 경험 분석 및 관리: 스마트 스피커 사례)

  • Dine Yeon;Gayeon Park;Hee-Woong Kim
    • Information Systems Review
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    • v.22 no.2
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    • pp.77-99
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    • 2020
  • Smart speaker is a device that provides an interactive voice-based service that can search and use various information and contents such as music, calendar, weather, and merchandise using artificial intelligence. Since AI technology provides more sophisticated and optimized services to users by accumulating data, early smart speaker manufacturers tried to build a platform through aggressive marketing. However, the frequency of using smart speakers is less than once a month, accounting for more than one third of the total, and user satisfaction is only 49%. Accordingly, the necessity of strengthening the user experience of smart speakers has emerged in order to acquire a large number of users and to enable continuous use. Therefore, this study analyzes the user experience of the smart speaker and proposes a method for enhancing the user experience of the smart speaker. Based on the analysis results in two stages, we propose ways to enhance the user experience of smart speakers by model. The existing research on the user experience of the smart speaker was mainly conducted by survey and interview-based research, whereas this study collected the actual review data written by the user. Also, this study interpreted the analysis result based on the smart speaker user experience dimension. There is an academic significance in interpreting the text mining results by developing the smart speaker user experience dimension. Based on the results of this study, we can suggest strategies for enhancing the user experience to smart speaker manufacturers.

AutoML Machine Learning-Based for Detecting Qshing Attacks Malicious URL Classification Technology Research and Service Implementation (큐싱 공격 탐지를 위한 AutoML 머신러닝 기반 악성 URL 분류 기술 연구 및 서비스 구현)

  • Dong-Young Kim;Gi-Seong Hwang
    • Smart Media Journal
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    • v.13 no.6
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    • pp.9-15
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    • 2024
  • In recent trends, there has been an increase in 'Qshing' attacks, a hybrid form of phishing that exploits fake QR (Quick Response) codes impersonating government agencies to steal personal and financial information. Particularly, this attack method is characterized by its stealthiness, as victims can be redirected to phishing pages or led to download malicious software simply by scanning a QR code, making it difficult for them to realize they have been targeted. In this paper, we have developed a classification technique utilizing machine learning algorithms to identify the maliciousness of URLs embedded in QR codes, and we have explored ways to integrate this with existing QR code readers. To this end, we constructed a dataset from 128,587 malicious URLs and 428,102 benign URLs, extracting 35 different features such as protocol and parameters, and used AutoML to identify the optimal algorithm and hyperparameters, achieving an accuracy of approximately 87.37%. Following this, we designed the integration of the trained classification model with existing QR code readers to implement a service capable of countering Qshing attacks. In conclusion, our findings confirm that deriving an optimized algorithm for classifying malicious URLs in QR codes and integrating it with existing QR code readers presents a viable solution to combat Qshing attacks.

Development of Filter Sorting Process for Cigarette Butt Recycling and Extraction of Cellulose Acetate (담배꽁초 재활용을 위한 필터 선별공정 개발 및 셀룰로오스 아세테이트의 추출)

  • Minseon Park;Minjung Jung;Noh-sup Lee;Soochul Rhee;Namhoon Lee
    • Journal of the Korea Organic Resources Recycling Association
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    • v.32 no.2
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    • pp.5-14
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    • 2024
  • A study approached the development of a process for efficiently recycling discarded cigarette butts, reported as a major source of microplastic pollution in aquatic environments. Cigarette butts were sorted to extract filters, and cellulose acetate, the raw material of the filters, was extracted to a high degree of purity. The sorting of filters from cigarette butts was conducted through both wet and dry processes, each with optimized sorting conditions. Wet stirring sorting considered factors such as solid-liquid ratio, stirring speed, and stirring temperature. The highest efficiency of wet stirring sorting, at 46.21%, was observed with a solid-liquid ratio of 1:45, stirring speed of 200 rpm, and stirring temperature of 50℃. Dry wind power sorting took into account moisture content and residence time. The filter sorting efficiency reached its peak at 57.10% with a moisture content of 20% and a residence time of 5 minutes. There was no significant difference in the recovery rate of cellulose acetate between the two sorting processes. Dry wind power sorting was deemed a more advantageous process in terms of energy and environmental considerations within the scope of this study.

Production of Dendropanax morbiferus extract containing multi-functional ingredients by serial fermentation using Bacillus subtilis HA and Lactobacillus plantarum KS2020 (고초균-젖산균의 순차적 복합 발효를 통한 복합 기능성 물질 함유 황칠나무 추출물의 생산)

  • Su-Jin Son;Hye-Mi Kang;Yun-Ho Park;Mi-Hyang Hwangbo;Sam-Pin Lee
    • Food Science and Preservation
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    • v.31 no.1
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    • pp.138-148
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    • 2024
  • The production of poly-γ-glutamic acid (γ-PGA) and γ-aminobutyric acid (GABA) was optimized by serial fermentation of Dendropanax morbiferus extract (DME) using Bacillus subtilis HA and Lactobacillus plantarum KS2020. The 1st alkaline fermentation was performed on 60% DME including 2% glucose and 10% monosodium ʟ-glutamate (MSG) as a precursor. The 1st fermented DME had 57 mg% tyrosine. Consequently, the 2nd lactic acid fermentation for 5 days increased the tyrosine content of 106 mg%. The mucilage containing γ-PGA showed a high content of 3.50% on the first day of alkaline fermentation and then increased to 4.10% after 2 days. The precursor (MSG) remaining in the 1st fermented DME was efficiently converted to GABA by the 2nd lactic acid fermentation in the presence of 5% skim milk, 1.5% glucose and 0.5% yeast extract, resulting in the production of 18.29 mg/mL GABA. The viable cells of lactic acid bacteria increased and indicated 9.49 log CFU/mL on the fermentation for 5 days, and the acidity of co-fermented DME indicated the highest value of 1.55%. Conclusively, the serial fermented DME has multi-functional ingredients containing γ-PGA, GABA, peptides and probiotics.

Highly efficient genome editing via CRISPR-Cas9 ribonucleoprotein (RNP) delivery in mesenchymal stem cells

  • A Reum Han;Ha Rim Shin;Jiyeon Kweon;Soo Been Lee;Sang Eun Lee;Eun-Young Kim;Jiyeon Kweon;Eun-Ju Chang;Yongsub Kim;Seong Who Kim
    • BMB Reports
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    • v.57 no.1
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    • pp.60-65
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    • 2024
  • The CRISPR-Cas9 system has significantly advanced regenerative medicine research by enabling genome editing in stem cells. Due to their desirable properties, mesenchymal stem cells (MSCs) have recently emerged as highly promising therapeutic agents, which properties include differentiation ability and cytokine production. While CRISPR-Cas9 technology is applied to develop MSC-based therapeutics, MSCs exhibit inefficient genome editing, and susceptibility to plasmid DNA. In this study, we compared and optimized plasmid DNA and RNP approaches for efficient genome engineering in MSCs. The RNP-mediated approach enabled genome editing with high indel frequency and low cytotoxicity in MSCs. By utilizing Cas9 RNPs, we successfully generated B2M-knockout MSCs, which reduced T-cell differentiation, and improved MSC survival. Furthermore, this approach enhanced the immunomodulatory effect of IFN-r priming. These findings indicate that the RNP-mediated engineering of MSC genomes can achieve high efficiency, and engineered MSCs offer potential as a promising therapeutic strategy.

Feasibility of Deep Learning-Based Analysis of Auscultation for Screening Significant Stenosis of Native Arteriovenous Fistula for Hemodialysis Requiring Angioplasty

  • Jae Hyon Park;Insun Park;Kichang Han;Jongjin Yoon;Yongsik Sim;Soo Jin Kim;Jong Yun Won;Shina Lee;Joon Ho Kwon;Sungmo Moon;Gyoung Min Kim;Man-deuk Kim
    • Korean Journal of Radiology
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    • v.23 no.10
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    • pp.949-958
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    • 2022
  • Objective: To investigate the feasibility of using a deep learning-based analysis of auscultation data to predict significant stenosis of arteriovenous fistulas (AVF) in patients undergoing hemodialysis requiring percutaneous transluminal angioplasty (PTA). Materials and Methods: Forty patients (24 male and 16 female; median age, 62.5 years) with dysfunctional native AVF were prospectively recruited. Digital sounds from the AVF shunt were recorded using a wireless electronic stethoscope before (pre-PTA) and after PTA (post-PTA), and the audio files were subsequently converted to mel spectrograms, which were used to construct various deep convolutional neural network (DCNN) models (DenseNet201, EfficientNetB5, and ResNet50). The performance of these models for diagnosing ≥ 50% AVF stenosis was assessed and compared. The ground truth for the presence of ≥ 50% AVF stenosis was obtained using digital subtraction angiography. Gradient-weighted class activation mapping (Grad-CAM) was used to produce visual explanations for DCNN model decisions. Results: Eighty audio files were obtained from the 40 recruited patients and pooled for the study. Mel spectrograms of "pre-PTA" shunt sounds showed patterns corresponding to abnormal high-pitched bruits with systolic accentuation observed in patients with stenotic AVF. The ResNet50 and EfficientNetB5 models yielded an area under the receiver operating characteristic curve of 0.99 and 0.98, respectively, at optimized epochs for predicting ≥ 50% AVF stenosis. However, Grad-CAM heatmaps revealed that only ResNet50 highlighted areas relevant to AVF stenosis in the mel spectrogram. Conclusion: Mel spectrogram-based DCNN models, particularly ResNet50, successfully predicted the presence of significant AVF stenosis requiring PTA in this feasibility study and may potentially be used in AVF surveillance.

T2 Mapping with and without Fat-Suppression to Predict Treatment Response to Intravenous Glucocorticoid Therapy for Thyroid-Associated Ophthalmopathy

  • Linhan Zhai;Qiuxia Wang;Ping Liu;Ban Luo;Gang Yuan;Jing Zhang
    • Korean Journal of Radiology
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    • v.23 no.6
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    • pp.664-673
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    • 2022
  • Objective: To evaluate the performance of baseline clinical characteristics and pretherapeutic histogram parameters derived from T2 mapping of the extraocular muscles (EOMs) in the prediction of treatment response to intravenous glucocorticoid (IVGC) therapy for active and moderate-to-severe thyroid-associated ophthalmopathy (TAO) and to investigate the effect of fat-suppression (FS) in T2 mapping in this prediction. Materials and Methods: A total of 79 patients clinically diagnosed with active, moderate-to-severe TAO (47 female, 32 male; mean age ± standard deviation, 46.1 ± 10 years), including 43 patients with a total of 86 orbits in the responsive group and 36 patients with a total of 72 orbits in the unresponsive group, were enrolled. Baseline clinical characteristics and pretherapeutic histogram parameters derived from T2 mapping with FS (i.e., FS T2 mapping) or without FS (i.e., conventional T2 mapping) of EOMs were compared between the two groups. Independent predictors of treatment response to IVGC were identified using multivariable analysis. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performance of the prediction models. Differences between the models were examined using the DeLong test. Results: Compared to the unresponsive group, the responsive group had a shorter disease duration, lower kurtosis (FS-kurtosis), lower standard deviation, larger 75th, 90th, and 95th (FS-95th) T2 relaxation times in FS mapping and lower kurtosis in conventional T2 mapping. Multivariable analysis revealed that disease duration, FS-95th percentile, and FS-kurtosis were independent predictors of treatment response. The combined model, integrating all identified predictors, had an optimized area under the ROC curve of 0.797, 88.4% sensitivity, and 62.5% specificity, which were significantly superior to those of the imaging model (p = 0.013). Conclusion: An integrated combination of disease duration, FS-95th percentile, and FS-kurtosis was a potential predictor of treatment response to IVGC in patients with active and moderate-to-severe TAO. FS T2 mapping was superior to conventional T2 mapping in terms of prediction.

Bone Age Assessment Using Artificial Intelligence in Korean Pediatric Population: A Comparison of Deep-Learning Models Trained With Healthy Chronological and Greulich-Pyle Ages as Labels

  • Pyeong Hwa Kim;Hee Mang Yoon;Jeong Rye Kim;Jae-Yeon Hwang;Jin-Ho Choi;Jisun Hwang;Jaewon Lee;Jinkyeong Sung;Kyu-Hwan Jung;Byeonguk Bae;Ah Young Jung;Young Ah Cho;Woo Hyun Shim;Boram Bak;Jin Seong Lee
    • Korean Journal of Radiology
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    • v.24 no.11
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    • pp.1151-1163
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    • 2023
  • Objective: To develop a deep-learning-based bone age prediction model optimized for Korean children and adolescents and evaluate its feasibility by comparing it with a Greulich-Pyle-based deep-learning model. Materials and Methods: A convolutional neural network was trained to predict age according to the bone development shown on a hand radiograph (bone age) using 21036 hand radiographs of Korean children and adolescents without known bone development-affecting diseases/conditions obtained between 1998 and 2019 (median age [interquartile range {IQR}], 9 [7-12] years; male:female, 11794:9242) and their chronological ages as labels (Korean model). We constructed 2 separate external datasets consisting of Korean children and adolescents with healthy bone development (Institution 1: n = 343; median age [IQR], 10 [4-15] years; male: female, 183:160; Institution 2: n = 321; median age [IQR], 9 [5-14] years; male: female, 164:157) to test the model performance. The mean absolute error (MAE), root mean square error (RMSE), and proportions of bone age predictions within 6, 12, 18, and 24 months of the reference age (chronological age) were compared between the Korean model and a commercial model (VUNO Med-BoneAge version 1.1; VUNO) trained with Greulich-Pyle-based age as the label (GP-based model). Results: Compared with the GP-based model, the Korean model showed a lower RMSE (11.2 vs. 13.8 months; P = 0.004) and MAE (8.2 vs. 10.5 months; P = 0.002), a higher proportion of bone age predictions within 18 months of chronological age (88.3% vs. 82.2%; P = 0.031) for Institution 1, and a lower MAE (9.5 vs. 11.0 months; P = 0.022) and higher proportion of bone age predictions within 6 months (44.5% vs. 36.4%; P = 0.044) for Institution 2. Conclusion: The Korean model trained using the chronological ages of Korean children and adolescents without known bone development-affecting diseases/conditions as labels performed better in bone age assessment than the GP-based model in the Korean pediatric population. Further validation is required to confirm its accuracy.

Study of 68Ga Labelled PET/CT Scan Parameters Optimization (68Ga 표지 PET/CT 검사의 최적화된 매개변수에 대한 연구)

  • In Suk Kwak;Hyuk Lee;Si Hwal Kim;Seung Cheol Moon
    • The Korean Journal of Nuclear Medicine Technology
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    • v.27 no.2
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    • pp.111-127
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    • 2023
  • Purpose: Gallium-68 (68Ga) is increasingly used in nuclear medicine imaging for various conditions such as lymphoma and neuroendocrine tumors by labeling tracers like Prostate Specific Membrane Antigen (PSMA) and DOTA-TOC. However, compared to Fluorine-18 (18F) used in conventional nuclear medicine imaging, 68Ga has lower spatial resolution and relatively higher Signal to Background Ratio (SBR). Therefore, this study aimed to investigate the optimized parameters and reconstruction methods for PET/CT imaging using the 68Ga radiotracer through model-based image evaluation. Materials and Methods: Based on clinical images of 68Ga-PSMA PET/CT, a NEMA/IEC 2008 PET phantom model was prepared with a Hot vs Background (H/B) ratio of 10:1. Images were acquired for 9 minutes in list mode using DMIDR (GE, Milwaukee WI, USA). Subsequently, reconstructions were performed for 1 to 8 minutes using OS-EM (Ordered Subset Expectation Maximization) + TOF (Time of Flight) + Sharp IR (VPFX-S), and BSREM (Block Sequential Regularized Expectation Maximization) + TOF + Sharp IR (QCFX-S-400), followed by comparative evaluation. Based on the previous experimental results, images were reconstructed for BSREM + TOF + Sharp IR / 2 minutes (QCFX-S-2min) with varying β-strength values from 100 to 700. The image quality was evaluated using AMIDE (freeware, Ver.1.0.1) and Advanced Workstation (GE, USA). Results: Images reconstructed with QCFX-S-400 showed relatively higher values for SNR (Signal to Noise Ratio), CNR (Contrast to Noise Ratio), count, RC (Recovery Coefficient), and SUV (Standardized Uptake Value) compared to VPFX-S. SNR, CNR, and SUV exhibited the highest values at 2 minutes/bed acquisition time. RC showed the highest values for a 10 mm sphere at 2 minutes/bed acquisition time. For small spheres of 10 mm and 13 mm, an inverse relationship between β-strength increase and count was observed. SNR and CNR peaked at β-strength 400 and then decreased, while SUV and RC exhibited a normal distribution based on sphere size for β-strength values of 400 and above. Conclusion: Based on the experiments, PET/CT imaging using the 68Ga radiotracer yielded the most favorable quantitative and qualitative results with a 2 minutes/bed acquisition time and BSREM reconstruction, particularly when applying β-strength 400. The application of BSREM can enhance accurate quantification and image quality in 68Ga PET/CT imaging, and an optimization process tailored to each institution's imaging objectives appears necessary.

Analysis of User Demand for University Library Services in Korea (국내 대학도서관 이용자 수요 분석)

  • YouRa Youn;Youngmi Jung
    • Journal of Korean Library and Information Science Society
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    • v.54 no.4
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    • pp.229-254
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    • 2023
  • The university library's service strategy needs to be established based on users, who are actual service consumers, including an outlook on changes in the social environment. Accordingly, in this study, college and graduate students, instructors, and researchers who are university library users were identified to understand users' perceptions of the university library functions and services currently provided, and the demand for services that need to be improved or developed. Data was collected through an online survey, with 1,216 responses from the student group and 433 responses from the researcher group. The survey results were organized by each group, and implications were drawn from common results. First, it was found that both groups had a continuous demand for strengthening the collection and access to information resources. Second, there was a need to expand information provision services, such as strengthening the sharing of information resources through cooperation with other organizations and wishing to use overseas academic materials in various ways. Third, although the library was recognized as an important institution, it was found that satisfactory use was not achieved due to lack of publicity. Fourth, it was found that university libraries recognize that they must provide open services to everyone without discrimination. The results of this study can be used as basic data when establishing strategies to develop and improve university library services optimized for users.