• Title/Summary/Keyword: Quality evaluation

Search Result 14,126, Processing Time 0.044 seconds

Analysis of the Effect of Intralesional Steroid Injection on the Voice During Laryngeal Microsurgery (후두 미세수술 중 병변 내 스테로이드 주입이 음성에 미치는 효과 분석)

  • Jae Seon, Park;Hyun Seok, Kang;In Buhm, Lee;Sung Min, Jin;Sang Hyuk, Lee
    • Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
    • /
    • v.33 no.3
    • /
    • pp.166-171
    • /
    • 2022
  • Background and Objectives Vocal fold (VF) scar is known to be the most common cause of dysphonia after laryngeal microsurgery (LMS). Steroids reduce postoperative scar formation by inhibiting inflammation and collagen deposition. However, the clinical evidence of whether steroids are helpful in reducing VF scar formation after LMS is still lacking. The purpose of this study is to determine whether intralesional VF steroid injection after LMS helps to reduce postoperative scar formation and voice quality. Materials and Method This study was conducted on 80 patients who underwent LMS for VF polyp, Reinke's edema, and leukoplakia. Among them, 40 patients who underwent VF steroid injection after LMS were set as the injection group, and patients who had similar sex, age, and lesion size and who underwent LMS alone were set as the control group. In each group, stroboscopy, multi-dimensional voice program, Aerophone II, and voice handicap index (VHI) were performed before and 1 month after surgery, and the results were statistically analyzed. Results There were no statistically significant differences in the distribution of sex, age, symptom duration, occupation and smoking status between each group. Both groups consisted of VF polyp (n=21), Reinke's edema (n=11), and leukoplakia (n=9). On stroboscopy, the lesion disappeared after surgery, and the amplitude and mucosal wave were symmetrical on both sides of the VFs in all patients. Acoustic parameters and VHI significantly improved after surgery in all patients. However, there was no significant difference between the injection and control group in most of the results. Conclusion There was no significant difference in the results of stroboscopy, acoustic, aerodynamic, and subjective evaluation before and after surgery in the injection group and the control group.

Evaluation of Bio-cha's ability to secure underground penetration water and its effect on water quality improvement (바이오차의 지하 침투수 확보 능력 및 수질개선 효과 평가)

  • Tae Seong Kang;Jeong Ha Lim;Dong Hyuk Kum;Min Hwan Shin;Jong Gun Kim
    • Proceedings of the Korea Water Resources Association Conference
    • /
    • 2023.05a
    • /
    • pp.468-468
    • /
    • 2023
  • 최근 급격한 기후변화에 의한 이상가뭄 발생 등을 대비하기 위한 비상용수 또는 대체 수자원으로서의 지하수 개발수요가 증가함에 따라 기저유량 확보 및 수질개선 방안을 수립하는 것은 지속가능한 수자원 이용 관리 측면에 있어서 매우 중요하다. 국내 지하수 사용에 따른 하천유량의 변동에 관한 연구는 활발히 진행되었으나, 실질적으로 적용가능한 지하수 저감 방안 및 지하 수질개선방안에 대한 연구는 미비한 실정이다. 이에 본 연구에서는 바이오차를 이용하여 시험포를 설계 및 시공하였으며, 실내 인공강우 실험을 통해 지하 침투수 확보 능력 및 수질개선 효과를 평가하였다. 대조구는 폭 1 m × 길이 1 m × 깊이 0.60 m로 시공하였으며, 바이오차 시험포는 폭 1 m × 길이 1 m, 시험포 상단과 하단 각 0.10 m씩 대조구와 동일한 흙으로 채웠으며, 그 사이 0.40 m만큼은 바이오차를 채워서 시공하였다. 시험의 정밀도를 높이기 위해 동일한 조건으로 대조구와 바이오차 시험포 각 2개씩, 총 4개의 시험포를 시공하여 실내 인공강우 실험을 진행하였으며, 시험포에서 발생한 직접유출수와 기저유출수를 이용하여 바이오차의 지하 침투량 확보 및 수질개선효과를 분석하였다. 시험포 완공 후 총 2번의 실내인공강우 실험 결과 대조구에서 발생한 직접유출량은 총 0.214 m3, 바이오차 시험포에서는 총 0.194 m3로 대조구 대비 총 직접유출량 저감효과는 9.4%로 나타났다. 기저유출의 경우 바이오차 시험포(0.036 m3)에서 대조구(0.003 m3) 대비 약13배 많은 양의 기저유출수가 발생한 것으로 나타났다. 각 시험포에서 발생한 유출수의 오염부하를 산정해 대조구 시험포 대비 바이오차 시험포에서 발생한 직접유출수의 오염부하 저감효과를 분석한 결과 BOD5 항목과 CODMn 항목, 그리고 TOC 항목의 경우 26.3%과 22.0%, 그리고 27.6%로 저감 된 것으로 나타났으나, SS 항목과 T-N 항목, 그리고 T-P 항목의 경우 저감효과가 없는 것으로 나타났다. 이와 같이 바이오차는 지하 침투수 확보 능력은 효과적인 것으로 나타났으나, 직접유출수의 수질개선 효과는 미비한 것으로 나타났다. 그러나 바이오차의 지하 침투량 및 수질개선 효과는 바이오차 생산 시 사용된 열분해 방식, 사용된 바이오차의 양 등에 따라 편차가 클것으로 판단되며, 바이오차의 생산 방법, 토양 흡착 기간, 바이오차의 양 등 다양한 조건에서의 모니터링을 통해 정량화 되어야 할 것으로 판단된다.

  • PDF

EEG Feature Engineering for Machine Learning-Based CPAP Titration Optimization in Obstructive Sleep Apnea

  • Juhyeong Kang;Yeojin Kim;Jiseon Yang;Seungwon Chung;Sungeun Hwang;Uran Oh;Hyang Woon Lee
    • International journal of advanced smart convergence
    • /
    • v.12 no.3
    • /
    • pp.89-103
    • /
    • 2023
  • Obstructive sleep apnea (OSA) is one of the most prevalent sleep disorders that can lead to serious consequences, including hypertension and/or cardiovascular diseases, if not treated promptly. Continuous positive airway pressure (CPAP) is widely recognized as the most effective treatment for OSA, which needs the proper titration of airway pressure to achieve the most effective treatment results. However, the process of CPAP titration can be time-consuming and cumbersome. There is a growing importance in predicting personalized CPAP pressure before CPAP treatment. The primary objective of this study was to optimize the CPAP titration process for obstructive sleep apnea patients through EEG feature engineering with machine learning techniques. We aimed to identify and utilize the most critical EEG features to forecast key OSA predictive indicators, ultimately facilitating more precise and personalized CPAP treatment strategies. Here, we analyzed 126 OSA patients' PSG datasets before and after the CPAP treatment. We extracted 29 EEG features to predict the features that have high importance on the OSA prediction index which are AHI and SpO2 by applying the Shapley Additive exPlanation (SHAP) method. Through extracted EEG features, we confirmed the six EEG features that had high importance in predicting AHI and SpO2 using XGBoost, Support Vector Machine regression, and Random Forest Regression. By utilizing the predictive capabilities of EEG-derived features for AHI and SpO2, we can better understand and evaluate the condition of patients undergoing CPAP treatment. The ability to predict these key indicators accurately provides more immediate insight into the patient's sleep quality and potential disturbances. This not only ensures the efficiency of the diagnostic process but also provides more tailored and effective treatment approach. Consequently, the integration of EEG analysis into the sleep study protocol has the potential to revolutionize sleep diagnostics, offering a time-saving, and ultimately more effective evaluation for patients with sleep-related disorders.

Effect of Pre-treatment and Packaging Method on Freshness Prolongation of Spring Kimchi Cabbage during Low Temperature Storage (봄배추의 전처리 및 포장방법이 저온저장 중 선도유지에 미치는 효과)

  • Se-Jin Park;Ji-Young Kim;Andri Jaya Laksana;Byeong-Sam Kim
    • KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
    • /
    • v.29 no.2
    • /
    • pp.119-128
    • /
    • 2023
  • This study was examined for investigating the quality changes of spring kimchi cabbage under various treatments (pre-drying/pre-cooling, packaging types, and stacking and loading in container and pallete in the storage room) during cold storage. The results showed that control (upward stacking without pre-drying/pre-cooling and HDPE or PVC film cover) was increased significantly in weight loss and trimming loss, compared to other treatments such as DPDH (downard stacking + pre-drying + HDPE), DPDP (downard stacking + pre-drying + PVC), DPCH (downnard stacking + pre-cooling + HDPE), and UPCH (upward stacking + pre-cooling +HDPE) during storage for three months. In Sensory evaluation, judging from marketable properties, the desirable appearance of spring kimchi cabbage with the modified pallet-unit MA packed, PE, and PVC film wrapping could be maintained until 9 weeks after pre-drying/pre-cooling. Meanwhile, the control without any treatments after 6 weeks, the sensory score was declined, significantly. In general, the low temperature (10℃ and 2℃) of pre-treatment with combination of plastic film packaging in spring kimchi cabbage storage could inhibit the physiological activity and reduce the direct exposure of environmental cold air in the storage. Therefore, these two variables were the key points for extending the shelf-life of spring kimchi cabbage.

Exploring the Direction of the Clothing Life Education Curriculum according to Changes in the Future Educational Environment (미래 교육환경 변화에 따른 의생활교육과정의 방향)

  • Lee, Eun Hee
    • Journal of Korean Home Economics Education Association
    • /
    • v.34 no.4
    • /
    • pp.93-111
    • /
    • 2022
  • This study started with the question of 'What innovative task should elementary and secondary school clothing life education perform in accordance with the changes in the future educational environment?' It is time to prepare for a major shift in the educational paradigm that improves the quality of life for all everyone, based on social innovations such as the 4th industrial revolution and the transition to the post-corona era. This study examined the literature for the characteristics of changes in the future educational environment from an educational perspective, and examined the curriculum focusing on the clothing life with the porpose of presenting the direction for the clothing life education. In order to carry out this study, various literature including previous studies related to clothing life education and the national curriculum from the first curriculum to the 2015 revision were analyzed. In conclusion, the direction of the clothing life education curriculum according to the changes in the future educational environment is proposed as follows: First, nurturing convergence education experts that can combine human emotion, environment, and clothing life culture to artificial intelligence(AI); second, developing a clothing life education curriculum that links software competency and practical problem-solving competency; and lastly, implementing fashion maker education using artificial intelligence(AI) and value-oriented clothing life education. In the future, it is expected that the direction of teaching/learning methods and evaluation in clothing life education curriculum is proposed, and that this educational discussion process will help establish the identity of clothing life education in school education.

Evaluating Essential Aspects of Novel Architectural Products: An In-depth Application of Importance-Performance Analysis (중요도-성취도 분석을 통한 건축 신제품의 요구사항 분석 연구)

  • Lee, Ung-Kyun;Kim, Jae-Yeob
    • Journal of the Korea Institute of Building Construction
    • /
    • v.23 no.3
    • /
    • pp.305-313
    • /
    • 2023
  • With an increasing interest in the commercialization of research results in the present societal climate, especially in the construction industry, preliminary product analysis plays a critical role when introducing a new product to the market. It significantly influences the product's success or failure. In this context, this study aims to investigate the utility of Importance-Performance Analysis (IPA) as a management strategy tool for preliminary analysis in the commercialization of new architectural technologies. The study specifically assesses a smart ball product engineered for pipeline inspection. The evaluation is carried out based on product quality, convenience, and usability categories. Seventeen factors are recognized as sub-items, and a survey is conducted among relevant experts and consumer groups. From the survey, four key items are chosen: "Keep up the good work," "Concentrate here," "Low priority," and "Possible overkill." Suitable strategic measures are derived for each item. By conducting a correlation analysis between product importance and performance, this study offers a method to establish priority directions for future development. This analysis assists in identifying areas that necessitate improvement or additional focus to increase the product's commercial potential. On the whole, this study contributes to understanding and applying Importance-Performance Analysis as a valuable tool in the preliminary analysis and commercialization of novel technologies in the field of architecture.

A Study on Improvement of Research Ethic System in University (대학 연구윤리체계의 발전방안 연구)

  • Ahn, Sang-Yoon
    • Journal of Digital Convergence
    • /
    • v.20 no.1
    • /
    • pp.203-211
    • /
    • 2022
  • This study is to examine the causes of research misconduct such as plagiarism, forgery, redundant publication, unfair author expression, and incapacitation of the research ethics system of university researchers and to suggest improvement plan. It basically relied on literature research. In order to supplement the deficiencies in literature research, I sought advice from an expert professor who had experience working in a research-related field in university or who is currently in a position related to research ethics through the delphi-method. As a result of the study, from the perspective of individual researchers, the complacent attitude, dishonesty, and greed for research funds were identified as the main reasons. In terms of organization, it was analyzed for reasons such as lack of detail and application of regulations, lack of verification system, and performance-oriented research environment. In order to overcome research misconduct caused by the researcher's personal reasons, regularization, increase in the number of research ethics education, and strengthening personal penalties were suggested. As a way to overcome irregularities arising from institutional reasons, the reinforcement of the verification system, the reinforcement of the whistle-blower's personal protection system, the omission of promotion, and the quality and quantitative balance of research evaluation was suggested.

Accuracy Assessment of Land-Use Land-Cover Classification Using Semantic Segmentation-Based Deep Learning Model and RapidEye Imagery (RapidEye 위성영상과 Semantic Segmentation 기반 딥러닝 모델을 이용한 토지피복분류의 정확도 평가)

  • Woodam Sim;Jong Su Yim;Jung-Soo Lee
    • Korean Journal of Remote Sensing
    • /
    • v.39 no.3
    • /
    • pp.269-282
    • /
    • 2023
  • The purpose of this study was to construct land cover maps using a deep learning model and to select the optimal deep learning model for land cover classification by adjusting the dataset such as input image size and Stride application. Two types of deep learning models, the U-net model and the DeeplabV3+ model with an Encoder-Decoder network, were utilized. Also, the combination of the two deep learning models, which is an Ensemble model, was used in this study. The dataset utilized RapidEye satellite images as input images and the label images used Raster images based on the six categories of the land use of Intergovernmental Panel on Climate Change as true value. This study focused on the problem of the quality improvement of the dataset to enhance the accuracy of deep learning model and constructed twelve land cover maps using the combination of three deep learning models (U-net, DeeplabV3+, and Ensemble), two input image sizes (64 × 64 pixel and 256 × 256 pixel), and two Stride application rates (50% and 100%). The evaluation of the accuracy of the label images and the deep learning-based land cover maps showed that the U-net and DeeplabV3+ models had high accuracy, with overall accuracy values of approximately 87.9% and 89.8%, and kappa coefficients of over 72%. In addition, applying the Ensemble and Stride to the deep learning models resulted in a maximum increase of approximately 3% in accuracy and an improvement in the issue of boundary inconsistency, which is a problem associated with Semantic Segmentation based deep learning models.

Evaluation of the usefulness of Images according to Reconstruction Techniques in Pediatric Chest CT (소아 흉부 CT 검사에서 재구성 기법에 따른 영상의 유용성 평가)

  • Gu Kim;Jong Hyeok Kwak;Seung-Jae Lee
    • Journal of the Korean Society of Radiology
    • /
    • v.17 no.3
    • /
    • pp.285-295
    • /
    • 2023
  • With the development of technology, efforts to reduce the exposure dose received by patients in CT scans are continuing with the development of new reconstruction techniques. Recently, deep learning reconstruction techniques have been developed to overcome the limitations of repetitive reconstruction techniques. This study aims to evaluate the usefulness of images according to reconstruction techniques in pediatric chest CT images. Patient study conducted a study on 85 pediatric patients who underwent chest CT scan at P-Hospital in Gyeongsangnam-do from January 1, 2021 to December 31, 2022. The phantom used in the Phantom Study is the Pediatrics Whole Body Phantom PBU-70. After the test, the images were reconstructed with FBP, ASIR-V (50%) and DLIR (TF-Medium, High), and the images were evaluated by obtaining SNR and CNR values by setting ROI of the same size. As a result, TF-H of deep learning reconstruction techniques had the lowest noise value compared to ASIR-V (50%) and TF-M in all experiments, and SNR and CNR had the highest values. In pediatric chest CT scans, TF images with deep learning reconstruction techniques were less noisy than ASiR-V images with adaptive statistical iterative reconstruction techniques, CNR and SNR were higher, and the quality of images was improved compared to conventional reconstruction techniques.

Evaluation of Radon Exposure During Highway Tunnel Construction by New Austrian Tunneling Method (NATM 공법에 의한 고속도로 터널 공사 중 라돈 노출 평가)

  • Ye-Ji Yu;Hyoung-Ryoul Kim;Mo-Yeol Kang;Sangjun Choi
    • Journal of Korean Society of Occupational and Environmental Hygiene
    • /
    • v.33 no.2
    • /
    • pp.115-125
    • /
    • 2023
  • Objectives: This study was conducted to measure the level of radon in the air at a highway tunnel construction site in a gneiss area using the New Austrian Tunneling Method (NATM) and to evaluate exposure levels by occupation. Methods: Radon concentrations in the air were measured using E-PERM at points 300 m, 600 m, and 900 m from the tunnel entrance during the excavation and waterproofing work inside the tunnel. In addition, radon concentrations were measured during external excavation to compare with the inside of the tunnel. Personal exposure levels for major occupations including tunnel workers, construction equipment operators, waterproofers, shotcrete workers, and safety and health managers who participated in the construction were estimated using radon concentration measured in the work process area and working hours by occupation. Results: As a result of a total of 77 radon measurements, the geometric mean (GM) concentration was 71.1 Bq/m3, and the maximum concentration was 127.3 Bq/m3, which was below the indoor air quality criteria. Radon concentration by process decreased in the order of the tunnel excavation process (GM= Bq/m3, GSD=1.2), waterproofing process (GM=73.35 Bq/m3, GSD=1.2), and outside excavating process (GM=45.28 Bq/m3, GSD=1.2). Processes inside the tunnel were significantly higher than outside excavating processes (p<0.05). There was no statistically significant difference in radon concentration measured inside by distance from the tunnel entrance, but the innermost point of the tunnel, 900 m (GM=79.24 Bq/m3, GSD=1.27), measured the highest. Conclusions: The occupation with the highest individual exposure to radon was tunnel worker (64.16 Bq/m3), followed by construction equipment driver (64.04 Bq/m3) and waterproofer (63.13 Bq/m3).