• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권7호
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• pp.1807-1822
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• 2023

Innovation and rapid increased functionality in user friendly smartphones has encouraged shutterbugs to have picturesque image macros while in work environment or during travel. Formal signboards are placed with marketing objectives and are enriched with text for attracting people. Extracting and recognition of the text from natural images is an emerging research issue and needs consideration. When compared to conventional optical character recognition (OCR), the complex background, implicit noise, lighting, and orientation of these scenic text photos make this problem more difficult. Arabic language text scene extraction and recognition adds a number of complications and difficulties. The method described in this paper uses a two-phase methodology to extract Arabic text and word boundaries awareness from scenic images with varying text orientations. The first stage uses a convolution autoencoder, and the second uses Arabic Character Segmentation (ACS), which is followed by traditional two-layer neural networks for recognition. This study presents the way that how can an Arabic training and synthetic dataset be created for exemplify the superimposed text in different scene images. For this purpose a dataset of size 10K of cropped images has been created in the detection phase wherein Arabic text was found and 127k Arabic character dataset for the recognition phase. The phase-1 labels were generated from an Arabic corpus of quotes and sentences, which consists of 15kquotes and sentences. This study ensures that Arabic Word Awareness Region Detection (AWARD) approach with high flexibility in identifying complex Arabic text scene images, such as texts that are arbitrarily oriented, curved, or deformed, is used to detect these texts. Our research after experimentations shows that the system has a 91.8% word segmentation accuracy and a 94.2% character recognition accuracy. We believe in the future that the researchers will excel in the field of image processing while treating text images to improve or reduce noise by processing scene images in any language by enhancing the functionality of VGG-16 based model using Neural Networks.

• 문화기술의 융합
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• 제9권3호
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• pp.145-151
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• 2023

본 연구는 간호학과 신입생을 대상으로 간호학 전공에 대한 인식을 파악함으로써 간호학 전공 교육과정 개발 및 신입생 유치에 대한 입시전략의 기초자료를 제공하고자 시도되었다. 본 연구의 참여자는 2021년 1학기에 개설된 신입생 필수 교양인 자기 탐색을 이수한 간호학과 신입생 중 연구 참여에 동의한 40명을 대상으로 하였다. 자료수집은 15주 수업 후 참여자들이 작성한 학습일지였으며, 자료 분석은 Heieh와 Shannon이 제시한 전통적 내용분석 방법을 적용하였다. 연구 결과 '간호학 전공 입문 동기', '간호학 전공의 가치', '간호학 전공의 걸림돌'의 3개의 주제가 도출되었다. 따라서 대학 및 학과는 중·고등학교와 연계한 체험형 학과 견학프로그램을 개발 및 진행하는 입시전략을강화해야겠으며, 기초학습 능력이 부족한 학생들을 대상으로 한 교과 및 비교과 프로그램을 제공하여 전공과목 수강에 어려움을 해결해 줘야겠다.

• 문화기술의 융합
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• 제9권3호
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• pp.159-166
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• 2023

본 지능정보사회에서 인문학은 기술 자체만큼이나 중요성을 지닌다. 감성적이고 인간성을 반영한 인간 중심의 융복합 정보기술(IT)은 예측하기 어려운 미래 시대에 낙관적 전망을 가진 독보적 기술이라 할 수 있다. 이러한 연구 배경에 따라 본 논문은 융복합 교육모델들에 관한 선행연구 분석을 통해 초·중등학생, 예비교원, 현직교원, 학교 관리자, 일반인 등 여러 학습자의 IT인문학 역량을 제고할 수 있는 교육을 구성할 수 있는 교육모델을 제안하였다. 나아가, 제안하는 모델의 실천적 측면을 면밀히 고찰하여 제안하는 교육모델이 교육 현장에 안정적으로 접목되고 활용될 수 있도록 하였다. 본 논문에서 제안하는 교육모델의 실천 전략은 총 7가지로 교재 및 교수·학습자료 연구, 연구 성과의 대중적 확산 활동 및 교육 연계 활동의 활성화, 메이커 스페이스 조성, 글로벌 공동연구, 온라인 교육 운영, 리빙랩 거버넌스 구축, 지속 가능한 실천 교육을 위한 자생플랫폼 다각화 등을 포함한다. 향후 전문가 Delphi를 통한 타당도 검증이 후속 연구로 요구된다.

• Journal of Hospice and Palliative Care
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• 제25권2호
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• pp.55-65
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• 2022

Caring for patients with cancer is highly stimulating and rewarding, attracting health professionals to the field who enjoy the challenge of managing a complex illness. Health professionals often form close bonds with their patients as they confront ongoing disease or treatment impacts, which may be associated with multiple losses involving function and/or eventual loss of life. Ongoing exposure to patient loss, along with a challenging work setting, may pose significant stress and impact health professionals' well-being. The prevalence rates of burnout and compassion fatigue (CF) are significant, yet health professionals have little knowledge on these topics. A 6-week continuing education program consisting of weekly small-group video-conferencing sessions, case-based learning, and an online community of practice was delivered to health care providers providing oncology care. Program content included personal, organization and team-related risk and protective factors associated with CF, grief models, and strategies to mitigate against CF. Content analysis was completed as part of the program evaluation. In total, 189 participants (93% nurses) completed the program, which was associated with significant improvements in confidence and knowledge of CF and strategies to support self and team resilience. Qualitative themes and vignettes from experiences with the program are presented. Key themes included knowledge gaps, a lack of support related to CF and strategies to support resilience, organization-and team-based factors that can inhibit expression about the impacts of clinical work, the health professional as a "person" in caregiving, and the role of personal variables, self-skill practices, and recommendations for education and support for self and teams.

• 한국콘텐츠학회논문지
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• 제22권5호
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• pp.667-684
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• 2022

본 연구는 현재 고등학교에서 사용되는 피부 미용 교과서를 NCS 능력 단위를 기준으로, 고등학교 교과서의 문제점과 개선방안에 대해 분석하였다. NCS 기준을 바탕으로 고등학교 과정 동안 습득 가능한 내용의 포함 여부 및 내용의 적합성을 중심으로 분석하였으며 연구의 주요 결과는 다음과 같다. 첫째, 고등학교 기간동안 학습이 가능지만 누락된 NCS 능력 단위를 추가하는 방향으로 개편이 필요하다. 둘째, 고등학교 수준을 벗어난 NCS 능력 단위 5 수준은 교체 작업이 필요하다. 셋째, 삽화 자료와 사진 자료는 학습의 이해를 돕기 위하여 선명도와 일관성을 유지하는 방향으로 개선이 필요하다. 넷째, 교과서의 실습과 관련된 내용들은 구체적인 설명과 이와 관련된 학습자료의 첨부가 요구된다. 다섯째, 피부 미용에서 사용되는 전문용어의 개념 정리와 표기 방식에 대한 논의가 필요하다. 본 연구의 결과는 피부 미용 분야 NCS 학습 모듈 개발과 고등학교 피부 미용 교과서의 개선방안을 모색하는데 기초 자료로 활용될 수 있다. 연구의 한계점으로 학습 대상자의 견해를 반영되지 못한 부분이 있다. 학생들의 교과서에 대한 만족도 및 개선방안에 대한 견해를 살펴보는 후속 연구가 필요할 것으로 생각된다.

• Structural Engineering and Mechanics
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• 제87권3호
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• pp.221-229
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• 2023

Urbanization and industrialization have significantly increased the amount of solid waste produced in recent decades, posing considerable disposal problems and environmental burdens. The practice of waste utilization in concrete has gained popularity among construction practitioners and researchers for the efficient use of resources and the transition to the circular economy in construction. This study employed Lytag aggregate, an environmentally friendly pulverized fuel ash-based lightweight aggregate, as a substitute for natural coarse aggregate. At the same time, fly ash, an industrial by-product, was used as a partial substitute for cement. Concrete mix M20 was experimented with using fly ash and Lytag lightweight aggregate. The percentages of fly ash that make up the replacements were 5%, 10%, 15%, 20%, and 25%. The Compressive Strength (CS), Split Tensile Strength (STS), and deflection were discovered at these percentages after 56 days of testing. The concrete cube, cylinder, and beam specimens were examined in the explorations, as mentioned earlier. The results indicate that a 10% substitution of cement with fly ash and a replacement of coarse aggregate with Lytag lightweight aggregate produced concrete that performed well in terms of mechanical properties and deflection. The cementitious composites have varying characteristics as the environment changes. Therefore, understanding their mechanical properties are crucial for safety reasons. CS, STS, and deflection are the essential property of concrete. Machine learning (ML) approaches have been necessary to predict the CS of concrete. The Artificial Fish Swarm Optimization (AFSO), Particle Swarm Optimization (PSO), and Harmony Search (HS) algorithms were investigated for the prediction of outcomes. This work deftly explains the tremendous AFSO technique, which achieves the precise ideal values of the weights in the model to crown the mathematical modeling technique. This has been proved by the minimum, maximum, and sample median, and the first and third quartiles were used as the basis for a boxplot through the standardized method of showing the dataset. It graphically displays the quantitative value distribution of a field. The correlation matrix and confidence interval were represented graphically using the corrupt method.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.213-215
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• 2022

최근 이미지를 처리하는 딥러닝 기술이 화재 감지나 자율주행, 불량품 검출 등에서 다양하게 활용되고 있다. 특히, 제품이 오염되었는지 아닌지를 파악하기 위해 기존 센서 데이터에서 넘어온 오염물질을 통해 파악할 수 있지만, 제품의 균열이나 오염물질 자체를 이미지로 인식하는 기술도 다양한 분야에서 활발히 연구되고 있다. 본 논문에서는 오염되지 않은 정상적인 컵과 오염된 컵을 이미지를 통해 분류하는 시스템을 설계하고 이를 구현하였다. 이미지는 오픈 이미지와 촬영한 이미지를 사용하였고, 3D 객체 인식을 위한 Google Objectron을 활용해 컵 이미지의 상단 부분을 추출하여 이미지를 분석하였다. 본 연구를 통해 위생 분야에서 필요한 제품의 오염도를 이미지 기반으로 추출할 수 있는 연구에 다각도로 활용할 것으로 사료된다.

• Advances in concrete construction
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• 제14권3호
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• pp.185-194
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• 2022

For producing cement and concrete, the construction field has been encouraged by the usage of industrial soil waste (or) secondary materials since it decreases the utilization of natural resources. Simultaneously, for ensuring the quality, the analyses of the strength along with durability properties of that sort of cement and concrete are required. The prediction of strength along with other properties of High-Performance Concrete (HPC) by optimization and machine learning algorithms are focused by already available research methods. However, an error and accuracy issue are possessed. Therefore, the Enhanced Deep Neural Network (EDNN) based strength along with durability prediction of HPC was utilized by this research method. Initially, the data is gathered in the proposed work. Then, the data's pre-processing is done by the elimination of missing data along with normalization. Next, from the pre-processed data, the features are extracted. Hence, the data input to the EDNN algorithm which predicts the strength along with durability properties of the specific mixing input designs. Using the Switched Multi-Objective Jellyfish Optimization (SMOJO) algorithm, the weight value is initialized in the EDNN. The Gaussian radial function is utilized as the activation function. The proposed EDNN's performance is examined with the already available algorithms in the experimental analysis. Based on the RMSE, MAE, MAPE, and R² metrics, the performance of the proposed EDNN is compared to the existing DNN, CNN, ANN, and SVM methods. Further, according to the metrices, the proposed EDNN performs better. Moreover, the effectiveness of proposed EDNN is examined based on the accuracy, precision, recall, and F-Measure metrics. With the already-existing algorithms i.e., JO, GWO, PSO, and GA, the fitness for the proposed SMOJO algorithm is also examined. The proposed SMOJO algorithm achieves a higher fitness value than the already available algorithm.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제37권4호
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• pp.591-614
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• 2023

오래전부터 NCTM(National Council of Teachers of Mathematics)과 같은 수학교육기관에서 글쓰기는 필수적인 부분으로 언급해 왔다. 그리고 최근 교육부 조사에 따르면 코로나 시대 이후 기초학력 저하의 심각성을 보고하였다. 본 연구는 수학교육에서 수학 쓰기를 재정의하고, 현재 수학교육에서 제시되는 역량 중 과거부터 언급해 온 문제해결, 의사소통, 추론 영역을 중심으로 글쓰기의 역할과 그 중요성을 파악하는 것을 목적으로 하였다. 연구 결과에서 문제해결에서의 글쓰기는 인지적인 부분을 정리함으로써 개념과 방법을 습득할 수 있는 능력을 기를 수 있고, 의사소통에서의 글쓰기는 재인지 과정을 통해 자신감을 가질 수 있으며, 추론에서의 글쓰기는 단계적으로 어떤 부분이 부족한지를 스스로 파악할 수 있다. 특히, AI를 활용하는 미래 사회에서 수업 환경이 달라지는 만큼 쓰기를 통한 진위성 판단이나 올바른 쓰기 문화 정착을 위해 연구가 이루어질 필요가 있다.

• 치위생과학회지
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• 제23권4호
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• pp.330-342
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• 2023

Background: As the medical knowledge base grows at an accelerating rate, evidence-based clinical performance becomes increasingly important for providing quality care. Previous studies have highlighted the need to promote job crafting to actualize evidence-based practical skills in the medical field. This study aimed to investigate the degree of evidence-based practice among dental hygienists and assess the impact of job crafting on the evidence-based practical skills of dental hygienists. Methods: Dental hygienists working at dental hospitals and clinics in Seoul and Gyeonggi Province were surveyed between February 28 and April 6, 2023. The sample was comprised of 267 participants. The hypotheses were tested independent t-tests, one-way analysis of variance, Pearson's correlation coefficients, and multiple regression analyses using SPSS 29.0. Results: The degree of job crafting by dental hygienists demonstrated significant differences based on educational attainment, workplace size, and workplace type. Evidence-based practical skills exhibited significant variations based on educational attainment and job position. All job crafting subfactors demonstrated positive correlations with evidence-based practical skills. The job crafting subfactors affecting the evidence-based practical skills of dental hygienists were 'increasing structural job resources' and 'increasing challenging job demands,' which together explained 38.7% of the variance in evidence-based practical skills. Conclusion: This study demonstrates that job crafting was positively and significantly correlated with evidence-based practical skills. To strengthen the job crafting ability of dental hygienists, improving environmental conditions and fostering an organizational culture that motivates continued participation in education is necessary. The development and promotion of programs that enable learning of the latest evidence should be actively pursued. Additionally, regular attendance at workshops and participation in organizational evidence-based practice education programs are necessary.