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| WoS | SCOPUS | Document Type | Document Title | Abstract | Authors | Affiliation | ResearcherID (WoS) | AuthorsID (SCOPUS) | Author Email(s) | Journal Name | JCR Abbreviation | ISSN | eISSN | Volume | Issue | WoS Edition | WoS Category | JCR Year | IF | JCR (%) | FWCI | FWCI Update Date | WoS Citation | SCOPUS Citation | Keywords (WoS) | KeywordsPlus (WoS) | Keywords (SCOPUS) | KeywordsPlus (SCOPUS) | Language | Publication Stage | Publication Year | Publication Date | DOI | JCR Link | DOI Link | WOS Link | SCOPUS Link |
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| ○ | ○ | Article | Effectiveness of Postoperative Dietary Intervention in Patients with Gastric Cancer who Underwent Gastrectomy: Quasi-Experimental Study Design | Objectives: This article aims to investigate the effects of a postoperative dietary intervention on fatigue, self-efficacy in managing gastrointestinal side effects, self-efficacy for nutritional management, self-care activity, and unmet nursing needs among patients with gastric cancer who have undergone gastrectomy. Methods: We used a quasi-experimental study design (nonequivalent control group pretest-posttest). Data were collected from 59 patients with gastric cancer (30 in the experimental group and 29 in the control patients) hospitalized for gastrectomy in Daegu, South Korea. The control group completed a preintervention survey, received routine care, and then completed a postintervention survey. After the control group finished their routine care and tests, the experimental group received a postoperative dietary intervention. This intervention included individual face-to-face education and telephone counseling on managing gastrectomy side effects, eating methods to prevent symptoms, foods to avoid, ways to consume sufficient calories, maintaining a balanced diet, and pledge writing. The control group served as a waitlist control. After all interventions and tests for the experimental group were completed, the same dietary intervention was offered to the control group upon their request. This experimental study was conducted from June 2021 to February 2023. Results: Compared with the control group, the experimental group showed significant improvements in fatigue (P = .005), self-efficacy in managing gastrointestinal side effects (P < .001), self-efficacy for nutritional management (P = .03), self-care activity (P < .001), and unmet nursing needs (P < .001). Conclusion: Postoperative dietary interventions contribute to improving self-efficacy, fatigue levels, and self-care activity among patients with gastric cancer. Implications for Nursing Practice: Upon discharge, implementing a needs-based and loss-framed message-based dietary intervention, alongside routine discharge education, for patients who underwent gastrectomy for gastric cancer can enhance fatigue levels, self-efficacy in managing nutrition and gastrointestinal side effects, self-care activity, and unmet nursing needs. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. | Kim, Dahye; Lee, Myung Kyung | Kyungpook Natl Univ, Coll Nursing, Grad Sch, Daegu, South Korea; Kyungpook Natl Univ, Res Inst Nursing Innovat, Coll Nursing, Daegu, South Korea | 57210748420; 40661513200 | mlee@knu.ac.kr; | SEMINARS IN ONCOLOGY NURSING | 0749-2081 | 1878-3449 | 41 | 1 | 0 | 2025-05-07 | 1 | 1 | Postoperative dietary interventions; Gastric cancer; Gastrointestinal surgery; Nutritional deficiencies; Self-care activity; Nurse-led; Oncology nursing; Experimental study; Loss-framed; Malnutrition | CHALLENGES; SURVIVORS; EFFICACY; NURSE; NEEDS | Experimental study; Gastric cancer; Gastrointestinal surgery; Loss-framed; Malnutrition; Nurse-led; Nutritional deficiencies; Oncology nursing; Postoperative dietary interventions; Self-care activity | Adult; Aged; Fatigue; Female; Gastrectomy; Humans; Male; Middle Aged; Postoperative Care; Republic of Korea; Self Efficacy; Stomach Neoplasms; adult; aged; fatigue; female; gastrectomy; human; male; middle aged; postoperative care; procedures; self concept; South Korea; stomach tumor; surgery | English | 2025 | 2025-02 | 10.1016/j.soncn.2024.151797 | 바로가기 | 바로가기 | 바로가기 | |||||||||
| ○ | Article | Effects of a Narrative Therapy Training Program Utilizing MetaverseZEP for Psychiatric Mental Health Nurses | Purpose: This study aimed to evaluate the effects of a narrative therapy training program using MetaverseZEP on attitudes toward severe mental illness, counselor self-efficacy, and emotional exhaustion in psychiatric mental health nurses. Methods: A non-equivalent control group pretest-posttest design was used. Participants included 47 psychiatric mental health nurses. The program consisted of 14 sessions, each lasting 60 minutes, conducted over four weeks (three to four sessions per week). Its effectiveness was assessed using pre-test, post-test, and follow-up test with the Attitudes to Severe Mental Illness Scale, Counselor Self-Efficacy Scale, and Emotional Exhaustion Scale. Data were analyzed using x2 tests, Fisher’s exact probability test, t-tests, and repeated measures ANOVA in IBM SPSS Statistics 25. Results: Participants in the experimental group showed significant improvements in attitudes toward severe mental illness (F=3.29, p=.047) and counseling self-efficacy (F=7.14, p=.002) compared to the control group. Conclusion: The narrative therapy training program using MetaverseZEP effectively enhances counselor self-efficacy and attitudes toward severe mental illness in psychiatric mental health nurses. These findings suggest its potential as a valuable nurse training program. © 2025 The Korean Academy of Psychiatric and Mental Health Nursing. | Shin, Jina; Kim, Hee Sook | College of Nursing, The Research Institute of Nursing Science, Kyungpook National University, Daegu, South Korea; College of Nursing, The Research Institute of Nursing Science, Kyungpook National University, Daegu, South Korea | 59752284200; 58668801200 | hskim4114@nate.com; | Journal of Korean Academy of Psychiatric and Mental Health Nursing | 1225-8482 | 34 | 1 | 0 | 2025-05-07 | 0 | Counselors; Narrative therapy; Psychiatric nursing; Self-efficacy | Korean | Final | 2025 | 10.12934/jkpmhn.2025.34.1.79 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Article | Effects of Shared Leadership and Communication Competence on Nursing Team Effectiveness in Comprehensive Nursing Service Units: Focusing on the Team Nursing System; [간호 ‧ 간병통합서비스 병동에서의 공유리더십과 의사소통능력이 팀 효과성에 미치는 영향: 팀 간호체계를 중심으로] | This study aimed to identify the effects of shared leadership, communication skills, and team effectiveness, as perceived by nurses and nursing assistants in comprehensive nursing service units. Methods: A cross-sectional research design was adopted, and the sample included 306 nurses, nurse assistants, and caregivers working in nine hospitals with fewer than 500 beds in two South Korean cities. The data were analyzed using descriptive statistics, t-tests, ANOVA, Pearson’s correlation coefficient, and four-step hierarchical regression analysis. Results: The factors influencing team effectiveness in the hierarchal multiple regression analysis were shared leadership (β=.57, p<.001) and communication skills (β=.18, p<.001). These factors explained 49% of the total variance. Conclusion: To enhance team effectiveness in compressive nursing service units, educational programs focusing on shared leadership and communication skills among nurses, nursing assistants, and caregivers must be developed. © 2025 Korean Academy of Nursing Administration. | Kim, Hye Jin; Lee, Eunjoo | College of Nursing, Kyungpook National University, South Korea; College of Nursing, Research Institute of Nursing Innovation, Kyungpook National University, South Korea | 58369326600; 56502620400 | jewelee@knu.ac.kr; | Journal of Korean Academy of Nursing Administration | 1225-9330 | 31 | 2 | 0 | 2025-05-07 | 0 | Communication; Leadership; Nursing care service; Patient care team; Team effectiveness | Korean | Final | 2025 | 10.11111/jkana.2025.31.2.143 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Article | Effects of subtitle sequence on L2 vocabulary acquisition through video viewing | This study explores how subtitle order affects vocabulary acquisition in English video viewing among Korean learners. It specifically examines whether different subtitle sequences (English-to-Korean, Korean-to-English, and Korean-to-Korean) influence the learning of word forms, meanings, and their interplay. Sixty intermediate-level Korean university students participated, each assigned to one of the three conditions and watching a TED-Ed video twice. Results show that while the Korean-to-English subtitle order yielded the greatest improvement in word form recognition, the English-to-Korean subtitle order led to higher performance in immediate and delayed meaning recall tests. In the meaning recognition post-test, the Korean-to-English subtitle group achieved the highest scores, though group differences were not statistically significant. Notably, prior vocabulary knowledge was significantly correlated with learning outcomes, especially in the Korean-to-English subtitle condition, suggesting its critical role in vocabulary learning. This study highlights the potential of sequential subtitle use in reducing cognitive load and enhancing vocabulary learning in both classroom and independent video-based learning contexts. © 2025 KASELL All rights reserved. | Lee, Jooeon; Kim, Donghyun | Department of English Language and Literature, Kyungpook National University, South Korea; Department of English Language and Literature, Kyungpook National University, South Korea | 59905544400; 57199164041 | donghyun@knu.ac.kr; | Korean Journal of English Language and Linguistics | 1598-1398 | 25 | 0 | 2025-06-11 | 0 | audiovisual input; captions; incidental vocabulary learning; prior vocabulary knowledge; subtitles; vocabulary recall; vocabulary recognition | Korean | Final | 2025 | 10.15738/kjell.25..202504.538 | 바로가기 | 바로가기 | |||||||||||||||||
| ○ | ○ | Proceedings Paper | Efficient Medical Image Segmentation Using Probabilistic KNN Label Downsampling | Deep learning-based medical image segmentation has advanced diagnostic precision and treatment planning. However, training on high-dimensional data remains computationally challenging due to substantial memory and processing demands. Downsampling is a widely employed strategy that reduces memory requirements and accelerates training processes to mitigate these issues. Conventionally, nearest neighbor (NN) interpolation has been utilized to downsample ground truth labels. However, this approach often leads to loss of class information and can detrimentally impact segmentation performance compared to training on the original high-dimensional data. This study proposes a Probabilistic K-Nearest Neighbors (PKNN) downsampling method that effectively preserves class details over NN interpolation. Evaluations at half and quarter resolutions with varying K values demonstrate that PKNN consistently outperforms NN interpolation on the KNUH Abdominal CT and CVC-ClinicDB datasets, improving Intersection over Union (IoU) by up to 2.29% and 2.88%, respectively. PKNN's performance closely approximates models trained on full-resolution data, confirming its suitability for maintaining segmentation accuracy despite reduced resolution. | Ali, Shahzad; Khan, Muhammad Salman; Lee, Yu Rim; Park, Soo Young; Tak, Won Young; Jung, Soon Ki | Kyungpook Natl Univ, Sch Comp Sci & Engn, Seoul, South Korea; Kyungpook Natl Univ Hosp, Dept Internal Med, Coll Med, Seoul, South Korea | 57709386500; 58725569000; 59712240600; 8620671000; 59802036700; 57226791905 | shahzadali@knu.ac.kr; salmandurrani@knu.ac.kr; skjung@knu.ac.kr; | 40TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING | 0 | 2025-06-11 | 0 | 0 | Probabilistic KNN; Nearest neighbor interpolation; Label downsampling; Medical image segmentation | INTERPOLATION METHODS | label downsampling; medical image segmentation; nearest neighbor interpolation; probabilistic KNN | Deep learning; k-nearest neighbors; Advanced diagnostics; Down sampling; High dimensional data; Label downsampling; Medical image segmentation; Nearest neighbor interpolation; Nearest-neighbour; Probabilistic KNN; Probabilistics; Treatment planning; Image segmentation | English | 2025 | 2025 | 10.1145/3672608.3707967 | 바로가기 | 바로가기 | 바로가기 | |||||||||||||
| ○ | Conference paper | ELLAR: An Action Recognition Dataset for Extremely Low-Light Conditions with Dual Gamma Adaptive Modulation | In this paper, we address the challenging problem of action recognition in extremely low-light environments. Currently, available datasets built under low-light settings are not truly representative of extremely dark conditions because they have a sufficient signal-to-noise ratio, making them visible with simple low-light image enhancement methods. Due to the lack of datasets captured under extremely low-light conditions, we present a new dataset with more than 12K video samples, named Extremely Low-Light condition Action Recognition (ELLAR). This dataset is constructed to reflect the characteristics of extremely low-light conditions where the visibility of videos is corrupted by overwhelming noise and blurs. ELLAR also covers a diverse range of dark settings within the scope of extremely low-light conditions. Furthermore, we propose a simple yet strong baseline method, leveraging a Mixture of Experts in gamma intensity correction, which enables models to be flexible and adaptive to a range of low illuminance levels. Our approach significantly surpasses state-of-the-art results by 3.39% top-1 accuracy on ELLAR dataset. The dataset and code are available at https://github.com/knu-vis/ELLAR. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. | Ha, Minse; Bae, Wan-Gi; Bae, Geunyoung; Lee, Jong Taek | School of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea; School of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea; School of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea; School of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea | 59254381700; 59485584600; 59154157500; 24341317500 | jongtaeklee@knu.ac.kr; | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | 0302-9743 | 15477 LNCS | 0 | 2025-05-07 | 0 | Action recognition; Extremely low-light conditions dataset | Adaptive modulation; Light modulation; Action recognition; Dark conditions; Extremely low-light condition dataset; Light environment; Low light; Low light conditions; Low-light images; Noise ratio; Signal to noise; Simple++; Image enhancement | English | Final | 2025 | 10.1007/978-981-96-0960-4_2 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Conference paper | Emotion-Driven Interaction Design in Regional Public Brand Apps- Enhancing User Experience Through Emotional Engagement | This study aims to explore how emotion-driven interaction design affects user experience, particularly in the context of regional public brand app design. From a user experience perspective, this paper focuses on analyzing the role of emotional factors in the user-app interaction process and how design optimization can enhance emotional experience and satisfaction. First, a literature review was conducted to analyze the relationship between user emotional experience and app design. Then, using case analysis and cluster analysis, relevant market products were investigated, and users’ emotional experience elements were categorized into visceral, behavioral, and reflective levels. The extracted design elements were combined with the user experience honeycomb model to propose design principles for regional public brand apps under the user emotional experience perspective. Following this, user behavior flow analysis was used to identify design points from three dimensions of emotional experience, leading to specific design strategies. Ultimately, a regional public brand app design scheme was developed and evaluated for user satisfaction. The results indicate that integrating user emotional experience theory into the design of regional public brand apps meets users’ diverse emotional needs from sensory, interactive, and emotional dimensions. This integration not only enhances the effectiveness and sustainability of sales and communication for regional public brands but also meets the new development requirements of the agricultural industry. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. | Guo, Qihan; Shi, Mingxi; Zhang, Peng; Li, Ruichi; Lee, Kyoungyong; Xu, Zhe | Wuhan University of Technology, Hubei, Wuhan, 430070, China; Kyungpook National University, Daegu, 41566, South Korea; Yanshan University, Hebei, Qinhuangdao, 066000, China; Yanshan University, Hebei, Qinhuangdao, 066000, China; Kyungpook National University, Daegu, 41566, South Korea; Yanshan University, Hebei, Qinhuangdao, 066000, China | 59170865600; 59170301700; 59926873800; 59927139200; 58246924400; 59954966800 | 395333802@qq.com; | Communications in Computer and Information Science | 1865-0929 | 2528 CCIS | 0 | Emotion-Driven Design; Interaction Design; Regional Public Brand; User Emotional Experience; User Experience | Agriculture; Human computer interaction; User centered design; User experience; User profile; Design optimization; Emotion-driven design; Emotional engagements; Emotional experiences; Emotional factors; Interaction design; Interaction process; Regional public brand; User emotional experience; Users' experiences; Behavioral research | English | Final | 2025 | 10.1007/978-3-031-94168-9_32 | 바로가기 | 바로가기 | ||||||||||||||||||
| ○ | Article | Enhancing process monitoring and control in novel carbon capture and utilization biotechnology through artificial intelligence modeling: An advanced approach toward sustainable and carbon-neutral wastewater treatment | Integrating carbon capture and utilization (CCU) technologies into wastewater treatment plants (WWTPs) is essential for mitigating greenhouse gas (GHG) emissions and enhancing environmental sustainability, but further advancements in process monitoring and control are critical to optimizing treatment performance. This study investigates the application of artificial intelligence (AI) modeling to enhance process monitoring and control in a novel integrated CCU biotechnology with a moving bed biofilm reactor (MBBR) sequenced with an algal photobioreactor (aPBR). This system reduces GHG and odour emissions simultaneously. Several machine learning (ML) models, including artificial neural networks (ANNs), support vector machines (SVM), random forest (RF), and least-squares boosting (LSBoost), were tested. The LSBoost was the most suitable for modeling the MBBR + aPBR system, exhibiting the highest accuracy in predicting CO2 (R2 = 0.97) and H2S (R2 = 0.95) emissions from the MBBR. LSBoost also achieved the highest accuracy for predicting CO2 (R2 = 0.85) and H2S (R2 = 0.97) outlet concentrations from the aPBR. These findings underscore the importance of aligning AI algorithms to the characteristics of the treatment technology. The proposed AI models outperformed conventional statistical methods, demonstrating their ability to capture the complex, nonlinear dynamics typical of processes in environmental technologies. This study highlights the potential of AI-driven monitoring and control systems to significantly improve the efficiency of CCU biotechnologies in WWTPs for climate change mitigation and sustainable wastewater management. © 2025 | Cairone, Stefano; Oliva, Giuseppina; Romano, Fabiana; Pasquarelli, Federica; Mariniello, Aniello; Zorpas, Antonis A.; Pollard, Simon J.T.; Choo, Kwang-Ho; Belgiorno, Vincenzo; Zarra, Tiziano; Naddeo, Vincenzo | Sanitary Environmental Engineering Division (SEED), Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II #132, SA, Fisciano, 84084, Italy; Sanitary Environmental Engineering Division (SEED), Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II #132, SA, Fisciano, 84084, Italy; Sanitary Environmental Engineering Division (SEED), Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II #132, SA, Fisciano, 84084, Italy; Sanitary Environmental Engineering Division (SEED), Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II #132, SA, Fisciano, 84084, Italy; Sanitary Environmental Engineering Division (SEED), Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II #132, SA, Fisciano, 84084, Italy; Laboratory of Chemical Engineering and Engineering Sustainability, Faculty of Pure and Applied Sciences, Open University of Cyprus, Giannou Kranidioti 89, Latsia, Nicosia, 2231, Cyprus; Cranfield University, Water Science Institute, Faculty of Engineering and Applied Sciences, Bedfordshire, Cranfield, MK43 0AL, United Kingdom; Department of Environmental Engineering, Kyungpook National University (KNU), 80 Daehak-ro, Bukgu, Daegu, 41566, South Korea; Sanitary Environmental Engineering Division (SEED), Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II #132, SA, Fisciano, 84084, Italy; Sanitary Environmental Engineering Division (SEED), Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II #132, SA, Fisciano, 84084, Italy; Sanitary Environmental Engineering Division (SEED), Department of Civil Engineering, University of Salerno, Via Giovanni Paolo II #132, SA, Fisciano, 84084, Italy | 58798490200; 20735093300; 59391152900; 58942420600; 58167308000; 6603816522; 7101930669; 7102083272; 6508019638; 16176861400; 57225215311 | vnaddeo@unisa.it; | Chemosphere | 0045-6535 | 376 | 0 | 2025-05-07 | 1 | Advanced process control; Bioprocess modeling; Carbon neutrality; Gaseous emission control; Integrated algal biotechnology; Odour treatment technology; Supervised machine learning | Artificial Intelligence; Biofilms; Biotechnology; Carbon; Carbon Dioxide; Carbon Sequestration; Greenhouse Gases; Machine Learning; Neural Networks, Computer; Photobioreactors; Support Vector Machine; Waste Disposal, Fluid; Wastewater; Adaptive boosting; Carbon capture and storage; Carbon sequestration; Direct air capture; Greenhouse gas emissions; Kyoto Protocol; Low emission; Support vector machines; carbon dioxide; hydrogen sulfide; carbon; carbon dioxide; Advanced Process Control; Bioprocess modeling; Carbon neutralities; Emissions control; Gaseous emission control; Integrated algal biotechnology; Odor treatment technology; Odour treatments; Supervised machine learning; Treatment technologies; artificial intelligence; biofilm; biotechnology; climate change; control system; greenhouse gas; machine learning; wastewater treatment; wastewater treatment plant; Article; artificial intelligence; artificial neural network; biotechnology; carbon capture; carbon neutrality; carbon utilization; concentration (parameter); controlled study; greenhouse gas; greenhouse gas emission; least square analysis; machine learning; nonlinear system; process control; process monitoring; random forest; support vector machine; sustainable development; waste water management; biofilm; biotechnology; carbon sequestration; chemistry; photobioreactor; procedures; sewage; wastewater; Carbon capture and utilization | English | Final | 2025 | 10.1016/j.chemosphere.2025.144299 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Article | Enhancing QA System Evaluation: An In-Depth Analysis of Metrics and Model-Specific Behaviors | The purpose of this study is to examine how evaluation metrics influence the perception and performance of question answering (QA) systems, particularly focusing on their effectiveness in QA tasks. We compare four different models: BERT, BioBERT, Bio-ClinicalBERT, and RoBERTa, utilizing ten EPIC-QA questions to assess each model’s answer extraction performance. The analysis employs both semantic and lexical metrics. The outcomes reveal clear model-specific behaviors: Bio-ClinicalBERT initially identified irrelevant phrases before focusing on relevant information, whereas BERT and BioBERT continually converge on similar answers, exhibiting a high degree of similarity. RoBERTa, on the other hand, demonstrates effective use of long-range dependencies in text. Semantic metrics outperform lexical metrics, with BERTScore attaining the maximum accuracy (0.97), highlighting the significance of semantic evaluation. Our findings indicate that the choice of evaluation metrics significantly influences the perceived efficacy of models, suggesting that semantic metrics offer more nuanced and insightful assessments of QA system performance. This study contributes to the field of natural language processing and machine learning by providing guidelines for selecting evaluation metrics that align with the strengths and weaknesses of various QA approaches. © 2025 [Heesop Kim, Aluko Ademola] This article is distributed under the Creative Commons Attribution License (CC BY), allowing unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. It is published by the Korea Institute of Science and Technology Information (KISTI). | Kim, Heesop; Ademola, Aluko | Department of Library Information Science, Kyungpook National University, Korea National Library of Korea, Daegu, South Korea; Department of Library Information Science, Kyungpook National University, Daegu, South Korea | 8865330100; 58062880800 | heesop@knu.ac.kr; | Journal of Information Science Theory and Practice | 2287-9099 | 13 | 1 | 0 | 2025-06-11 | 0 | BERT; evaluation metrics; natural language processing; question answering systems; transformer models | English | Final | 2025 | 10.1633/jistap.2025.13.1.6 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Conference paper | Enhancing RSA with Random Insertion Method: A New Approach to Secure Cryptography | RSA was developed in 1978 and it has been used widely. The Random Insertion Method (RIM) in cryptography is a newly devised technique incorporating randomness into the encryption process. In this work, we find new transcendental numbers that are useful for encryption algorithms. Combining the concepts of RSA and RIM, three types of encryption and decryption procedures are developed. Computational complexity required in decrypting the encryption by the proposed cryptosystem in terms of the size of the encryption is analysed. It demonstrates that compared to RSA using a public key, the number of bit operations TRSA-RIM needed for decryption is significantly higher than that of traditional RSA TRSA: TRSA≪TRSA-RIM. Since the encryption of a message in our joint RSA-RIM cryptosystem makes use of both the RSA and RIM, the resulting encryption has high randomness. It has the needed confusion and diffusion to the interceptor; further, it is not necessary to make blocks of the message even though the original message is very long. For the message encryption, RSA uses the power of the numerical message which comes from the numerical value of the alphabets, whereas our approach uses numerical properties independent of alphabet values. This gives a very secure encryption of messages even if intercepted. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. | Raja Durai, R.S.; Hwang, Suk-Geun; Kumar, Ashwini; Nam, Ki-Bong | Department of Mathematics, Jaypee University of Information Technology, Solan, Waknaghat, 173 234, India; Department of Mathematics Education, Kyungpook National University, Taegu, 41566, South Korea, Department of Mathematics, University of Wisconsin-Whitewater, Whitewater, 53190, WI, United States; Department of Applied Sciences, Chitkara University, Punjab, Rajpura, 140401, India; Department of Mathematics, University of Wisconsin-Whitewater, Whitewater, 53190, WI, United States | 23992685200; 7404626569; 58845366200; 8582936400 | rsraja.durai@juit.ac.in; | Lecture Notes in Networks and Systems | 2367-3370 | 1284 LNNS | 0 | 2025-05-07 | 0 | Computational complexity; Cryptography; Gelfond-Schneider theorem; Random insertion method; RSA encryption; Transcendental number | Encryption algorithms; Encryption and decryption; Gelfond-schneider theorem; Insertion methods; New approaches; Random insertion method; Random insertions; RSA encryption; Schneider; Transcendental number; Encryption algorithms | English | Final | 2025 | 10.1007/978-3-031-85363-0_26 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Review | Epigenetic regulation of angiogenesis and its therapeutics | Angiogenesis, the formation of new blood vessels from preexisting ones, is essential for normal development, wound healing, and tissue repair. However, dysregulated angiogenesis is implicated in various pathological conditions, including cancer, diabetic retinopathy, and atherosclerosis. Epigenetic modifications, including DNA methylation, histone modification, and noncoding RNAs (e.g., miRNAs), play a crucial role in regulating angiogenic gene expression without altering the underlying DNA sequence. These modifications tightly regulate the balance between pro-angiogenic and anti-angiogenic factors, thereby influencing endothelial cell proliferation, migration, and tube formation. In recent years, epigenetic drugs, such as DNA methyltransferase inhibitors (e.g., azacitidine, decitabine), histone deacetylase inhibitors (e.g., vorinostat, romidepsin), and BET inhibitors (e.g., JQ1), have emerged as promising therapeutic strategies for targeting abnormal angiogenesis. These agents modulate gene expression patterns, reactivating silenced tumor suppressor genes while downregulating pro-angiogenic signaling pathways. Additionally, miRNA modulators, such as MRG-110 and MRG-201, provide precise regulation of angiogenesis-related pathways, demonstrating significant therapeutic potential in preclinical models. This review underscores the intricate interplay between epigenetic regulation and angiogenesis, highlighting key mechanisms and therapeutic applications. Advancing our understanding of these processes will enable the development of more effective and targeted epigenetic therapies for angiogenesis-related diseases, paving the way for innovative clinical interventions. © The Author(s) 2025. | Choi, Dong Kyu | BK21 FOUR KNU Creative BioResearch Group, School of Life Science and Biotechnology, Kyungpook National University, Daegu, South Korea | 57215816624 | dongkyu@knu.ac.kr; | Genomics and Informatics | 2234-0742 | 23 | 1 | 0 | 2025-05-07 | 1 | Angiogenesis; Epigenetic drugs; Epigenetic modification | English | Final | 2025 | 10.1186/s44342-025-00038-3 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Erratum | Erratum: Development of Lead-free Ag2Te QDs-based Photodetector for SWIR Detection (Journal of Sensor Science and Technology, 33, 6, (448-452), 10.46670/JSST.2024.33.6.448) | Before Correction ACKNOWLEDGMENT This study has been conducted with the support of the Korea Institute of Industrial Technology as "Train of four (TOF)-based muscle relaxation monitoring with electromyography" (KitechUR-24-0038). This research was financially supported by the Ministry of Small and Medium-sized Enterprises (SMEs) and Startups (MSS), Korea, under the “Regional Specialized Industry, Development Plus Program (R&D, S3366018),” supervised by the Korea Technology and Information Promotion Agency for SMEs. This study was supported by a KOITA grant funded by MSIT (1711199734). After Correction ACKNOWLEDGMENT This study has been conducted with the support of the Korea Institute of Industrial Technology as "Train of four (TOF)-based muscle relaxation monitoring with electromyography" (KitechUR-24-0038). This research was financially supported by the Ministry of Small and Medium-sized Enterprises (SMEs) and Startups (MSS), Korea, under the “Regional Specialized Industry, Development Plus Program (R&D, S3366018),” supervised by the Korea Technology and Information Promotion Agency for SMEs. This study was supported by a KOITA grant funded by MSIT (1711199734). This research was supported by the Korea Water Cluster (KWC) as Korea Water Cluster ProjectLab. This work was supported by the Technology Innovation Program (155736, Development of Miniaturized Sensor Module Technology for Non-invasive Arterial Blood Carbon Dioxide Real-time Monitoring) funded By the Ministry of Trade, Industry & Energy (MOTIE, Korea). © 2025, Korean Sensors Society. All rights reserved. | Choi, Suji; Kwak, Nuri; Kwon, Jin Beom; Jeong, Donggeon; Lee, Won Oh; Jung, Daewoong | Advanced Mobility System Group, Korea Institute of Industrial Technology (KITECH), Daegu, 42994, South Korea, School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, 41566, South Korea; Advanced Mobility System Group, Korea Institute of Industrial Technology (KITECH), Daegu, 42994, South Korea; Advanced Mobility System Group, Korea Institute of Industrial Technology (KITECH), Daegu, 42994, South Korea; Advanced Mobility System Group, Korea Institute of Industrial Technology (KITECH), Daegu, 42994, South Korea; S-package solution co., Ltd, Daegu, 41566, South Korea; Advanced Mobility System Group, Korea Institute of Industrial Technology (KITECH), Daegu, 42994, South Korea | 58017819200; 59498660400; 57191591392; 59498309400; 58782092900; 36019307900 | dwjung@kitech.re.kr; | Journal of Sensor Science and Technology | 1225-5475 | 34 | 1 | 0 | 2025-05-07 | 0 | English | Final | 2025 | 10.46670/jsst.2025.34.1.63 | 바로가기 | 바로가기 | |||||||||||||||||
| ○ | Erratum | Erratum: Fabrication and Evaluation of Single Layer Graphene/SnO2 Based Gas Sensor for NO2 Detection (Journal of Sensor Science and Technology, 33, 6 (493-498), 10.46670/JSST.2024.33.6.498) | The original version of this article (Vol. 33, No. 6, pp.493-498, http://dx.doi.org/10.46670/JSST.2024.33.6.498) contained an error in the acknowledgments. Before Correction ACKNOWLEDGMENT This work was supported by the Technology Development Program (S3366415) funded by the Ministry of SMEs and Startups of Korea (MSS, Korea). Additionally, this study was conducted with the support of the Korea Institute of Industrial Technology under “Development of high-performance pressure sensor for self-diagnosis brake system of hybrid/electric vehicle (Kitech UI-24-0008)”. After Correction ACKNOWLEDGMENT This work was supported by the Technology Development Program (S3366415) funded by the Ministry of SMEs and Startups of Korea (MSS, Korea). Additionally, this study was conducted with the support of the Korea Institute of Industrial Technology under “Development of high-performance pressure sensor for self-diagnosis brake system of hybrid/electric vehicle (Kitech UI-24-0008)”. This research was supported by the Korea Water Cluster (KWC) as Korea Water Cluster ProjectLab. This work was supported by the Technology Innovation Program (155736, Development of Miniaturized Sensor Module Technology for Non-invasive Arterial Blood Carbon Dioxide Real-time Monitoring) funded By the Ministry of Trade, Industry & Energy (MOTIE, Korea). © 2025, Korean Sensors Society. All rights reserved. | Jeong, Dong Hyuk; Jung, Dong Geon; Jung, Daewoong | Mobility System Group, Korea Institute of Industrial Technology (KITECH), Yeongcheon, 38822, South Korea, School of Electronic and Electrical Engineering, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu, 41566, South Korea; Mobility System Group, Korea Institute of Industrial Technology (KITECH), Yeongcheon, 38822, South Korea; Mobility System Group, Korea Institute of Industrial Technology (KITECH), Yeongcheon, 38822, South Korea | 58525972300; 56675241000; 36019307900 | dwjung@kitech.re.kr; | Journal of Sensor Science and Technology | 1225-5475 | 34 | 1 | 0 | 2025-05-07 | 0 | English | Final | 2025 | 10.46670/jsst.2025.34.1.64 | 바로가기 | 바로가기 | |||||||||||||||||
| ○ | Erratum | Erratum: Highly Sensitive Platinum-Decorated Tungsten Oxide for Ultra-Low-Concentration Hydrogen Detection (33, No. 6, (504-509), 10.46670/JSST.2024.33.6.504) | Before Correction ACKNOWLEDGEMENT This study was conducted with the support of the Korea Institute of Industrial Technology for the development of an artificial intelligence-based hydrogen sensor to ensure fuel cell vehicle safety in real driving environments (Kitech UR-24-0028). This work was supported by the Korea Innovation Foundation (INNOPOLIS) grant funded by the Korean government; (MSIT) (2020-DDUP-0348). After Correction ACKNOWLEDGEMENT This study was conducted with the support of the Korea Institute of Industrial Technology for the development of an artificial intelligence-based hydrogen sensor to ensure fuel cell vehicle safety in real driving environments (Kitech UR-24-0028). This work was supported by the Korea Innovation Foundation (INNOPOLIS) grant funded by the Korean government; (MSIT) (2020-DD-UP-0348). This research was supported by the Korea Water Cluster (KWC) as Korea Water Cluster ProjectLab. This work was supported by the Technology Innovation Program (155736, Development of Miniaturized Sensor Module Technology for Non-invasive Arterial Blood Carbon Dioxide Real-time Monitoring) funded By the Ministry of Trade, Industry & Energy (MOTIE, Korea). © 2025, Korean Sensors Society. All rights reserved. | Ha, Yuntae; Jung, Dong Geon; Lee, Junyeop; Yang, Yijun; Han, Uksu; Jung, Daewoong | Korea Institute of Industrial Technology, KITECH 320, Techno sunhwan ro, Yuga-eup, Dalseong-gun, Daegu, 42994, South Korea, School of Electronic and Electrical Engineering, Kyungpook National University 80, Daehak-ro, Buk-gu, Daegu, 41566, South Korea; Korea Institute of Industrial Technology, KITECH 320, Techno sunhwan ro, Yuga-eup, Dalseong-gun, Daegu, 42994, South Korea; Korea Institute of Industrial Technology, KITECH 320, Techno sunhwan ro, Yuga-eup, Dalseong-gun, Daegu, 42994, South Korea; Korea Institute of Industrial Technology, KITECH 320, Techno sunhwan ro, Yuga-eup, Dalseong-gun, Daegu, 42994, South Korea, School of Electronic and Electrical Engineering, Kyungpook National University 80, Daehak-ro, Buk-gu, Daegu, 41566, South Korea; Korea Institute of Industrial Technology, KITECH 320, Techno sunhwan ro, Yuga-eup, Dalseong-gun, Daegu, 42994, South Korea, School of Electronic and Electrical Engineering, Kyungpook National University 80, Daehak-ro, Buk-gu, Daegu, 41566, South Korea; Korea Institute of Industrial Technology, KITECH 320, Techno sunhwan ro, Yuga-eup, Dalseong-gun, Daegu, 42994, South Korea | 58018481200; 56675241000; 57203736115; 58142256700; 58927970700; 36019307900 | dwjung@kitech.re.kr; | Journal of Sensor Science and Technology | 1225-5475 | 34 | 1 | 0 | 2025-05-07 | 0 | English | Final | 2025 | 10.46670/jsst.2025.34.1.65 | 바로가기 | 바로가기 | |||||||||||||||||
| ○ | Article | Evaluating effectiveness of pre-parental education for university students using Kirkpatrick model | Pre-parental education is designed to equip prospective parents with essential parenting skills. Korea recently introduced it alongside population education as part of a broader strategy to address declining birth rates. However, there remains a scarcity of comprehensive studies evaluating its effectiveness in influencing childbirth-related attitudes. The Kirkpatrick training evaluation model, which assesses training effectiveness across four stages—reaction, learning, behavior, and results—has been widely applied in educational assessments. This study aims to evaluate how university students' reactions (Level 1) and learning outcomes (Level 2) from pre-parental education impact their expected number of children (a behavioral outcome, Level 3) using the Kirkpatrick model. A 10-week pre-parental education program, Healthy Parenting Recipe, was implemented for university students at K University in D City, South Korea, during the second semester of 2024. A total of 67 students participated in the study, and evaluations were conducted up to Level 3. Data were analyzed using SPSS/PC Windows 29.0, employing descriptive statistics and ordinal logistic regression. Greater satisfaction with course content (Level 1: Reaction) was associated with higher expected number of children (B = .234, CI: .063– .405, p = .007). Increased parenting knowledge (Level 2: Learning) also correlated with a higher expected number of children (B = 2.818, CI: .130–5.505, p = .04). Additionally, students prioritizing maternal career continuity expected more children (B = .771, CI: .188–1.353, p = .01), whereas those prioritizing meeting infant needs expected fewer (B = –.556, CI: –1.110– –.003, p = .049). These findings indicate that the results from Levels 1 and 2 significantly influence behavioral outcomes (Level 3). This study validates the interconnections among evaluation levels proposed by the Kirkpatrick model. Furthermore, it confirms the model’s effectiveness as a comprehensive evaluation framework for pre-parental education among university students. © 2025 by the authors; licensee Learning Gate. | Lee, Sung Hee; Lee, Seung A. | College of Nursing, Kyungpook National University, South Korea; Department of Nursing, Keimyung College University, South Korea | 56824569300; 59499147300 | salee@kmcu.ac.kr; | Edelweiss Applied Science and Technology | 2576-8484 | 9 | 5 | N/A | 0 | Education; Low fertility; Offspring; Parenting; University | English | Final | 2025 | 10.55214/25768484.v9i5.7217 | 바로가기 | 바로가기 |
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