bluuebunny/crossref_metadata_2025 huggingface dataset:
Elaboração de guia simplificado de consulta de Enfermagem na graduação
Authors: Rosa Lucelia Cruz , Cortez Débora Oliveira , Franco Joel Levi Ferreira , Santos Ana Paula Baptistelli dos Rei , Viana Lúcia Helena Ferreira , Nakashima Lilian Sanchez , Santos Célia Maria Pinheiro dos , Lima Poliana de Andrade
Published: May 2024

Objetivo: elaborar um guia para subsidiar graduandos de Enfermagem a realizar a Consulta de Enfermagem conforme as etapas do Processo de Enfermagem. Método: trata-se de um a um relato de experiência pois envolve estudos que abordam de forma detalhada a descrição de produtos de inovação tecnológica no caso de desenvolvimento de tecnologias educacionais, com vistas a construir um guia de CE simplificado, sendo realizada a organização do conteúdo para compor o referencial teórico e criado um repertório com imagens, de própria autoria e da literatura. Os conteúdos foram organizados nas cinco etapas do Processo de Enfermagem e nas técnicas propedêuticas de exame físico.  Por toda a extensão do guia foram demonstradas as etapas que devem ser seguidas para a elucidação do diagnóstico de Enfermagem assertivo na consulta propriamente dita. Resultados: a diretriz é chamada de Guia de Consulta de Enfermagem e sua versão final é composta por capa, folha de rosto e 80 páginas, contendo um total de 74 ilustrações. Conclusão: acredita-se que há um grande déficit no ensino de práticas clínicas durante a graduação de Enfermagem. Como solução eficaz, um guia sequencial de exame físico somado às etapas do PE pode servir de treinamento aos estudantes.
Կոմիտասի կերպարը ժամանակակիցների հուշերում / The Character of Komitas in the Memories of Contemporaries
Authors: MNATSAKANYAN YEVA
Published: May 2024

The research was conducted using biographical, descriptive and analytical methods. As a result of the study, we came to a conclusion that the events of Komitas’s life, presented in the memoirs of contemporaries, as a sacred relic and testaments should be passed on to present and future generations, since, as Paruyr Sevak aptly states, "it is not only the people who produce geniuses, but the genius also revitalizes the people with their talent."
GEOGRAPHICAL INDICATIONS UNDER JAPANESE LAW
Authors: СЕДОВ П.Д.
Published: May 2024

Статья посвящена актуальным аспектам регулирования географических указаний в Японии. Отмечается, что в правовом регулировании Японии имеется ряд особенностей, которые присущи только дан- ной юрисдикции. В России географические указания появились относительно недавно и только начинают ста- новиться популярным средством индивидуализации. В связи с тем, что гражданское законодательство Рос- сийской Федерации, регулирующее географическое указание, только появилось, исследование зарубежного опыта регулирования даст возможность успешно адаптировать данный опыт для России. Представляется, что в ближайшей перспективе необходимо продолжать активную регуляторную и практическую работу в направле- нии совершенствования механизма правового регулирования географического указания.

The article is devoted to current aspects of the regulation of geographical indications in Japan. It is noted that the legal regulation of Japan has a number of features that are unique to this jurisdiction. In Russia, geographical indications appeared relatively recently and are just beginning to become a popular means of individualization. Due to the fact that the civil legislation of the Russian Federation regulating geographical indications has just appeared, the study of foreign regulatory experience will make it possible to successfully adapt this experience for Russia. It seems that in the near future it is necessary to continue active regulatory and practical work towards improving the mechanism of legal regulation of geographical indications.
1. TỔNG QUAN VỀ THỰC TRẠNG HIỆN NAY ÁP DỤNG CÓ HIỆU QUẢ CÁC KHUYẾN CÁO MỚI CỦA TỔ CHỨC Y TẾ THẾ GIỚI VỀ PHÁC ĐỒ ĐIỀU TRỊ BỆNH LAO KHÁNG THUỐC TẠI VIỆT NAM VÀ NHỮNG GIẢI PHÁP NĂM 2023
Authors: Thuỷ Hoàng Thị Thanh
Published: May 2024

Mục tiêu: Dựa trên các khuyến cáo của Tổ chức Y tế Thế giới (WHO); thông qua việc đánh giá thực trạng tại Việt Nam; tác giả đề xuất một số giải pháp với hy vọng tham mưu trong việc áp dụng phác đồ điều trị mới cho người bệnh lao kháng thuốc tại Việt Nam một cách an toàn và hiệu quả.
Phương pháp: Tổng quan tài liệu từ các trang web chính thức của quốc tế và Việt Nam, các tài liệu lưu trữ của Chương trình Chống lao Quốc gia Việt Nam.
Kết quả: Khả năng tiếp cận xét nghiệm kháng sinh đồ (KSĐ) đối với thuốc lao hàng hai chưa đầy đủ do hạn chế về nguồn lực, hệ thống vận chuyển mẫu và chuỗi cung ứng sinh phẩm xét nghiệm. Việc theo dõi đáp ứng vi khuẩn học trong quá trình điều trị vẫn còn hạn chế do những khó khăn ảnh hưởng tới khả năng tuân thủ của người bệnh. Theo dõi an toàn thuốc, giám sát điều trị còn bất cập do thiếu nguồn lực và chưa phân tuyến tới y tế cơ sở.
Kết luận: Việt Nam cần đầu tư nguồn lực để cải thiện những hạn chế liên quan đến tiếp cận xét nghiệm KSĐ và các dịch vụ y tế chăm sóc hỗ trợ người bệnh nhằm áp dụng phác đồ mới cho người bệnh lao kháng thuốc một cách an toàn và hiệu quả nhất.
8. BÁO CÁO TRƯỜNG HỢP LAO PHỔI TIỀN SIÊU KHÁNG THUỐC KẾT HỢP LAO GAN TẠI BỆNH VIỆN PHỔI TRUNG ƯƠNG NĂM 2023
Authors: Thái Trương Đức , Cương Nguyễn Kim
Published: May 2024

Mục tiêu: Chúng tôi báo cáo ca bệnh lao phổi tiền siêu kháng thuốc kết hợp lao gan hiếm gặp, với hi vọng góp tiếng nói của mình trong thống kê y học, cũng như chia sẻ kinh nghiệm trong chẩn đoán và điều trị bệnh lý hiếm gặp này.
Báo cáo ca bệnh: Chúng tôi báo cáo một trường hợp bệnh nhân nữ, 21 tuổi nhập viện với triệu chứng ho khạc đờm vàng, thi thoảng lẫn ít dây máu đỏ tươi kèm sốt thất thường về chiều tối, không có triệu chứng về tiêu hóa. Bệnh nhân tình cờ phát hiện tổn thương phúc mạc bao gan và tổn thương nhu mô gan qua siêu âm ổ bụng và được khẳng định chẩn đoán bằng chụp cộng hưởng từ ổ bụng và sinh thiết nốt phúc mạc bao gan. Kết quả mô bệnh học bệnh phẩm sinh thiết là tổn thương viêm hạt gợi ý do lao. Chúng tôi chẩn đoán đây là một trường hợp lao phổi tiền siêu kháng thuốc kết hợp lao phúc mạc và lao gan. Bệnh nhân được điều trị thuốc lao theo hướng dẫn của Chương trình Chống lao Quốc gia và các khuyến cáo trên thế giới. Sau 10 tháng điều trị, bệnh nhân đáp ứng tốt về triệu chứng lâm sàng, tổn thương phổi trên phim X-quang ngực và tổn thương trên phim chụp cộng hưởng từ ổ bụng.
Bàn luận: Bàn luận về dịch tễ, chẩn đoán và điều trị lao gan. Chúng tôi phân tích quá trình chẩn đoán ca bệnh này dựa trên bệnh cảnh lâm sàng và các xét nghiệm chẩn đoán hình ảnh cũng như các xét nghiệm vi sinh và mô bệnh học.
Kết luận: Đây là trường hợp lao phổi tiền siêu kháng kết hợp lao gan hiếm gặp.
12. CÁC YẾU TỐ ẢNH HƯỞNG ĐẾN KẾT QUẢ ĐIỀU TRỊ BỆNH LAO TRẺ EM TẠI KHOA NHI, BỆNH VIỆN PHỔI TRUNG ƯƠNG GIAI ĐOẠN 2017-2020
Authors: Hằng Nguyễn Thị , Sỹ Đinh Ngọc , Vân Hoàng Thanh
Published: May 2024

Mục tiêu: Xác định các yếu tố ảnh hưởng đến kết quả điều trị bệnh lao trẻ em tại khoa Nhi – Bệnh viện Phổi Trung ương.
Phương pháp nghiên cứu: Nghiên cứu mô tả tiến cứu.
Kết quả: Kết quả điều trị bệnh lao của 320 bệnh nhi tại khoa Nhi – Bệnh viện Phổi Trung ương cho thấy: Tỉ lệ điều trị thành công (khỏi và hoàn thành điều trị) là 95,9%; bỏ trị 1,9%; tử vong 2,2%; kéo dài thời gian điều trị là 11,6%; di chứng là 7,5%; nhập viện lại trong thời gian điều trị ngoại trú là 35,3%. Không có sự khác biệt về tỉ lệ điều trị thành công theo bằng chứng vi khuẩn (VK); lao phổi và lao ngoài phổi; nhóm tuổi. Tỉ lệ điều trị thành công thấp hơn ở nhóm lao nhiều cơ quan và nhóm được phát hiện bệnh muộn > 2 tháng. Tỉ lệ tử vong cao ở nhóm lao nhiều cơ quan (3 cơ quan: 27,3%); thời gian bị bệnh > 2 tháng (11,7%). Bỏ trị gặp nhiều nhất ở nhóm trẻ < 5 tuổi (2,6%). Tỉ lệ bệnh nhi kéo dài điều trị gặp nhiều hơn nhóm lao phổi (15,2%); nhóm < 5 tuổi và 10-15 tuổi (13,5% và 13,8%); nhóm chẩn đoán lao có bằng chứng VK (18,5%). Tỉ lệ nhập viện lại cao ở nhóm < 5 tuổi (48,4%) và lao 3 cơ quan (81,8%); lao 4 cơ quan (33,3%). Di chứng gặp chủ yếu ở nhóm lao ngoài phổi (16,5%) và lao 3 cơ quan (9,1%).
Kết luận: Kết quả điều trị bệnh lao ở trẻ em có liên quan với tuổi, bằng chứng vi khuẩn học, thể lao, số cơ quan bị lao và thời gian phát hiện bệnh.
37. ĐẶC ĐIỂM LÂM SÀNG, CẬN LÂM SÀNG VÀ KẾT QUẢ ĐIỀU TRỊ NHẮM TRÚNG ĐÍCH BỆNH NHÂN UNG THƯ PHỔI KHÔNG TẾ BÀO NHỎ CÓ ĐỘT BIẾN KÉP GEN EGFR GIAI ĐOẠN 2019-2023
Authors: Linh Lê Tú , Lượng Đinh Văn , Quảng Lê Văn , Anh Nguyễn Hoàng , Thư Lê Ngọc Minh , Anh Hoàng Huy , My Nguyễn Diệu , Nhung Nguyễn Viết , Trang Nguyễn Thi , Hiếu Dương Hũu , Bộ Dương Danh
Published: May 2024

Đặt vấn đề: Điều trị nhắm trúng đích cho bệnh nhân ung thư phổi không tế bào nhỏ (UTPKTBN) có đột biến EGFR giúp cải thiện chất lượng cuộc sống cũng như thời gian sống thêm cho bệnh nhân. Nghiên cứu của chúng tôi tập trung vào việc đánh giá kết quả điều trị ở những bệnh nhân mắc UTPKTBN có đồng đột biến gen EGFR, từ đó tiên lượng đáp ứng điều trị với thuốc EGFR-TKIs.
Đối tượng và phương pháp nghiên cứu: Nghiên cứu thuần tập hồi cứu được tiến hành dựa trên bộ dữ liệu giải trình tự gen thế hệ mới (NGS) từ tháng 1 năm 2019 đến tháng 6 năm 2023. Tất cả bệnh nhân được chia thành 2 nhóm: Nhóm bệnh nhân có đột biến gen EGFR đơn độc (nhóm 1), và nhóm bệnh nhân có đồng đột biến EGFR (nhóm 2).
Kết quả: Trong số 109 bệnh nhân có đột biến EGFR, 72 bệnh nhân đáp ứng một phần (66,1%), 1 bệnh nhân đáp ứng hoàn toàn (0,9%) và 17 bệnh nhân bệnh ổn định (15,6%); 19 bệnh nhân có bệnh tiến triển (17,4%). ORR là 67,0% và DCR là 82,6%. PFS ở nhóm có đột biến EGFR đơn độc và nhóm có đồng đột biến EGFR tương ứng là 15,03 tháng (CI 95%: 13,17-16,89) và 11,00 tháng (CI 95%: 9,95-12,05) (p= 0,001). Trong số 43 bệnh nhân có đồng đột biến, nhóm mắc thêm đột biến ALK có PFS dài nhất (13,43 tháng), theo sau là nhóm mắc thêm đột biến PIK3CA (11,00 tháng), PFS ở nhóm có thêm đột biến MET thấp nhất (4,77 tháng).
Kết luận: Kết quả điều trị nhắm trúng đích ở bệnh nhân có đồng đột biến thấp hơn so với bệnh nhân đợn đột biến EGFR. NGS nên thực hiện thường quy ở các bệnh nhân để xác định tình trạng đột biến gen trước khi điều trị đích.
46. KHẢO SÁT TÌNH HÌNH SỬ DỤNG CHẾ PHẨM MÁU TẠI BỆNH VIỆN PHỔI TRUNG ƯƠNG TỪ NĂM 2022 ĐẾN 2023
Authors: Dung Tống Thị , Anh Nguyễn Phương , Thành Võ Trọng
Published: May 2024

Mục tiêu: Đánh giá tình hình sử dụng các chế phẩm máu tại Bệnh viện Phổi Trung ương trong 2 năm từ 2022 đến 2023.
Đối tượng và phương pháp nghiên cứu: Phân tích hồi cứu số liệu từ số lượng các chế phẩm máu sử dụng tại Bệnh viện Phổi Trung ương từ tháng 01 năm 2022 đến tháng 12 năm 2023.
Kết quả: Trong 2 năm từ 2022 đến 2023, Bệnh viện Phổi Trung ương đã sử dụng 8.909 đơn vị khối hồng cầu (KHC), 6.402 đơn vị huyết tương tươi đông lạnh (HTTĐL), 2.032 đơn vị khối tiểu cầu (KTC), 89 đơn vị Tủa lạnh giàu yếu tố VIII. Các chế phẩm máu sử dụng có xu hướng giảm vào tháng 1 đến tháng 2 hằng năm. Sử dụng KHC các năm tăng dần: 4.091 đơn vị (2022) và 4.818 đơn vị (2023). Nhóm máu O được sử dụng nhiều nhất với tỷ lệ 45,7%, tiếp đến là nhóm máu B với tỷ lệ 27,6%, nhóm máu A 20,59 %, cuối cùng là nhóm AB với tỷ lệ 6,11%. Các khoasử dụng chế phẩm máu nhiều nhất: Hồi sức tích cực (4.797 đơn vị), Cấp cứu (2175 đơn vị), Lao hô hấp (1.998) và có xu hướng tăng dần theo các năm. Việc sử dụng các chế phẩm khác như KTC, tủa lạnh thay đổi tùy theo tình hình bệnh tật và nguồn cung cấp ở từng thời điểm.
Kết luận: Tổng số chế phẩm máu đã sử dụng từ tháng 1 năm 2022 đến tháng 12 năm 2023 là 17.447 đơn vị. Các chế phẩm máu sử dụng tăng vào các tháng 3,4,5,6 và giảm vào các tháng 1,2. Các khoa sử dụng chế phẩm máu nhiều nhất là khoa Hồi sức tích cực và khoa Cấp cứu. Nhu cầu sử dụng chế phẩm KTC, tủa lạnh thay đổi tùy theo tình hình bệnh tật và nguồn cung cấp chế phẩm máu ở từng thời điểm.
Aprendizaje mediado por videojuegos : la potencialidad de Portal para el estudio del movimiento en el plano
Authors: Margarita del Rosario Escobar
Published: May 2024

La creciente popularidad de los videojuegos a nivel masivo en las últimas tres décadas ha generado un interés significativo en su potencial para el aprendizaje en diversas disciplinas, incluyendo las ciencias naturales. A pesar de esta tendencia, la comprensión de cómo los videojuegos realmente contribuyen al aprendizaje en este contexto sigue siendo incipiente. Esta tesis doctoral presenta los resultados de una investigación enfocada en el aprendizaje de la física del movimiento en el plano a través del videojuego ampliamente conocido, Portal. La presente investigación doctoral se propone contribuir a la comprensión del proceso de aprendizaje del movimiento en el plano mediado por el videojuego Portal. Siguiendo el enfoque teórico del Conocimiento en Piezas (A. A. diSessa, 1993), esta tesis examina en su primera etapa el conocimiento intuitivo expresado por estudiantes universitarios en la interacción con Portal. Estos resultados permitieron el diseño y la implementación de una secuencia didáctica que incorpora el videojuego como herramienta educativa para el estudio del movimiento en el plano. Durante esta segunda etapa, se aborda el desarrollo conceptual de los estudiantes dentro del marco de la teoría de Clases de Coordinación (A. A. diSessa y Wagner, 2005). A través de un análisis cualitativo de los registros de las interacciones, se evidencia un avance significativo tanto en la conceptualización como en la representación y modelización del movimiento en relación a situaciones presentadas en Portal. Este trabajo se propone como contribución al campo de la didáctica de la física, en un momento histórico en donde los videojuegos y las tecnologías digitales desempeñan un papel sin precedentes en la formación y el desarrollo del potencial humano.
Praxis škola i feminizam
Authors: Čakardić Ankica
Published: May 2024

U ovom radu nećemo detaljnije diskutirati o klasičnim praxis temama, već ćemo (1) nakon uvodne skice o praxis orijentaciji, u prvom redu zagrebačkoj školi, (2) pokušati interpretativno-analitički repertoar praxis filozofije dopuniti feminističkim čitanjem ove svjetski poznate intelektualne tradicije. Polazimo od statusa autorica u Praxisu, bilo da je riječ o njihovoj brojčanoj zastupljenosti, njihovim konkretnim teorijskim preokupacijama te rodnoj podjeli rada u uredničkim redovima Časopisa. Pokušat ćemo dati odgovor na neuralgično pitanje zašto je u Praxisu u deset godina njegova postojanja radove objavio vrlo mali broj autorica, ali (3) istovremeno dekonstruirati i analitički iscijediti rijetkopostojeće eseje iz časopisa koji su bliski filozofsko-rodnoj problematici. U tako postavljenom epistemološkom registru (4) ukratko ćemo predstaviti i jedinstvenu marksističko-feminističku filozofiju praksisovke Blaženke Despot, čiji se rad u kontekstu filozofijsko-rodne problematike nažalost neće naći na stranicama Praxisa, već u nekim drugim publikacijama.
PENGUATAN LITERASI POLITIK DAN LITERASI MEDIA BAGI GENERASI CERDAS MENUJU PEMILU 2024
Authors: Fitria Nurul Jannah Lailatul , Rahmadi Andhi Nur
Published: May 2024

The 2024 general election is a political democracy through the electoral system. This involves young people who are the largest group of voters. However, the findings in the field are that the younger generation lacks political literacy and media literacy. So there needs to be a socialisation of strengthening political literacy and media literacy for the younger generation. In order to increase the ability and knowledge of the younger generation related to political literacy and media literacy. The activity was aimed at 25 partners. The implementation of the event went well and was classified as on target, on time, and on purpose. As well as showing results according to the target indicators of the success of programme achievements. The results of monitoring and evaluation on the results of the questionnaire show that all partners have strongly agreed on this socialisation event and can be held further events. The interview results showed that partners experienced changes and increased understanding and actions on partners related to political literacy and media literacy. In particular, partners are able and skilled in searching, selecting and disseminating political information appropriately and using social media more wisely and can help the public regarding public information.
Weights Must Not be Taken Lightly: Burden of Severe Acute Malnutrition Patients in a Rural Tertiary Care Hospital of Maharashtra
Authors: Panjwani Monalisa , Rajib Chatterjee , P Jadhav Jayashree
Published: May 2024

Aim: To identify the magnitude of the burden of co-morbidities of severe acute malnutrition (SAM) in a rural tertiary care centre in Maharashtra, to facilitate necessary planning for care to reduce disparity in urban and rural outcomes of these patients.
Methods: From March 2023 to April 2024, data was collected from the wards of a tertiary care rural hospital. Children with SAM were examined and managed for primary complaints, any associated co morbidities, and nutritional rehabilitation was done.
Results: Presenting diagnosis was most commonly respiratory tract infection, including tuberculosis, and acute gastroenteritis, followed by anemia and acute febrile illness. Co-morbidities such as chronic diarrhoea (12, 14%), congenital heart disease (4, 4.7%), neurological involvement such as cerebral palsy, meningitis, infantile tremor syndrome and spinal muscular atrophy (14, 16.6%), bony abnormalities such as rickets with spine deformities and bowed legs causing abnormal posture and delayed mobility (10, 11.9%) also contributed to the burden in our setup.
Conclusion: This study is an attempt to enhance data about the gravity of malnutrition and thus the need for improvement in facilities for the care of these patients to reduce the vicious cycle of malnutrition and infections.

Key words: Malnutrition, child health, SAM, diet, anemia, edema, wasting
La valoración del contenido emocional en el arte tecnológico
Authors: Villagomez Oviedo Cynthia Patricia
Published: May 2024

El libro aborda el trabajo de los pioneros del arte con el uso de tecnología, así como las incursiones tecnológicas de artistas reconocidos y la experimentación con las posibilidades artísticas de la tecnología, en una primera instancia, de ingenieros y científicos. Se realiza una descripción caracterológica del arte con el uso de tecnología, la importancia de la interacción y la intersubjetividad entre la obra y el público; esto como preámbulo para llegar a una comprensión de la importancia de las emociones en el arte y la estética, por lo que se hace una aproximación al proceso que desencadenan las emociones, los sentimientos y las acciones, así como las reacciones que cada individuo es capaz de experimentar dependiendo de las conexiones que establezca con determinadas obras artísticas. Es debido a lo anterior que se describen y analizan diversas obras por la emoción que provocan, al tiempo que se discurre sobre la interacción, la intersubjetividad y el ciberespacio, así como el comportamiento humano en torno a las emociones y el arte tecnológico. Se analizan obras de arte con el uso de tecnología o arte electrónico donde las emociones son el centro y tema principal de la obra. Finalmente, en este libro se describen algunas de las principales emociones y las obras más representativas que para cada emoción existen en el arte tecnológico.
Using Cross-Cultural Machine Translation Technology to Promote Communication and Cooperation in English Courses
Authors: XiaoLei Song
Published: May 2024

In an increasingly globalized world, effective cross-cultural communication and cooperation are paramount skills for individuals across various domains. This research paper investigates the integration of machine translation technology into English language courses as a means to enhance cross-cultural communication skills and foster cooperation among diverse linguistic communities. The study explores the efficacy of machine translation tools in facilitating language comprehension, expression, and interaction among learners from different cultural backgrounds. Drawing on both theoretical frameworks and empirical evidence, the paper examines the impact of machine translation on language learning outcomes, intercultural competence development, and collaborative learning experiences. Additionally, the research evaluates the perceptions, attitudes, and experiences of students and instructors towards the integration of machine translation technology in English language education. Through a combination of qualitative and quantitative analyses, this study contributes to the understanding of how technology can be leveraged to bridge linguistic and cultural divides in educational settings. The findings offer valuable insights into the potential benefits and challenges associated with the use of machine translation technology for promoting cross-cultural communication and cooperation in English courses, with implications for curriculum design, pedagogical practices, and future research in language education and technology-enhanced learning..
Optimization algorithm of 500kVGIS circuit breaker electric field simulation based on GPU acceleration
Authors: Dongwen Zheng
Published: May 2024

It proposes an optimization approach for electric field simulation in 500kV gas-insulated switchgear (GIS) circuit breakers that use GPU acceleration. Accurate modelling of electric field distribution within GIS circuit breakers is critical for assuring the dependability and safety of high voltage power systems. However, the computational complexity of simulating these systems presents substantial obstacles to established approaches. The goal of this work is to improve the speed, efficiency, and scalability of electric field simulations by leveraging GPU parallel processing capabilities. They methodically build and refine the simulation algorithm, utilizing techniques such as parallel algorithm design, GPU architecture optimization, and efficient memory management. Through rigorous performance studies, they demonstrate significant increases in computational efficiency relative to CPU-based techniques, with an average speed up of 15x. Furthermore, the scalability of the GPU-accelerated method is evaluated, demonstrating near-linear scalability up to 8 GPUs. Validation against experimental observations and analytical models indicates that the simulation findings are accurate and robust. This study helps the progress of electric field simulation tools for GIS circuit breakers by providing insights into electric field behaviour and aiding design optimization and performance evaluation in high voltage power systems.
Computational Analysis of Predicting Stress Intensity Factor Using Hdmr Technique
Authors: L. Ramaprasad Reddy
Published: May 2024

The present research focused to develop meta-model (MM) as a low-cost substitute for the Finite Element Method (FEM), to forecast the Stress Intensity Factor (SIF) of a semi-elliptic crack propagating. Multi-linear regression (MLR) based MM is developed for predicting the crack propagation. Three parameters—Root Mean Square Error (RMSE), Maximum Absolute Error (AAE), and Average Absolute Error—are examined to compare the MM's precision (AAE).
Multilingual Information Retrieval Using Graph Neural Networks: Practical Applications in English Translation
Authors: Hao Yang
Published: May 2024

Multilingual information retrieval using graph neural networks offers practical applications in English translation by leveraging advanced computational models to enhance the efficiency and accuracy of cross-lingual search and translation tasks. By representing textual data as graphs and utilizing graph neural networks (GNNs), this approach captures intricate relationships between words and phrases across different languages, enabling more effective language understanding and translation. GNNs can learn complex linguistic structures and semantic similarities from multilingual corpora, facilitating the development of more robust translation systems that are capable of handling diverse language pairs and domains. The paper introduces a novel approach termed the Multilingual Ant Bee Optimization Graph Neural Network (MABO-GNN) for addressing optimization, classification, and multilingual translation tasks. MABO-GNN integrates ant bee optimization algorithms with graph neural networks to provide a versatile framework capable of optimizing objective functions, improving classification accuracy iteratively, and facilitating high-quality translations across multiple languages. Through comprehensive experimentation, the efficacy of MABO-GNN is demonstrated across various tasks, languages, and datasets. in optimization experiments, MABO-GNN achieves objective function values of 0.012, 0.015, 0.011, and 0.013 in Experiment 1, Experiment 2, Experiment 3, and Experiment 4, respectively, with convergence times ranging from 90 to 150 seconds. In classification tasks, the model exhibits notable performance improvements over iterations, with BLEU scores reaching 0.84 and METEOR scores reaching 0.78 in the fifth iteration. The translation results showcase BLEU scores of 0.85 for English, 0.82 for French, 0.79 for German, 0.81 for Spanish, and 0.75 for Chinese, indicating the model's proficiency in generating high-quality translations across diverse languages.
Personalized Recommendation of English Online Teaching Content Based on Logistic Regression Algorithm
Authors: Ying Han
Published: May 2024

English online teaching content encompasses a wide range of materials designed to facilitate language learning in digital environments. These resources include interactive lessons, video tutorials, audio recordings, quizzes, vocabulary exercises, grammar explanations, and authentic texts such as articles, short stories, and dialogues. The content aims to cover various language skills, including listening, speaking, reading, and writing, catering to learners of different proficiency levels and learning styles. This paper introduces a Cross-Domain Personalized Recommendation System (CDPRS) designed to enhance the delivery of English language teaching content. Leveraging machine learning algorithms and data analytics techniques, the CDPRS tailors recommendations to individual user preferences, learning objectives, and proficiency levels across diverse content domains. Through a series of analyses and evaluations, including regression analysis and simulation studies, the effectiveness and utility of the CDPRS are demonstrated. Through a series of analyses and evaluations, including regression analysis and simulation studies, the effectiveness and utility of the CDPRS are demonstrated. Results indicate that the system achieves high levels of accuracy (mean accuracy = 0.85), diversity (mean diversity = 0.72), novelty (mean novelty = 0.78), and user satisfaction (mean satisfaction = 0.82) in providing personalized recommendations.
Improving the Accuracy of Recognition and Evaluation of Technical Movements of Basketball Players Using Deep Learning Algorithms
Authors: Sun Huafei
Published: May 2024

Deep learning algorithms are revolutionizing the analysis of technical movements in basketball players by extracting intricate patterns and insights from vast amounts of video data. By training neural networks on annotated video sequences of basketball games, these algorithms can automatically detect and classify various technical movements such as dribbling, shooting, passing, and defensive maneuvers. The use of deep learning enables the identification of subtle nuances in player movements, facilitating more accurate performance assessment and actionable feedback for athletes and coaches. This paper introduces a novel approach for analyzing basketball player movements utilizing Anthropometrical Variable Assessment Deep Learning (AVADL). By integrating anthropometric variables with deep learning algorithms, AVADL offers a comprehensive framework for accurately recognizing and evaluating technical movements on the basketball court. We present experimental results demonstrating the effectiveness of AVADL across various dataset sizes and player profiles, showcasing high accuracy and performance metrics. The incorporation of anthropometric measurements provides valuable context into the diverse physical attributes of basketball players, enhancing our understanding of their playing style and performance. Experimental results demonstrate the effectiveness of AVADL across various dataset sizes and player profiles, with training accuracies ranging from 90% to 97% and testing accuracies from 85% to 92%. Precision, recall, and F1-Score metrics consistently show values above 0.80, indicating the robustness of the approach. The incorporation of anthropometric measurements provides valuable context into the diverse physical attributes of basketball players, enhancing our understanding of their playing style and performance.
A Collaborative Study of English Teaching Based on Optimized Apriori Algorithm under the Integration of Curriculum Civics
Authors: Yuanyuan Qian
Published: May 2024

The new period introduces new intellectual and political demands for college-level English courses and fosters favourable conditions as well as new intellectual and political opportunities. The knowledge and politics courses currently taught in our higher education institutions combine English instruction with cooperative research and knowledge and politics courses, producing some excellent results in China. However, there are still significant challenges to implementing the relatively new ideas for education reform. In order to increase the effectiveness of the mine, this paper will enhance the apriori calculation method in accordance with the features of a large amount of data, and it requests the English Education Graduate School's participation for a demonstration. To address the issue of inaccurate existing metrics, this document integrates the proposed measures with conventional measures. In the past, the new measuring technique and the enhanced algorithm were used to create a model of the mining system based on the performance of the pupils. In the end, we used the student successes to build the mine system model, integrate the new measurement technique with the improved algorithm, and draw significant data-driven conclusions. According on experimental findings, the proposed algorithm performs better than Mr. Apriori. The mixed metre tonnes serve as the foundation for the most precise selection as compared to the general metre tonnes. The system offers a range of data extraction services in accordance with the university's role, which serves to enhance college English education's collaboration with curriculum and governmental thinking.
Munir: Weakly Supervised Transformer for Arabic Computational Propaganda Detection on Social Media
Authors: Bodor Moheel Almotairy
Published: May 2024

The intentional manipulation of public opinion has become prevalent in the realm of computational propaganda. The swift spread of misinformation through social networking sites poses significant challenges for governments and society, impacting various aspects of human life. Arab countries are considered among the most affected countries. Accurately identifying and countering computational propaganda is crucial, especially given the impracticality of manually annotating large volumes of social media-generated data. Moreover, the constant propagandists' evolving tactics pose a challenge to accounting models, making the immediate preparation of responsive training data difficult. To address this issue, this research proposes a novel weakly supervised learning approach, leveraging programmatic labeling to label training data in a systematic and timely manner. New labeling functions (LFs) are introduced, where experts' heuristics, knowledge, new proposed lexicons, different fine-tuned pre-trained models are turned into rules to label the data. Leveraging these LFs, we fine-tune a deep learning model for computational propaganda detection. The proposed model achieves a remarkable 94% accuracy and 86% precision in the minority class, outperforming a fine-tuned, fully supervised deep learning model. This research contributes a substantial dataset, a robust weakly supervised model, and lexicons, offering valuable tools for combating computational propaganda on Arabic social media. The code and the dataset are publicly available at https://github.com/Bmalmotairy/Arabic-Propaganda-Detection.
QoIoTX: A QoE-Aware IoT Service Discovery Framework
Authors: Rawan Sanyour
Published: May 2024

Quality of Experience QoE is a research area that evaluates performance based on subjective and objective metrics for the use of a product or a service. Currently, the substantial majority of QoE works mainly focus on multimedia services. However, the introduction of Internet of Things IoT has brought a new level of complexity into the field of QoE evaluation. With the evolution of new IoT technologies such as machine to machine communication and artificial intelligence, utilizing additional evaluation factors alongside the traditional ones is a crucial demand. This paper proposes QoIoTX, a QoE-based service discovery framework that can be utilized to evaluate the QoE of IoT service/application on the fly considering multiple parameters about data, network, users, and services. It extends the conventional QoE and goes beyond its legacy evaluation phases. Also, provides a novel alternative approach to evaluate the IoT services subjectively rather than using the traditional approaches that do not cope with the rapidly evolving services. Although each of the identified QoE factors is measured on a different scale and may involve different units of measurement, the proposed work can effectively evaluate the QoE through providing a single value that represents the acceptability degree of each service.
Comparative Study of Performance Metrics for Smart Inverter Control in Solar PV-Based EV Charging Stations
Authors: Vishal S. Wadkar
Published: May 2024

Photovoltaic (PV) panels harness sunlight as a clean and renewable energy source, providing a sustainable alternative to fossil fuels. In India, PV technology is gaining traction due to its environmental benefits and governmental support. This study analyzes typical PV generation profiles, identifying daily and seasonal variations influenced by factors like cloud cover. Additionally, it investigates the effectiveness of three EV charging strategies—uncontrolled, smart, and vehicle-to-home (V2H)—using rule-based and Model Predictive Control (MPC) algorithms. Simulations reveal that MPC consistently outperforms rule-based control in reducing household costs, with V2H charging showing potential for cost savings during peak electricity pricing. However, the efficacy of control strategies varies across seasons, suggesting the need for adaptive optimization approaches.
The Integration and Utilization of Mobile Application in Healthcare Consultation Services for Quirino Province
Authors: Jennyvi G. Pascua
Published: May 2024

The use of mobile devices has been rapidly increasing because of its versatile and useful applications. As a result, its high-tech features and Users have ready-made and customizable alternatives thanks to open source platforms., making it particularly helpful for healthcare services at any time and from any location. Healthcare services for the rural areas are limited since hospitals are also limited and their location is also one of the problems in availing healthcare service in the province.
The main objective of this study focuses on the integration and utilization of mobile application as an alternative solution for healthcare consultation services.
The descriptive and survey method was used in the data gathered from the respondents which comprised a number of people from the six municipalities of the province specifically rural areas. A questionnaire-checklist was administered to determine the possibility of the integration of mobile application for healthcare consultation services. Statistical Package for the Social Sciences (SPSS) a statistical tool used to determine the number of interested respondents to avail such mobile platform and to determined economic aspect of the study.
The study proves that there is a possibility for the integration of mobile application as an online platform for healthcare consultation services. This will be beneficial to Quirinians and nearby provinces.
Securing the Cloud: A New Horizon of Hybrid Automated System for Storage Protection
Authors: Srividya B V
Published: May 2024

While cloud storage seems dependable and scalable, the necessity for it is increasing every day. The intricacies involved in securing data in terms of privacy and confidentiality makes the storing and administration of user information at a remote location problematic. The cloud third party who is in charge of handling the issues concerned with data security present within the cloud systems could end up being an unreliable insider. In order to enhance the protection of data and ensure the confidentiality of information without any sort of interruption from cloud third parties, the current research provides an automated hybrid Cryptographic algorithm for Cloud Data Storage. Improved automated Asynchronous Encryption for Data Streams (AEDS) and enhanced automated Concurrent Encryption for Data Blocks (CEDB) are two encryption techniques that are used to achieve great performance and efficiency. We introduce a unique encryption method in Enhanced Automated Concurrent Encryption by transforming the fixed S-box in the conventional AES to a varying S-box utilising a Ternary Galois field and Complementary Ternary Galois field in the proposed work. Additionally, the Ternary Galois field and Complementary Ternary Galois field are employed to transform the matrix used for the AES mix column technique into a dynamic matrix.
Improvement of Power Factor in Wireless Electric Vehicle Charging Using Inductive Power Transfer Topology
Authors: Shivam Singh
Published: May 2024

The EV requires energy supplied to its motors to function properly. This required energy either can be transmitted by a physical wired connection or by wireless power transfer firstly to the battery using charging of the EV system and then battery discharges to supply to the vehicle. This paper deals with the wireless transfer of power using the induction method for charging battery of the vehicle using electric energy for its functioning as it is the most suitable and fast mode to charge the batteries of many vehicles altogether at charging station. The challenges recently faced by EV’s includes the movement of energy from the energy supply point to the destination i.e., EV’s without the direct interaction of battery and energy source. Many topologies have been introduced in this regard and several simulation models are built.
Gait-Based Human Activity Recognition Using Efficient Sensor Fusion and Deep Learning Approach
Authors: Aniket Bandyopadhyay
Published: May 2024

Human activity recognition is an important area of computer vision research. Its applications include surveillance systems, patient monitoring systems, and a variety of systems that involve interactions between persons and electronic devices such as human-computer interfaces. Most of these applications require an automated recognition of high-level activities, composed of multiple simple (or atomic) actions of persons. A novel feature selection approach is then proposed in order to select a subset of discriminant features, construct an online activity recognizer with better generalization ability, and reduce the smartphone power consumption. Experimental results on a publicly available data set show that the fusion of both accelerometer and gyroscope data contributes to obtain better recognition performance than that of using single source data, and that the proposed feature selector outperforms three other comparative approaches in terms of four performance measures. Such activity profiling systems are dependent on classification algorithms which can effectively interpret body-worn sensor data and identify different activities.  the key research challenges that human activity recognition shares with general pattern recognition and identify those challenges that are specific to human activity recognition. The aim of paper is to explore real life applications like contactless employee recognition system using gait analysis which uses sensor data as base to identify employees based on their gait movement. This requires understanding the dimensions of sensor data and its application exploring other potential real-life applications and optimizing the methodology are also one of the core objectives.
Application of Artificial Intelligence-based Technology in College Archives Management
Authors: Jianping Hu
Published: May 2024

This study looks into the use of artificial intelligence (AI)-based technologies, notably Convolutional Neural Network (CNN) models and data augmentation approaches, in college archives management. With the rapid expansion of digital information, archive organizations have enormous issues in maintaining, organizing, and giving access to their vast collections of historical documents and scholarly resources. AI solutions present possible solutions to these difficulties by automating labor-intensive operations and improving the efficiency and accuracy of preservation workflows. In this study, they investigate the transformational potential of CNN models in digitization activities, utilizing their visual data processing skills to automate and enhance the digitization of visual resources within college archives. In addition, they look into how data augmentation techniques might improve the resilience and generalization capabilities of AI models, reducing biases and improving performance across a variety of archive collections. Using empirical research, theoretical analysis, and case studies, they present insights into the opportunities and obstacles of implementing AI-based technology in college archive management. Furthermore, they discuss ethical implications for the deployment of AI solutions, emphasizing the significance of transparency, accountability, and stakeholder participation. This study aims to inform archival practitioners, technologists, and stakeholders about the effective and responsible integration of AI technologies in cultural heritage preservation and promotion within academic institutions by elucidating the practical applications and implications of CNN models and data augmentation techniques in archival contexts.
Image Segmentation Technology Based on Ant Colony Algorithm
Authors: Xiaoyan Wang
Published: May 2024

Image segmentation is a key task in computer vision, with applications ranging from medical diagnosis to autonomous driving. The Ant Colony Algorithm (ACO), modeled after ant foraging behavior, has emerged as a viable segmentation methodology. However, ACO-based segmentation algorithms frequently generate segmented outputs with jagged or uneven boundaries, which reduces their interpretability and usability. To alleviate this problem, they study the use of boundary-smoothing approaches in ACO-based segmentation. In this paper, they investigate image segmentation technology based on the Ant Colony Algorithm, with a focus on border smoothing. They examine the fundamentals of ACO and its application to image segmentation, emphasizing its strengths and limits. They also look at several boundary smoothing strategies, such as morphological operations, edge-preserving filters, and active contours (snakes), and how they affect segmentation performance. Through experimental validation and comparative analysis, they show that boundary smoothing improves the accuracy and visual quality of segmented images produced by ACO-based segmentation algorithms. These results help to design more robust and visually appealing segmentation algorithms, which have potential applications in medical imaging, remote sensing, and industrial automation.
Study and Analysis of RBFN based MPPT controller for wind energy integrated with Traction Power Supply System
Authors: Mebratu Delelegn
Published: May 2024

The need of energy for railway is rising due to the increased speed at which trains must operate to maintain safety and dependability. This situation implies more electricity consumption and more challenges to railway operation stability. Therefore, this research suggests configuring wind energy integration with the current railway traction substations built on the current traction substation. The suggested setup consists of a converter that converts DC to DC with RBFN-based MPPT regulator wind energy source linked to a permanent magnet synchronous generator (PMSG), a rectifier, and a conventional traction system. The proposed system is modelled and analyzed by utilizing a radial basis function network (RBFN) in this study. Three traction substations: Aysha, Adegla and Dewanle:-are the subject of the case study, which integrates wind energy with the railway electric power system working at 25 kV AC. For the Aysha wind farm, a MATLAB/Simulink simulation is run in order to confirm the suggested technology. The setup with or without MPPT was used in order to evaluate the results. The proposed system produces an average output of 260.3kW without MPPT and 289.3kW with MPPT controller at wind speed of 20m/sec. The simulation findings suggest that the RBFN-based control method performs better under diverse wind conditions and is more suited for wind energy integration with traction system.
End User Incentive-based Approach for Fast Charging Station
Authors: Lokendra Kumar
Published: May 2024

The development of electric vehicles (EVs) is influenced by various factors such as cost, autonomy, charging speed, and infrastructure. The objective of this research paper is to model an EV fast-charging station that provides incentives to end users in terms of money. The charging station incorporates a renewable energy source (solar) and an energy storage system, taking into account the demand for EVs, state of charge (SOC), and vehicle arrival and departure times. This approach aims to increase the revenue of the station and reduce the high energy demand from the grid. To incentivize end users, the vehicle-to-grid (V2G) and battery swapping modes have been implemented. The Monte Carlo approach is used to model the demand for EVs and the production of renewable energy, considering hourly intervals. Subsequently, the installation and utilization of the EV fast-charging station (EVCS) are optimized using the Adaptive Harris Hawk Optimization (AHHO) algorithm. The system is analyzed with and without V2G and battery swapping modes. The comparison between the two modes reveals that the system with V2G and battery swapping provides both revenue and incentives to end users.
Solar Photo Voltaic Connected Quasi Z Source Inverter for Grid and utility Application
Authors: Muneeb Ahmad
Published: May 2024

This paper discusses the use of quasi-Z-source inverters, in utility grid systems. These inverters enhanced dependability and one-stage buck and boost abilities make them appropriate for photovoltaic power conditioning applications. The small signal sate space method utilized for the proposed system using Quasi ZSI for utility and grid integration application. Shoot through state also implemented on dc side to enhanced the voltage gain. The Controlling of dc side and ac side also implemented in MATLAB using state space transfer function. A two-stage controlling technique implemented on two level 6 switch inverters with SPWM with P & O MPPT and PI controller. The proposed system has solar PV array rating of 5.5kW and utilized in distribution purpose. A simple boost controlling technique has been implemented to obtained the desired gain and less ripples are present in the current due to the presence of inductor in the QZSI impedance network. During light loading the surplus power injected to the grid with the help of PLL system and when load demand increases the power take from the grid smoothly without loss of synchronism. The system has better stability and fast dynamic response during transient. The THD has been observed at the inverter and load side with LC filter, THD within the permissible limit as per IEEE std 1547.