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Artículos de revistas sobre el tema "Physics-guided"

Autor: Grafiati

Publicado: 25 de mayo de 2024

Última modificación: 31 de julio de 2025

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1

Gutierrez, Mario A., Jack Dvorkin, and Amos Nur. "Stratigraphy-guided rock physics." Leading Edge 21, no. 1 (2002): 98–103. http://dx.doi.org/10.1190/1.1445859.

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Eaton, D. J. "Physics Support of Image-guided Radiotherapy." Clinical Oncology 25, no. 3 (2013): e31. http://dx.doi.org/10.1016/j.clon.2012.12.003.

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Zhu, Dan, Jiayu Peng, and Cong Ding. "A Neural Network with Physical Mechanism for Predicting Airport Aviation Noise." Aerospace 11, no. 9 (2024): 747. http://dx.doi.org/10.3390/aerospace11090747.

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Airport noise prediction models are divided into physics-guided methods and data-driven methods. The prediction results of physics-guided methods are relatively stable, but their overall prediction accuracy is lower than that of data-driven methods. However, machine learning methods have a relatively high prediction accuracy, but their prediction stability is inferior to physics-guided methods. Therefore, this article integrates the ECAC model, driven by aerodynamics and acoustics principles under the framework of deep neural networks, and establishes a physically guided neural network noise p

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4

Pawar, Suraj, Omer San, Burak Aksoylu, Adil Rasheed, and Trond Kvamsdal. "Physics guided machine learning using simplified theories." Physics of Fluids 33, no. 1 (2021): 011701. http://dx.doi.org/10.1063/5.0038929.

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Pawar, Suraj, Omer San, Burak Aksoylu, Adil Rasheed, and Trond Kvamsdal. "Physics guided machine learning using simplified theories." Physics of Fluids 33, no. 1 (2021): 011701. http://dx.doi.org/10.1063/5.0038929.

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Keyser, Paul T. "Aristotle's Physics: A Guided Study. Joe Sachs." Isis 87, no. 4 (1996): 716–17. http://dx.doi.org/10.1086/357668.

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Gupta, Kishor Datta, Sunzida Siddique, Roy George, Marufa Kamal, Rakib Hossain Rifat, and Mohd Ariful Haque. "Physics Guided Neural Networks with Knowledge Graph." Digital 4, no. 4 (2024): 846–65. http://dx.doi.org/10.3390/digital4040042.

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Over the past few decades, machine learning (ML) has demonstrated significant advancements in all areas of human existence. Machine learning and deep learning models rely heavily on data. Typically, basic machine learning (ML) and deep learning (DL) models receive input data and its matching output. Within the model, these models generate rules. In a physics-guided model, input and output rules are provided to optimize the model’s learning, hence enhancing the model’s loss optimization. The concept of the physics-guided neural network (PGNN) is becoming increasingly popular among researchers a

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8

Lu, XinPei, and Kostya (Ken) Ostrikov. "Guided ionization waves: The physics of repeatability." Applied Physics Reviews 5, no. 3 (2018): 031102. http://dx.doi.org/10.1063/1.5031445.

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Yang, Gangjun, Liping Xie, Ying Tan, and Zhihua Cui. "Artificial physics optimisation algorithm guided by diversity." International Journal of Computer Applications in Technology 46, no. 4 (2013): 369. http://dx.doi.org/10.1504/ijcat.2013.053428.

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Yusuf, Yusniati H. Muh. "PENERAPAN MODEL PEMBELAJARAN PROCESS ORIENTED GUIDED INQUIRY DAN MODEL PEMBELAJARAN GUIDED INQUIRY UNTUK MENINGKATKAN PENGETAHUAN PROSEDURAL FISIKA SISWA SMP NEGERI 3 AMANUBAN TENGAH." Jurnal Fisika : Fisika Sains dan Aplikasinya 4, no. 2 (2019): 100–107. http://dx.doi.org/10.35508/fisa.v4i2.1835.

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Abstrak Penelitian ini merupakan penelitian eksperimen dengan desain penelitian desain penelitian Randomized Control Group Pretest-Posttest Design, yang dilaksanakan di SMP Negeri 3 Amanuban Tengah pada bulan Februari tahun ajaran 2018/2019 . Adapun tujuan dari penelitian ini (1) Untuk mengetahui ada tidaknya perbedaan pengetahuan prosedural fisika siswa yang signifikan antara siswa yang diajar dengan menerapkan model pembelajaran Process Oriented Guided Inquiry Learning (POGIL) dengan siswa yang diajar dengan menerapkan model pembelajaran Guided Inquiry. (2) Untuk mengetahui peningkatan penge

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Subramaniam, Geetha, and Rasidah Sapri. "A Guided Discovery Learning Model to Improve Conceptual Understanding in Learning Physic." Jurnal Pendidikan Sains dan Matemaitk Malaysia 12, no. 2 (2022): 77–92. https://doi.org/10.37134/jpsmm.vol12.2.6.2022.

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Physics, a fundamental branch of science, significantly contributes to a wide range of inventions starting to revolutionize contemporary life and has helped to describe many daily events in detail. Physics is vital for understanding the complexity of current technology and is crucial for the technical advancement of a nation. However, despite its importance, physics is the least popular science subject among students. Students appear to view physics as conceptually tricky and abstract. Utilizing a learning model to improve physics students' conceptual comprehension is possible. The guided expl

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Fauziah, Arsyad Muhammad, and Helmi. "Influence of Discovery Learning Model and Learning Motivation on Physics Learning Outcomes in Students." International Journal of Social Science and Human Research 08, no. 01 (2025): 46–53. https://doi.org/10.5281/zenodo.14607588.

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The purpose of this study is to (1) analyze the differences in physics learning outcomes of students in class XI MIPA SMAN 1 Woha who are taught with discovery learning and guided inquiry, (2) analyze the differences in physics learning outcomes of students who are taught with discovery learning and guided inquiry was reviewed from high learning motivation and low learning motivation and (3) analyzed the interaction between discovery learning and learning motivation on students physics learning outcomes. The population consists of class XI MIPA SMAN 1 Woha. The number of samples used in classe

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13

Syamsidar, S., Khaeruddin Khaeruddin, and Helmi Helmi. "The Effectiveness of using Student Worksheets to Practice Science Process Skills on Hooke's Law Material." Jurnal Penelitian & Pengembangan Pendidikan Fisika 7, no. 1 (2021): 83–90. http://dx.doi.org/10.21009/1.07109.

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This study aims to analyze the effectiveness of guided inquiry-based physics worksheets in training students' science process skills. This case study was conducted at SMAN 4 Sidenreng Rappang with 28 respondents. Students use worksheets based on guided inquiry for four meetings in Hooke's law material. The worksheets were developed using the ADDIE model, consisting of analysis, design, development, implementation, and evaluation, including expert validation. We obtained the expert analysis of student worksheets based on guided inquiry from two experts, namely 3.16 out of 4 Likert scales with a

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14

Nurhasanah, Nurhasanah, and Dasmo Dasmo. "Studi Meta-Analisis Model Pembelajaran Inquiry Terbimbing dalam Pembelajaran Fisika." Navigation Physics : Journal of Physics Education 2, no. 2 (2020): 69–73. http://dx.doi.org/10.30998/npjpe.v2i2.485.

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This study aims to analyze the influence of the guided inquiry learning model in physics learning through the overall effect size, based on the dependent variable and region. This research uses a descriptive method with a meta-analysis approach to the results of scientific research publications in national electronic journals. There are 11 national journals that fit the research category. The results showed that overall learning using the guided inquiry model could improve students' physics learning outcomes with the effect size of 0.487 from the control group. Meanwhile, based on the distribu

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15

Ebokaiwe, Nkechi T., O. P. Ajaja, and E. Kpangban. "Effect of 5E guided inquiry, team teaching, and lecture method on physics students academic achievement in secondary schools in Delta State." International Journal of Education, Training and Learning 8, no. 1 (2024): 1–5. https://doi.org/10.33094/ijetl.v8i1.1346.

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The present study investigated the effect of 5E-guided inquiry, team teaching, and lecture methods on the academic achievement of physics students in Delta State secondary schools. The purpose of this research was to investigate the effect of 5E-guided inquiry, team teaching, and lecture methods on physics students’ academic achievement. The study used the quasi-experimental non-randomized pre-test, post-test, and planned variation group design. A total of three hundred and twenty-six (326) physics students from nine secondary schools were recruited and sampled in the present study. The study

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Murphy, Cara P., and John P. Kerekes. "Physics-guided neural network for predicting chemical signatures." Applied Optics 60, no. 11 (2021): 3176. http://dx.doi.org/10.1364/ao.420688.

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Silaban, Eka Setiaji, and Alkhafi Maas Siregar. "VALIDITY OF GUIDED INQUIRY-BASED PHYSICS LEARNING MODULE." Journal of Learning and Technology in Physics 5, no. 1 (2024): 1. http://dx.doi.org/10.24114/jltp.v5i1.53034.

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The learning resources used in learning physics class XI SMAN 1 Namorambe is only a package book. In fact, teachers and students are not satisfied with the existing learning resources, therefore a new learning resource is needed and is expected to meet the needs of teachers and students. This research focuses on the development of physics learning modules on sound waves material class XI SMA. This study aims to determine the validity level of the guided inquiry-based module on the subject of sound waves that have been developed. This research is an R & D (Research and Development) developm

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18

Nissani, Moti, Clifford L. Maier, and Norma Shifrin. "A guided discovery exercise for introductory physics labs." Physics Teacher 32, no. 2 (1994): 104–7. http://dx.doi.org/10.1119/1.2343917.

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19

Bensky, Thomas J., and Catherine A. Taff. "Computer-Guided Solutions to Physics Problems Using Prolog." Computing in Science & Engineering 12, no. 1 (2010): 88–95. http://dx.doi.org/10.1109/mcse.2010.8.

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20

Nivalainen, Ville, Mervi A. Asikainen, and Pekka E. Hirvonen. "Open Guided Inquiry Laboratory in Physics Teacher Education." Journal of Science Teacher Education 24, no. 3 (2013): 449–74. http://dx.doi.org/10.1007/s10972-012-9316-x.

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WADA, Kazunari, Katsuyuki SUZUKI, and Kazuo YONEKURA. "Physics Guided cWGAN-gp for accurate airfoil generation." Proceedings of OPTIS 2022.14 (2022): U00057. http://dx.doi.org/10.1299/jsmeoptis.2022.14.u00057.

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22

Safitri, Riski, Jumadi Jumadi, and Nadia Natalia Simamora. "Development of Guided Inquiry-Based Physics e-LKPD to Improve Students' Critical Thinking Abilities." JIPF (Jurnal Ilmu Pendidikan Fisika) 9, no. 3 (2024): 353. https://doi.org/10.26737/jipf.v9i3.4821.

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The development of guided inquiry-based physics e-LKPD is based on the lack of learning media in the MAN 1 Yogyakarta physics subject that can help students think critically. The purpose of this research is to develop a proper, effective, and practical guided inquiry-based physics e-LKPD to help students improve their critical thinking ability. The method is the R&amp;D 4D design model, including: define, design, develop, and disseminate. The data analysis technique used is quantitative. Quantitative data analysis is used to determine the level of feasibility, practicality, and effectivene

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23

Gaitari, Windri Suci, Silvi Yulia Sari, Yenni Darvina, Hufri, and Fanni Rahmatina Rahim. "ANALYSIS OF AVAILABILITY OF GUIDED INQUIRY MODEL ON LESSON PLANS PHYSICS GRADE XI SEMESTER 1 IN SENIOR HIGH SCHOOLS." PILLAR OF PHYSICS EDUCATION 14, no. 2 (2021): 130. http://dx.doi.org/10.24036/11646171074.

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In the revised 2013 curriculum, students are required to have skills that fit the challenges of the 21st century. To train these skills is to apply the right model in learning, namely the guided inquiry model. The availability of guided inquiry models in learning can be seen from the lesson plans. All lesson plan at public high schools has not been identified whether they have a guided inquiry model. Therefore, this research aims to find out the availability of guided inquiry models in lesson plan Physics grade XI Semester 1 in high schools. This research is descriptive research with a qualita

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24

Amir, Syamsudin, and Dewi Hikmah Marisda. "Effectiveness of Guided Inquiry Learning Models Viewed From Physics Learning Achievements." Berkala Ilmiah Pendidikan Fisika 9, no. 2 (2021): 135. http://dx.doi.org/10.20527/bipf.v9i2.8630.

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This study aimed to analyze the improvement in physics learning outcomes of XI MIA State Madrasah Aliyah 2 students in East Flores after being taught using the Guided Inquiry Learning model. The type of research was a pre-experimental design with one group Pretest – Post-test. The sample in this study was saturated, namely all students of class XI MIA MAN 2 Flores. The research instrument used was a learning achievement test consisting of 30 items in multiple-choice, validated by two experts. The data obtained was then analyzed in a quantitative descriptive manner for the increased learning ac

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25

Kadir, Fitriani, Imam Permana, I. Gede Purwana Edi Saputra, and Azmar. "Effect of Guided Discovery Methods on Students' Motivation and Learning Outcomes." Jurnal Penelitian Pendidikan IPA 9, no. 11 (2023): 9893–98. http://dx.doi.org/10.29303/jppipa.v9i11.4326.

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This research aimed to determine the effect of guided discovery methods on students' motivation and learning outcomes by compare the result on guided discovery method and conventional learning method at MAN 2 Model Makassar. The research method was true experiment with randomized posttest only control group design. The sample of the research were determined randomly by using group random sampling technique and obtained two classes. The first class was the experiment class which was taught by guided discovery method and the second class was control class which was taught by conventional method.

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Hidayatullah, Silmi, and Ratna Wulan. "Meta-analysis of the influence of 21st century high school students’ skills in learning physics using a guided inquiry model." Journal of Physics: Conference Series 2309, no. 1 (2022): 012057. http://dx.doi.org/10.1088/1742-6596/2309/1/012057.

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Abstract Education is one of the important things in current government policies. Education is pursued by the government in accordance with the demands of the 21st century. The current demand for education is the industrial revolution 4.0 where education further enhances student skills. In fact, students’ skills are still low, especially aspects of science process skills, critical thinking, and students’ mastery of concepts. Researchers analyzed 30 journals that used a guided inquiry model on 3 aspects of student skills. Student skills will be seen during the learning process and can be assess

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Yulianci, Syahriani, Gunawan Gunawan, and Aris Doyan. "MODEL INKUIRI TERBIMBING BERBANTUAN MULTIMEDIA INTERAKTIF UNTUK MENINGKATKAN PENGUASAAN KONSEP FISIKA PESERTA DIDIK." Jurnal Pendidikan Fisika dan Teknologi 3, no. 2 (2017): 146. http://dx.doi.org/10.29303/jpft.v3i2.365.

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The purpose of this study is to examine the effectiveness of learning use the guided inquiry model with interactive multimedia toward mastery of concept physics students. The study involved 68 students who were divided into two groups, the experimental group and control group. The research instrument used a mastery of concept physics students. Data were analyzed by using normalized gain scores. The result showed an increase in mastery of concept physics in both groups but experimental have the high increase more than control group. The result indicate that the guided inquiry learning with inte

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Dianty, Alivea Pisca, Supeno Supeno, and Sri Astutik. "KEMAMPUAN DECISION MAKING SISWA SMA DALAM PEMBELAJARAN FISIKA BERBASIS INKUIRI TERBIMBING." JURNAL PEMBELAJARAN FISIKA 9, no. 1 (2020): 1. http://dx.doi.org/10.19184/jpf.v9i1.17935.

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Students must be able to make decisions effectively in urgent conditions and be able to formulate strategies to take action in an effort to make the situation under control. During learning at school, there are still many students who tend to be more receptive to information than to provide solutions that can solve the problems. The ability to make decisions can be trained using the guided inquiry learning model, because the essence of the guided inquiry strategy is relate to the decision making skills. The use of guided inquiry models in learning can increase student to think critically, be m

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Yu, Runlong, Chonghao Qiu, Robert Ladwig, Paul Hanson, Yiqun Xie, and Xiaowei Jia. "Physics-Guided Foundation Model for Scientific Discovery: An Application to Aquatic Science." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 27 (2025): 28548–56. https://doi.org/10.1609/aaai.v39i27.35078.

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Physics-guided machine learning (PGML) has become a prevalent approach in studying scientific systems due to its ability to integrate scientific theories for enhancing machine learning (ML) models. However, most PGML approaches are tailored to isolated and relatively simple tasks, which limits their applicability to complex systems involving multiple interacting processes and numerous influencing features. In this paper, we propose a Physics-Guided Foundation Model (PGFM) that combines pre-trained ML models and physics-based models and leverages their complementary strengths to improve the mod

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Sugiarti, Sugiarti. "Hasil Belajar dan Aktivitas Siswa Setelah Diterapkan Pembelajaran Guided Inquiry Pada Materi Penerapan Listrik DC dan AC." SEJ (Science Education Journal) 1, no. 2 (2017): 92. http://dx.doi.org/10.21070/sej.v1i2.1220.

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This study aims to determine the results of student learning after applied physics learning using guided inquiry model and student activities during the process of physics-based learning guided inquiry in high school on the material Application of AC and DC Power. Implementation of this learning using one group pretest-posttest design, the first step to make measurements as the initial test, then subject to treatment within a certain time, then performed the final test. After doing teaching and learning activities on the material application of DC electricity and AC classical completeness reac

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Putri Lisa, Tessa Destia, Asrizal Asrizal, and Festiyed Festiyed. "Effect Size Analysis of the Use of Guided Inquiry-Based Teaching Materials on Students’ Competence." Journal of Innovative Physics Teaching 1, no. 1 (2023): 85–95. http://dx.doi.org/10.24036/jipt/vol1-iss1/6.

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Teaching materials are needed in learning to deliver information systematically to students in order to achieve the expected competencies. The real condition in the field show that the use of teaching materials based on certain learning models were still limited. For this reason, this research was conducted to analyze the effect size of the use of guided inquiry-based physics and science teaching materials on students’ competence. The research method used is meta-analysis based on effect size with research subjects, namely 20 national and international articles. The results showed that the use

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Banyay, Gregory A., and Andrew S. Wixom. "Predictive capability assessment for physics-guided learning of vortex-induced vibrations." Journal of the Acoustical Society of America 152, no. 4 (2022): A48. http://dx.doi.org/10.1121/10.0015496.

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We seek here a computationally parsimonious and credible means to simulate the complex phenomena of vortex-induced vibrations (ViV), as one tool to assist in mitigating risk associated with ViV-induced instabilities that can cause non-negligible structural acoustic response. To address current limitations in data-driven modeling, for which credibility assessment proves challenging, or physics-based simulation (i.e., constrained by governing partial differential equations (PDEs)), which often includes prohibitive computational expense, we explore recent state-of-the-art approaches to optimally

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Akinbobola, Akinyemi Olufunminiyi, and Folashade Afolabi. "Constructivist practices through guided discovery approach: The effect on students’ cognitive achievement in Nigerian senior secondary school physics." International Journal of Physics & Chemistry Education 2, no. 1 (2010): 16–25. http://dx.doi.org/10.51724/ijpce.v2i1.180.

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The study investigated constructivist practices through guided discovery approach and the effect on students’ cognitive achievement in Nigerian senior secondary school Physics. The study adopted pretest-posttest control group design. A criterion sampling technique was used to select six schools out of nine schools that met the criteria. A total of 278 students took part in the study; this was made up of 141 male students and 137 female students in their respective intact classes. Physic Achievement Test (PAT) with the internal consistency of 0.77 using Kuder Richardson formula 21 was the instr

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Okeke, Uchenna Kingsley, Sam Ramaila, and Edidiong E. Ukoh. "Effects of Cognitively Guided Instruction on Senior Secondary School Students’ Attitude towards Physics." International Journal of Learning, Teaching and Educational Research 22, no. 11 (2023): 188–211. http://dx.doi.org/10.26803/ijlter.22.11.11.

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In an effort to achieve educational goals and improve students' enthusiasm for Physics, it is important to take into account the prior experiences that students bring with them to the classroom. Teachers' exploration of these prior experiences is crucial when implementing the constructivist approach to classroom instruction, as it helps in achieving the desired objectives. Consequently, this research aimed to investigate how the application of cognitively guided instruction influences the attitudes of senior secondary school students towards Physics. The study employed a pretest-posttest contr

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Qin, Bao, and Zheng Zhong. "A Physics-Guided Machine Learning Model for Predicting Viscoelasticity of Solids at Large Deformation." Polymers 16, no. 22 (2024): 3222. http://dx.doi.org/10.3390/polym16223222.

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Physics-guided machine learning (PGML) methods are emerging as valuable tools for modelling the constitutive relations of solids due to their ability to integrate both data and physical knowledge. While various PGML approaches have successfully modeled time-independent elasticity and plasticity, viscoelasticity remains less addressed due to its dependence on both time and loading paths. Moreover, many existing methods require large datasets from experiments or physics-based simulations to effectively predict constitutive relations, and they may struggle to model viscoelasticity accurately when

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Peciuliauskiene, Palmira. "PROMOTION OF INFORMATION LITERACY ABILITIES OF SECONDARY SCHOOL LEARNERS BY PHYSICS LABS." SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference 2 (May 26, 2016): 240. http://dx.doi.org/10.17770/sie2016vol2.1373.

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The article deals with the role of Physics labs in promoting information literacy abilities of secondary school learners. The methodological basis of research is inquiry-based learning. The article focuses on the second level of inquiry-based learning referred to Guided inquiry. According to the The article deals with the role of Physics labs in promoting information literacy abilities of secondary school learners. The methodological basis of research is inquiry-based learning. The article focuses on the third level of inquiry-based learning referred to Guided Inquiry. According to the Guided

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Zhang, Jianjing, Chuanping Liu, and Robert X. Gao. "Physics-guided Gaussian process for HVAC system performance prognosis." Mechanical Systems and Signal Processing 179 (November 2022): 109336. http://dx.doi.org/10.1016/j.ymssp.2022.109336.

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Huang, Zhou, Xinfeng Yin, and Yang Liu. "Physics-guided deep neural network for structural damage identification." Ocean Engineering 260 (September 2022): 112073. http://dx.doi.org/10.1016/j.oceaneng.2022.112073.

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Jørgensen, Ulrik, Pauline Røstum Belingmo, Brian Murray, Svein Peder Berge, and Armin Pobitzer. "Ship route optimization using hybrid physics-guided machine learning." Journal of Physics: Conference Series 2311, no. 1 (2022): 012037. http://dx.doi.org/10.1088/1742-6596/2311/1/012037.

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Abstract This paper presents a method for energy efficient weather routing of a ferry in Norway. Historical operational data from the ferry and environmental data are used to develop two models that predict the energy consumption. The first is a purely data-driven linear regression energy model, while the second is as a hybrid model, combining physical models with data-driven models using machine learning techniques. With an established energy model, it is possible to develop a route optimization that proposes efficient routes with less energy usage compared to fixed speed and heading control.

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Lei, Lei, Yang Gang, and Guo Jing. "Physics-guided neural network for underwater glider flight modeling." Applied Ocean Research 121 (April 2022): 103082. http://dx.doi.org/10.1016/j.apor.2022.103082.

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Wang, Lei, Qun Zhou, and Shuangshuang Jin. "Physics-guided Deep Learning for Power System State Estimation." Journal of Modern Power Systems and Clean Energy 8, no. 4 (2020): 607–15. http://dx.doi.org/10.35833/mpce.2019.000565.

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42

Rauseo, Marco, Fanzhou Zhao, and Mehdi Vahdati. "Physics guided machine learning modelling of compressor stall flutter." Journal of the Global Power and Propulsion Society 8 (August 13, 2024): 295–309. http://dx.doi.org/10.33737/jgpps/187996.

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Modern aircraft engines need to meet ever more stringent requirements that greatly increase the complexity of design, which strives for enhanced performance, reduced operating costs, emissions and noise simultaneously. The drive for performance leads to the development of thin, lightweight, highly loaded fan and compressor blades which are increasingly more prone to incur high, sustained vibratory stresses and aeroelastic problems such as flutter. The current practice employs preliminary design tools for flutter that are often based on empiricism or simplified analytical models, requiring exte

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Wang, Jinjiang, Yilin Li, Rui Zhao, and Robert X. Gao. "Physics guided neural network for machining tool wear prediction." Journal of Manufacturing Systems 57 (October 2020): 298–310. http://dx.doi.org/10.1016/j.jmsy.2020.09.005.

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Georg, D. "Image-guided and adaptive radiotherapy: medical physics challenges ahead." Radiotherapy and Oncology 118 (February 2016): S45—S46. http://dx.doi.org/10.1016/s0167-8140(16)30094-9.

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Lee, Jonghwan. "Physics-Guided Neural Modeling for Low-Dimensional Thermoelectric Module." IEEE Electron Device Letters 40, no. 11 (2019): 1812–15. http://dx.doi.org/10.1109/led.2019.2944395.

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Liu, Libin, Michiel Van De Panne, and Kangkang Yin. "Guided Learning of Control Graphs for Physics-Based Characters." ACM Transactions on Graphics 35, no. 3 (2016): 1–14. http://dx.doi.org/10.1145/2893476.

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Wang, Zhihao, Yiqun Xie, Zhili Li, et al. "SimFair: Physics-Guided Fairness-Aware Learning with Simulation Models." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 20 (2024): 22420–28. http://dx.doi.org/10.1609/aaai.v38i20.30249.

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Resumen

Fairness-awareness has emerged as an essential building block for the responsible use of artificial intelligence in real applications. In many cases, inequity in performance is due to the change in distribution over different regions. While techniques have been developed to improve the transferability of fairness, a solution to the problem is not always feasible with no samples from the new regions, which is a bottleneck for pure data-driven attempts. Fortunately, physics-based mechanistic models have been studied for many problems with major social impacts. We propose SimFair, a physics-guide

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"Aristotle's Physics: a guided study." Choice Reviews Online 33, no. 03 (1995): 33–1591. http://dx.doi.org/10.5860/choice.33-1591.

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Carter, A., S. Imtiaz, and G. Naterer. "Imperfect Physics-guided Neural Networks." Chemical Engineering Science, December 2024, 121153. https://doi.org/10.1016/j.ces.2024.121153.

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Dwivedi, Anmol, Santiago Paternain, and Ali Tajer. "Blackout Mitigation Via Physics-Guided RL." IEEE Transactions on Power Systems, 2024, 1–12. http://dx.doi.org/10.1109/tpwrs.2024.3472570.

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