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Seminar on Advances in Mathematics, Science and Engineering for Elementary School, SAMSES 2018

作者： Ruskandi, K. Hikmawan, R. Suwangsih, E. Study Program of Primary Teacher Education Universitas Pendidikan Indonesia Bandung Indonesia Study Program of System and Information Technology Education Universitas Pendidikan Indonesia Bandung Indonesia

In 21 centuries, teacher area required to have high accountability in facilitating their students to achieve various knowledge and life skills in society. An appropriate learning model that meet the students' needs is essential to develop social skills because the learning model that emphasizes only on the skills of the students as individuals will not allow them to face the challenges of life that demand them to collaborate with other. This research aimed at developing an innovative learning model that facilitate students to optimally achieve social skills as one of the social studies objectives and investigating the significance of the effect of project-based learning model on the social skills of fifth grade students of elementary. The research is done by experimental method with non-equivalent control group design. Based on our findings, it was concluded that project-based learning model had no significant effect on improving the student's social skills. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Wallas model problem-solving to identify prospective mathematics teachers ’expectations of students’ creative thinking processes

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AIP Conference Proceedings 2024年第1期3148卷

作者： Mohammad Tohir Muhasshanah Muhasshanah Ahmad Choirul Anam Leni Agustina Daulay Wahyu Sardjono Mathematics Education Ibrahimy University Situbondo East Java 68374 Indonesia Information Technology Ibrahimy University Situbondo East Java 68374 Indonesia Mathematics Education State Islamic Institute of Takengon Aceh 24519 Indonesia Information System Management Department BINUS Graduate Program - Master of Information Systems Management. Bina Nusantara University Jakarta 11480 Indonesia

The mathematical thinking processes of prospective teachers in solving mathematical problems vary, especially the thinking processes they expect from their students. The four stages of the Wallas Model creative thinking process are preparation, incubation, illumination, and verification. The purpose of this research is to describe the creative thinking process that prospective teachers expected from their students in solving mathematical problems based on the Wallas model. The research technique employed is a mixed-methods approach. The participants in this study were 34 aspiring math teachers in mathematics education study program at Ibrahimy University. The Miles and Huberman model was used to evaluate the data collected from observation, test results, and interviews was confirmed using triangulation. The results of this study show that:(1) Prospective teachers expect their students to be able to carry out the four steps of the Wallas model of the creative thinking process when solving mathematical problems; (2) the expectations of the subject of the majority of high groups want students to be able to meet all stages of the Wallas model; (3) medium and low group subject expectations tend to desire the three-stage Wallas model reasonably; (4) the percentage of achievement indicator of the thinking process creative expected by prospective teachers to students in problem-solving based on the Wallas model were obtained for Preparation (73.53%), Incubation (91.18%), Illumination (82.35%), and Verification (44.12%). This research results findings should be followed up in a teacher or lecturer meeting to learn students’ creative thinking expectations in mathematics and other disciplines.

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Artificial intelligence for geoscience:Progress,challenges,and perspectives

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The Innovation 2024年第5期5卷 136-160,135页

作者： Tianjie Zhao Sheng Wang Chaojun Ouyang Min Chen Chenying Liu Jin Zhang Long Yu Fei Wang Yong Xie Jun Li Fang Wang Sabine Grunwald Bryan MWong Fan Zhang Zhen Qian Yongjun Xu Chengqing Yu Wei Han Tao Sun Zezhi Shao Tangwen Qian Zhao Chen Jiangyuan Zeng Huai Zhang Husi Letu Bing Zhang Li Wang Lei Luo Chong Shi Hongjun Su Hongsheng Zhang Shuai Yin Ni Huang Wei Zhao Nan Li Chaolei Zheng Yang Zhou Changping Huang Defeng Feng Qingsong Xu Yan Wu Danfeng Hong Zhenyu Wang Yinyi Lin Tangtang Zhang Prashant Kumar Antonio Plaza Jocelyn Chanussot Jiabao Zhang Jiancheng Shi Lizhe Wang Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China School of Computer Science China University of GeosciencesWuhan 430078China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China Key Laboratory of Virtual Geographic Environment(Ministry of Education of PRC) Nanjing Normal UniversityNanjing 210023China Data Science in Earth Observation Technical University of Munich80333 MunichGermany The National Key Laboratory of Water Disaster Prevention Yangtze Institute for Conservation and DevelopmentHohai UniversityNanjing 210098China Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China School of Geographical Sciences Nanjing University of Information Science and TechnologyNanjing 210044China State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China Soil Water and Ecosystem Sciences DepartmentUniversity of FloridaPO Box 110290GainesvilleFLUSA Materials Science Engineering Program Cooperating Faculty Member in the Department of Chemistry and Department of Physics Astronomy University of CaliforniaCaliforniaRiversideCA 92521USA Institute of Remote Sensing and Geographical Information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Key Laboratory of Computational Geodynamics University of Chinese Academy of SciencesBeijing 100049China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China College of Geography and Remote Sensing Hohai UniversityNanjing 211100China Department of Geography The University of Hong KongHong Kong 999077SARChina Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Nanjing 210044China School of Environmental Science and Engineering Nanjing University of Information Science&TechnologyNanjing 210044China Collaborative Inno

This paper explores the evolution of geoscientific inquiry,tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence(AI)and data collection *** models,which are grounded in physical and numerical frameworks,provide robust explanations by explicitly reconstructing underlying physical ***,their limitations in comprehensively capturing Earth’s complexities and uncertainties pose challenges in optimization and real-world *** contrast,contemporary data-driven models,particularly those utilizing machine learning(ML)and deep learning(DL),leverage extensive geoscience data to glean insights without requiring exhaustive theoretical *** techniques have shown promise in addressing Earth science-related ***,challenges such as data scarcity,computational demands,data privacy concerns,and the“black-box”nature of AI models hinder their seamless integration into *** integration of physics-based and data-driven methodologies into hybrid models presents an alternative *** models,which incorporate domain knowledge to guide AI methodologies,demonstrate enhanced efficiency and performance with reduced training data *** review provides a comprehensive overview of geoscientific research paradigms,emphasizing untapped opportunities at the intersection of advanced AI techniques and *** examines major methodologies,showcases advances in large-scale models,and discusses the challenges and prospects that will shape the future landscape of AI in *** paper outlines a dynamic field ripe with possibilities,poised to unlock new understandings of Earth’s complexities and further advance geoscience exploration.

关键词： Earth utilizing landscape

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Two-stay two-stray model on improving mathematical communication skill of elementary school students

Two-stay two-stray model on improving mathematical communica...

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Seminar on Advances in Mathematics, Science and Engineering for Elementary School, SAMSES 2018

作者： Suwangsih, E. Budiarti, M.R. Ruskandi, K. Hendawati, Y. Majid, N.W.A. Study Program of Elementary School Teacher Training Universitas Pendidikan Indonesia Indonesia Study Program of System and Information Technology Education Universitas Pendidikan Indonesia Indonesia

The basis of this research is to observe the importance of improving the mathematical communication skill of elementary school students. In this case, this research attempted to discover learning alternative that could improve mathematical communication skill of students by employing Two-Stay Two-Stray (TSTS) cooperative learning model. This research aimed to examine students' mathematical communication skill and mathematics learning improvement by employing TSTS model. The employed method was a quasi-experiment of the non-equivalent pretest-posttest control group design. The participants for this study were the 5th-grade students of one of the public elementary schools in one of the districts in Purwakarta Regency. In this study, 26 students were employed as participants for each experimental and controlled group. This research discovered that: 1) students' mathematical communication skill improvement that was taught using TSTS learning model was higher compared conventional model;2) TSTS model was found influencing the improvement of students' mathematical communication skill;3) students' mathematics learning activity and process was more active and improved with TSTS model. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Reconstructing Suspended Sediment Concentrations in the Mekong River Basin Via Semi-Supervised-Based Deep Neural Networks

SSRN

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SSRN 2024年

作者： Nguyen, Thi-Thu-Ha Vu, Duc Quang Doan, Ngoc Phu Thi Khanh Chi, Huynh Li, Peixin Van Binh, Doan An, Yimeng Tuan Dung, Pham Hoang, Tuan A. Thai Son, Mai Laboratory of Environmental Sciences and Climate Change Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City70000 Viet Nam Faculty of Environment School of Technology Van Lang University Ho Chi Minh City70000 Viet Nam Department of Computer Science and Information System Thai Nguyen University of Education Viet Nam School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast United Kingdom College of Economics and Management Nanjing University of Aeronautics and Astronautics China Master program in Water Technology Reuse and Management Faculty of Engineering Vietnamese-German University Binh Duong Province Ben Cat Town820000 Viet Nam

The Mekong River Basin (MRB) is one of the highest biodiversity areas in the world and is the vital source of livelihoods for more than 60 millions of people over six countries in Southeast Asia. However, it is suffering from a severe sediment starvation problem caused by climate change and human activities, particularly dam constructions. Understanding long-term sediment changes thus plays a crucial role for management and contingency plans. Current sediment concentration data in the MRB are extremely sporadic, making it a non-trivial task to analyze them. This paper focuses on the sediment reconstruction to provide long-term reliable suspended sediment concentration (SSC) data using Machine Learning (ML) perspectives. In particular, a novel semi-supervised ML model, which can effectively deal with data sparsity, is introduced to predict/reconstruct missing sediment data. The key idea of this approach is to exploit abundant available hydroclimate data to reduce training overfitting rather than solely relying on sediment concentration data, thus enhancing the accuracy of the employed ML models. Extensive experiments on data obtained from 1979 to 2019 at the three main stations (i.e., Chiang Saen, Nong Khai, and Mukdahan) are conducted to demonstrate the performances of the proposed method compared to other state-of-the-art supervised techniques and traditional simulation methods commonly used in previous sediment forecasting/reconstruction studies. To the best of our knowledge, this approach is the first semi-supervised method to reconstruct sediment data in the field. Though this study focuses on the MRB, sediment sparsity is a very common problem in other river systems worldwide. Thus, this method can be widely applied for them for more effective sediment reconstruction/prediction in general. © 2024, The Authors. All rights reserved.

关键词： Biodiversity

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Contextual teaching and learning of physics at elementary school

Contextual teaching and learning of physics at elementary sc...

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Seminar on Advances in Mathematics, Science and Engineering for Elementary School, SAMSES 2018

作者： Hendawati, Y. Pratomo, S. Suhaedah, S. Lestari, N.A. Ridwan, T. Majid, N.W.A. Study Program of Elementary School Teacher Training Universitas Pendidikan Indonesia Bandung Indonesia Teacher Elementary School Bandung Indonesia Study Program of System and Information Technology Education Universitas Pendidikan Indonesia Bandung Indonesia

The student should be a master for science comprehension concepts, especially in material styles found in everyday life. The research aims to know influence approaching Contextual Teaching and Learning on the improve ability to comprehend the science concept. The experiment was carried out for 3 weeks involving 50 grade V elementary school students based on equal ability levels. pre-test and post-test refers to the falling motion material of an object due to gravitational force, how to enlarge and minimize friction force, as well as factors that influence the magnetic breakthrough force. As for each meeting an observation was carried out on 50 elementary school students conducted by the observer. The results of this test are processed and analyzed further using a t-test. The result showed that there is a significant difference between the ability of understanding concept students of experimental class using Contextual Teaching and Learning with control class students using direct learning method with pre-test post-test ≤ 0,05. Other than that the T test and N-gain of both classes showed the result of 0.000. That is approach Contextual Teaching and Learning influencing to improve understanding ability students' concept science learning method in elementary school. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Correlation between mathematic learning outcomes and self-regulated learning in the covid-19 pandemic situation

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Journal of Physics: Conference Series 2021年第1期1987卷

作者： H E Putri A S Sasqia A Abdulloh S Fuada I Muqodas N W A Majid Elementary Teacher Education Program Universitas Pendidikan Indonesia Purwakarta Indonesia Telecommunication System Program Universitas Pendidikan Indonesia Purwakarta Indonesia Childhood Education Program Universitas Pendidikan Indonesia Purwakarta Indonesia Information Technology Education System Program Universitas Pendidikan Indonesia Purwakarta Indonesia

The COVID-19 pandemic brought major changes in the education field in Indonesia. The face-to-face learning system that usually dominates the school learning system has changed to an online learning system. The purpose of this study is to reveal how much the correlation between mathematics learning outcomes and students self-regulated learning in elementary schools when online-based learning systems were applied during the COVID-19 pandemic. This research is a quasi-experiment of the fractions topic which applied to 54 students from one of the elementary schools in central Jakarta, Indonesia. Mathematics learning outcomes test and self-regulated learning questionnaires are given before and after online learning is conducted. Online learning is done with a group of the WhatsApp application and learning videos that are broadcasted through the YouTube channel. The results of the study show that the correlation between mathematics learning outcomes and self-regulated learning of elementary school students is 0.424. Based on the criteria from Guilford, the magnitude of the correlation value is in the medium criteria. The results of the study concluded that there is a correlation between mathematics learning outcomes and students self-regulated learning. The higher the student mathematics learning outcomes, the higher the self-regulated student circulation, and vice versa.

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Seeding Rate Detection and Distribution Evaluation Using the Developed Automatic Maize Seeding Machine

SSRN

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SSRN 2023年

作者： Li, Yunxia Zhang, Zhao Azizi, Afshin Kabir, Muhammand Hilal Igathinathane, Cannayen Wang, Xiqing Tahir, Muhammad Naveed Han, Xiongzhe Zhang, Man Key Laboratory of Smart Agriculture System Integration Ministry of Education Beijing100083 China Key Laboratory of Agricultural Information Acquisition Technology Ministry of Agriculture and Rural Affairs Beijing100083 China College of Information and Electrical Engineering China Agricultural University Beijing100083 China Department of Agricultural and Biosystems Engineering North Dakota State University 1231 Albrecht Blvd FargoND58102 United States College of Biological Sciences China Agricultural University Beijing100083 China Department of Agronomy PMAS-Arid Agriculture University Rawalpindi46300 Pakistan Department of Biosystems Engineering College of Agriculture and Life Sciences Kangwon National University Chuncheon24341 Korea Republic of Interdisciplinary Program in Smart Agriculture College of Agriculture and Life Sciences Kangwon National University Chuncheon Korea Republic of

Highlights● A new automatic maize seeding machine was developed and tested.● YOLOV5 combined with merge-NMS, with 960×960 images, can accurately detect maize seeding rate.● YOLOV5 with merge-NMS is robust for processing images under different illumination.● The seeding rate can be correctly detected with an average accuracy of 91.14%. © 2023, The Authors. All rights reserved.

关键词： Precision agriculture

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Improving health awareness with real-time monitoring through a three-dimensional visualized digital health avatar

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Smart Health 2024年 34卷

作者： Chokphukhiao, Chaturapron Pattaranit, Pattrawan Tun, Wonn Shweyi Thet Masa, Sakaowrat Leemananil, Rattikorn Natteerapong, Nuttaphorn Phetcharaburanin, Jutarop Boonlue, Sophon Sunat, Khamron Patramanon, Rina Information Technology International Program College of Computing Khon Kaen University Khon Kaen 40002 Thailand Center of Excellence in Digital Innovation Faculty of Education Khon Kaen University Khon Kaen 40002 Thailand Integrative Biomedical Informatics and Computational Imaging Center I-BIC Faculty of Associated Medical Science Khon Kaen University Khon Kaen 40002 Thailand Department of System Biosciences and Computational Medicine Faculty of Medicine Khon Kaen University Khon Kaen 40002 Thailand Khon Kaen University National Phenome Institute Khon Kaen University Khon Kaen 40002 Thailand Department of Biochemistry Faculty of Science. Khon Kaen University Khon Kaen 40002 Thailand Department of Microbiology Faculty of Science Khon Kaen University Khon Kaen 40002 Thailand Department of Computer Science College of Computing Khon Kaen University 40002 Thailand

Introduction: The use of modern technologies has become crucial for enhancing people's awareness of health problems. By early health risk detection, there will be better treatment outcomes, the severity of illness will decrease, and costs for treatment will also reduce. Performing routine checkups could help patients feel less anxious about their health in the future. In this study, the innovation of “Digital Health Avatar” enables users to monitor physical changes, raise awareness of medical conditions, and encourage healthy behaviors by visualizing health status as a 3D figure. Methods: Health data were collected using medical devices like blood test strips, body composition meters, and automatic blood pressure monitors. API technology and cloud computing systems were used to process these collected data and produced a three-dimensional avatar that indicated the user's health status. User satisfaction survey on using the health avatar system was assessed through a survey of 61 participants. Results: Health avatar system successfully generate the data and display the measurement results on the health report page of the system. Users can easily check and record their physiological conditions through the avatar. Moreover, users showed satisfaction on the use of the health avatar system and its effectiveness in health check-ups in the survey. Conclusions: The ‘Digital Health Avatar’ has the potential to significantly promote individual well-being and health awareness. Its development will be improved by user feedback and continued study, ensuring it becomes an efficient tool for promoting healthier lifestyles. © 2024 The Authors

关键词： Digital health avatar Health sensors Healthcare Three-dimensional model

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Rubber Plant Disease Diagnostic system Using Technique for Order Preference by Similarity to Ideal Solution

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Procedia Computer Science 2019年 161卷 484-492页

作者： Ramadiani M. Syahrir Ramadhani Muhammad Labib Jundillah Azainil Faculty of Computer Science and Information Technology Mulawarman University Samrinda Indonesia Magister Program of Information System School of Post Graduate Studies Diponegoro University Semarang Indonesia Faculty of Teacher Training and Education Mulawarman University Samarinda Indonesia

Data from the Plantation Office of East Kalimantan Province, the area of rubber plantations has decreased every year. One of the factors that make productivity of rubber plants low is the presence of pests and diseases. The time limit of an expert is an obstacle in identifying rubber plantations. To overcome this problem, we need an expert system that can identify rubber plant diseases such as an expert. This system was developed to be able to provide solutions in diagnosing rubber plant diseases such as White Root Fungus (Rigidoporus micropus), Upas Mushroom Disease (Corticium salmonicolor), Antraknosa Disease (Colletorichum gloeosporoides), Skin Necrosis (Fusarium sp.), And Cancer Lines (Phytoptora palmivore). This study uses the TOPSIS method. There are four variables used as assessment criteria in this study, namely: the level of damage to the root, the level of damage to the stem, the level of damage to the leaves and the level of damage to the tapping path or the intensity of tapping, with preference values from 0 to 100; none, Very Light Intensity (1), Mild Intensity (3), Medium Intensity (5), Weight Intensity (7) and Very Heavy Intensity (9). Each weight value C1= 0.3; C2= 0.22; C3= 0.28; C4= 0.2. The results of this study compare manual calculations and calculations on the system obtained 99.99% accuracy. This system is expected to help facilitate rubber farmers in identifying diseases and can help experts.

关键词： Rubber Plant Disease East Kalimantan TOPSIS Expert system

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