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The effect of the cyclic curricular design of modelling-based instruction with virtual labs

International Journal of science Education 2024年第1期46卷 46-72页

作者： Chang, Hsin-Yi Liu, Chen-Chung Wen, Chi-Ting Chang, Ming-Hua Fan Chiang, Shih-Hsun Hwang, Fu-Kwun Program of Learning Sciences and Institute for Research Excellence in Learning Sciences National Taiwan Normal University Taipei Taiwan Department of Computer Science and Information Engineering National Central University Taoyuan Taiwan Department of Computer Science and Information Management Soochow University Taipei Taiwan Department of Physics National Taiwan Normal University Taipei Taiwan

One issue facing teachers who implement model-based instruction within the school system is the tight curricular schedule. The ‘lesson objective tension’ calls for investigations to address instructional issues such as how to organise modelling-based instruction at the curriculum level which is across multiple units. We investigated the effect of the cyclic curricular design spacing out three modelling-based instruction units with virtual labs over three semesters, each involving 73, 181, and 150 junior high school students, respectively. Results indicate that, overall, the approach of modelling with virtual labs better promoted students’ scientific literacy than the traditional instruction did. Specifically, students with low and moderate school science achievements benefitted more as shown in their scientific literacy scores than did the high achievement students. Furthermore, this study found that receiving one unit of modelling-based instruction may not be sufficient to promote students’ scientific literacy, whereas the cyclic approach that suggests students receive two or more units of modelling-based instruction with virtual labs spaced over consecutive semesters had significant effects on promoting students’ scientific literacy. The results provide insights into when and how modelling-based learning with virtual labs can promote scientific literacy at a curricular level. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： lesson objective tension Modelling virtual labs

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Effects of an automated programming assessment system on the learning performances of experienced and novice learners

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Interactive Learning Environments 2023年第8期31卷 5347-5363页

作者： Cheng, Li-Chen Li, Wei Tseng, Judy C. R. Department of Information and Finance Management National Taipei University of Technology Taipei Taiwan STEM Education Research Center Wenzhou University Zhejiang Province Wenzhou China Ph.D. Program in Engineering Science Chung Hua University Hsinchu Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu Taiwan

programming ability is the core ability of this era and can be obtained and improved through practice. In this paper, an Automated programming Assessment system based on Mastery learning and Peer competition (APAMP) was proposed and developed. APAMP allows students to practice repeatedly by providing immediate feedback after their programs are submitted. It also presents an analytical dashboard as a competition mechanism for students to visualize their learning performance and compare their performance with peers. By incorporating APAMP into programming courses, students can master programming skills through repeated practice, and their enthusiasm for learning programming can also be encouraged by peer competition. To evaluate the effects of APAMP on the learning performance of students with programming language learning and novice students, a quasi-experiment was conducted in a high school. The experimental results showed that the learning achievement of the two groups of students improved significantly. Moreover, the learning attitude of students in the experienced group improved significantly, with the experienced students benefiting more from the system than the novice students. In fact, the novice students showed a significant decline in learning attitude and learning motivation, which was contrary to our intuition. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

关键词： automated programming assessment systems learning performance mastery learning peer competition programming instruction

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Advancements in sludge-to-energy strategies for rubber processing industries: a comprehensive review

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International Journal of Energy and Water Resources 2025年第2期9卷 1189-1199页

作者： Tin, K.K. Taweepreda, W. Singh, A. Kumar, A. Environmental Management Faculty of Environmental Management Prince of Songkla University Hat-Yai Songkhla 90110 Thailand Polymer Science Program Division of Physical Science Faculty of Science Prince of Songkla University Hat-Yai Songkhla 90110 Thailand Department of Zoology Swami Shraddhanand College University of Delhi Delhi 110036 India Department of Mechanical Engineering Delhi Technological University Delhi 110042 India Nodal Centre of Excellence in Energy Transition (NCEET) Delhi Technological University Delhi 110042 India

This study explores the energy potential of rubber sludge, highlighting its calorific value (13.92–22.15 MJ/kg) and significant organic content, making it a promising feedstock for renewable energy. Techniques such as pyrolysis, anaerobic digestion, combustion, and gasification can effectively harness this potential. Comparative analysis indicates that rubber sludge has an energy recovery potential comparable to or even higher than lignite. Thermochemical processes, including hydrothermal liquefaction and gasification, offer benefits such as reduced waste toxicity and volume, alongside energy and material recovery. However, challenges such as high costs, technical difficulties, and potential pollutant emissions persist. Cost–benefit analyses indicate economic feasibility under specific conditions like high conversion efficiency and favorable policies. Current global practices in rubber sludge management vary, with countries like Denmark, Germany, and Sweden implementing advanced treatments, while others face challenges in coordination and technology. Future research emphasizes improving conversion technologies and integrating hybrid energy systems to enhance energy recovery and reduce environmental impact. The study underscores the importance of life cycle assessments in optimizing the sustainability of rubber sludge-to-energy processes and advocates for innovative approaches through Design Thinking to develop tailored solutions. This comprehensive review highlights the potential of rubber sludge as a renewable energy source and provides a framework for future research and policy development. © The Author(s), under exclusive licence to Iranian Society of Environmentalists (IRSEN) and science and Research Branch, Islamic Azad University 2024.

关键词： Energy Factory Rubber processing Sludge Sustainable

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Concurrent Delay Analysis via Cooperative Game Theory

Concurrent Delay Analysis via Cooperative Game Theory

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Construction Research Congress 2024, CRC 2024

作者： Hajiashrafi, Fatemeh Huynh, Huu T. Lucko, Gunnar Eid, Mohamed S. Construction Engineering and Management Program Dept. of Civil and Environmental Engineering Catholic Univ. of America WashingtonDC United States Dept. of Civil and Environmental Engineering Catholic Univ. of America WashingtonDC United States Dept. of Construction and Building Engineering College of Engineering and Technology Arab Academy for Science Technology and Maritime Transport Cairo Egypt

ISBN: (数字)9780784485286

ISBN: (纸本)9780784485286

Despite various attempts throughout past decades to deal with concurrent delays in construction project schedules, they continue to be a vexing issue that has eluded an unambiguous solution. Prior studies have resorted to the prime contract, which only binds general contractor and owner, cannot be proven to be fair, and may even be biased. Therefore, this paper adopts a concept from cooperative game theory, the Shapley value, which apportions profits (which project participants seek to maximize). Creatively applying it to liquidated damages (which they seek to minimize), the model uses all participants' actual finish dates as input to gain percentage shares of liquidated damages as output. Analyzing all possible coalitions among participants and assigning weights comprehensively assesses their marginal contributions to the project finish date. This generalized view of participants explicitly includes subcontractors, whom prior approaches typically ignored. An example demonstrates how the model also implies an early completion bonus. This yields compelling implications for real-world incentives that can be cast into future contract clauses. © ASCE.

关键词： Contractors

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Using Real-Time Integrated Computer Vision and Deep Learning for Advanced Factory Safety 4

Using Real-Time Integrated Computer Vision and Deep Learning...

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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Tsai, Shang-Te Chang, Yu-Cheng Huang, Chao-Yi Yang, Fang-Yuan Chien, Wei Wu, Zong-Rong School Art and Design Sanming University Fujian China National Taipei University of Technology Department of Computer Science and Information Engineering Taipei Taiwan National Yunlin University of Science and Technology Department of Information Management Yunlin Taiwan Lunghwa University of Science and Technology Department of Computer Information and Network Engineering Taoyuan Taiwan National Yunlin University of Science and Technology Department of Technical and Vocational Program in Artificial Intelligence Yunlin Taiwan

ISBN: (纸本)9798350360721

Innovative safety in the workplace is vital as the high safety risks associated with electrical engineering construction can lead to injuries or even fatalities. Using computer vision technology, we experimented with scenarios such as 'normal operations' and 'unexpected incidents' to enhance safety measures. We integrated an Internet of Things system into the setup, enabling the system to quickly detect and alert to unexpected events in real-time, thereby improving workplace safety. © 2024 IEEE.

关键词： Computer vision

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Identification of Extreme Precipitation Changes Due to Climate Change in Indonesia 3rd

Identification of Extreme Precipitation Changes Due to Clima...

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3rd International Conference on Radioscience, Equatorial Atmospheric science and Environment, INCREASE 2023

作者： Aminah, Siti Riawan, Edi Syahputra, Muhammad Ridho Kuntoro, Arno Adi Master Program in Water Resource Management Faculty of Civil and Environmental Engineering Bandung Institute of Technology Bandung Indonesia Atmospheric Sciences Research Group Faculty of Earth Science and Technology Bandung Institute of Technology Bandung Indonesia Water Resources Engineering Research Group Faculty of Civil and Environmental Engineering Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9789819707393

This study uses Global Precipitation Measurement (GPM) and Coupled Model Intercomparison Project Phase 6 (CMIP6) precipitation data to identify extreme precipitation intensity and frequency changes in Indonesia. Extreme precipitation calculations were performed using the Gumbel distribution and return period fitted to annual maxima data. Extreme precipitation and frequency of extreme events were compared between the historical period and the near-future period (2026–2055) and the far-future period (2070–2099) to identify changes. The results showed that there were changes in extreme precipitation in Indonesia both in intensity and frequency of occurrence. Extreme precipitation with a 5-year return period in Indonesia generally has a change value in the range of − 5 to + 25% with most areas likely to increase. The increased value reaches + 20% in the near-future period and + 40% in the far-future period. For the frequency of extreme precipitation above the 5-year return period in Indonesia, the change value is generally in the range of − 40 to + 120% with most areas likely to increase. The increased value reaches + 160% in the near-future period and + 200% in the far-future period. In the higher emission scenario (SSP5-8.5), the areas with higher values of increase will expand both in the change in intensity and frequency of occurrence. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Climate change

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Identification of Cancer Biomarkers for Multi-class Diagnostics through Network Analysis of RNAseq Data of Tumor-Educated Platelets

Identification of Cancer Biomarkers for Multi-class Diagnost...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Toccacieli, Ali Petti, Manuela Sapienza University of Rome MSc Program in Engineering in Computer Science Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9781665468190

Tumor-educated platelets (TEPs) are circulating blood cells with a distinct tumor-driven phenotype and act as carriers and protectors of metastases. To date, some studies have shown that the TEPs transcriptome can be used for cancer diagnostics. The objective of this study is to propose a procedure based on differential gene expression and differential gene co-expression analyses to identify a set of key genes for multi-class cancer diagnostics. To reach this aim, we analyzed RNA-seq data (57736 genes) of 130 subjects, of whom 40 patients with glioblastoma multiforme (GBM), 35 patients with pancreatic adenocarcinoma (PAAD), and 55 healthy donors (HC). We focused our analysis on the subset of differentially expressed genes (DEGs), and we used these genes to build and analyze the differential co-expression networks, identifying the hub genes. With this procedure, we obtained a restricted set of DEGs that maximize the accuracy in classifying patients according to their conditions (GBM, PAAD, or HC). Indeed, we validated our results by comparing the achieved classification accuracy with that resulting from random selections of DEGs and we obtained that genes selected by differential co-expression (DCE) network analysis have greater predictive power than any other set of differentially expressed genes, including using all of them. © 2022 IEEE.

关键词： Platelets

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A Hybrid Learning Approach for Automatic Data Labelling and Anomaly Detection in IoT Networks 3

A Hybrid Learning Approach for Automatic Data Labelling and ...

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3rd IEEE International Conference on Artificial Intelligence, ICAI 2023

作者： Kanwal, Rimsha Noor, Umara Rashid, Zahid International Islamic University Faculty of Computing and Information Technology Department of Computer Science Islamabad Pakistan College of Engineering Technology Management Economics and Policy Program Seoul National University Seoul Korea Republic of

ISBN: (纸本)9798350322125

Internet of Things (IoT) is an environment in which digital equipment is augmented with sensors to share and receive data through network. When devices share data it can be effected by anomalies or any attack due to corrupted data or by any other uncertainty and ambiguity in data. The data can also be corrupted through a damage in device. These attacks or anomalies damage the working of the IoT networks. The anomalous data can be detected through detection techniques however most anomaly detection techniques depend upon labelled data but for IoT datasets, usually class labels are not available. Labeling is performed by a manual process which is time consuming and also costly. As data in IoT increases day by day so there is a need to label and classify data for future unseen data. In this paper a hybrid algorithm is proposed in which both clustering and classification techniques are applied for automatic labeling and classifying on IoT dataset. The model contains two function. In the first phase k-means clustering is employed for labelling dataset instances as normal or anomalous. In the second phase labelled dataset is used to train Random Forest model to detect anomalies in IoT networks. The results show that the proposed model is detecting anomalies in IoT networks with an accuracy 98%, precision 98 %, recall 98%, and F-meausre 0.98%. © 2023 IEEE.

关键词： Classification (of information)

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Online stochastic generators using Slepian bases for regional bivariate wind speed ensembles from ERA5

arXiv

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arXiv 2024年

作者： Song, Yan Khalid, Zubair Genton, Marc G. Statistics Program King Abdullah University of Science and Technology Saudi Arabia School of Science and Engineering Lahore University of Management Sciences Pakistan

Reanalysis data, such as ERA5, provide a comprehensive and detailed representation of the Earth’s system by assimilating observations into climate models. While crucial for climate research, they pose significant challenges in terms of generation, storage, and management. For 3-hourly bivariate wind speed ensembles from ERA5, which face these challenges, this paper proposes an online stochastic generator (OSG) applicable to any global region, offering fast stochastic approximations while storing only model parameters. A key innovation is the incorporation of the online updating, which allows data to sequentially enter the model in blocks of time and contribute to parameter updates. This approach reduces storage demands during modeling by eliminating the need to store and analyze the entire dataset, and enables near real-time emulations that complement the generation of reanalysis data. The Slepian concentration technique supports the efficiency of the proposed OSG by representing the data in a lower-dimensional space spanned by data-independent Slepian bases optimally concentrated within the specified region. We demonstrate the flexibility and efficiency of the OSG through two case studies requiring long and short blocks, specified for the Arabian-Peninsula region (ARP). For both cases, the OSG performs well across several statistical metrics and is comparable to the SG trained on the full dataset. Copyright © 2024, The Authors. All rights reserved.

关键词： Wind

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A Novel Blockchain-Based Strategy for Energy Conservation in Cognitive Wireless Sensor Networks 4

A Novel Blockchain-Based Strategy for Energy Conservation in...

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4th International Conference on Blockchain Technology and Information Security, ICBCTIS 2024

作者： Sharma, Khemraj Goyal, Rohit Bhagat, Sukesh Kumar Agarwal, Sheenu Bisht, Girish Singh Hussien, Mohemmed Nanhua University Department of Business Administration Doctoral Program in Management Sciences Dalin62248 Taiwan School of Engineering and Computing Dev Bhoomi Uttarakhand University Dehradun India Uttaranchal University Department of Computer Science & Engineering Dehradun India Uttarakhand Technical University Department of Electronics and Communication Engineering Dehradun India Tula's Institute Dehradun India Department of Computer Science and Engineering Dehradun248001 India The Islamic University Najaf Iraq

ISBN: (纸本)9798331528324

Internet of Things (IoT) industrial applications have increased in internet-connected devices. As a result, accessibility, scalability, connectivity, and adaptability have become major challenges. It is possible to create connections between loT devices over the wireless medium, but efficiently utilizing scarce spectrum is the biggest concern. The paper proposes a novel method for selecting sensing nodes with the goal of reducing energy usage and increasing sensing efficiency. In order to ensure that node trust values conform to each other without any ambiguity, cryptography encrypts all information that relates to a node in a central node (CN). Nodes participating in CSS are selected based on their performance. Based on a comparison of various algorithms using varying numbers of nodes, the proposed algorithm achieves a 10% sensing efficiency. © 2024 IEEE.

关键词： Blockchain Network Network Communication security Wireless Sensor

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