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Transformative Effects of ChatGPT on Modern Education: Emerging Era of AI Chatbots

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arXiv 2023年

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, was released to provide coherent and useful replies based on analysis of large volumes of data. In this article, leading scientists, researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research seeks to improve our knowledge of ChatGPT capabilities and its use in the education sector, identifying potential concerns and challenges. Our preliminary evaluation concludes that ChatGPT performed differently in each subject area including finance, coding and maths. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within Generative AI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023, CC0.

关键词： Machine learning

Chinese Named Entity Recognition in Industry Domain Based on Lexical Enhancement

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Chinese Named Entity Recognition in Industry Domain Based on...

Cyber Science and Technology Congress (CyberSciTech), IEEE

作者： Jingxin Zhao Zhenxing Ni Cuilan Liu Jiadong Ren Caiyun Liu Yuqing Zhang Institute of Applied Mathematics Hebei Academy of Sciences Shijiazhuang China School of Information Science and Engineering Yanshan University Qinhuangdao China HBIS Group Co. Ltd. Shijiazhuang China Guangzhou Research Institute Xidian University Guangzhou China China Industrial Control Systems Cyber Emergency Response Team Beijing China National Computer Network Intrusion Protection Center University of Chinese Academy of Science Beijing China

ISBN: (数字)9798331532093

ISBN: (纸本)9798331532109

Named entity recognition is the premise of realizing information extraction and information retrieval in industrial domain, and it is also the basic means of realizing industrial data security management. As an important basic industry in the industrial field, the steel field has huge data, complex text semantics and numerous proprietary terms, so it is difficult to identify named entities in steel domain because of the complex semantics of the text and the variety of proper nouns. In order to improve the performance of named entity recognition in steel domain, a named entity recognition dataset of steel and a MacBERT-FLAT-CRF model based on lexical enhancement are constructed. The results show that, compared with other NER models, this model has a good effect on the self-built named entity recognition dataset, which effectively improves the recognition effect of named entities in the steel field and improves the problems of insufficient use of vocabulary information and lack of data in the steel field.

关键词： Industries Deep learning Vocabulary Annotations Data security Semantics Named entity recognition Data augmentation Data models Steel

Coverage Probability of STAR-RIS assisted Massive MIMO systems with Correlation and Phase Errors

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arXiv 2022年

作者： Papazafeiropoulos, Anastasios Abdullah, Zaid Kourtessis, Pandelis Kisseleff, Steven Krikidis, Ioannis The Communications and Intelligent Systems Research Group University of Hertfordshire HatfieldAL10 9AB United Kingdom The SnT The University of Luxembourg Luxembourg The IRIDA Research Centre for Communi-Cation Technologies Department of Electrical and Computer Engineering University of Cyprus Cyprus Cyprus

In this paper, we investigate a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisting a massive multiple-input multiple-output (mMIMO) system. In particular, we derive a closed-form expression for the coverage probability of a STAR-RIS assisted mMIMO system while accounting for correlated fading and phase-shift errors. Notably, the phase configuration takes place at every several coherence intervals by optimizing the coverage probability since the latter depends on statistical channel state information (CSI) in terms of large-scale statistics. As a result, we achieve a reduced complexity and overhead for the optimization of passive beamforming, which are increased in the case of STAR-RIS networks with instantaneous CSI. Numerical results corroborate our analysis, shed light on interesting properties such as the impact of the number of RIS elements and the effect of phase errors, along with affirming the superiority of STAR-RIS against reflective-only RIS. © 2022, CC BY.

关键词： MIMO systems

Extensible logging and empirical attainment function for IOHexperimenter

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arXiv 2021年

作者： Dreo, Johann López-Ibáñez, Manuel Systems Biology Group Computational Biology Department Institut Pasteur Université de Paris France School of Computer Science and Engineering University of Málaga Málaga Spain

In order to allow for large-scale, landscape-aware, per-instance algorithm selection, a benchmarking platform software is key. IOHexperimenter provides a large set of synthetic problems, a logging system and a fast implementation. In this work, we refactor IOHexperimenter’s logging system, in order to make it more extensible and modular. Using this new system, we implement a new logger, which aim at computing performance metrics of an algorithm across a benchmark. The logger computes the most generic view on an anytime stochastic heuristic performances, in the form of the Empirical Attainment Function (EAF). We also provide some common statistics on the EAF and its discrete counterpart, the Empirical Attainment Histogram. Our work has eventually been merged in the IOHexperimenter codebase. Copyright © 2021, The Authors. All rights reserved.

关键词： Stochastic systems

Chances and Challenges of ChatGPT and Similar Models for Education in M&S

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Chances and Challenges of ChatGPT and Similar Models for Edu...

Simulation Winter Conference

作者： Andreas Tolk Philip Barry Margaret L. Loper Ghaith Rabadi William T. Scherer Levent Yilmaz Modeling and Analysis Innovation Center The MITRE Corporation Charlottesville VA USA Mission Analysis Group L3Harris Corporation Herndon VA USA Georgia Tech Research Institute Georgia Institute of Technology Atlanta GA USA University of Central Florida School of Modeling Simulation and Training Orlando FL USA Department of Systems and Information Engineering University of Virgina Charlottesville VA USA Samuel Ginn College of Engineering Computer Science and Software Engineering Auburn University Auburn AL USA

This position paper summarizes the inputs of a group of experts from academia and industry presenting their view on chances and challenges of using ChatGPT within Modeling and Simulation education. The experts also address the need to evaluate continuous education as well as education of faculty members to address scholastic challenges and opportunities while meeting the expectation of industry. Generally, the use of ChatGPT is encouraged, but it needs to be embedded into an updated curriculum with more emphasis on validity constraints, systems thinking, and ethics.

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High-field/high-frequency electron spin resonances of Fe-doped β−Ga2O3 by terahertz generalized ellipsometry: Monoclinic symmetry effects

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Physical Review B 2024年第21期109卷 214106-214106页

作者： Steffen Richter Sean Knight Oscar Bulancea-Lindvall Sai Mu Philipp Kühne Megan Stokey Alexander Ruder Viktor Rindert Viktor Ivády Igor A. Abrikosov Chris G. Van de Walle Mathias Schubert Vanya Darakchieva Competence Center for III-Nitride Technology C3NiT-Janzén Solid State Physics and NanoLund Competence Center for III-Nitride Technology C3NiT-Janzén Department of Physics Chemistry and Biology (IFM) Department of Physics Chemistry and Biology (IFM) Materials Department Department of Physics and Astronomy Department of Electrical and Computer Engineering Department of Physics of Complex Systems MTA–ELTE Lendület “Momentum” NewQubit Research Group Pázmány Péter Sétány 1/A 1117 Budapest Hungary

We demonstrate detection and measurement of electron paramagnetic spin resonances (EPR) of iron defects in β−Ga2O3 utilizing generalized ellipsometry at frequencies between 110 and 170 GHz. The experiments are performed on an Fe-doped single crystal in a free-beam configuration in reflection at 45∘ and magnetic fields between 3 and 7 T. In contrast with low-field, low-frequency EPR measurements, we observe all five transitions of the s=5/2 high-spin state Fe3+ simultaneously. We confirm that ferric Fe3+ is predominantly found at octahedrally coordinated Ga sites. We obtain the full set of fourth-order monoclinic zero-field splitting parameters for both octahedrally and tetrahedrally coordinated sites by employing measurements at multiple sample azimuth rotations. The capability of high-field EPR allows us to demonstrate that simplified second-order orthorhombic spin Hamiltonians are insufficient, and fourth-order terms as well as consideration of the monoclinic symmetry are needed. These findings are supported by computational approaches based on density-functional theory for second-order and on ligand-field theory for fourth-order parameters of the spin Hamiltonian. Terahertz ellipsometry is a way to measure spin resonances in a cavity-free setup. Its possibility of varying the probe frequency arbitrarily without otherwise changing the experimental setup offers unique means of truly disentangling different components of highly anisotropic spin Hamiltonians.

关键词： Defects Dopants Energy materials Paramagnets Wide band gap systems Spin Electron paramagnetic resonance Terahertz spectroscopy Terahertz techniques

Global Stability and Optimal Control of Epidemics in Heterogeneously Structured Populations Exhibiting Adaptive Behaviour

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SSRN

SSRN 2023年

作者： Liu, Lixiang Chen, Shanshan Small, Michael Moore, Jack Murdoch Shang, Keke Department of Computer Science School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai201620 China Complex Systems Group Department of Mathematics and Statistics The University of Western Australia Perth6009 Australia Mineral Resources Commonwealth Scientific and Industrial Research Organisation Kensington6151 Australia MOE Key Laboratory of Advanced Micro-Structured Materials School of Physics Science and Engineering Tongji University Shanghai200092 China Computational Communication Collaboratory Nanjing University Nanjing210093 China

During the outbreak of infectious diseases, individual always make some adaptive response to avoid infected the diseases. In this paper, we introduce SIRS model on scale-free networks that take into account behavioral memory and time delay to depict individuals’ adaptive feedback, which is better characterize the actual spread of epidemics. We address uniform persistence and find that the model has the sharp threshold property, that is, for the basic reproduction number less than one, the disease-free equilibrium is globally asymptotically stable, while for the basic reproduction number is above one, the endemic equilibrium is globally stable. We further analyze the effects of two control strategies (the vaccination of susceptible people and treatment of infected people) on epidemic dynamics by optimal control strategy. The existence and uniqueness of the optimal control strategy are obtained. Finally, we perform some stochastic network simulations that yield quantitative agreement with the deterministic mean-field approach. The final results show that the effect of time delay does not change the basic reproduction number, but it plays an important role in the process of disease transmission. The behavioral memory is able to affect the basic reproduction number, and it has important and positive implications for disease transmission and control. The work of this paper can provide a theoretical basis and reference for the prediction and prevention of infectious diseases. © 2023, The Authors. All rights reserved.

关键词： Diseases

A Web-Based Tool for Automatic Data Collection, Curation, and Visualization of Complex Healthcare Survey Studies including Social Network Analysis

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arXiv 2024年

作者： Benítez-Andrades, José Alberto Labra, José Emilio Quiroga, Enedina Martín, Vicente García, Isaías Marqués-Sánchez, Pilar Benavides, Carmen Department of Electrical and Systems Engineering Universidad de León Campus de Vegazana s/n León24071 Spain Department of Computer Science Universidad de Oviedo C/Calvo Sotelo s/n Oviedo33007 Spain SALBIS Research Group Facultad de Ciencias de la Salud Campus de Ponferrada Avda Astorga s/n Ponferrada León24402 Spain GIGAS Research Group Facultad de Ciencias de la Salud Campus de Vegazana s/n León24071 Spain

There is a great concern nowadays regarding alcohol consumption and drug abuse, especially in young people. Analyzing the social environment where these adolescents are immersed, as well as a series of measures determining the alcohol abuse risk or personal situation and perception using a number of questionnaires like AUDIT, FAS, KIDSCREEN, and others, it is possible to gain insight into the current situation of a given individual regarding his/her consumption behavior. But this analysis, in order to be achieved, requires the use of tools that can ease the process of questionnaire creation, data gathering, curation and representation, and later analysis and visualization to the user. This research presents the design and construction of a web-based platform able to facilitate each of the mentioned processes by integrating the different phases into an intuitive system with a graphical user interface that hides the complexity underlying each of the questionnaires and techniques used and presenting the results in a flexible and visual way, avoiding any manual handling of data during the process. Advantages of this approach are shown and compared to the previous situation where some of the tasks were accomplished by time consuming and error prone manipulations of data. © 2024, CC BY-NC-ND.

关键词： Visualization

A Q-learning-based smart clustering routing method in flying Ad Hoc networks

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Journal of King Saud University - computer and Information Sciences 2024年第1期36卷

作者： Hosseinzadeh, Mehdi Tanveer, Jawad Rahmani, Amir Masoud Aurangzeb, Khursheed Yousefpoor, Efat Yousefpoor, Mohammad Sadegh Darwesh, Aso Lee, Sang-Woong Fazlali, Mahmood Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Medicine and Pharmacy Duy Tan University Da Nang Viet Nam Department of Computer Science and Engineering Sejong University Seoul 05006 South Korea Future Technology Research Center National Yunlin University of Science and Technology Yunlin Taiwan Department of Computer Engineering College of Computer and Information Sciences King Saud University P.O. Box 51178 Riyadh 11543 Saudi Arabia Department of Computer Engineering Dezful Branch Islamic Azad University Dezful Iran Department of Information Technology University of Human Development Sulaymaniyah Iraq Pattern Recognition and Machine Learning Lab Gachon University 1342 Seongnamdaero Sujeonggu Seongnam 13120 South Korea Cybersecurity and Computing Systems Research Group School of Physics Engineering and Computer Science University of Hertfordshire Hertfordshire AL10 9AB United Kingdom

Flying ad hoc networks (FANETs) have particular importance in various military and civilian applications due to their specific features, including frequent topological changes, the movement of drones in a three-dimensional space, and their restricted energy. These features have created challenges for designing cluster-based routing protocols. In this paper, a Q-learning-based smart clustering routing method (QSCR) is suggested in FANETs. In QSCR, each node discovers its neighbors through the periodic exchange of hello messages. The hello time interval is different in each cluster, and cluster leaders determine this interval based on the average speed similarity. Next, an adaptive clustering process is presented for categorizing drones in the clusters. In this step, the cluster leader is selected based on a new parameter called merit value, which includes residual energy, centrality, neighbor degree, speed similarity, and link validity time. Then, a centralized Q-learning model is presented to tune weight coefficients related to merit parameters dynamically. In the last step, the routing process is done using a greedy forwarding technique. Finally, QSCR is run on NS2, and the simulation results of QSCR are compared with those of ICRA, WCA, and DCA. These results show that QSCR carries out the clustering process rapidly but has less cluster stability than ICRA. QSCR gets energy efficiency and improves network lifetime. In the routing process, QSCR has a high packet delivery rate compared to other schemes. Also, the number of isolated clusters created in QSCR is less than other clustering methods. However, the proposed scheme has a higher end-to-end delay than ICRA. Also, this scheme experiences more communication overhead than ICRA slightly. © 2024 The Author(s)

关键词： Clustering Flying ad hoc networks (FANETs) Machine learning (ML) Reinforcement learning (RL) Unmanned aerial vehicles (UAVs)