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41st International Conference on Machine Learning, ICML 2024

作者： Lin, Peijia Chen, Pin Jiao, Rui Mo, Qing Cen, Jianhuan Huang, Wenbing Liu, Yang Huang, Dan Lu, Yutong School of Computer Science and Engineering Sun Yat-sen University Guangzhou China National Supercomputer Center Guangzhou China Dept. of Comp. Sci. Tech. Institute for AI Tsinghua University Beijing China Institute for AIR Tsinghua University Beijing China Gaoling School of Artificial Intelligence Renmin University of China Beijing China Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China

In addressing the challenge of Crystal Structure Prediction (CSP), symmetry-aware deep learning models, particularly diffusion models, have been extensively studied, which treat CSP as a conditional generation task. However, ensuring permutation, rotation, and periodic translation equivariance during diffusion process remains incompletely addressed. In this work, we propose EquiCSP, a novel equivariant diffusion-based generative model. We not only address the overlooked issue of lattice permutation equivariance in existing models, but also develop a unique noising algorithm that rigorously maintains periodic translation equivariance throughout both training and inference processes. Our experiments indicate that EquiCSP significantly surpasses existing models in terms of generating accurate structures and demonstrates faster convergence during the training process. Code is available at https://***/EmperorJia/EquiCSP. Copyright 2024 by the author(s)

关键词： Crystal symmetry

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Algorithm for Solving Inverse Problems of Geoelectrical Prospecting for Vertical Electrical Sounding by the Indirect Near-Boundary Element Method

Algorithm for Solving Inverse Problems of Geoelectrical Pros...

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International computer sciences and Information Technologies (CSIT)

作者： Liubov Zhuravchak Nataliya Zabrodska Software Department of Institute of Computer Science and Information Technologies Lviv Polytechnic National University Lviv Ukraine Department of Geoelectromagnetic Methods of Carpathian Branch of S.I. Subbotin Institute of Geophysics National Academy of Sciences Lviv Ukraine

ISBN: (数字)9798331542634

ISBN: (纸本)9798331542641

using the indirect near-boundary element method, an algorithm for recognizing the physical and geometric parameters of the inclusion in a piecewise homogeneous half-plane, whose components are in ideal contact, based on the potential field data measured at its boundary, is constructed. The direct and inverse two-dimensional problems of the potential theory in relation to electrical prospecting, in particular, the method of vertical electrical soundings, have been solved. A computational experiment was conducted in which initial approximations for the electrical conductivity of the inclusion, its center of mass, orientation, and dimensions were determined by the nature of the change in apparent resistivity. The inverse problem is solved using excess boundary conditions by a number of iterations while minimizing the functional.

关键词： Electric potential Inverse problems Shape Groundwater Contacts Conductivity Soil Rocks Water pollution Electromagnetics

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The Cognitive Model “Self-regulation of Educational Activities”

The Cognitive Model “Self-regulation of Educational Activit...

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Aleksey E. Lozhnikov Cholpon K. Ryspayeva Oleg N. Luchko Nazgul Kyzy Nyshanbai Valentina A. Marenko faculty of IT and Computer Systems Omsk State Technical University Omsk Russia Institute of Intercultural Communication and Psychology International University of IT Bishkek Kyrgyz Republic dept. of Computer Science Mathematics and Natural Sciences Omsk Humanitarian Academy Omsk Russia lab. of Methods for Converting and Presenting Information Sobolev Institute of Mathematics Omsk Russia

ISBN: (数字)9798350389234

ISBN: (纸本)9798350353051

Various needs for specific professional knowledge manifest different levels of perseverance in students to complete the educational process from the start to its logical end. This process is a key feature of any learning format. These arguments determine the relevance to investigate the process of self-regulation in educational activity. The purpose of the work is to build the models that characterize self-regulation of the student’s cognitive activity and involvement in knowledge acquisition. To achieve the purpose, the following tasks are to be solved. 1. Review of scientific publications. 2. Building graphical and cognitive models of the problem under study. 3. Analysis of models using statistical and IT approach. 4. Formulation of conclusions. Statistical analysis shows that the level of self-regulation of behavior among the students in the city of Bishkek is higher than among the students in the city of Omsk. As for the level of self-regulation of educational activities, it is higher among the students in Omsk than among the students in Bishkek. As a result, it is found that the factors “motivation” of the student learning activity and the factor “flexibility” in actions are decisive for the investigation of the phenomenon. The results of q-connectivity show that the vertices of the graph of a cognitive model with highdimensional simplexes are these factors. The obtained results are recommended to specialists in the field of pedagogical science to manage the educational system as a whole.

关键词： Analytical models Statistical analysis Reviews Knowledge acquisition Urban areas Buildings Cognitive science

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Integrating AI-based adaptive learning into the flipped classroom model to enhance engagement and learning outcomes

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computers and Education: Artificial Intelligence 2025年 8卷

作者： Katona, Jozsef Gyonyoru, Klara Ida Katonane Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemet Hungary Department of Applied Quantitative Methods Faculty of Finance and Accountancy Budapest University of Economics and Business Budapest Hungary Department of Organizational Development and Communication Science Institute of Social Sciences University of Dunaujvaros Dunaujvaros Hungary

This study explores the integration of the AI-powered adaptive learning system within the flipped classroom model and discusses programming education. The increasing demand for the acquisition of programming skills in the digital era generates the development of innovative pedagogical approaches to help students overcome the difficulties in mastering programming concepts. The study investigates how AI-based adaptive feedback influences student engagement, motivation, and learning outcomes. This study was conducted for 13 weeks, with two groups of undergraduate students. In one of the groups, tshe traditional flipped classroom model was applied, while in the other group, AI-driven adaptive learning tools were introduced. In this research methodology, a mixed-methods approach was adopted, integrating quantitative analyses with qualitative data. These showed that the experimental group demonstrated significant improvements in learning results and motivation, thereby realiszing the value of real-time, personalized feedback provided through the AI system. The qualitative findings revealed that with the AI system, there was an increase in student autonomy;thus, there is increased responsibility among students to collaborate in in-class participation, which helps enhance a more dynamic and cooperative learning environment. On the whole, these findings reveal important implications of the integration of AI into flipped classrooms, while at the same time, they reveal how to make the modernization of programming education achieve a better overall experience in student learning. © 2025 The Authors

关键词： Contrastive Learning

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Intelligent Collision Danger Assessment of Autonomous Unmanned Sea-Going Vessels

Intelligent Collision Danger Assessment of Autonomous Unmann...

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2022 International Conference "Quality Management, Transport and Information Security, Information Technologies", IT and QM and IS 2022

作者： Sedova, Nelly A. Sedov, Viktor A. Bazhenov, Ruslan I. Alutina, Elena F. Arkhipova, Zoya V. Mendel, Viktor V. Maritime State University Named after G.I. Nevelskoy Automatic and Information Systems Vladivostok Russia Maritime State University Named after G.I. Nevelskoy Electrician Theoretical Bases Vladivostok Russia Sholom-Aleichem Priamursky State University Information Systems and Mathematics Birobidzhan Russia Blagoveschensk State Pedagogical University Computer Science and Methods of Teaching Computer Science Blagoveschensk Russia Baikal State University Mathematical Methods and Digital Technologies Irkutsk Russia Pacific National University Pedagogical Institute Khabarovsk Russia

ISBN: (数字)9781665488709

ISBN: (纸本)9781665488709

Navigation safety of both sea-going crewed ships and sea-going autonomous unmanned ships is possible to improve by enhancing navigation engineering facilities, including software and soft hardware (firmware), providing control over navigation tools on such ships. The article dwells on the technique of an intelligent assessment of collision danger for autonomous unmanned vessels with the surface crafts facing them along their seaway. The intelligent assessment is carried out by synthesizing three values given by three modules which are different in input data. The first module uses the information on bearing and distance, the second one is based on computing distance and time of approach of ships, and the third renders the information on bearing, speed and a target ship heading got from the radar system. Each module actively processes the information got from sensors for transferring it to the intelligent unit, which decides on the necessity of maneuvering of collision avoidance to the dangerous objects found on a seaway of an autonomous unmanned vessel. Each module uses a model explored in fuzzy and neuro-fuzzy bases. Upon that, quality assessment calculations show it is the neuro-fuzzy approach that allows for a uniquely determined danger level. © 2022 IEEE.

关键词： Fuzzy inference

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ESTIMATING THE FALSE DISCOVERY RISK OF (RANDOMIZED) CLINICAL TRIALS IN MEDICAL JOURNALS BASED ON PUBLISHED p-VALUES

arXiv

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arXiv 2023年

作者： Schimmack, Ulrich Bartoš, František Department of Psychology University of Toronto Mississauga Mississauga Canada Department of Psychological Methods University of Amsterdam Amsterdam Netherlands Institute of Computer Science Czech Academy of Sciences Prague Czech Republic

The influential claim that most published results are false raised concerns about the trustworthiness and integrity of science. Since then, there have been numerous attempts to examine the rate of false-positive results that have failed to settle this question empirically. Here we propose a new way to estimate the false positive risk and apply the method to the results of (randomized) clinical trials in top medical journals. Contrary to claims that most published results are false, we find that the traditional significance criterion of α = .05 produces a false positive risk of 13%. Adjusting α to .01 lowers the false positive risk to less than 5%. However, our method does provide clear evidence of publication bias that leads to inflated effect size estimates. These results provide a solid empirical foundation for evaluations of the trustworthiness of medical research. © 2023, CC BY.

关键词： Risk perception

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An Automatic CNN-based Face Mask Detection Algorithm Tested During the COVID-19 Pandemics

An Automatic CNN-based Face Mask Detection Algorithm Tested ...

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2022 International Conference of Yearly Reports on Informatics, Mathematics, and Engineering, ICYRIME 2022

作者： De Magistris, Giorgio Iacobelli, Emanuele Brociek, Rafal Napoli, Christian Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Roma00185 Italy Department of Mathematics Applications and Methods for Artificial Intelligence Faculty of Applied Mathematics Silesian University of Technology Gliwice44-100 Poland Institute for Systems Analysis and Computer Science Italian National Research Council Via dei Taurini 19 Roma00185 Italy

The ongoing COVID-19 pandemic has highlighted the importance of wearing face masks as a preventive measure to reduce the spread of the virus. In medical settings, such as hospitals and clinics, healthcare professionals and patients are required to wear surgical masks for infection control. However, the use of masks can hinder facial recognition technology, which is commonly used for identity verification and security purposes. In this paper, we propose a convolutional neural network (CNN) based approach to detect faces covered by surgical masks in medical settings. We evaluated the proposed CNN model on a test set comprising of masked and unmasked faces. The results showed that our model achieved an accuracy of over 96% in detecting masked faces. Furthermore, our model demonstrated robustness to different mask types and fit variations commonly encountered in medical settings. Our approaches reaches state of the art results in terms of accuracy and generalization. © 2022 Copyright for this paper by its authors.

关键词： COVID-19

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A memetic dynamic coral reef optimisation algorithm for simultaneous training, design, and optimisation of artificial neural networks (vol 14, 6961, 2024)

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SCIENTIFIC REPORTS 2024年第1期14卷 1-22页

作者： Berchez-Moreno, Francisco Duran-Rosal, Antonio M. Martinez, Cesar Hervas Gutierrez, Pedro A. Fernandez, Juan C. Department of Computer Science and Numerical Analysis University of Córdoba Córdoba Spain Maimonides Biomedical Research Institute of Córdoba IMIBIC University of Córdoba 14071 Córdoba Spain Department of Quantitative Methods Universidad Loyola Andalucía Córdoba Spain

Artificial Neural Networks (ANNs) have been used in a multitude of real-world applications given their predictive capabilities, and algorithms based on gradient descent, such as Backpropagation (BP) and variants, are usually considered for their optimisation. However, these algorithms have been shown to get stuck at local optima, and they require a cautious design of the architecture of the model. This paper proposes a novel memetic training method for simultaneously learning the ANNs structure and weights based on the Coral Reef Optimisation algorithms (CROs), a global-search metaheuristic based on corals’ biology and coral reef formation. Three versions based on the original CRO combined with a Local Search procedure are developed: (1) the basic one, called Memetic CRO; (2) a statistically guided version called Memetic SCRO (M-SCRO) that adjusts the algorithm parameters based on the population fitness; (3) and, finally, an improved Dynamic Statistically-driven version called Memetic Dynamic SCRO (M-DSCRO). M-DSCRO is designed with the idea of improving the M-SCRO version in the evolutionary process, evaluating whether the fitness distribution of the population of ANNs is normal to automatically decide the statistic to be used for assigning the algorithm parameters. Furthermore, all algorithms are adapted to the design of ANNs by means of the most suitable operators. The performance of the different algorithms is evaluated with 40 classification datasets, showing that the proposed M-DSCRO algorithm outperforms the other two versions on most of the datasets. In the final analysis, M-DSCRO is compared against four state-of-the-art methods, demonstrating its superior efficacy in terms of overall accuracy and minority class performance.

关键词： Artificial neural networks Classification Coral reef optimisation algorithm Local search Neuroevolution Robust estimators

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AI and IoT in Smart Cities: A Methodology, Transformation, and Challenges 8th

AI and IoT in Smart Cities: A Methodology, Transformation, a...

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8th International Conference on Information System Design and Intelligent Applications, ISDIA 2024

作者： Begishev, Ildar Isavnin, Alexey Nedelkin, Alexey Lydia, E. Laxmi Kumar, K. Vijaya Doctor of Law Institute of Digital Technologies and Law Department of Criminal Law and Procedure Kazan Innovative University named after V. G. Timiryasov Kazan Russia Doctor of Physical-Mathematical Sciences Department of Business-Informatics and Mathematical Methods in Economics Kazan Federal University Naberezhnye Chelny Institute KFU Naberezhnye Chelny Russia Department of Computer Science Plekhanov Russian University of Economics Moscow Russia Vijayawada520007 India GITAM School of Technology Visakhapatnam Campus Visakhapatnam India

ISBN: (纸本)9789819748945

The Internet of Things (IoT) with smart cities and smart homes enables us to progressively sense and alter our surroundings. However, Artificial Intelligence (AI) must leverage such distinguishing abilities and detected data. We are heading in that way with sophisticated IoT technologies. As connected items become more authoritative, we are seeing a smart city movement away from cloud-based IoT systems and toward edge AI and embedded AI. Lower latency, better privacy, and the necessity to process data close to the source have all influenced this decision. According to a current report, smart cities can have 70 billion linked things by 2023. These cities will become smarter as a result of these networked things and introduce hazards and privacy concerns. As a result of the numerous smart city initiatives and plans that have been implemented in current years, we will not only see the anticipated aids but also the hazards that have been presented. The present and future movements in smart cities and IoT are discussed. This chapter provides an overview of several smart city techniques and elements that can be or are now automated with the help of the Internet of Things (IoT), and Artificial Intelligence (AI). Novel components of smart cities of smart parking and smart governance are determined through Artificial Intelligence (AI) in the Internet of Things (IoT). Finally, the IoT's flaws and solutions in the context of smart cities are determined. This work focuses on identifying the transformation and challenges faced in developing a smart city in AI. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Artificial intelligence (AI) Challenges Internet of things (IoT) Smart cities Transformation

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Scenario Approach for Parametric Markov Models

arXiv

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arXiv 2023年

作者： Liu, Ying Turrini, Andrea Hahn, Moritz Xue, Bai Zhang, Lijun State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China University of Chinese Academy of Sciences China Institute of Intelligent Software Guangzhou China Formal Methods and Tools University of Twente Enschede Netherlands

In this paper, we propose an approximating framework for analyzing parametric Markov models. Instead of computing complex rational functions encoding the reachability probability and the reward values of the parametric model, we exploit the scenario approach to synthesize a relatively simple polynomial approximation. The approximation is probably approximately correct (PAC), meaning that with high confidence, the approximating function is close to the actual function with an allowable error. With the PAC approximations, one can check properties of the parametric Markov models. We show that the scenario approach can also be used to check PRCTL properties directly – without synthesizing the polynomial at first hand. We have implemented our algorithm in a prototype tool and conducted thorough experiments. The experimental results demonstrate that our tool is able to compute polynomials for more benchmarks than state-of-the-art tools such as PRISM and Storm, confirming the efficacy of our PAC-based synthesis. © 2023, CC BY.

关键词： Polynomial approximation

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