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arXiv 2023年

作者： Ballantine, Cristina Merca, Mircea Department of Mathematics and Computer Science College of the Holy Cross WorcesterMA01610 United States Department of Mathematical Methods and Models Fundamental Sciences Applied in Engineering Research Center University Politehnica of Bucharest BucharestRO-060042 Romania

We consider the number of the 6-regular partitions of n, b6(n), and give infinite families of congruences modulo 3 (in arithmetic progression) for b6(n). We also consider the number of the partitions of n into distinct parts not congruent to ±2 modulo 6, Q2(n), and investigate connections between b6(n) and Q2(n) providing new combinatorial interpretations for these partition functions. In this context, we discover new infinite families of linear inequalities involving Euler's partition function p(n). Infinite families of linear inequalities involving the 6-regular partition function b6(n) and the distinct partition function Q2(n) are proposed as open *** Codes 11P81, 11P82, 05A19, 05A20 © 2023, CC BY.

关键词： Combinatorial mathematics

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Prototype for the Model-Based Assets and Liabilities Management Support System

Prototype for the Model-Based Assets and Liabilities Managem...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Aleksandra Zhukova Anna Flerova Maxim Tarasenko Alexey Chernov Ruslan Gabbasov Department of Mathematical Modelling of Economic Systems Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russia Department of Mathematical Modelling of Economic Systems FRC CSC RAS Moscow Russia Laboratory of Numerical Methods of Applied Structural Optimization MIPT Moscow Russia

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

This paper presents the prototype of the instrument that supports the control of assets and liabilities by a bank using the mathematical computations. The specifics of the approach lies in the application of the recent advances in the control theory to provide the strategic analysis for various planning horizons and scenarios of external and internal factors.

关键词： Instruments Computational modeling Prototypes Mathematical models Planning Control theory Information technology

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The Reliability of Information Sources: Student Perceptions and Educational Opportunities

The Reliability of Information Sources: Student Perceptions ...

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International IEEE Conference and Workshop: Óbuda on Electrical and Power Engineering (CANDO-EPE)

作者： Anita Mihalovicsne Kollar Jozsef Katona 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 Business University Budapest Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

The modern digital age demands the skills to be able to assess information. In the current world, access to information and knowledge is abundant from different sources. Indeed, high-quality data are much needed in education and professional development, as the quality and accuracy of information directly influence the process of learning and decision-making. The study aims to investigate the perceptions of computer science students at the University of Dunaújváros related to the credibility of diverse information sources. Within a questionnaire, on a voluntary answer basis, 68 students took part, 59 males and nine females. This work is aimed at assessing the degree to which the surveyed students evaluate information sources based on a five-point Likert scale. The data shows that students find print books and textbooks as the most reliable sources; social media are the least reliable. The study also supports the importance of source credibility evaluation, for which lateral reading techniques and AI-based news source credibility identification systems can be helpful. These findings suggest the necessity of bettering the educational approaches to foster better source criticism skills in the students, especially for online content and social media. The study generally contributes to understanding the information society and helps prepare students to obtain and use reliable and accurate information in their future careers. Using AI-based tools and systems can then further support these educational efforts with robust mechanisms to evaluate information credibility in an ever more complex digital landscape.

关键词： Economics Power engineering Accuracy Social networking (online) Engineering profession Education Reliability engineering Information filters Information age Reliability

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Maintenance Devices Prioritization Decisions in Health Care Systems within Multigranular Linguistic 2-Tuple-ARAS Model

Maintenance Devices Prioritization Decisions in Health Care ...

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Technology Innovations for Healthcare (ICTIH), International Conference on

作者： Wiem Daoud BenAmor Hela Moalla Frikha Luis Martínez López Quantitative Methods Economic and Computer Sciences department OLID Laboratory Higher Institute of Industrial Management university of Sfax Sfax Tunisia Computer Science Department SINBAD2 Laboratory University of Jaén Jaén Spain

The Medical equipment plays a crucial role in modern healthcare. These critical medical devices must perform at the level of performance required to achieve accepted reliability standards in the healthcare sector. To assure the safety and reliability of critical medical equipment, clinical engineering departments in Tunisian hospitals have to build and continuously control a medical equipment management program. Thus, the Multi-Criterion Decision Making methods find naturally their place to solve such a problem. In this paper, we address to categorize medical equipments for maintenance strategies based on how crucial they are to improve significantly their reliability safety, and cost efficiency by applying a novel multi-granular linguistic 2-Tuple-ARAS method in the multi-expert environment.

关键词： Performance evaluation Technological innovation Medical devices Hospitals Linguistics Maintenance engineering Reliability engineering

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THE BLESSING OF RANDOMNESS: SDE BEATS ODE IN GENERAL DIFFUSION-BASED IMAGE EDITING

arXiv

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arXiv 2023年

作者： Nie, Shen Guo, Hanzhong Allan Lu, Cheng Zhou, Yuhao Zheng, Chenyu Li, Chongxuan Gaoling School of Artificial Intelligence Renmin University of China Beijing China Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China Department of Computer Science and Technology Tsinghua University Beijing China

We present a unified probabilistic formulation for diffusion-based image editing, where a latent variable is edited in a task-specific manner and generally deviates from the corresponding marginal distribution induced by the original stochastic or ordinary differential equation (SDE or ODE). Instead, it defines a corresponding SDE or ODE for editing. In the formulation, we prove that the Kullback-Leibler divergence between the marginal distributions of the two SDEs gradually decreases while that for the ODEs remains as the time approaches zero, which shows the promise of SDE in image editing. Inspired by it, we provide the SDE counterparts for widely used ODE baselines in various tasks including inpainting and image-to-image translation, where SDE shows a consistent and substantial improvement. Moreover, we propose SDE-Drag - a simple yet effective method built upon the SDE formulation for point-based content dragging. We build a challenging benchmark (termed DragBench) with open-set natural, art, and AI-generated images for evaluation. A user study on DragBench indicates that SDE-Drag significantly outperforms our ODE baseline, existing diffusion-based methods, and the renowned DragGAN. Our results demonstrate the superiority and versatility of SDE in image editing and push the boundary of diffusion-based editing methods. See the project page https://***/SDE-Drag-demo/for the code and DragBench dataset. Copyright © 2023, The Authors. All rights reserved.

关键词： Diffusion

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Covid severity prediction: Who cares about the data quality?

Covid severity prediction: Who cares about the data quality?

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Frontiers of Information Technology (FIT)

作者： Teodora Nae Johannes Krabbe Faiza Allah Bukhsh Jeewanie Jayasinghe Arachchige Faizan Ahmed Mathematics and Computer Science Faculty of Electrical Engineering University of Twente Enschede The Netherlands Medische Spectrum Twente Enschede The Netherlands Department of Computer Science University of Ruhuna Matara Sri Lanka Formal Methods and Tools Group University of Twente Enschede The Netherlands

ISBN: (纸本)9798350345940

COVID-19 is an ongoing pandemic disrupting daily life and overwhelming the healthcare infrastructure. Since the outburst of the pandemic, researchers have used various techniques to predict many aspects of the disease, including mortality rate and severity. The reproducibility of this research is challenging due to varying methodologies used to collect data, data quality, vague description of methodological approach to training prediction models, over-relying on data imputation, and over-fitting. This paper focuses on these challenges and provides a short yet comprehensive review of research on COVID mortality and severity prediction. The emphasis is on the reproducibility of the results and data quality issues. To further elaborate on the issue, we report the development of severity prediction models using two data sets. CRISP-DM is used as a methodological approach. We analyze and criticize the quality of the used data sets and how they affect the performance and limitations of the trained models. We conclude this paper with comments on data quality issues, the importance of reproducibility, and suggestions to improve reproducibility.

关键词： COVID-19 Training Support vector machines Pandemics Data integrity Biological system modeling Medical services

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Transformative Applications and Key Challenges of Generative AI

Transformative Applications and Key Challenges of Generative...

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International IEEE Conference and Workshop: Óbuda on Electrical and Power Engineering (CANDO-EPE)

作者： Attila Kovari Jozsef Katona Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary Institute of Digital Technology Faculty of Computer Science Eszterházy Károly Catholic University Eger Hungary Department of Institute of Engineering University of Dunaújváros Dunaujvaros Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemét Hungary Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Applied Quantitative Methods Faculty of Finance and Accountancy Budapest Business University Budapest Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

The paper discusses the integration and use of generative artificial intelligence technologies in education. Generative AI, such as OpenAI, in particular the GPT model, has fundamentally changed the way humans interact with machines. Advanced technologies in the field of generative AI in education are mostly used to personalize learning experiences by dynamically customizing learning materials according to the needs of learners, thus enabling the improvement of outcomes. This article explores the use of generative AI tools with the aim of assessing how useful students perceive these tools to be. The findings show mixed receptivity from users, highlighting the critical balance in using innovative AI capabilities through AI.

关键词： Power engineering Accuracy Generative AI Education Chatbots Market research Problem-solving Reliability

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Optimizing resource allocation in flex-grid entanglement distribution networks

Optimizing resource allocation in flex-grid entanglement dis...

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2022 IEEE Photonics Conference, IPC 2022

作者： Alnas, Jude Alshowkan, Muneer Nageswara Rao, S.V. Peters, Nicholas A. Lukens, Joseph M. University of Alabama Department of Electrical and Computer Engineering TuscaloosaAL35401 United States Quantum Information Science Section Oak Ridge National Laboratory Oak RidgeTN37831 United States Advanced Computing Methods Section Oak Ridge National Laboratory Oak RidgeTN37831 United States

We introduce a model for the distribution of frequency-polarization hyper-entangled photon pairs in a flexible-grid optical network. In order to optimize entanglement fidelity and entangled bit rate, we apply a geneti... 详细信息

ISBN: (数字)9781665434874

ISBN: (纸本)9781665434874

关键词： Genetic algorithms

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Student Perceptions of AI-Enhanced Adaptive Learning Systems: A Pilot Survey

Student Perceptions of AI-Enhanced Adaptive Learning Systems...

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International IEEE Conference and Workshop: Óbuda on Electrical and Power Engineering (CANDO-EPE)

作者： Klara Ida Katonane Gyonyoru Jozsef Katona Department of Organizational Development and Communication Science Institute of Social Sciences University of Dunaujvaros Dunaujvaros Hungary Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros 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 Business University Budapest Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

Artificial Intelligence (AI) significantly enhances adaptive learning by personalizing and tailoring instruction to individual student needs. AI analyzes data in real-time to create personalized learning paths based on students' strengths, weaknesses, and preferences, which keeps students engaged and motivated. A major benefit of AI in adaptive learning is the provision of real-time feedback and assessment, allowing students to correct mistakes promptly and understand concepts more thoroughly. AI-based intelligent tutoring systems are primarily intended to simulate personalized tutoring processes that guide students in complex problem-solving and answering questions. It is convenient in teaching mathematics, sciences, and languages. AI also supports inclusive education, dealing with diversified learning requirements and styles, such as those of learners with disabilities. For the teacher, AI acts as a reflector of student performance so that one can intervene early and make adjustments in the method of instruction by creating effective learning environments. AI technology is a field in constant development and harbors the potential to change the face of adaptive learning, bringing an upswing in educational outcomes. This article will summarize the advantages and features that merit improvement of the AI-embedded adaptive learning systems with student feedback.

关键词： Surveys Adaptive learning Power engineering Data security Real-time systems Mathematics Problem-solving Artificial intelligence Faces

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A C0FINITE ELEMENT ALGORITHM FOR THE SIXTH ORDER PROBLEM WITH SIMPLY SUPPORTED BOUNDARY CONDITIONS

arXiv

引用

arXiv 2023年

作者： Li, Hengguang Yin, Peimeng Wayne State University Department of Mathematics DetroitMI48202 United States Multiscale Methods and Dynamics Group Computer Science and Mathematics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States

In this paper, we study the sixth order equation with the simply supported boundary conditions in a polygonal domain. We propose a new mixed formulation that decomposes the sixth order problem into a system of Poisson equations. Depending on the interior angles of the domain, additional Poisson problems may be needed to confine the solution to the correct Sobolev space. In addition, we propose a C0finite element algorithm for the sixth order problem and provide the optimal error analysis. Numerical results are reported to verify the theoretical findings. © 2023, CC BY-NC-ND.

关键词： Boundary conditions

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