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Out of the Norm-Groundbreaking and Unparalleled

TELEMEDICINE AND E-HEALTH 2025年第1期31卷 1-2页

作者： Doarn, Charles R. Editor-in-Chief

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Derivation of computational formulas for certain class of finite sums: Approach to generating functions arising from p$$ p $$-adic integrals and special functions

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MATHEMATICAL METHODS IN THE APPLIED SCIENCES 2022年第16期45卷 9520-9544页

作者： Simsek, Yilmaz Univ Akdeniz Dept Math Fac Sci TR-07058 Antalya Turkey

The aim of this paper is to construct generating functions for certain families of special finite sums by using the Newton-Mercator series, hypergeometric functions, and p$$ p $$-adic integral. By using these generating functions with their functional and partial derivative equations, many novel computational formulas involving the special finite sums of (inverse) binomial coefficients, the Bernoulli type polynomials and numbers, Euler polynomials and numbers, the Stirling numbers, the (alternating) harmonic numbers, the Leibnitz polynomials, and others are derived. We also develop a computation algorithm for these finite sums and provide some of their special values. By using these finite sums and combinatorial numbers, we find some formulas involving multiple alternating zeta functions, the Bernoulli polynomials of higher order and the Euler polynomials of higher order. We then obtain a decomposition from these formulas, which are related to the multiple Hurwitz zeta functions.

关键词： computational algorithm finite sums generating function multiple alternating zeta functions p-adic integral special functions and special numbers

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Automated detection of spreading depolarizations in electrocorticography

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SCIENTIFIC REPORTS 2025年第1期15卷 1-15页

作者： Puchala, Sreekar Muchnik, Ethan Ralescu, Anca Hartings, Jed A. Univ Cincinnati Dept Comp Sci Cincinnati OH 45267 USA Univ Oregon Dept Electrochem Eugene OR USA Univ Cincinnati Coll Med Dept Neurosurg 231 Albert Sabin Way Cincinnati OH 45267 USA

Spreading depolarizations (SD) in the cerebral cortex are a novel mechanism of lesion development and worse outcomes after acute brain injury, but accurate diagnosis by neurophysiology is a barrier to more widespread application in neurocritical care. Here we developed an automated method for SD detection by training machine-learning models on electrocorticography data from a 14-patient cohort that included 1,548 examples of SD direct-current waveforms as identified in expert manual scoring. As determined by leave-one-patient-out cross-validation, optimal performance was achieved with a gradient-boosting model using 30 features computed from 400-s electrocorticography segments sampled at 0.1 Hz. This model was applied to continuous electrocorticography data by generating a time series of SD probability [PSD(t)], and threshold PSD(t) values to trigger SD predictions were determined empirically. The developed algorithm was then tested on a novel dataset of 10 patients, resulting in 1,252 true positive detections (/1,953;64% sensitivity) and 323 false positives (6.5/day). Secondary manual review of false positives showed that a majority (224, or 69%) were likely real SDs, highlighting the conservative nature of expert scoring and the utility of automation. SD detection using sparse sampling (0.1 Hz) is optimal for streaming and use in cloud computing applications for neurocritical care.

关键词： Spreading depolarization Spreading depression Electroencephalography Machine learning Automated detection computational algorithm Neurocritical care

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Novel design and optimization of S band patch antenna for space application by using a gravitational search algorithm

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INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM 2023年第3期17卷 1131-1148页

作者： Zafrane, Mohammed Amine Mebrek, Mohammed Ali Souillah, Hadjer Madouri, Zineb Bouchra Abes, Bachir Univ Sci & Technol Oran Mohamed Boudiaf Dept Elect Lab Signaux Syst Donnees LSSD USTO Mb BP 1505 Oran 31000 Algeria Algerian Space Agcy Ctr Satellite Dev Oran Algeria Univ Sci & Technol Oran Mohamed Boudiaf Dept Elect USTO Mb BP 1505 Oran 31000 Algeria Univ Sci & Technol Oran Mohamed Boudiaf Dept Mecan USTO Mb BP 1505 Oran 31000 Algeria

The design of the patch antenna oriented for space application is a balanced solution between multiple disciplines. New disciplines are considered in these studies such as vibration and cost. To address the challenges, a novel framework called Multidisciplinary Design Optimization is developed including problem definition, multidisciplinary modeling and a heuristic optimizer. The Gravitational Search algorithm is used to enhance the performance parameters of the proposed configuration. The performance parameters are computed at the resonating frequencies of the proposed antenna. Two polarized configurations in S-band are proposed: rectangular and circular. A proof-of-concept design example is the 2.4 GHz patch antenna using Rogers substrate material which has demonstrated the effectiveness of the proposed framework. The proposed antenna could be a successful choice for micro satellite applications.

关键词： S-band Microsatellite Patches antenna computational algorithm Response surface method Monte Carlo

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Explaining Supervisor Set for Machine Learning Methods

Explaining Supervisor Set for Machine Learning Methods

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International Joint Conference on Neural Networks (IJCNN)

作者： Nowakowski, Andrzej Fulmanski, Piotr Lipnicka, Marta Univ Lodz Fac Math & Comp Sci Lodz Poland

ISBN: (纸本)9798350359329;9798350359312

The problem of explaining learning considered in this paper is based on Vapnik's learning machine model and is that of choosing from the given set of functions the one that best approximates the supervisor's response. We define that family in the rigorous way using a set of partial differential equations. Such a formulation of the family of functions together with a risk functional allows to apply tools from optimal control theory. We build a new dynamic programming method to derive verification theorem for approximate solution to that new control problem. That approach to machine learning enables a construction of a numerical algorithm to compute a function which approximates supervisor set.

关键词： supervisor set machine learning optimal control suficient optimality conditions computational algorithm

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Statistical Filtering of Images in the Spectral Domain 13th

Statistical Filtering of Images in the Spectral Domain

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13th Computer Science Online Conference

作者： Vasilevskiy, Valery V. Natl Res Univ Moscow Aviat Inst 4 Volokolamskoe Highway Moscow 125993 Russia

ISBN: (纸本)9783031705175;9783031705182

The problem of increasing the efficiency of search and identification of anomalies in multispectral images obtained in observation systems is investigated. The approach based on the use of the spectral form of the mathematical description of the observation system model and statistical filtering of video information performed in the spatial-frequency domain is considered. The method is based on finding the spectral characteristic of the image and filtering operators, transition to solving the system of linear algebraic equations of generalized characteristic functions and estimation of the posterior distribution density of the image state vector. To perform optimal statistical filtering and image anomaly detection, an algorithm of recurrent processing of video information by a multichannel frequency filter is implemented, providing maximum suppression of noise additively distorting the useful image signal #CSOC1120.

关键词： Observation System Image Model Statistical Filtering Distribution Density Function Spectral Response Filter Transition Function computational algorithm

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Solving heterogeneous-belief asset pricing models with short-selling constraints and many agents

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MACROECONOMIC DYNAMICS 2024年第8期28卷 1715-1738页

作者： Hatcher, Michael Univ Southampton Dept Econ Southampton England

Short-selling constraints are common in financial markets, while physical assets such as housing often lack markets for short-selling altogether. As a result, investment decisions are often restricted by such constraints. This paper studies asset prices in behavioral heterogeneous-belief models with short-selling constraints and arbitrarily many belief types. We provide conditions on beliefs such that short-selling constraints bind for different types, along with analytic expressions for price and demands that allow us to construct fast solution algorithms relevant for a wide range of models. An application studies how an alternative uptick rule, as in the United States, affects price dynamics and wealth distribution in a market with many belief types in evolutionary competition. In a numerical example, we highlight a scenario in which a modified version of the alternative uptick rule, triggered by smaller percentage falls in price, reduces both asset mispricing and wealth inequality relative to the current regulation. As extensions, we show how our method applies to multiple asset markets with short-selling constraints, additional heterogeneities, and price setting by a market maker.

关键词： Asset pricing heterogeneous beliefs short-selling constraints computational algorithm evolutionary competition

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Estimation of Graphical Models: An Overview of Selected Topics

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International Statistical Review 2024年第2期92卷 194-245页

作者： Chen, Li-Pang Department of Statistics National Chengchi University Taipei Taiwan

Graphical modelling is an important branch of statistics that has been successfully applied in biology, social science, causal inference and so on. Graphical models illuminate connections between many variables and can even describe complex data structures or noisy data. Graphical models have been combined with supervised learning techniques such as regression modelling and classification analysis with multi-class responses. This paper first reviews some fundamental graphical modelling concepts, focusing on estimation methods and computational algorithms. Several advanced topics are then considered, delving into complex graphical structures and noisy data. Applications in regression and classification are considered throughout. © 2023 International Statistical Institute.

关键词： complex and noisy data computational algorithm conditional inference graphical LASSO graphical models multivariate linear models network structure optimisation pairwise dependence supervised learning

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Proposed mapping and evaluation model of sustainable development goals in graduate programs in environmental sciences in Brazil

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INTERNATIONAL JOURNAL OF SUSTAINABILITY IN HIGHER EDUCATION 2023年第7期24卷 1452-1473页

作者： Gomes Junior, Jose Carmino Corbari, Sandra Dalila Kniess, Claudia Terezinha Nogueira da Silva, Gersica Moraes Piontkewicz, Simone Caroline Melo, Maiara de Souza Carbone, Amanda Silveira Mantovaneli Jr, Oklinger Martins Sobral, Maria do Carmo Philippi Junior, Arlindo Fernandez, Felipe de Aguiar Dutra, Ana Regina Birch, Robert Samuel Osorio de Andrade Guerra, Jose Baltazar Salgueirinho Cioce Sampaio, Carlos Alberto Sao Judas Tadeu Univ USJT Dept Informat Sao Paulo Brazil State Univ Ponta Grossa UEPG Sao Paulo Brazil Fed Univ Sao Paulo USP Sao Paulo Brazil Sao Judas Tadeu Univ USJT Grad Program Civil Engn Sao Paulo Brazil Anima Inst IA Sao Paulo Brazil Fed Univ Pernambuco UFPE Environm Management Grp Recife Brazil Univ Sao Paulo Adv Studies Inst Sao Paulo Brazil Reg Univ Blumenau FURB Blumenau SC Brazil Fed Inst Paraiba IFPB Joao Pessoa Paraiba Brazil Univ Sao Paulo Sao Paulo Brazil Fed Univ Pernambuco UFPE Recife Pe Brazil Univ Southern Santa Catarina Ctr Sustainable Dev Grad Program Adm PPGARes Grp Energy Efficiency & SustainabilGREEN Tubarao SC Brazil Reg Univ Blumenau FURB Grad Program Reg Dev Blumenau SC Brazil Univ Southern Sante Catarina UNISUL Grad Program Environm Sci Tubarao SC Brazil ISAE Higher Inst Econ & Adm Grad Program Governance & Sustainabil Curitiba Brazil

PurposeThis paper aim to propose a methodological mapping approach for the evaluation of dissertations and theses of graduate programs in the area of environmental sciences in Brazil in relation to the UN sustainable development goals (SDGs). Design/methodology/approachThe research is characterized as exploratory with qualitative/quantitative approach. The proposed model was developed as a computational algorithm with a pilot being adopted as a professional master in national network for teaching in environmental sciences (ProfCiAmb) comprising associated courses from nine Brazilian public universities. 230 dissertations completed between 2018 and 2020 were analyzed. FindingsA total of 266 correlations were identified between the texts and descriptors of each SDG. Correlation values between 0.100 (minimum value - Vmin) and 0.464 (maximum value - Vmax) were observed. SDG 4 - Quality Education (Vmax = 0.399) and SDG 6 - Drinking Water and Sanitation (Vmax = 0.464) were those with the highest correlation values, followed by SDG 3 - Health and Well-Being (Vmax = 0.299) and SDG 17 - Partnerships and Means of Implementation (Vmax = 0.249). Practical implicationsThe construction of the computational algorithm provided consistent quantitative analyses with potential to contribute to the improvement of the multidimensional evaluation of graduate studies, as well as to support public policies related to teaching and research and strategic planning of the programs. Originality/valueThe relevance of this study lies in the creation of a model that involves the creation of metrics and tools regarding the impact of graduate studies on society.

关键词： Mapping Evaluation Model computational algorithm Graduate Impact on society Environmental sciences

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A tri-level approach for computing Stackelberg Markov game equilibrium: computational analysis

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JOURNAL OF computational SCIENCE 2023年 68卷

作者： Clempner, Julio B. Inst Politecn Nacl Escuela Super Fiis & Matemat Bldg 9Ave Inst Politecn Nacl Mexico City 07738 DF Mexico Natl Polytech Inst Sch Phys & Math Mexico City DF Mexico

Tri-level game-theory problems have been drawing serious interest because of their applicability to a broad range of real applications. It is considered a hierarchical game (min-min-min) in which multiple leaders and followers compete restricted to finite, controllable and ergodic Markov games. We determine the relationship involving the Nash and Stackelberg equilibrium notions and typify the circumstances under which the proximal/gradient method converges to a Stackelberg equilibrium: the hierarchical structure considers that leaders and followers are in a Nash framework with a Stackelberg constraint model. Despite recent considerable progress, the literature to date has focused mostly on solutions based on linear programming. This paper introduces a new proximal/gradient method for computing the equilibrium point for a tri-level Stackelberg game played between multiple leaders and followers. This procedure guaranteed the convergence to a Stackelberg equilibrium. We also provide the analysis of the convergence and the rate of convergence to Stackelberg equilibrium point. Finally, we prove the effectiveness and utility of the proposed method using a numerical example.

关键词： computational algorithm Tri-level game Non-linear programming Stackelberg game Equilibrium Game theory Proximal gradient method

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