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Structural Effects and Aggregation in a Social-Network Model of Natural Resource Consumption

IFAC-PapersOnLine 2017年第1期50卷 7675-7680页

作者： Manzoor T. Rovenskaya E. Muhammad A. Department of Electrical Engineering Lahore University of Management Sciences (LUMS) Lahore Pakistan Center for Water Informatics & Technology (WIT) Lahore University of Management Sciences (LUMS) Pakistan Advanced Systems Analysis Program International Institute for Applied Systems Analysis (IIASA) Laxenburg Austria Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Moscow Russian Federation

In this paper we consider a networked system of natural-resource consumption, where the agents are governed by a recently reported model of consumer psychology Dynamics of the consumption for each agent are influenced by the state of the resource and consumption of her neighbors. The process is parameterized by the psychological characteristics of each agent. This study extends the original model to incorporate the underlying network topology and explores the effects of aggregation via densely-connected communities present in the network. The exercise yields new interpretations of the predictions made by the original model in context of the influence network. We present aggregation mechanisms first for certain canonical structures of the consuming population and later on for a class of non-canonically structured populations. In the end we present an approximate aggregation scheme for populations where only some inaccurate information of the consumer characteristics is available. © 2017

关键词： Control in economics identification of environmental systems Modeling Multi-agent systems Natural resources management Social Networks

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Comparative studies of commercial window with standard shielding concretes on the basis of photon interaction parameters 2nd

Comparative studies of commercial window with standard shiel...

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2nd International Conference on applied Physics and Material Applications, ICAPMA 2015

作者： Sangwaranatee, N.W. Sangwaranatee, N. Kaewkhao, J. Chanthima, N. Informatics Mathematics Faculty of Science and Technology Suan Sunandha Rajabhat University Bangkok10300 Thailand Applied Physics Faculty of Science and Technology Suan Sunandha Rajabhat University Bangkok10300 Thailand Science Program Faculty of Science and Technology Nakhon Pathom Rajabhat University Nakhon Pathom73000 Thailand Nakhon Pathom Rajabhat University Nakhon Pathom73000 Thailand

ISBN: (纸本)9783038356837

Commercial window added with BaSO4 have been studies on the mass attenuation coefficient and compared it with some standard shielding concretes. This parameter has been investigated at photon energy from 1 keV to 100 GeV on the basis of calculation. The theoretical values of photon interaction were obtained by the WinXCom program. The variations of mass attenuation coefficient of commercial window and standard shielding concretes are shown graphically with photon energy. It has been observed that the commercial window added with 30% BaSO4 has higher value of mass attenuation coefficient than all of standard shielding concretes at the photon energy range above 40-400 keV. Also, discontinuous jump of mass attenuation coefficient at the lower energy has been discusses. © 2016 Trans Tech Publications, Switzerland.

关键词： Radiation shielding

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Setting the physical scale of dimensional reduction in causal dynamical triangulations

arXiv

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arXiv 2018年

作者： Cooperman, Joshua H. Dorghabekov, Manuchehr Department of Physics and Astronomy Bucknell University LewisburgPA United States Physics Program Bard College Annandale-on-Hudson NY United States Applied Mathematics and Informatics Program American University of Central Asia Bishkek Kyrgyzstan

Within the causal dynamical triangulations approach to the quantization of gravity, striking evidence has emerged for the dynamical reduction of spacetime dimension on sufficiently small scales. Specifically, the spectral dimension decreases from the topological value of 4 towards a value near 2 as the scale being probed decreases. The physical scales over which this dimensional reduction occurs have not previously been ascertained. We present and implement a method to determine these scales in units of either the Planck length or the quantum spacetime geometry’s effective de Sitter length. We find that dynamical reduction of the spectral dimension occurs over physical scales of the order of 10 Planck lengths, which, for the numerical simulation considered below, corresponds to the order of 10−1 de Sitter lengths. Copyright © 2018, The Authors. All rights reserved.

关键词： Triangulation

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Effective atomic numbers and electron densities of BaO-Na2O-B2O3-SiO2 glass system: Theoretical calculation 2nd

Effective atomic numbers and electron densities of BaO-Na2O-...

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2nd International Conference on applied Physics and Material Applications, ICAPMA 2015

作者： Sangwaranatee, N.W. Sangwaranatee, N. Sarachai, S. Tuscharoen, S. Kaewkhao, J. Informatics Mathematics Faculty of Science and Technology Suan Sunandha Rajabhat University Bangkok10300 Thailand Applied Physics Faculty of Science and Technology Suan Sunandha Rajabhat University Bangkok10300 Thailand Nakhon Pathom Rajabhat University Nakhon Pathom73000 Thailand Physics Program Faculty of Science and Technology Nakhon Pathom Rajabhat University Nakhon Pathom73000 Thailand

ISBN: (纸本)9783038356837

In this work, the mass attenuation coefficients, the effective atomic numbers and the effective electron densities of BaO-Na2O-B2O3-SiO2 glass have been studied at 662 keV using WinXCom program. The result show that the mass attenuation coefficients increased with increasing of BaO concentration, reflecting that more photon is attenuated. The effective atomic numbers and the effective electron densities are similar trend with mass attenuation coefficients, reflecting that more virtual electron when higher BaO concentration and more interaction will be occurred in glass matrices. © 2016 Trans Tech Publications, Switzerland.

关键词： Glass

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Three-Dimensional Wound Reconstruction using Point Descriptors: A Comparative Study

Three-Dimensional Wound Reconstruction using Point Descripto...

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Annual IEEE Symposium on Computer-Based Medical Systems

作者： José R. A. Souto Fellipe M. C. Barbosa Bruno M. Carvalho Graduate Program in Systems and Computing Federal University of Rio Grande do Norte Natal Brazil Department of Informatics and Applied Mathematics Federal University of Rio Grande do Norte Natal Brazil

Precise measurements of chronic wound areas are very important for measuring the efficacy of different treatments, since it provides a clear picture of the chosen treatment evolution. The most used techniques still in use for measuring the wound areas involve manual measuring, paper scales and/or acetate tracing, with each health professional possibly measuring the wounds in slightly different ways, specially when dealing with the wound's depth. Thus, it is common to observe inconsistent wound area estimations by different health workers on the same wounds. Moreover, the measuring process requires direct contact with the wound, increasing the contamination and infection risks, besides possibly causing discomfort for the patient. An alternative that has already been proved successful is the use of Structure from Motion (SfM) to recover three-dimensional representations of a wound's surface and estimate that area. In this work, we analyze the effectiveness of several widely used point descriptors (BRIEF, DRINK, FREAK, ORB, SIFT and SURF) in the SfM wound reconstruction task when applied to real images of realistic synthetic wounds made of latex placed on different areas of the body. The results showed that SIFT, SURF and DRINK produced better area estimates. Since the execution time is a factor, we selected DRINK as the standard descriptor for our system, since it is approximately 9.3 and 4.9 times faster than SIFT and SURF, respectively.

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CONTINUOUS-TIME ANALYSIS OF ADAPTIVE OPTIMIZATION AND NORMALIZATION

arXiv

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arXiv 2024年

作者： Gould, Rhys Tanaka, Hidenori Department of Applied Mathematics and Theoretical Physics University of Cambridge United Kingdom CBS-NTT Physics of Intelligence Program Harvard University Physics & Informatics Laboratories NTT Research Inc United States

Adaptive optimization algorithms, particularly Adam and its variant AdamW, are fundamental components of modern deep learning. However, their training dynamics lack comprehensive theoretical understanding, with limited insight into why common practices—such as specific hyperparameter choices and normalization layers—contribute to successful generalization. This work presents a continuous-time formulation of Adam and AdamW, facilitating a tractable analysis of training dynamics that can shed light on such practical questions. We theoretically derive a stable region for Adam’s hyperparameters (β, γ) that ensures bounded updates, empirically verifying these predictions by observing unstable exponential parameter growth outside of this stable region. Furthermore, we theoretically justify the success of normalization layers by uncovering an implicit meta-adaptive effect of scale-invariant architectural components. This insight leads to an explicit optimizer, 2-Adam, which we generalize to k-Adam—an optimizer that applies an adaptive normalization procedure k times, encompassing Adam (corresponding to k = 1) and Adam with a normalization layer (corresponding to k = 2). Overall, our continuous-time formulation of Adam facilitates a principled analysis, offering deeper understanding of optimal hyperparameter choices and architectural decisions in modern deep learning. © 2024, CC BY.

关键词： Adaptive algorithms

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Setting the physical scale of dimensional reduction in causal dynamical triangulations

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Physical Review D 2019年第2期100卷 026014-026014页

作者： Joshua H. Cooperman Manuchehr Dorghabekov Department of Physics and Astronomy Bucknell University Lewisburg Pennsylvania 17837 USA Physics Program Bard College Annandale-on-Hudson New York 12504 USA* Applied Mathematics and Informatics Program American University of Central Asia Bishkek Kyrgyz Republic*

Within the causal dynamical triangulations approach to the quantization of gravity, striking evidence has emerged for the dynamical reduction of spacetime dimension on sufficiently small scales. Specifically, the spectral dimension decreases from the topological value of 4 toward a value near 2 as the scale being probed decreases. The physical scales over which this dimensional reduction occurs have not previously been ascertained. We present and implement a method to determine these scales in units of either the Planck length or the quantum spacetime geometry’s effective de Sitter length. We find that dynamical reduction of the spectral dimension occurs over physical scales of the order of 10 Planck lengths, which, for the numerical simulation considered below, corresponds to the order of 10−1 de Sitter lengths.

关键词： Quantum gravity

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An Empirical Analysis of Meta-learning for the Automatic Choice of Architecture and Components in Ensemble Systems

An Empirical Analysis of Meta-learning for the Automatic Cho...

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Brazilian Conference on Intelligent Systems (BRACIS)

作者： Diego S.C. Nascimento Anne M.P. Canuto André L.V. Coelho Information System Group. Federal Institute of Rio Grande do Norte (IFRN) Ipanguaçu RN Brazil Informatics and Applied Mathematics Department Federal University of Rio Grande do Norte (UFRN) Natal RN Brazil University of Fortaleza (UNIFOR) Graduate Program in Applied Informatics Fortaleza CE Brazil

Studies with ensemble systems have gained attention recently and, most of them, propose new methods for the design (generation) of different components in these systems. In parallel, new contributions of meta-learning have been presented as an efficient alternative to automatic recommendation of algorithms. In this paper, we apply meta-learning in the process of recommendation of important parameters of ensemble systems, which are: architecture and individual classifiers. The main goal is to provide an efficient way to design ensemble systems. In order to validate the proposed approach, an empirical investigation is conducted, recommending three possible types of ensemble architectures (Bagging, Boosting and Multi-Boosting) and five possible types of learning algorithms to compose the ensemble systems (individual classifiers or components). An initial analysis of the results confirms that meta-learning can be a promising tool to be used in the automatic choice of important parameters in ensemble systems.

关键词： Barium Boosting Bagging Support vector machines Error analysis Algorithm design and analysis Niobium

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Dimensional reduction using conditional entropy for incomplete information systems 1

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15th International Conference on Parallel Computing Technologies, PaCT 2019

作者： Deris, Mustafa Mat Senan, Norhalina Abdullah, Zailani Mamat, Rabiei Handaga, Bana Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit Raja Malaysia Faculty of Entrepreneurship and Business Universiti Malaysia Kelantan Pengkalan Chepa Kota BharuKelantan16100 Malaysia Faculty of Informatics and Applied Mathematics University of Malaysia Terengganu Kuala TerengganuTerengganu21030 Malaysia Program Studi Informatika Universitas Muhammadiah Surakarta SurakartaCentral Java57162 Indonesia

ISBN: (数字)9783030256364

ISBN: (纸本)9783030256357

Dimension reduction approach is one of the main data reduction approaches in order to reduce the storage and processing time while maintaining the integrity of the original data. A wide range of dimension reduction approaches are based on classical approaches such as PCA and Bayer’s, and machine learning approaches such as clustering, and feature selection techniques. However, many of the approaches do not consider the incomplete information systems where some attribute values are missing or incomplete. Only few studies were proposed for the problem in incomplete information systems due to its complexities, specifically on attribute selection. The most popular approaches is based on probability theory to replace missing values with the most common values, or remove the missing objects from the information systems. However, it needs to know the probability distribution of data in advance. To overcome these issues, we propose a new approach based on conditional entropy to reduce dimensionality. The results show that the proposed approach achieves better data reduction with higher accuracy for objects and dimensionality reduction in incomplete information systems. © 2019, Springer Nature Switzerland AG.

关键词： Data reduction

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Bibliometric Analysis: Research Trends in Leaf Image Segmentation and Classification

Bibliometric Analysis: Research Trends in Leaf Image Segment...

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Artificial Intelligence and Mechatronics Systems (AIMS), International Conference on

作者： Eka Puji Agustini Rahmad Gernowo Kurnianingsih Adi Wibowo Budi Warsito Doctoral Program of Information System School of Postgraduated Studies Diponegoro University Semarang Indonesia Doctoral Program of Information System Diponegoro University Semarang Indonesia Master of Applied Science Program Polytechnic Semarang Indonesia Department of Informatics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia Department of Statistics Faculty of Science and Mathematics Diponegoro Universitty Semarang Indonesia

Exploring various phenomena and issues related to leaf images is paramount, particularly in segmentation and classification of such images. This study employs bibliometric analysis to delve into two overarching themes: the trends in publication and the evolution of publications, along with a keyword-based analysis. The research methodology unfolds in two stages: (1) data collection and (2) analysis. The dataset comprises 1,248 articles sourced from the Scopus database, covering the period from 1988 to 2023. The research findings unveil a noteworthy surge in publication trends, peaking at 231 documents in 2023. An in-depth examination of journal names demonstrates that studies on the segmentation and classification of leaf images are predominantly featured in computer science journals, exemplified by the publication of 589 documents. Furthermore, an analysis of frequently used keywords highlights “Extraction” as the predominant term, employed a total of 364 times. This underscores that the research focus on leaf image segmentation and classification presents ample opportunities for researchers to delve more profoundly into the subject.

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