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On the Evaluation of the Eigendecomposition of the Airy Integral Operator

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arXiv 2021年

作者： Shen, Zewen Serkh, Kirill Dept. of Computer Science University of Toronto TorontoONM5S 2E4 Canada Dept. of Math. and Computer Science University of Toronto TorontoONM5S 2E4 Canada

The distributions of the k-th largest level at the soft edge scaling limit of Gaussian ensembles are some of the most important distributions in random matrix theory, and their numerical evaluation is a subject of great practical importance. One numerical method for evaluating the distributions uses the fact that they can be represented as Fredholm determinants involving the so-called Airy integral operator. When the spectrum of the integral operator is computed by discretizing it directly, the eigenvalues are known to at most absolute precision. Remarkably, the Airy integral operator is an example of a so-called bispectral operator, which admits a commuting differential operator that shares the same eigenfunctions. In this paper, we develop an efficient numerical algorithm for evaluating the eigendecomposition of the Airy integral operator to full relative precision, using the eigendecomposition of the commuting differential operator. This allows us to rapidly evaluate the distributions of the k-th largest level to full relative precision rapidly everywhere, except in the left tail, where they are computed to absolute precision. In addition, we characterize the eigenfunctions of the Airy integral operator, and describe their extremal properties in relation to an uncertainty principle involving the Airy transform. We observe that the Airy integral operator is fairly universal, and we describe a separate application to Airy beams in optics. © 2021, CC BY.

关键词： Eigenvalues and eigenfunctions

Studying the effects of feature selection approaches on machine learning techniques for Mushroom classification problem

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Studying the effects of feature selection approaches on mach...

IT and Industrial Technologies (ICIT), International Conference on

作者： Abu Bakar Siddique Muhammad Abu Bakar Raja Hashim Ali Usama Arshad Nisar Ali Zain Ul Abideen Talha Ali Khan Ali Zeeshan Ijaz Muhammad Imad Faculty of Computer Science & Engg GIK Institute of Engg. Sciences & Tech Khyber Pakhtunkhwa Pakistan Faculty of Computer Science & Engg AI Research Group GIK Institute of Engg. Sciences & Tech Khyber Pakhtunkhwa Pakistan Faculty of Electronic Systems Engg University of Regina Regina Canada BCMaterials Basque Center for Materials Applications & Nanostructure Leioa Basque Country Spain Dept. of Tech & Software Engg Univ. of Europe of Applied Sciences Berlin Germany

Feature selection is a critical factor affecting the performance of optimization algorithms. Without proper feature selection, optimization algorithms may suffer from slow convergence, overfitting, increased computational requirements, and longer execution times. On the other hand, omitting important features can lead to loss of relevant information, decreased accuracy, bias, and increased vulnerability to noise and outliers. This study investigates the use of genetic algorithms as a feature selection technique for a classification problem, specifically the mushrooms classification problem. Random forest is employed as the machine learning classifier, and genetic algorithms are compared with correlation as the feature selection method. The results show that genetic algorithms achieve higher accuracy, precision, recall, and F1-score compared to correlation-based feature selection. However, genetic algorithms have limitations in their applicability to specific optimization problems, the need for proper parameter setup, and longer convergence times. Despite these drawbacks, genetic algorithms prove to be superior to other feature selection techniques, particularly correlation-based approaches. This study highlights the importance of selecting appropriate feature selection techniques for optimization algorithms to improve their performance and achieve better results. In addition, this study explored the performance of various machine learning approaches on the complete mushroom dataset with 22 features and shows that genetic algorithms with feature selection as the most accurate method.

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Android CompCache based on Graphics Processing Unit 7

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Android CompCache based on Graphics Processing Unit

7th International Conference on Software Defined Systems, SDS 2020

作者： Almiani, Muder Razaque, Abdul Ziqi, Shen Yaqin, Ge Atiewi, Saleh Alweshah, Mohammed Al-Dmour, Ayman Magableh, Basel Al-Hussein Bin Talal University College of Information Technology Jordan International IT University Dept. of Computer Engineering Telecommunication Almaty Kazakhstan New York Institute of Technology Department of Computer Science Nanjing Campus China Al-Balqa Applied University Amman Jordan Applied Science University Department of Computer Science Manama Bahrain Technological University Dublin Ireland

ISBN: (纸本)9781728172194

Android systems have been successfully developed to meet the demands of users. The following four methods are used in Android systems for memory management: backing swap, CompCache, traditional Linux swap, and low memory killer. These memory management methods are fully functioning. However, Android phones cannot swap memory into solid-state drives, thus slowing the processor and reducing storage lifetime. In addition, the compression and decompression processes consume additional energy and latency. Therefore, the CompCache requires an extension. An extended Android CompCache using a graphics processing unit to compress and decompress memory pages on demand and reduce the latency is introduced in this paper. This paper characterizes each data compression and decompression utility by measuring compression ratio, compression and decompression throughput, and energy efficiency to validate the process. Experimental results prove that data compression and decompression utilities can be beneficial to reduce the latency and perform faster compression and decompression compared with existing approaches. © 2020 IEEE.

关键词： Energy utilization

Semantic preserving bijective mappings of mathematical formulae between document preparation systems and computer algebra systems

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arXiv 2021年

作者： Cohl, Howard S. Schubotz, Moritz Youssef, Abdou Greiner-Petter, André Gerhard, Jürgen Saunders, Bonita V. McClain, Marjorie A. Applied and Computational Mathematics Division NIST GaithersburgMD United States Dept. of Computer and Information Science University of Konstanz Konstanz Germany Dept. of Computer Science GWU WashingtonDC United States DSIMG Technische Universität Berlin Germany Maplesoft WaterlooON Canada

Document preparation systems like LaTeX offer the ability to render mathematical expressions as one would write these on paper. Using LaTeX, LaTeXML, and tools generated for use in the National Institute of Standards (NIST) Digital Library of mathematical Functions, semantically enhanced mathematical LaTeX markup (semantic LaTeX) is achieved by using a semantic macro set. computer algebra systems (CAS) such as Maple and mathematica use alternative markup to represent mathematical expressions. By taking advantage of Youssef's Part-of-math tagger and CAS internal representations, we develop algorithms to translate mathematical expressions represented in semantic LaTeX to corresponding CAS representations and vice versa. We have also developed tools for translating the entire Wolfram Encoding Continued Fraction Knowledge and University of Antwerp Continued Fractions for Special Functions datasets, for use in the NIST Digital Repository of mathematical Formulae. The overall goal of these efforts is to provide semantically enriched standard conforming mathML representations to the public for formulae in digital mathematics libraries. These representations include presentation mathML, content mathML, generic LaTeX, semantic LaTeX, and now CAS representations as well. © 2021, CC BY.

关键词： Semantics

Tracking the mid-infrared fine structure of quasi-1D excitons controlled by magnetic order

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Tracking the mid-infrared fine structure of quasi-1D exciton...

International Conference on Infrared and Millimeter Waves

作者： M. Liebich M. Florian N. Nilforoushan F. Mooshammer K. Mosina Z. Sofer F. Dirnberger M. Kira R. Huber Department of Physics University of Regensburg Regensburg Germany Dept. of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA Department of Physics Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Erlangen Germany Department of Inorganic Chemistry University of Chemistry and Technology Prague Prague 6 Czech Republic Institute of Applied Physics Dresden University of Technology Dresden Germany

ISBN: (数字)9798350370324

ISBN: (纸本)9798350370331

We use phase-locked few-cycle mid-infrared pulses to probe internal Rydberg-like transitions of quasi-one-dimensional excitons in the magnetic semiconductor CrSBr. The experimentally observed fine structure encompasses a lifted degeneracy of the 2p states induced by the anisotropic optoelectronic properties of the crystal. Furthermore, the Coulomb correlations are effectively controlled via the magnetic structure. By inducing a phase transition from antiferromagnetic to paramagnetic states either thermally or by applying an external magnetic field, we can switch excitons from strongly bound and mono-layer-localized to weakly bound and interlayer-delocalized species. A state-of-the-art many-body theory fully captures these findings and identifies the spin restrictions of the interlayer tunneling. In the paramagnetic phase, the reduced quantum confinement lowers the binding energy and increases the phase space for scattering. This in situ control of Coulomb correlations opens a path to shape phase transitions on demand.

关键词： Correlation Excitons Shape Magnetic confinement Scattering Switches Perpendicular magnetic anisotropy Probes Magnetic semiconductors Magnetic tunneling

Interpretable ML for Imbalanced Data

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arXiv 2022年

作者： Dablain, Damien A. Bellinger, Colin Krawczyk, Bartosz Aha, David W. Chawla, Nitesh V. Lucy Family Institute for Data & Society Dept. Computer Science and Engineering University of Notre Dame Notre DameIN46556 United States National Research Council of Canada OttawaK1A 0R6 Canada Dept. Computer Science Virginia Commonwealth University RichmondVA23824 United States Navy Center for Applied Research in AI Naval Research Laboratory WashingtonDC20375 United States

Deep learning models are being increasingly applied to imbalanced data in high stakes fields such as medicine, autonomous driving, and intelligence analysis. Imbalanced data compounds the black-box nature of deep networks because the relationships between classes may be highly skewed and unclear. This can reduce trust by model users and hamper the progress of developers of imbalanced learning algorithms. Existing methods that investigate imbalanced data complexity are geared toward binary classification, shallow learning models and low dimensional data. In addition, current eXplainable Artificial Intelligence (XAI) techniques mainly focus on converting opaque deep learning models into simpler models (e.g., decision trees) or mapping predictions for specific instances to inputs, instead of examining global data properties and complexities. Therefore, there is a need for a framework that is tailored to modern deep networks, that incorporates large, high dimensional, multi-class datasets, and uncovers data complexities commonly found in imbalanced data (e.g., class overlap, sub-concepts, and outlier instances). We propose a set of techniques that can be used by both deep learning model users to identify, visualize and understand class prototypes, sub-concepts and outlier instances;and by imbalanced learning algorithm developers to detect features and class exemplars that are key to model performance. Our framework also identifies instances that reside on the border of class decision boundaries, which can carry highly discriminative information. Unlike many existing XAI techniques which map model decisions to gray-scale pixel locations, we use saliency through back-propagation to identify and aggregate image color bands across entire classes. This facilitates the high-level analysis of foreground and background colors used by models to discern classes (e.g., blue sky for airplanes). Our framework is publicly available at https://***/dd1github/XAI_for_Imbalanced_

关键词： Decision trees

As a mechanism that achieves the goal of decision management

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As a mechanism that achieves the goal of decision management

2021 International Conference on Information science and Communications Technologies, ICISCT 2021

作者： Raximov, Nodir Quvondikov, Jurabek Dusanov, Xurshid Daminova, Barno Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Dept. of Software of Information Technologies Tashkent Uzbekistan Applied Mathematics and Informatics Jizzakh Branch of National University of Uzbekistan Named after Mirzo Ulugbek Jizzakh Uzbekistan Karshi State University Methods of Teaching Computer Science Karshi Uzbekistan

ISBN: (纸本)9781665432580

Working with different data depending on the appearance and content of the object. Formation of types of objects and content of processes within the framework of human activity. Based on this, the control mechanism is also different. Management effects in the learning system are understood as the transfer of knowledge in the subject area to the student using the methods and tools formed by the teacher in the educational environment, taking into account all the factors generated in this process. The control system in this view is a simple system with a nonlinear feedback section. It combines complexes consisting of technical, software, telecommunications and methodological tools used in the educational process. They can be used to form alternative solutions not only by delivering parts of the training materials, but also by collecting and processing the information needed to manage the learning process. The training method is chosen according to the requirements of the learning environment and depends on the topic. If the chosen method is accepted, the training part is provided, which is fixed (question-answer or in another form), which makes it possible to work independently. © 2021 IEEE.

关键词： Learning systems

A Comparative Risk Analysis on CyberShip System with STPA-Sec, STRIDE and CORAS

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arXiv 2022年

作者： Sahay, Rishikesh Estay, D.A. Sepulveda Meng, Weizhi Jensen, Christian D. Barfod, Michael Bruhn Business Management Dept. Oregon Institute of Technology Klamath FallsOR97601 United States Digitalization Group Rigshospitalet Denmark Dept. of Applied mathematics & Computer Science Technical University of Denmark DK-2800 Kgs. Lyngby Denmark DTU Management Engineering Technical University of Denmark DK-2800 Kgs. Lyngby Denmark

The widespread use of software-intensive cyber systems in critical infrastructures such as ships (CyberShips) has brought huge benefits, yet it has also opened new avenues for cyber attacks to potentially disrupt operations. Cyber risk assessment plays a vital role in identifying cyber threats and vulnerabilities that can be exploited to compromise cyber systems. Understanding the nature of cyber threats and their potential risks and impact is essential to improve the security and resilience of cyber systems, and to build systems that are secure by design and better prepared to detect and mitigate cyber attacks. A number of methodologies have been proposed to carry out these analyses. This paper evaluates and compares the application of three risk assessment methodologies: system theoretic process analysis (STPA-Sec), STRIDE and CORAS for identifying threats and vulnerabilities in a CyberShip system. We specifically selected these three methodologies because they identify threats not only at the component level, but also threats or hazards caused due to the interaction between components, resulting in sets of threats identified with each methodology and relevant differences. Moreover, STPA-Sec which is a variant of the STPA is widely used for safety and security analysis of cyber physical systems (CPS);CORAS offers a framework to perform cyber risk assessment in a top-down approach that aligns with STPA-Sec;and STRIDE (Spoofing, Tampering, Repudiation,Information disclosure, Denial of Service, Elevation of Privilege) considers threat at the component level as well as during the interaction that is similar to STPA-Sec. As a result of this analysis, this paper highlights the pros and cons of these methodologies, illustrates areas of special applicability, and suggests that their complementary use as threats identified through STRIDE can be used as an input to CORAS and STPA-Sec to make these methods more structured. Copyright © 2022, The Authors. All rights reserved.

关键词： Risk assessment

The effect of phased recurrent units in the classification of multiple catalogs of astronomical lightcurves

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arXiv 2021年

作者： Donoso-Oliva, Cristobal Cabrera-Vives, G. Protopapas, P. Carrasco-Davis, R. Estevez, P.A. Dept. of Computer Science Universidad De Concepcion Millennium Institute of Astrophysics Chile Institute for Applied Computational Science Harvard University Gatsby Computational Neuroscience Unit University College London Dept. of Electrical Engineering Universidad de Chile