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Transport through Amorphous Photonic Materials with Localization and Bandgap Regimes

Physical Review Letters 2022年第15期129卷 157402-157402页

作者： Frank Scheffold Jakub Haberko Sofia Magkiriadou Luis S. Froufe-Pérez Department of Physics University of Fribourg CH-1700 Fribourg Switzerland Faculty of Physics and Applied Computer Science AGH University of Science and Technology Aleja Mickiewicza 30 Krakow 30-059 Poland

We propose a framework that unifies the description of light transmission through three-dimensional amorphous dielectric materials that exhibit both localization and a photonic bandgap. We argue that direct, coherent reflection near and in the bandgap attenuates the generation of diffuse or localized photons. Using the self-consistent theory of localization and considering the density of states of photons, we can quantitatively describe the total transmission of light for all transport regimes: transparency, light diffusion, localization, and bandgap. Comparison with numerical simulations of light transport through hyperuniform networks supports our theoretical approach.

关键词： Anderson localization Photonic crystals Photonics Scattering theory Disordered systems Diffusion & random walks Finite-difference time-domain method Light scattering

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Cultivating Archipelago of Forests: Evolving Robust Decision Trees Through Island Coevolution 39

Cultivating Archipelago of Forests: Evolving Robust Decision...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zychowski, Adam Perrault, Andrew Mańdziuk, Jacek Faculty of Mathematics and Information Science Warsaw University of Technology Poland Department of Computer Science and Engineering The Ohio State University United States Faculty of Computer Science AGH University of Krakow Poland Center of Excellence in Artificial Intelligence AGH University of Krakow Poland

ISBN: (纸本)157735897X

Decision trees are widely used in machine learning due to their simplicity and interpretability, but they often lack robustness to adversarial attacks and data perturbations. The paper proposes a novel island-based coevolutionary algorithm (ICoEvoRDF) for constructing robust decision tree ensembles. The algorithm operates on multiple islands, each containing populations of decision trees and adversarial perturbations. The populations on each island evolve independently, with periodic migration of top-performing decision trees between islands. This approach fosters diversity and enhances the exploration of the solution space, leading to more robust and accurate decision tree ensembles. ICoEvoRDF utilizes a popular game theory concept of mixed Nash equilibrium for ensemble weighting, which further leads to improvement in results. ICoEvoRDF is evaluated on 20 benchmark datasets, demonstrating its superior performance compared to state-ofthe-art methods in optimizing both adversarial accuracy and minimax regret. The flexibility of ICoEvoRDF allows for the integration of decision trees from various existing methods, providing a unified framework for combining diverse solutions. Our approach offers a promising direction for developing robust and interpretable machine learning models. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Adversarial machine learning

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Non-Destructive Ethanol-Aqueous Solution with Modified Jerusalem Resonator for Disinfectants Against COVID-19 Characterization

Non-Destructive Ethanol-Aqueous Solution with Modified Jerus...

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2023 IEEE International Symposium on Antennas and Propagation, ISAP 2023

作者： Sangpet, Patchadaporn Akkaraekthalin, Prayoot Pechrkool, Tanaporn Chudpooti, Sukanya Chudpooti, Nonchanutt King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Industrial Physics and Medical Instrumentation Bangkok Thailand

ISBN: (纸本)9798350341140

This paper describes a liquid-mixture sensor based on a mushroom-shaped zeroth-order resonator (ZOR). The Jerusalem-shaped mushroom-like structure is designed to reduce the dimensions of a resonator and provide a high Q-factor with an operating frequency of 5.90 GHz. Using perturbation theory, every dielectric property of the liquid-mixture influences the resonance frequency. The structure of the sensor is composed of the modified Jerusalem resonator and 3D-printed case for locking the liquid under test (LUT) to reduce the problematic error from position measurement. Five Ethanol-aqueous concentrations, e.g., 60%, 65%, 70%, 75% and 80%, are chosen to investigate the responsibility of the modified Jerusalem resonator. By detecting the change in resonant frequency of the reflection coefficient, S11, the measured results can classify five conditions of the LUT. Other benefits of the zeroth-order resonator sensor include a nondestructive method, real-time monitoring, and no life-cycle limitation. © 2023 IEEE.

关键词： Ethanol-aqueous solution Jerusalem resonator microwave sensor non-destructive method Zeroth-order resonator

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Enhanced Explanations for Knowledge-Augmented Clustering using Subgroup Discovery 10

Enhanced Explanations for Knowledge-Augmented Clustering usi...

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10th IEEE International Conference on Data science and Advanced Analytics, DSAA 2023

作者： Szelazek, MacIej Hudson, Dan Bobek, Szymon Nalepa, Grzegorz J. Atzmueller, Martin Agh University Faculty of Applied Computer Science Kraków Poland Institute of Applied Computer Science Jagiellonian University Jagiellonian Human-Centered Artificial Intelligence Laboratory Mark Kac Center for Complex Systems Research Kraków Poland Osnabrück University Semantic Information Systems Group Osnabrück Germany Osnabrück Germany

ISBN: (纸本)9798350345032

Contemporary machine learning techniques are capable of extracting complex structure from data in a way that complements or exceeds manual examination, yet, as is welldocumented, many of these techniques suffer from a lack of interpretability. This paper extends previous work on explainable and interpretable machine learning, in particular on the 'Knowledge-Augmented Clusters (KnAC)' approach, allowing human users to benefit from uninterpretable 'black box' models to extract structure from datasets by clustering and to make this better understandable. One of the key functions of KnAC is to relate expert-annotated clusters to clusters that have been identified by a machine learning method, and then provide a comprehensible explanation, thus clarifying the relationships that KnAC discovered. Our novel contribution in this paper is to examine the usefulness of subgroup discovery as a way to generate comprehensible explanations within KnAC, and to compare this to the existing approach based on the XAI algorithm Anchors through a detailed evaluation. We find that the approach using subgroup discovery performs equally or better in our extensive experimentation testing this on six different datasets. © 2023 IEEE.

关键词： Machine learning

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Enabling MPI communication within Numba/LLVM JIT-compiled Python code using numba-mpi v1.0

arXiv

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arXiv 2024年

作者： Derlatka, Kacper Manna, Maciej Bulenok, Oleksii Zwicker, David Arabas, Sylwester Faculty of Mathematics and Computer Science Jagiellonian University Kraków Poland Max Planck Institute for Dynamics and Self-Organization Göttingen Germany Faculty of Physics and Applied Computer Science AGH Univeristy of Krakow Poland

The numba-mpi package offers access to the Message Passing Interface (MPI) routines from Python code that uses the Numba just-in-time (JIT) compiler. As a result, high-performance and multi-threaded Python code may utilize MPI communication facilities without leaving the JIT-compiled code blocks, which is not possible with the mpi4py package, a higher-level Python interface to MPI. For debugging purposes, numba-mpi retains full functionality of the code even if the JIT compilation is disabled. The numba-mpi API constitutes a thin wrapper around the C API of MPI and is built around Numpy arrays including handling of non-contiguous views over array slices. Project development is hosted at GitHub leveraging the mpi4py/setup-mpi workflow enabling continuous integration tests on Linux (MPICH, OpenMPI & Intel MPI), macOS (MPICH & OpenMPI) and Windows (MS MPI). The paper covers an overview of the package features, architecture and performance. As of v1.0, the following MPI routines are exposed and covered by unit tests: size/rank, [i]send/[i]recv, wait[all|any], test[all|any], allreduce, bcast, barrier, scatter/[all]gather & wtime. The package is implemented in pure Python and depends on numpy, numba and mpi4py (the latter used at initialization and as a source of utility routines only). The performance advantage of using numba-mpi compared to mpi4py is depicted with a simple example, with entirety of the code included in listings discussed in the text. Application of numba-mpi for handling domain decomposition in numerical solvers for partial differential equations is presented using two external packages that depend on numba-mpi: py-pde and PyMPDATA-MPI. Copyright © 2024, The Authors. All rights reserved.

关键词： Python

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Joining Cast Mg AZ91 and Wrought Al 6082 Through Friction Stir Welding 12th

Joining Cast Mg AZ91 and Wrought Al 6082 Through Friction St...

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12th Symposium on Friction Stir Welding and Processing, held at the TMS Annual Meeting and Exhibition, TMS 2023

作者： Mroczka, Krzysztof Dymek, Stanislaw Pietras, Adam Węglowska, Aleksandra Hamilton, Carter Kopyściański, Mateusz Department of Materials Engineering Faculty of Materials Science and Physics Cracow University of Technology Krakow Poland Faculty of Metal Engineering and Industrial Computer Science AGH University of Science and Technology Krakow Poland The Lukasiewicz Research Network Institute of Welding Gliwice Poland Department of Mechanical and Manufacturing Engineering Miami University College of Engineering and Computing 56N Garland Hall OxfordOH45056 United States

ISBN: (纸本)9783031226601

Dissimilar welds of cast magnesium AZ91 with wrought aluminium 6082-T6 were fabricated by friction stir welding (6 mm thick) with the alloys alternately placed on the advancing and retreating sides. The unique weld microstructures were characterized through light and electron microscopies (SEM, EDS), tensile tests were performed on samples containing the entire welds and the microhardness was measured across the weld cross-sections. Preliminary results demonstrate that some regions contain a significant amount of the brittle Al12Mg17 phase. To complement the microstructural and mechanical characterization, numerical simulations of the welding process provided deeper insight into the material flow during mixing and to the temperature distributions across the weld zones. Future work will include micro tensile specimens (cross-sectional area of 0.7 × 0.7 mm) to supplement the conventional tensile tests. These micro tensile specimens will be excised from distinct weld areas to highlight differences in local properties that influence weld behavior. © 2023, The Minerals, Metals & Materials Society.

关键词： Welds

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Modeling and Visualization of Complex Systems with the Use of GraphTool 1

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20th International Conference on Cooperative Design, Visualization and Engineering, CDVE 2023

作者： Świderska, Iwona Grabska, Ewa Palacz, Wojciech Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University ul. prof. Stanislawa Lojasiewicza 11 Kraków30-348 Poland

ISBN: (数字)9783031438158

ISBN: (纸本)9783031438141

This paper proposes a model of a complex design system in the form of a system of graphs with attributed and labeled not only nodes and edges but also entire graphs. The primary task of the graph system is to collect data from information provided by the context and organize this data according to the relationships between them, including adding metadata represented by layers with graph labels that designate the appropriate graphs for layers. At the layer level, we can define relationships between layers as relationships between nodes of graphs belonging to different layers. The proposed model has been implemented in GraphTool which is designed to support modeling and visualization of this graph system type using computer tools for graph transformation. The approach presented in this paper will be illustrated by an example that, concerns human resources management in a large software company and is an example of a description of human cooperation. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Visualization

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An Overview of Machine Learning Applications in Blockchain for Green Energy Exchanges 33

An Overview of Machine Learning Applications in Blockchain f...

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33rd Southern African Universities Power Engineering Conference, SAUPEC 2025

作者： Nemakonde, Pfano Nemangwele, Fhulufhelo Ratshitanga, Mukovhe University of Venda Faculty Science Engineering and Agriculture Dept. of Physics Thohoyandou South Africa Cape Peninsula University of Technology Dept. of Electrical Electronic and Computer Engineering Bellville South Africa

ISBN: (纸本)9798331535162

There is an increasing demand for affordable, decentralised and distributed electricity, which is one of the key motivating factors that has incentivised this review article's writing. Industrial 4.0 has been a conduit through which the conventional grids shift towards a self-autonomous system, and blockchain platforms are emerging as viable solutions to facilitate that paradigm. With the advent of peer-to-peer (P2P) energy trading, community-based energy exchanges have significantly contributed to reduced grid dependency. Machine learning (ML) is being implemented in predictive analytics for energy forecasting (EF), thereby aiding both distribution network operators (DNOs) and aggregators to precisely and predictably monitor, optimise and stabilise grid operations through smart agents. The main aim of this review paper is to provide a detailed analysis of the existing research and implementation approaches on blockchain-based P2P energy trading and a comparative overview of how ML applications aid predictive analytics in community-based energy exchanges. © 2025 IEEE.

关键词： Predictive analytics

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Study of the second-generation of CdTe and CIGS thin film PV modules under natural sunlight conditions

Renewable Energy and Power Quality Journal

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Renewable Energy and Power Quality Journal 2021年 19卷 379-384页

作者： Dyndal, K. Sanetra, J. Marszalek, K.W. Institute of Electronics Faculty of Computer Science Electronics and Telecommunications AGH University of Science and Technology Al. Mickiewicza 30 Kraków Poland

There is a significant amount of research in the literature concerning the performance of solar panels operating during outdoor exposure, but the full topic is not yet exhausted. One of the reasons is that the photovoltaic cell technology is constantly evolving. In this paper, a comparison of two types of CdTe and CIGS modules operated with a nominal power of 80 W and 140 W, respectively is studied. The module tests were performed under external conditions during autumn, winter, spring, and summer from October 2019 to July 2020 in the temperate climate of Miękinia, South Poland. The photovoltaic panels were connected to the electric grid via microinverters. During the tests, the temperature of the panels was monitored. To determine the influence of solar radiation on the energy conversion efficiency of photovoltaic panels, a pyranometer installed in the plane of the panels was used. Based on the monitoring of the atmospheric conditions and the measurement of instantaneous power, the efficiency of the modules is determined. © 2021, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Cadmium telluride

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Intelligent Deep Convolutional Neural Network Based Object DetectionModel for Visually Challenged People

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computer Systems science & Engineering 2023年第9期46卷 3191-3207页

作者： S.Kiruthika Devi Amani Abdulrahman Albraikan Fahd N.Al-Wesabi Mohamed K.Nour Ahmed Ashour Anwer Mustafa Hilal Department of Computing Technology SRM Institute of Science and TechnologyIndia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Engineering Mathematics and Physics Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Artificial Intelligence(AI)and computer Vision(CV)advancements have led to many useful methodologies in recent years,particularly to help visually-challenged *** detection includes a variety of challenges,for example,handlingmultiple class images,images that get augmented when captured by a camera and so *** test images include all these variants as *** detection models alert them about their surroundings when they want to walk *** study compares four CNN-based pre-trainedmodels:ResidualNetwork(ResNet-50),Inception v3,DenseConvolutional Network(DenseNet-121),and SqueezeNet,predominantly used in image recognition *** on the analysis performed on these test images,the study infers that Inception V3 outperformed other pre-trained models in terms of accuracy and *** further improve the performance of the Inception v3 model,the thermal exchange optimization(TEO)algorithm is applied to tune the hyperparameters(number of epochs,batch size,and learning rate)showing the novelty of the *** accuracy was achieved owing to the inclusion of an auxiliary classifier as a regularizer,hyperparameter optimizer,and factorization ***,Inception V3 can handle images of different *** makes Inception V3 the optimum model for assisting visually challenged people in real-world communication when integrated with Internet of Things(IoT)-based devices.

关键词： Pre-trained models object detection visually challenged people deep learning Inception V3 DenseNet-121

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