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International Conference on Information science and technology (ICIST)

作者： Youness Manzali Khalidou Abdoulaye Barry Mohamed El Far Applied Physics Computer Science and Statistics Laboratory Faculty of Sciences Dhar El Mahraz Sidi Mohammed Ben Abdellah University Fez Morocco

K-Nearest Neighbors is a widely used algorithm due to its simplicity and efficacity. However, KNN suffers from many drawbacks, such as it does not work well with datasets with a high number of features. Also, not all the features contribute to the classification process. To resolve these issues, we present an improved KNN algorithm which uses KNN as a base learner in an ensemble method and correlation for selecting the features subsets. The experiment results show that the proposed algorithm performed better than other machine learning algorithms.

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Energy dependence of proton-proton elastic scattering at large momentum transfer

arXiv

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arXiv 2023年

作者： Ferreira, Erasmo Kohara, Anderson Kendi Instituto de Física Universidade Federal do Rio de Janeiro C.P. 68528 Rio de Janeiro Rio de Janeiro21945-970 Brazil AGH University Of Science and Technology Faculty of Physics and Applied Computer Science Mickiewicza 30 Kraków30-059 Poland

The measurements of proton-proton elastic scattering for large momentum transfer at energies in the range ≈ 20 to 60 GeV show a simple behaviour of form dσ/dt ≈ const |t|−8, apparently with no energy dependence. In the present work detailed analysis of the data shows a decrease of the magnitude of the tail with the energy, still with preservation of the power |t|−8. The analysis allows the definition of a band for the energy dependence of the amplitude with central line A(√s) = 0.389 log (100)/ log √s GeV6 . The rate of decrease describes well the data at the distant energy √s = 13 TeV, with reduction of the cross section by a factor 5.71. This result gives prediction for new experiments at high energies, and opens important question for theoretical investigation. Copyright © 2023, The Authors. All rights reserved.

关键词： Elastic scattering

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Evaluating Optimal Reference Translations

arXiv

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arXiv 2023年

作者： Zouhar, Vilém Kloudová, Věra Popel, Martin Bojar, Ondřej ETH Zürich Department of Computer Science Switzerland Institute of Formal and Applied Linguistics Faculty of Mathematics and Physics Charles University Czech Republic

The overall translation quality reached by current machine translation (MT) systems for high-resourced language pairs is remarkably good. Standard methods of evaluation are not suitable nor intended to uncover the many translation errors and quality deficiencies that still persist. Furthermore, the quality of standard reference translations is commonly questioned and comparable quality levels have been reached by MT alone in several language pairs. Navigating further research in these high-resource settings is thus difficult. In this article, we propose a methodology for creating more reliable document-level human reference translations, called "optimal reference translations," with the simple aim to raise the bar of what should be deemed "human translation quality." We evaluate the obtained document-level optimal reference translations in comparison with "standard" ones, confirming a significant quality increase and also documenting the relationship between evaluation and translation editing. © 2023, CC BY.

关键词： Quality control

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Enhanced Spin Voltage of Si/Y3fe5o12/Co-Multilayer for Spin Seebeck Effect

SSRN

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SSRN 2024年

作者： Farooq, Umar Wongjom, Poramed Wongjom, Chalothon Maiaugree, Wasan Infasang, Yingyot Horprathum, Mati Chananonnawathorn, Chanunthorn Lertvanithphol, Tossaporn Pinitsoontorn, Supree Ummartyotin, Sarute Pijitrojana, Wanchai Electrical and Computer Engineering Department Thammasat School of Engineering Thammasat University Rangsit campus Klongluang Pathumthani12120 Thailand Divisions of Physics Faculty of Science and Technology Thammasat University Klongluang Pathumthani12120 Thailand Pathumthani12120 Thailand Department of Physics Faculty of Science Khon Kaen University Khon Kaen40002 Thailand Department of Materials and Textile Technology Faculty of Science and Technology Thammasat University Klongluang Pathum Thani12120 Thailand

The inverse spin Hall effect (ISHE) is acted for conversion of spin current to charge current. This study, we propose the advantage of ISHE for spin thermoelectric in YIG/Co multilayer. The YIG/Co multilayers thin film were prepared by sputtering techniques. The crystalline structure, sample thickness and magnetic moment were analyzed by x-ray diffraction (XRD), electron scanning microscope (SEM) and vibration sample magnetometer (VSM), respectively. The spin Seebeck effect (SSE) is observed for magnetic field dependence and temperature dependence, respectively. The result is shown the enhancement of the combination between ANE and SSE on YIG/Co multilayer. The enhancement voltage of YIG/Co multilayer is about ~2 times which compared with single layer. The YIG/Co multilayer film is the polycrystalline structure. The film thickness of YIG and Co is approximate about 90 nm and 10 nm, respectively. The YIG film is shown non-magnetic behavior for non-annealed sample but it is shown soft ferromagnetic film with 800 °C annealed sample. Lastly, the multilayer technique is graduated increased about five layers. So, we recommend that the approximate of preparing film by YIG/Co multilayer technique is well employed about 3 layers. © 2024, The Authors. All rights reserved.

关键词： Ferromagnetic materials

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Magnetoresitance vs. Electronic Structure in Cu Doped Single Crystalline Bi2se3 3d Topological Insulator

SSRN

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SSRN 2023年

作者： Chrobak, Maciej Maćkosz, Krzysztof Nowak, Kamil Naumov, Andrii Przybylski, Marek Faculty of Physics and Applied Computer Science AGH University of Krakow Mickiewicza Av. 30 Krakow30-059 Poland Academic Centre for Materials and Nanotechnology AGH University of Krakow Mickiewicza Av. 30 Krakow30-059 Poland Empa-Swiss Federal Laboratories for Materials Science and Technology Laboratory for Mechanics of Materials and Nanostructures Feuerwerkerstrasse 39 ThunCH-3602 Switzerland

Bismuth selenide (Bi2Se3) is one of the 3D topological insulators (TI) that can be characterised as materials of a semiconducting volume and a conductive surface. The evolution of the electronic structure of (Bi1−xCux)2Se3 (x=0, 0.025, 0.05, 0.09 and 0.125) was investigated by angle-resolved photoemission spectroscopy (ARPES), scanning tunnelling microscopy (STM/STS) and Shubnikov-de Haas oscillations (SdH). The results show that doping with Cu does not change the electronic structure, in particular it does not destroy the nontrivial topology of the system. The lack of superconductivity is discussed in view of intercalated CuxBi2Se3 in which superconductivity is observed. © 2023, The Authors. All rights reserved.

关键词： Bismuth compounds

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Improvement of Task Scheduling with Energy Efficiency including Fault Tolerant with Resilient Computing System in Parallel and Distributed Communication Network 2

Improvement of Task Scheduling with Energy Efficiency includ...

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2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Kumar, Vijay Madhuri, P. Yamini, R. Sravani, Palla Muthukumar, K. Graphic Era Hill University Department of Physics Dehradun India Hyderabad501401 India Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Computing Technologies Tamil Nadu Kattankulathur603203 India Raghu Engineering College Department of Computer Science and Engineering Andhra Pradesh Visakhapatnam531162 India Sri Krishna College of Engineering and Technology Department of Electrical and Electronics Engineering Tamilnadu Coimbatore India

ISBN: (纸本)9798350325799

In parallel and distributed communication networks, task scheduling is essential for attaining the best system performance. Innovative ways that may intelligently distribute computing resources while minimizing energy consumption and maintaining system resilience are required due to the rising need for energy efficiency and fault tolerance. This system, offers a unique approach to job scheduling in parallel and distributed communication networks that integrate genetic algorithms (GA) and machine learning (ML).Using ML approaches, proposed method analyses historical task execution data to discover patterns that may be applied to task execution time prediction in various computing systems. As a result, this can assign tasks to resources effectively, maximize resource usage, and cut down on execution time as a whole. In addition, using predefined objectives like energy efficiency and fault tolerance, GA is used to find the best task-resource assignments. This applies resilient computing approaches to the job scheduling procedure to overcome problems with fault tolerance. This prevents the execution of crucial operations from being hampered by system faults or resource shortages by utilizing fault detection and recovery technologies. This system can adapt dynamically to shifting network conditions through the combination of ML, GA, and resilient computing, which raises the entire system's reliability and availability. © 2023 IEEE.

关键词： Machine learning

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FEASIBILITY STUDIES OF DARK PHOTON SEARCHES WITH THE J-PET DETECTOR

Acta Physica Polonica B, Proceedings Supplement

引用

Acta Physica Polonica B, Proceedings Supplement 2024年第1期17卷 1A51-1A58页

作者： Mędrala-Sowa, Justyna del Rio, Elena Perez Krzemień, Wojciech Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Kraków30-348 Poland Centre for Theranostics Jagiellonian University Kraków31-501 Poland High Energy Physics Division National Centre for Nuclear Research 05-400 Poland

The positronium, a bound state of electron and positron, is a unique system to perform highly precise tests, due to no hadronic background and precise Quantum Electrodynamics (QED) predictions. Being a system of lepton and antilepton, its properties are precisely described by QED in the Standard Model (SM). The final events topology can be simulated using Monte Carlo techniques. The J-PET detector is a multi-purpose, large acceptance system that is very well-suitable to the studies of positronium decay due to its excellent angular (1◦) and timing resolutions. We present preliminary results on the feasibility of searching for Dark Matter (DM) candidates in the decay o-Ps → invisible with the J-PET, which is well-suited for the detection of positronium-decay products. Toy Monte Carlo simulations have been prepared to incorporate DM decay models to the oPs decay expectations in order to assess the detector capabilities to search for such an elusive component of our Universe. © 2024 Jagiellonian university. All rights reserved.

关键词： Positrons

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Forward Brillouin Point Sensor in a Multi-Core Fiber 27

Forward Brillouin Point Sensor in a Multi-Core Fiber

引用

27th International Conference on Optical Fiber Sensors, OFS 2022

作者： Shemer, Keren Bashan, Gil Zehavi, Elad Diamandi, Hilel Hagai Bernstein, Alon Sharma, Kavita London, Yosef Barrera, David Sales, Salvador Zadok, Avi Faculty of Engineering and Institute for Nano-Technology and Advanced Materials Bar-Ilan University Ramat-Gan5290002 Israel Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot7610001 Israel Currently with Applied Physics Division Soreq NRC Yavne81800 Israel Photonics Research Labs Universitat Politècnica de València Valencia46022 Spain

Forward Brillouin point sensing is demonstrated in a multi-core fiber. Acoustic waves are stimulated by light in one core and monitored using a grating in another. Measurements distinguish between ethanol and water ou... 详细信息

ISBN: (纸本)9781957171142

关键词： Effective refractive index Fiber optic sensors Forward scattering Multicore fibers Phase modulation Tunable diode lasers

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A New Approach Towards Identification of Individuals Belonging to Different Subpopulations Using Machine Learning Models and CLC Data

A New Approach Towards Identification of Individuals Belongi...

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IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Małgorzata Charytanowicz Kajetan Perzanowski Maciej Januszczak Aleksandra Wołoszyn-Gałęza Maria Sobczuk Piotr Kulczycki Department of Computer Science Lublin University of Technology Lublin Poland Systems Research Institute Polish Academy of Sciences Warsaw Poland Institute of Biological Sciences John Paul II Catholic University of Lublin Lublin Poland Museum and Institute of Zoology Polish Academy of Sciences Ustrzyki Dolne Poland Chair of Animal Genetics and Conservation Warsaw University of Life Sciences Warsaw Poland Faculty of Physics and Applied Computer Science AGH University of Krakow Krakow Poland

ISBN: (数字)9798331530631

ISBN: (纸本)9798331530648

Spatial distributions of wisents (European bison) Bison bonasus (Linnaeus 1758), were studied in the Bieszczady Mountains (south-eastern Poland) on the basis of telemetric data obtained from two subpopulations: the western – inhabiting the forest districts of Baligród, Komańcza, Cisna and Lesko, and the eastern – dwelling within the districts of Lutowiska, Stuposiany, and in Bieszczadzki National park. Data was collected between 2002-2021. In our study, we propose a novel approach for classifying wisent subpopulations that utilizes machine learning methods and CLC data. For this purpose, the performances of eight algorithms: Naive Bayes, Logistic Regression, Support Vector Machine, Multilayer Perceptron, Random Forest, Extreme Gradient Boosting, k-Nearest Neighbors and Decision Tree were investigated. The algorithms were compared according to the following indicators: accuracy, Cohen’s-Kappa, precision, recall and F1 score. Their assessment was enhanced through the application of statistical inference (the Friedman test with post-hoc analysis) and SHAP values. The lowest results were achieved by Naive Bayes and Logistic Regression methods (accuracy of 73.69% and 74.43%, respectively), whilst significantly higher results were achieved by eXtreme Gradient Boosting, k-Nearest Neighbors and Decision Tree classifiers, with the classification accuracy exceeding 90% (91.81%, 92.8%, 93.47%, respectively). Based on the results, we conclude that CLC data represents a valuable source of information regarding the affinity of wisents towards different habitat conditions.

关键词： Logistic regression Accuracy Machine learning algorithms Nearest neighbor methods Boosting Inference algorithms Classification algorithms Bayes methods Telemetry Decision trees

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Effect of Annealing Temperature and MoO3 Composition on the Mechanical Properties of PEDOT:PSS-MoO3 Blend Thin Film Layers for Organic Solar Cells and Organic Light Emitting Diodes Applications

Effect of Annealing Temperature and MoO3 Composition on the ...

引用

Multidisciplinary Engineering and applied science (ICMEAS), International Conference on

作者： Kum Tatchen Buh Daniel Iramofu Amune Vitalis Chioh Anye Odette Fayen Ngasoh Abdulhakeem Bello Sadiq Thomas Department of Materials Science and Engineering African University of Science and Technology (AUST) Abuja Nigeria Department of Materials Science and Engineering Department of Electical-Electronics Engineering Faculty of Engineering African University of Science and Technology (AUST) Nile University of Nigeria Abuja Nigeria Department of Mechanical Engineering African University of Science and Technology (AUST) Abuja Nigeria Department of Theoritical & Applied Physics African University of Science and Technology (AUST) Abuja Nigeria Department of Computer Engineering Faculty of Engineering Nile University of Nigeria Abuja Abuja Nigeria

ISBN: (数字)9798350358834

ISBN: (纸本)9798350358841

Experimental and computational methods are employed in this study to examine how varying heat treatment temperatures and composition of Moo3nanoparticles, a transition metal oxide (TMO) impact the mechanical properties of PEDOT:PSS/MoO3 thin film blends for organic photovoltaics (OPVs) and organic light emitting diode (OLED) applications. The study primarily investigates the mechanical properties (hardness and Young's modulus), microstructure and surface morphology of solution-processed PEDOT:PSS/MoO3 ink blends of different compositions prepared at temperature regimes between 60 to 120 °C. Nanoindentation is used to investigate mechanical properties and Scanning Probe Microscopy to examine the surface morphological and microstructural changes. Mechanical maps and statistical deconvolutions are used to show the distribution of mechanical properties and phases respectively in the PEDOT:PSS/Mo03 thin film blends at the different annealing temperatures (60 - 120 °C). The experimental and computational results lead to the conclusion that incorporating different percentages of Moo3into PEDOT:PSS can, depending on the blended ratio improve the microstructure, mechanical properties and surface morphology of the PEDOT:PSS/MoO3 blends. Lightly doped PEDOT:PSS/MoO3 blends (1:0.1, 1:0.3), generally exhibit improved surface morphologies, enhanced elastic modulus and hardness, suitable for applications in efficient and mechanically durable electronic devices.

关键词： Temperature Annealing Surface morphology Morphology Organic light emitting diodes Mechanical factors Microstructure

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