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A New-fangled Classification Algorithm for Medical Heart Diseases Analysis using Wavelet Transforms

Open Public Health Journal 2024年 17卷

作者： Nayak, Soumya Ranjan Selvarasu, Sivakumar Sripathy, B. Singh, Prabhishek Diwakar, Manoj Gupta, Indrajeet Ravi, Vinayakumar Mazroa, Alanoud Al School of Computer Engineering KIIT Deemed to be University Odisha Bhubaneswar 751024 India Department of Computer Applications Faculty of Science and Humanities SRM Institute of Science and Technology Kattankulathur Chennai 603203 India Department of Mathematics School of Advanced Sciences Vellore Institute of Technology (VIT) Vellore 632 014 India School of Computer Science Engineering & Technology Bennett University Greater Noida India CSE Department Graphic Era deemed to be University Uttarakhand Dehradun India Graphic Era Hill University Uttarakhand Dehradun India School of Computer Science & AI SR University Telangana Warangal 506371 India Center for Artificial Intelligence Prince Mohammad Bin Fahd University Khobar Saudi Arabia Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University (PNU) P.O. Box 84428 Riyadh 11671 Saudi Arabia

Background: In this article, the Mixed Mode Database Miner (MMDBM) algorithm is introduced for the classification of data. This algorithm depends on the decision tree classifier, which handles the numerical and categorical attributes. For the experimental analysis in a well-explored heart disease data set collected from the UCI Repository. Aims: Understanding the fundamentals of every classification method and how to apply them to CUDA is the aim of this study. After reviewing the literature, the approach that is most suited is selected for implementing the suggested algorithm in the MMDM classifier along with the discrete wavelet decomposition. From this experimental analysis, we observed that the use of the wavelet technique in the MMDBM algorithm provides better and more accurate results for data classification. Objective: The main objective of the manuscript is to identify the early stage of heart attack that was caused either by smoking, smoking with tobacco, or non-smoking. Additionally, this study aims to check the validity of the MMDM classifier along with the discrete wavelet decomposition. From this experimental analysis, we observed that the use of the wavelet technique in the MMDBM algorithm provides better and more accurate results for data classification. Methods: In the modern digital world today, data has a major impact on everyone’s life. Every database contains a lot of information hidden either in the form of numerical data, characteristic data, or a mixture of both. Moreover, to accurately decode every dataset, a fast and efficient classifier is essential.. Moreover, by using this hybrid technique based on both MMDBM and Wavelet processes, it compresses the data with minimum storage capacity. Results: The experimental results are compared with the classified data to wavelet data output. These results prove that our presented technique is more prominent and robust in an analysis of heart diseases. Conclusion: This algorithm is based on a decision

关键词： Big data Classification Algorithms Data mining Haar wavelets Healthcare Tobacco

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Results of the Ultra-Heavy Cosmic-Ray Analysis with CALET on the International Space Station 38

Results of the Ultra-Heavy Cosmic-Ray Analysis with CALET on...

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38th International Cosmic Ray Conference, ICRC 2023

作者： Zober, Wolfgang V. Rauch, Brian F. Adriani, O. Akaike, Y. Asano, K. Asaoka, Y. Berti, E. Bigongiari, G. Binns, W.R. Bongi, M. Brogi, P. Bruno, A. Cannady, N. Castellini, G. Checchia, C. Cherry, M.L. Collazuol, G. de Nolfo, G.A. Ebisawa, K. Ficklin, A.W. Fuke, H. Gonzi, S. Guzik, T.G. Hams, T. Hibino, K. Ichimura, M. Ioka, K. Ishizaki, W. Israel, M.H. Kasahara, K. Kataoka, J. Kataoka, R. Katayose, Y. Kato, C. Kawanaka, N. Kawakubo, Y. Kobayashi, K. Kohri, K. Krawczynski, H.S. Krizmanic, J.F. Maestro, P. Marrocchesi, P.S. Messineo, A.M. Mitchell, J.W. Miyake, S. Moiseev, A.A. Mori, M. Mori, N. Motz, H.M. Munakata, K. Nakahira, S. Nishimura, J. Okuno, S. Ormes, J.F. Ozawa, S. Pacini, L. Papini, P. Rauch, B.F. Ricciarini, S.B. Sakai, K. Sakamoto, T. Sasaki, M. Shimizu, Y. Shiomi, A. Spillantini, P. Stolzi, F. Sugita, S. Sulaj, A. Takita, M. Tamura, T. Terasawa, T. Torii, S. Tsunesada, Y. Uchihori, Y. Vannuccini, E. Wefel, J.P. Yamaoka, K. Yanagita, S. Yoshida, A. Yoshida, K. Zober, W.V. Department of Physics McDonnell Center for the Space Sciences Washington University St. LouisMO63130 United States Department of Physics University of Florence Via Sansone 1 Sesto Fiorentino50019 Italy INFN Sezione di Firenze Via Sansone 1 Sesto Fiorentino50019 Italy Waseda Research Institute for Science and Engineering Waseda University 17 Kikuicho Shinjuku Tokyo162-0044 Japan JEM Utilization Center Human Spaceflight Technology Directorate Japan Aerospace Exploration Agency 2-1-1 Sengen Ibaraki Tsukuba305-8505 Japan Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa Chiba277-8582 Japan Via Madonna del Piano 10 Sesto Fiorentino50019 Italy Department of Physical Sciences Earth and Environment University of Siena via Roma 56 Siena53100 Italy INFN Sezione di Pisa Polo Fibonacci Largo B. Pontecorvo 3 Pisa56127 Italy Department of Physics McDonnell Center for the Space Sciences Washington University One Brookings Drive St. LouisMO63130-4899 United States Heliospheric Physics Laboratory NASA GSFC GreenbeltMD20771 United States Center for Space Sciences and Technology University of Maryland Baltimore County 1000 Hilltop Circle BaltimoreMD21250 United States Astroparticle Physics Laboratory NASA GSFC GreenbeltMD20771 United States Center for Research and Exploration in Space Sciences and Technology NASA GSFC GreenbeltMD20771 United States Department of Physics and Astronomy Louisiana State University 202 Nicholson Hall Baton RougeLA70803 United States Department of Physics and Astronomy University of Padova Via Marzolo 8 Padova35131 Italy INFN Sezione di Padova Via Marzolo 8 Padova35131 Italy Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo Kanagawa Sagamihara252-5210 Japan Kanagawa University 3-27-1 Rokkakubashi Kanagawa Kanagawa Yokohama221-8686 Japan Faculty of Science and Technology Graduate School of Science and Te

The CALorimetric Electron Telescope (CALET), launched to the ISS in August 2015 and in continuous operation since, measures cosmic-ray (CR) electrons, nuclei, and gamma rays. CALET, with its 27 radiation length deep Total Absorption Calorimeter (TASC), measures particle energy, allowing for the determination of spectra and secondary to primary ratios of the more abundant CR nuclei through 28Ni, while the main charge detector (CHD) can measure Ultra-Heavy (UH) CR nuclei through 40Zr. Previous CALET UHGCR analyses used a special high duty cycle (∼90%) UH trigger that does not require passage through the TASC and used time- and position-dependent detector response corrections based on 14Si and 26Fe and an angle-dependent geomagnetic cutoff rigidity selection to show abundances of even nuclei in agreement with SuperTIGER and ACE-CRIS. The work shown here further improves upon those results by restricting UH events to those that pass through both the TASC and CHD. While this constraint does reduce the number of events to ∼1/6 of the original UH trigger analysis, the loss of statistics is compensated by improvements in event selection from an energy-binned charge determination and minimum deposited energy that substitutes for the previous minimum geomagnetic rigidity selection. The results shown here represent 7 years of observation for the abundances of elements from Z=10 to Z=40 relative to 26Fe and are compared to previous measurements from ACE-CRIS, SuperTIGER, and HEAO-3. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmology

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Detecting quantum entanglement with unsupervised learning

arXiv

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arXiv 2021年

作者： Chen, Yiwei Pan, Yu Zhang, Guofeng Cheng, Shuming Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou310027 China Department of Applied Mathematics The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong The Hong Kong Polytechnic University Shenzhen Research Institute Shenzhen518057 China The Department of Control Science and Engineering Tongji University Shanghai201804 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai201804 China Institute for Advanced Study Tongji University Shanghai200092 China

Quantum properties, such as entanglement and coherence, are indispensable resources in various quantum information processing tasks. However, there still lacks an efficient and scalable way to detecting these useful features especially for high-dimensional and multipartite quantum systems. In this work, we exploit the convexity of samples without the desired quantum features and design an unsupervised machine learning method to detect the presence of such features as anomalies. Particularly, in the context of entanglement detection, we propose a complex-valued neural network composed of pseudo-siamese network and generative adversarial net, and then train it with only separable states to construct non-linear witnesses for entanglement. It is shown via numerical examples, ranging from 2-qubit to 10-qubit systems, that our network is able to achieve high detection accuracy which is above 97.5% on average. Moreover, it is capable of revealing rich structures of entanglement, such as partial entanglement among subsystems. Our results are readily applicable to the detection of other quantum resources such as Bell nonlocality and steerability, and thus our work could provide a powerful tool to extract quantum features hidden in multipartite quantum data. © 2021, CC BY.

关键词： Quantum entanglement

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Results from CALorimetric Electron Telescope (CALET) Observations of Gamma-rays on the International Space Station 38

Results from CALorimetric Electron Telescope (CALET) Observa...

引用

38th International Cosmic Ray Conference, ICRC 2023

作者： Mori, Masaki Cannady, Nicholas Adriani, O. Akaike, Y. Asano, K. Asaoka, Y. Berti, E. Bigongiari, G. Binns, W.R. Bongi, M. Brogi, P. Bruno, A. Cannady, N. Castellini, G. Checchia, C. Cherry, M.L. Collazuol, G. de Nolfo, G.A. Ebisawa, K. Ficklin, A.W. Fuke, H. Gonzi, S. Guzik, T.G. Hams, T. Hibino, K. Ichimura, M. Ioka, K. Ishizaki, W. Israel, M.H. Kasahara, K. Kataoka, J. Kataoka, R. Katayose, Y. Kato, C. Kawanaka, N. Kawakubo, Y. Kobayashi, K. Kohri, K. Krawczynski, H.S. Krizmanic, J.F. Maestro, P. Marrocchesi, P.S. Messineo, A.M. Mitchell, J.W. Miyake, S. Moiseev, A.A. Mori, M. Mori, N. Motz, H.M. Munakata, K. Nakahira, S. Nishimura, J. Okuno, S. Ormes, J.F. Ozawa, S. Pacini, L. Papini, P. Rauch, B.F. Ricciarini, S.B. Sakai, K. Sakamoto, T. Sasaki, M. Shimizu, Y. Shiomi, A. Spillantini, P. Stolzi, F. Sugita, S. Sulaj, A. Takita, M. Tamura, T. Terasawa, T. Torii, S. Tsunesada, Y. Uchihori, Y. Vannuccini, E. Wefel, J.P. Yamaoka, K. Yanagita, S. Yoshida, A. Yoshida, K. Zober, W.V. Department of Physical Sciences Ritsumeikan University 1-1-1 Noji Higashi Kusatsu525-8577 Japan Center for Space Sciences and Technology University of Maryland Baltimore County 1000 Hilltop Circle BaltimoreMD21250 United States Astroparticle Physics Laboratory NASA GSFC GreenbeltMD20771 United States Center for Research and Exploration in Space Sciences and Technology NASA GSFC GreenbeltMD20771 United States Department of Physics University of Florence Via Sansone 1 Sesto Fiorentino50019 Italy INFN Sezione di Firenze Via Sansone 1 Sesto Fiorentino50019 Italy Waseda Research Institute for Science and Engineering Waseda University 17 Kikuicho Shinjuku Tokyo162-0044 Japan JEM Utilization Center Human Spaceflight Technology Directorate Japan Aerospace Exploration Agency 2-1-1 Sengen Ibaraki Tsukuba305-8505 Japan Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa Chiba277-8582 Japan Via Madonna del Piano 10 Sesto Fiorentino50019 Italy Department of Physical Sciences Earth and Environment University of Siena via Roma 56 Siena53100 Italy INFN Sezione di Pisa Polo Fibonacci Largo B. Pontecorvo 3 Pisa56127 Italy Department of Physics McDonnell Center for the Space Sciences Washington University One Brookings Drive St. LouisMO63130-4899 United States Heliospheric Physics Laboratory NASA GSFC GreenbeltMD20771 United States Department of Physics and Astronomy Louisiana State University 202 Nicholson Hall Baton RougeLA70803 United States Department of Physics and Astronomy University of Padova Via Marzolo 8 Padova35131 Italy INFN Sezione di Padova Via Marzolo 8 Padova35131 Italy Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo Kanagawa Sagamihara252-5210 Japan Kanagawa University 3-27-1 Rokkakubashi Kanagawa Kanagawa Yokohama221-8686 Japan Faculty of Science and Technology Graduate School of Science and Technology Hirosaki U

The CALorimetric Electron Telescope (CALET) cosmic ray detector on the International Space Station (ISS) has been in operation since its launch in 2015. The main instrument, the CALorimeter (CAL), is optimized to observe high-energy electrons up to TeV energies, but its three-storied, composite and thick detector enable us to discriminate gamma rays from overwhelming background of charged cosmic rays. Thus, it is monitoring the gamma ray sky from 1 GeV up to 10 TeV with a field of view of about 2 sr, but the exposure is somewhat non-uniform because of the limitation imposed by the inclination angle (51.6 degree) of the ISS orbit. In this paper we report results from gamma ray observations obtained during its mission for more than seven years with increased statistics compared with previous reports. They include properties of the Galactic diffuse gamma rays, spectra of bright Galactic point sources, and light curves of extragalactic active galactic nuclei, which show good consistencies with Fermi-LAT observations of which energy range overlaps with CALET. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmic ray detectors

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From sensing to energy savings: A comprehensive survey on integrating emerging technologies for energy efficiency in WBANs

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Digital Communications and Networks 2024年

作者： Shumaila Javaid Hamza Fahim Sherali Zeadally Bin He Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai 201804 China National Key Laboratory of Autonomous Intelligent Unmanned Systems Tongji University Shanghai 201210 China Frontiers Science Center for Intelligent Autonomous Systems Shanghai 201210 China Department of Computer Science Faculty of Computer Sciences Ilma University Karachi 75190 Pakistan College of Communication and Information University of Kentucky Lexington KY USA Academy of Computer Science & Software Engineering University of Johannesburg Johannesburg South Africa

Energy is essential for human existence, and its high consumption is a growing concern in today's technology-driven society. Global initiatives aim to reduce energy consumption and pollution by developing and deploying energy-efficient sensing technologies for long-term monitoring, control, automation, security, and interactions. Wireless Body Area Networks (WBANs) benefit a lot from the continuous monitoring capabilities of these sensing devices, which include medical sensors worn on or implanted in the human body for healthcare monitoring. Despite significant advancements, achieving energy efficiency in WBANs remains a significant challenge. A deep understanding of the WBAN architecture is essential to identify the causes of its energy inefficiency and develop novel energy-efficient solutions. We investigate energy efficiency issues specific to WBANs. We discuss the transformative impact that artificial intelligence and Machine Learning (ML) can have on achieving the energy efficiency of WBANs. Additionally, we explore the potential of emerging technologies such as quantum computing, nano-technology, biocompatible energy harvesting, and Simultaneous Wireless Information and Power Transfer (SWIPT) in enabling energy efficiency in WBANs. We focus on WBANs' architecture, hardware, and software components to identify key factors responsible for energy consumption in the WBAN environment. Based on our comprehensive review, we introduce an innovative, energy-efficient three-tier architecture for WBANs that employs ML and edge computing to overcome the limitations inherent in existing energy-efficient solutions. Finally, we summarize the lessons learned and highlight future research directions that will enable the development of energy-efficient solutions for WBANs.

关键词： Artificial intelligence Energy Healthcare Sensors Wireless body area networks

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Distributing Potential Games on Graphs Part I. Game formulation

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IFAC-PapersOnLine 2020年第2期53卷 6697-6702页

作者： Mohamed I. El-Hawwary Jonas Mårtensson Division of Decision and Control Systems School of Electrical Engineering & Computer Science KTH Royal Institute of Technology SE-100 44 Stockholm Sweden Department of Electrical Power Engineering Faculty of Engineering Cairo University Giza 12613 Egypt

The paper presents the problem of distributing potential games over communication graphs. Suppose a potential game can be designed for a group of agents (players) where each has access to all others’ actions (strategies). The paper shows how to design a corresponding potential game for these agents if the full information assumption is replaced with communication over a network depicted by undirected graphs with certain properties. A state-based formulation for potential games is utilized. This provides degrees of freedom to handle the previous information limitation. Notions of Nash’s equilibria for the developed game (called here distributed potential game) are presented, and relations between these equilibria and those of the full information game are studied. In part II of the paper learning Nash equilibria for the newly developed game is studied. The development focuses on providing a way to utilize available algorithms of the full information game. The motivation for the results comes from a platoon matching problem for heavy duty vehicles. Utilizing the newly developed distributed game, recent results based on potential games can be extended, providing a basis for an on-the-go strategy where platoon matching on road networks can be solved locally.

关键词： Potential games distributed optimization multi-agents

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Distributing Potential Games on Graphs Part II. Learning with application to platoon matching

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IFAC-PapersOnLine 2020年第2期53卷 6703-6708页

In part I of the paper the problem of distributing potential games over undirected graphs was formulated. A restricted information potential game was designed using state-based formulation. Here, learning Nash equilibria for this game is studied. An algorithm is developed with mainly two phases, an estimation phase and a learning phase. The setting allows for available learning methods of the full information game to be directly incorporated in the learning phase. The result matches the outcome (i.e. converges to the same equilibria) of the full information game. In addition, the design takes into account considerations of convergence time, and synchrony of actions update. The developed distributed game and learning algorithm are used to solve a platoon matching problem for heavy duty vehicles. This serves two objectives. First, it provides a motivation for the presented gaming results. Second, the problem addressed can facilitate platoon matching where it provides a basis for an on-the-go strategy.

关键词： Potential games distributed optimization multi-agents platoon matching

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Incorporating forecasting and peer-to-peer negotiation frameworks into a distributed model predictive control approach for meshed electric networks

arXiv

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arXiv 2021年

作者： Monasterios, Pablo Baldivieso R. Verba, Nandor Morris, Euan A. Morstyn, Thomas Konstantopoulos, George C. Gaura, Elena McArthur, Stephen The School of Engineering University of Edinburgh EdinburghEH9 3JL United Kingdom The Department of Automatic Control & Systems Engineering University of Sheffield Sheffield United Kingdom The Faculty Research Centre for Computational Science & Mathematical Modelling Coventry University Coventry United Kingdom The Department of Electronic and Electrical Engineering University of Strathclyde Glasgow United Kingdom

The continuous integration of renewable energy sources into power networks is causing a paradigm shift in energy generation and distribution with regards to trading and control;the intermittent nature of renewable sources affects pricing of energy sold or purchased;the networks are subject to operational constraints, voltage limits at each node, rated capacities for the power electronic devices, current bounds for distribution lines. These economic and technical constraints coupled with intermittent renewable injection may pose a threat to system stability and performance. We propose a novel holistic approach to energy trading composed of a distributed predictive control framework to handle physical interactions, i.e., voltage constraints and power dispatch, together with a negotiation framework to determine pricing policies for energy transactions. We study the effect of forecasting generation and consumption on the overall network’s performance and market behaviours. We provide a rigorous convergence analysis for both the negotiation framework and the distributed control. Lastly, we assess the impact of forecasting in the proposed system with the aid of testing scenarios. © 2021, CC BY-SA.

关键词： Forecasting

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Stabilizing Zinc Anodes with Sodium Lignosulfonate-Doped Polypyrrole

SSRN

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SSRN 2024年

作者： Ni, Yaqi Liu, Qifan Xue, Tao Zang, Limin Qiu, Jianhui Yu, Xiuwen Zhang, Jiali Yang, Chao MOE Key Laboratory of New Processing Technology for Nonferrous Metal and Materials Guangxi Key Laboratory of Optical and Electronic Materials and Devices Guangxi Colleges Universities Key Laboratory of Natural and Biomedical Polymer Materials Guilin University of Technology Guilin541004 China Guangxi Colleges Universities Key Laboratory of Environmental-friendly Materials and New Technology for Carbon Neutralization Guangxi Key Laboratory of Advanced Structural Materials and Carbon Neutralization School of Materials and Environment Guangxi Minzu University Nanning530105 China Department of Machine Intelligence and Systems Engineering Faculty of Systems Science and Technology Akita Prefectural University Yurihonjo015-0055 Japan

Despite zinc-based electrochemical energy storage being considered a safe and efficient energy storage system, problems such as uncontrolled dendrite growth, hydrogen precipitation reactions, and corrosion have seriously hindered its commercialization. Mitigating dendrite growth and other associated issues is crucial for the successful commercialization of these systems. Herein, we propose a sodium lignosulfonate-doped polypyrrole protective layer for zinc anodes with good hydrophilicity, electrical conductivity, and a porous structure, which can effectively inhibit the growth of zinc dendrites and the side reactions. The doping of sodium lignosulfonate introduces numerous zincophilic groups. The sulfonic acid groups enhance zinc ion interaction and regulate flux, while phenolic hydroxyl groups increase zincophilic sites, aiding in the uniform deposition of zinc. As expected, the Zn||Zn symmetric cell with this protective layer provides high cycling stability of more than 1960 hours at 0.5 mAh cm-2, 0.25 mA cm-2. This study presents a feasible approach for realizing stable zinc anodes. © 2024, The Authors. All rights reserved.

关键词： Polypyrroles

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A New Method for Quantifying Workload of Drivers and Application in Analyzing Stabilization Time after Critical Events in Varying Automation Levels

SSRN

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SSRN 2022年

作者： Zhai, Junda Lu, Guangquan Chen, Facheng Liu, Miaomiao School of Transportation Science and Engineering Beihang University Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Department of Traffic Management School People’s Public Security University of China Beijing100038 China Beijing100088 China

The workload of drivers increases rapidly after the critical events and the period of time for workload to stabilize is worthy to investigate due to the close relationship between the workload and driving performance of drivers. It is yet unclear if the stabilization time of drivers varies across the different automation levels. In previous studies, a number of measurements have been utilized in evaluating the workload of drivers while most of the existing methods have limitations in studying the stabilization time. Therefore, this study introduces a new method for quantifying the cognitive workload of drivers with a measurement frequency of 2 seconds based on the performance of drivers to a newly designed calculating NDRT. A driving simulator experiment containing three automated driving levels and two critical events was conducted for the verification and application of the quantification method. Data were collected from 52 participants. The workload before and after critical events was analyzed and the results of quantified workload, the measurement acquired through the quantification method, showed a high similarity with heart rate and pupil diameter, which supported that the measurement could well reflect the workload of drivers with and without critical events. Moreover, the quantification method was applied to analyzing stabilization time after the critical situations and it was observed that quantified workload was a more appropriate measurement in determining the stabilization time of workload compared to heart rate and pupil diameter. In addition, the analysis results based on the workload quantification method showed that the effect of automation levels on the stabilization time of drivers after the critical events occurred was not significant. © 2022, The Authors. All rights reserved.

关键词： Automobile drivers

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