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Development of a Model for the Process of Anaerobic Digestion and Its Solution by the Modified Adomian Decomposition Method

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International Journal of Applied and Computational Mathematics 2021年第1期7卷 1-14页

作者： Silva, M.I. De Bortoli, A.L. Graduate Program in Applied Mathematics Federal University of Rio Grande do Sul Av. Bento Gonçalves 9500 Porto Alegre RS Brazil Graduate Program in Applied Mathematics Federal University of Rio Grande do Sul Porto Alegre Brazil Graduate Program in Chemical Engineering Federal University of Rio Grande do Sul Porto Alegre Brazil

Modeling the transformation of biomass into biogas is complex, because it involves a nonlinear and coupled set of ordinary differential equations. Thus, obtaining an analytical-numerical solution becomes attractive for this problem. In this paper, five chemical reactions are used to model the chemical kinetics of the anaerobic digestion process. The rate of production of each reaction is estimated by Gibbs free energy value. The equation system of the model is solved by the Modified Adomian Decomposition Method, applied to the time variable. The results obtained agree with the expected solution. © 2020, Springer Nature India Private Limited.

关键词： Adomian decomposition method Anaerobic digestion Chemical kinetics Differential equations system Simulation

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Machine Learning Methods for Predicting the Necessity of Caesareans Section of Childbirth 5

Machine Learning Methods for Predicting the Necessity of Cae...

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5th IEEE International Conference on Information Technology, Information Systems and Electrical engineering, ICITISEE 2021

作者： Sunge, Aswan Supriyadi Heryadi, Yaya Abdurachman, Edi Kartowisatro, Iman H. Bina Nusantara University BINUS Graduate Program- Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Faculty Of Engineering Computer Science Departement - BINUS Graduate Program Computer Science Computer Engineering Department Jakarta11480 Indonesia

ISBN: (纸本)9781665401968

In the process of delivery usually the baby comes out of the vagina but under some circumstances a cesarean section is performed. Caesarean section, on the one hand can have short-term and long-term effects for the mother but on the other hand it is a life-saving procedure for both mother and child. The purpose of this study is to predict whether or not a caesarean section is necessary for a pregnant mother using a machine learning classifier model and some features from medical records as input data. In this study, some machine models were explored including Logistic Regression, K-Nearest Neighbor, Random Forest, Decision Tree, Gradient Boosting and Support Vector Machine. The experiment found that Logistic Regression model achieved the highest performance as measured by average accuracy 95%, average precision 86%, average recall 95%, and average F1 86%. © 2021 IEEE.

关键词： Forecasting

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Peripheral pulse harmonic analysis and its clinical application: A systematic review

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Journal of Traditional and Complementary Medicine 2024年第2期14卷 223-236页

作者： Hsiao, Kun-Yuan Kang, Jiunn-Horng Wu, Yeong-Shing Chang, Hen-Hong Yang, Cheng-Ta Institute of Allied Health Sciences National Cheng Kung University Tainan Taiwan Department of Chinese Medicine Cishan Hospital Ministry of Health and Welfare Kaohsiung Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Graduate Institute of Nanomedicine and Medical Engineering College of Biomedical Engineering Taipei Medical University Taipei Taiwan Department of Physical Medicine and Rehabilitation Taipei Medical University Hospital Taipei Taiwan Graduate Institute of Integrated Medicine College of Chinese Medicine and Chinese Medicine Research Center China Medical University Taichung Taiwan Department of Chinese Medicine China Medical University Hospital Taichung Taiwan Department of Psychology National Cheng Kung University Tainan Taiwan Graduate Institute of Mind Brain and Consciousness Taipei Medical University Taipei Taiwan Graduate Institute of Health and Biotechnology Law Taipei Medical University Taipei City Taiwan

Introduction: Pulse harmonic analysis is a quantitative and objective methodology within traditional Chinese medicine (TCM) used to evaluate pulse characteristics. However, interpreting pulse wave data is challenging due to its inherent complexity. This study aims to provide a comprehensive review and comparison of existing human pulse wave harmonic analysis methods to elucidate their patterns and characteristics. Methods: A systematic review of clinical research reports published from 1990 to 2021 was conducted, focusing on variations in harmonic characteristics across different medical conditions and physiological states. Keyword searches included terms related to analysis methods (e.g., “Pulse Spectrum,” "harmonic analysis," “harmonic index”) and measured indicators (e.g., “vascular response,” "PPG," “Photoplethysmography,” "aortic," “arterial,” "blood pressure"). Supplementary research using PubMed's Mesh terms specifically targeted “Pulse wave analysis” within the methods and statistical analysis domain. Articles were filtered based on predefined criteria, including human participants and research related to pulse pressure or vascular volume changes. Conference papers, animal studies, and irrelevant research were excluded, with literature evaluation scales selected based on the retrieved research reports. Results: Initially, 6487 research reports were identified, and after screening, 50 reports were included in the review. The analysis revealed that low-frequency harmonics increase following vigorous activity or sympathetic excitation but decrease during rest or parasympathetic excitation. Cardiovascular patients exhibited elevated first harmonics associated with the liver meridian, while diabetes patients displayed weakened third harmonics related to the spleen meridian. Liver dysfunction was linked to changes in the first harmonic, and cancer patients showed signs of liver and kidney yin deficiency in the first and second harmonics. These findings underscore

关键词： Diagnostic tools Harmonic characteristics Pulse diagnosis Pulse harmonic analysis Traditional Chinese medicine

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Sample Complexity of Kernel-Based Q-Learning

arXiv

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arXiv 2023年

作者： Yeh, Sing-Yuan Chang, Fu-Chieh Yueh, Chang-Wei Wu, Pei-Yuan Bernacchia, Alberto Vakili, Sattar MediaTek Research Graduate Program of Data Science National Taiwan University Academia Sinica Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Department of Electrical Engineering National Taiwan University Taiwan

Modern reinforcement learning (RL) often faces an enormous state-action space. Existing analytical results are typically for settings with a small number of state-actions, or simple models such as linearly modeled Q-functions. To derive statistically efficient RL policies handling large state-action spaces, with more general Q-functions, some recent works have considered nonlinear function approximation using kernel ridge regression. In this work, we derive sample complexities for kernel based Q-learning when a generative model exists. We propose a nonparametric Q-learning algorithm which finds an ǫ-optimal policy in an arbitrarily large scale discounted MDP. The sample complexity of the proposed algorithm is order optimal with respect to ǫ and the complexity of the kernel (in terms of its information gain). To the best of our knowledge, this is the first result showing a finite sample complexity under such a general model. © 2023, CC BY.

关键词： Reinforcement learning

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Optimal Planning of Integrating Distributed Generations in Unbalanced Distribution Network by Using Particle Swarm Optimization

Optimal Planning of Integrating Distributed Generations in U...

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International Conf on Electrical and Electronic engineering (ICEEE)

作者： Kitipong Chumwong Suttichai Premrudeepreechacharn Dept. of Electrical Engineering Graduate Program in Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand Provincial Electricity Authority Bangkok Thailand Dept. of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand

ISBN: (数字)9798350362541

ISBN: (纸本)9798350362558

In recent years, Distributed Generation (DG) have been a high penetration rate in the distribution network. Planning the active power of electricity from DG can save energy from grid side and reduce power losses in the unbalanced distribution system by considering the capacity to generate electricity. This research was aimed to appropriately generate the active power of DG for managing the energy on grid side and enable distributed system operators (DSO) can forecast production capabilities, maintain the grid balancing, and ensuring the stability of the distribution system. Particle Swarm Optimization (PSO) algorithm was implemented in MATLAB for optimal active power for each DG using Peer-to-Peer (P2P) communication with DIgSILENT for power flow analysis by shared data via comma-separated values file. Additionally, specifying equality and inequality constraint were applied. The results indicated that the active power of DG who is injected to the grid effect to the total power loss, voltage deviation, and power flow direction. In conclusion, the DSO can use them as the considerate guideline for issuing commands to adjust the increase or decrease in the production capacity of DG within reliability and security of the distributed system.

关键词： Electricity Voltage Production Distribution networks Planning Distributed power generation Peer-to-peer computing Security Reliability Particle swarm optimization

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Control of Three-Level PWM Inverter-Fed Induction Motor Drives

Control of Three-Level PWM Inverter-Fed Induction Motor Driv...

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IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific)

作者： Sutthimat Mueangngoen Neerakorn Jarutus Yuttana Kumsuwan Department of Electrical Engineering Faculty of Engineering Graduate Program in Electrical Engineering Chiang Mai University Chiang Mai Thailand Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand

This paper presents the control of three-level PWM committed to a three-level twelve-switch inverter-fed induction motor drive. The proposed control is totally capable of extracting the maximum DC utilization with the classical continuous and discontinuous PWM. Moreover, in the light of the multi-level inherency, the low switching frequency is attractive to this application to avoid the high power losses, while it can maintain the stability of the operation. Regardless of the single or double carrier waves, optimized switching states associated with the proposed logical operation part, which is responsible for obtaining the multi-level characteristic of the inverter, are also proposed. Importantly, through the MATLAB/Simulink program, the steady-state and dynamic response of the high-performance drive with the classically indirect vector control are definitely investigated to confirm the effectiveness of the proposed control strategy.

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An Investigation of Heuristic Control Strategies for Multi-Electrolyzer Wind-Hydrogen Systems Considering Degradation

An Investigation of Heuristic Control Strategies for Multi-E...

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2023 IEEE Conference on Control Technology and Applications, CCTA 2023

作者： Tully, Zachary Starke, Genevieve Johnson, Kathryn King, Jennifer Colorado School of Mines Advanced Energy Systems Graduate Program GoldenCO80401 United States National Renewable Energy Laboratory GoldenCO80401 United States Colorado School of Mines Electrical Engineering Department GoldenCO80401 United States

ISBN: (纸本)9798350335446

With the growing demand for renewable-energy-powered hydrogen generation and the corresponding increase in plant capacity, individually controlling many electrolyzer stacks will be critical for increasing the plant's lifetime and efficiency. This paper introduces a rule-based controller framework targeting electrolyzer degradation to explore the opportunity space in multi-stack hydrogen plant control. A novel control-oriented degradation model is also presented in this work, which quantifies the impact of steady power input, fluctuating power input, and the number of startup/shutdown cycles on electrolyzer degradation. Using a wind power input signal, 13 controller configurations are tested on 5 MW hydrogen plants consisting of 2, 5, 10, and 25 stacks. These configurations are evaluated on their capability to mitigate electrolyzer degradation and efficiently produce hydrogen from the time-varying input power. The results show that multi-stack control for degradation can extend the plant's lifetime by more than a factor of 3 with minimal impact on instantaneous hydrogen production. © 2023 IEEE.

关键词： Controllers

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AutoTemplate: enhancing chemical reaction datasets for machine learning applications in organic chemistry

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Journal of Cheminformatics 2024年第1期16卷 74页

作者： Chen, Lung-Yi Li, Yi-Pei Department of Chemical Engineering National Taiwan University Taiwan International Graduate Program on Sustainable Chemical Science and Technology (TIGP-SCST)

Abstract: This paper presents AutoTemplate, an innovative data preprocessing protocol, addressing the crucial need for high-quality chemical reaction datasets in the realm of machine learning applications in organic chemistry. Recent advances in artificial intelligence have expanded the application of machine learning in chemistry, particularly in yield prediction, retrosynthesis, and reaction condition prediction. However, the effectiveness of these models hinges on the integrity of chemical reaction datasets, which are often plagued by inconsistencies like missing reactants, incorrect atom mappings, and outright erroneous reactions. AutoTemplate introduces a two-stage approach to refine these datasets. The first stage involves extracting meaningful reaction transformation rules and formulating generic reaction templates using a simplified SMARTS representation. This simplification broadens the applicability of templates across various chemical reactions. The second stage is template-guided reaction curation, where these templates are systematically applied to validate and correct the reaction data. This process effectively amends missing reactant information, rectifies atom-mapping errors, and eliminates incorrect data entries. A standout feature of AutoTemplate is its capability to concurrently identify and correct false chemical reactions. It operates on the premise that most reactions in datasets are accurate, using these as templates to guide the correction of flawed entries. The protocol demonstrates its efficacy across a range of chemical reactions, significantly enhancing dataset quality. This advancement provides a more robust foundation for developing reliable machine learning models in chemistry, thereby improving the accuracy of forward and retrosynthetic predictions. AutoTemplate marks a significant progression in the preprocessing of chemical reaction datasets, bridging a vital gap and facilitating more precise and efficient machine learning applicati

关键词： Atom-to-atom mapping Data preprocessing Reaction data curation Reaction template

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Creating Mathematical Models to Help Formulate Company Strategies for Knowledge Management System Implementation

Creating Mathematical Models to Help Formulate Company Strat...

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International Conference on Information Management and Technology (ICIMTech)

作者： Wahyu Sardjono Widhilaga Gia Perdana Dewi Sagita Pranata Information Systems Management Department BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Post Graduate Program of Management Science State University of Jakarta Jakarta Indonesia Department of Informatics Cyber Security Studi Program Faculty of Natural Mathematical & Engineering Sciences King's College London Strands West Minster UK

ISBN: (数字)9798350390025

ISBN: (纸本)9798350390032

This research aims to build a mathematical model to formulate the problems of implementing knowledge management systems in companies that often face obstacles in achieving the desired objectives and goals. With increasing competition in the business sector, organizations or organizations realize the importance of utilizing the knowledge assets that reside in each individual and organization. If this knowledge can be managed optimally, it can become a competitive advantage for the company due to the emergence of innovative ideas by the concepts of knowledge management theory. By implementing optimal knowledge management (KM), companies can design innovative solutions to improve business operations and increase overall revenue. The factor analysis method will be used to find the determining factors for the success of the implementation of knowledge management systems (KMS) and the regression analysis method will also be used to form a mathematical model of several new factors which are formed as independent variables with the current level of community understanding of KMS as the dependent variable. The research results provide insight into strategies to improve success factors to successfully facilitate KMS implementation. This study contributes to existing knowledge management by providing insight into dynamics that go beyond the technical aspects of KMS, ultimately developing strategies for more effective and efficient utilization of knowledge and organizational growth and supporting competitive advantage for companies.

关键词： Performance evaluation Knowledge acquisition Collaboration Companies Knowledge management Mathematical models Regression analysis Information management Problem-solving System implementation

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On-Board Integrated Charger Based on Open-End Winding AC Machine

On-Board Integrated Charger Based on Open-End Winding AC Mac...

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IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific)

作者： Thidarat Thanakam Neerakorn Jarutus Yuttana Kumsuwan Department of Electrical Engineering Faculty of Engineering Graduate Program in Electrical Engineering Chiang Mai University Chiang Mai Thailand Department of Electrical Engineering Faculty of Engineering Chiang Mai University Chiang Mai Thailand

This paper presents an on-board integrated charger for electric vehicles (EVs) based on an open-end winding AC machine. To reduce weight, volume, and costs, including additional space area in EVs, the main component of the traction system is utilized as a part of the charger system, i.e., the wound rotor open-end winding AC machine fed by a dual converter with a single battery source. In charging operation, the rotor winding side of the AC machine is at standstill and reconfigured through magnetic contactors to interface with the three-phase utility grid, whereas the stator winding side is still connected to the converters. It performs as a transformer isolated by itself. On the other hand, the rotor windings are shorted together for the driving operation. Besides, the charger system assists the stability of the utility grid by consuming constant power, absorbing maximum power rated at 22 kW. To enhance excellent control, the modulation strategy of the dual converter is determined by means of different phase angles of 120° As a result, the differential-mode voltage problem is suppressed. The simulation results are validated to confirm the performance of the proposed system.

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