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The Journal of Machine Learning Research 2024年第1期25卷 2557-2625页

作者： Chanwoo Park Ernest K. Ryu Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Massachusetts Department of Mathematical Sciences Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Korea

In this work, we present a novel algorithm design methodology that finds the optimal algorithm as a function of inequalities. Specifically, we restrict convergence analyses of algorithms to use a prespecified subset of inequalities, rather than utilizing all true inequalities, and find the optimal algorithm subject to this restriction. This methodology allows us to design algorithms with certain desired characteristics. As concrete demonstrations of this methodology, we find new state-of-the-art accelerated first-order gradient methods using randomized coordinate updates and backtracking line searches.

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Influence of Graphene Dispersion in P3HT-Based Thin Film Organic Field Effect Transistors

Influence of Graphene Dispersion in P3HT-Based Thin Film Org...

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2022 IEEE International Conference on Emerging Electronics, ICEE 2022

作者： Malik, Ankit Nath, Bidisha Ramamurthy, Praveen C. Panchal, Ashutosh Shrivastava, Mayank Indian Institute of Science Department of Materials Engineering Bengaluru India Indian Institute of Science Interdisciplinary Center for Energy Research Bengaluru India Indian Institute of Science Department of Electronics Systems Engineering Bengaluru India

ISBN: (纸本)9781665491853

P3HT has been an important candidate in the domain of organic field-effect transistors. The impact of instilling graphene in P3HT for enhanced mobility of the combined system to utilize the best of both need not occur. This work demonstrates the impact of graphene in P3HT (g-P3HT) based thin film OFET. There is a drop in mobility with a low concentration of graphene in P3HT until a sufficient amount of quantity is infused into the P3HT system, beyond which the mobility starts increasing. The lowest mobility in the presence of graphene has been found to be 2.24 x 10E-4 compared to 2.34 x 10E-4 of pristine P3HT. © 2022 IEEE.

关键词： Graphene

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The Centrifugal Nuclear Thermal Rocket: Foundations, Challenges, and Progress

The Centrifugal Nuclear Thermal Rocket: Foundations, Challen...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Thomas, Dale Houts, Michael Wang, Dean Hollingsworth, Keith Frederick, Robert Cassibry, Jason Department of Industrial & Systems Engineering and Engineering Management The University of Alabama in Huntsville HuntsvilleAL35899 United States Space Nuclear Propulsion Program Office NASA Marshall Space Flight Center HuntsvilleAL35812 United States Department of Mechanical & Aerospace Engineering The Ohio State University ColumbusOH43210 United States Department of Mechanical & Aerospace Engineering and Interim Dean of the Honors College The University of Alabama in Huntsville HuntsvilleAL35899 United States Department of Mechanical & Aerospace Engineering Propulsion Research Center The University of Alabama in Huntsville HuntsvilleAL35899 United States Department of Mechanical & Aerospace Engineering The University of Alabama in Huntsville HuntsvilleAL35899 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

The Centrifugal Nuclear Thermal Rocket (CNTR) is a Nuclear Thermal Propulsion (NTP) concept designed to heat propellant directly by the reactor fuel. The primary difference between the CNTR concept and traditional NTP systems is that rather than using traditional solid fuel elements, the CNTR uses liquid fuel with the liquid contained in rotating cylinders by centrifugal force. If the concept can be successfully realized, the CNTR would have a high specific impulse (up to 1800 s) at high thrust, which may enable (i) viable near-term human Mars exploration by reducing round-trip times to 420 days and (ii) direct injection orbits for scientific rendezvous missions to the Solar System outer planets and Kuiper Belt objects. Research is presently underway to determine resolutions for the significant engineering challenges that the CNTR concept presents. These challenges, the study plans to address them, and progress have been described previously;this paper provides an update on progress to date for the overall research effort, including strategies and key results on revision of a reference configuration, definition of key parameters which allows integration of the results of various analyses, and reviews strategies to mitigate the problem of Uranium vapor saturating the propellant exhaust and significantly impacting the CNTR’s specific impulse. Analyses and experiments, both underway and planned, to update estimates of engine key performance parameters including specific impulse, thrust and thrust to weight ratio along with the identification of selected design margins within the engine itself are described – all toward the goal of enabling plans for a laboratory demonstration of a single Centrifugal Fuel Element. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Rockets

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A Planning Model for Distributed Resources and Hydrogen System Considering Network’s Enhancement 8

A Planning Model for Distributed Resources and Hydrogen Syst...

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8th IEEE International Energy Conference, ENERGYCON 2024

作者： Al-Bukhaytan, Adnan S. Asif, Muhammad Electrical Engineering Department King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia Architectural Engineering and Construction Management King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia Interdisciplinary Research Center for Renewable Energy and Power Systems King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia

ISBN: (纸本)9798350382150

This research develops a comprehensive planning model that integrates various distributed energy resources (DERs) to supply the load in a distribution network (DN) at optimal minimum costs. The DERs include renewable energy resources (RESs) such as photovoltaic systems (PV) and wind turbines (WT), thermal generators (TG), and battery energy storage systems (BESS). Moreover, hydrogen systems comprising components such as electrolyzers (ED), fuel cells (FC), and hydrogen storage (HS) are considered. Additionally, the DN is assumed to be grid-connected, allowing the distribution system operator (DSO) to buy the required electrical energy from the grid at hourly market prices. Moreover, the DN enhancement is also considered an option for the DSO. The main objective is to develop an optimization model that determines the optimal sizing and location of the DERs along with the selected lines to be upgraded, aiming to meet the load at the optimal minimum cost while maintaining DN constraints. The proposed model has been tested on a modified IEEE-38 bus radial DN. Various case studies and sensitivity analyses were implemented to evaluate the effectiveness of the proposed model. ©2024 IEEE.

关键词： Electric power distribution

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Preliminary Plan for Data Collection on Stakeholder Information Interdependence in Area-Business Continuity Management: A Case Study of Flood Management in Thai Industrial Zones 23

Preliminary Plan for Data Collection on Stakeholder Informat...

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23rd International Symposium on Communications and Information Technologies, ISCIT 2024

作者： Arayachookiat, Penpitcha Saengtabtim, Kumpol Kodaka, Akira Leelawat, Natt Tang, Jing Watanabe, Kenji Risk and Disaster Management Program Graduate School Chulalongkorn University Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Industrial Engineering Bangkok Thailand Chulalongkorn University Disaster and Risk Management Information Systems Research Unit Bangkok Thailand Graduate School of System Design and Management Keio University Kanagawa Japan International School of Engineering Chulalongkorn University Faculty of Engineering Bangkok Thailand Graduate School of Social Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (纸本)9798350353952

The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity Management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness. © 2024 IEEE.

关键词： Area-Business Continuity Management Flood Index of Item-Objective Congruence Information Interdependence

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CFD SIMULATIONS FOR TRAJECTORY PREDICTION OF AN UNDERWATER GLIDER UNDER THE INFLUENCE OF OCEAN CURRENTS

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Journal of Taiwan Society of Naval Architects and Marine Engineers 2023年第3期42卷 129-137页

作者： Chen, H.-C. Liu, T.-L. Pan, K.-C. Master Program of Naval Architecture and Ocean Engineering CCIT National Defense University Taiwan Department of Power Vehicle and Systems Engineering CCIT National Defense University Taiwan

The Autonomous Underwater Glider (AUG) is equipped with a self-adjusting buoyancy engine, allowing it to modify its buoyancy and center of gravity. Through this capability, the AUG can control its motion and achieve both ascending and descending movements. The theoretical mechanism employed by the AUG for adjusting its depth is based on this motion control. However, as an energy-efficient underwater vehicle, the AUG primarily relies on ocean currents for propulsion, which significantly impacts its trajectory in terms of direction and speed. Therefore, trajectory planning plays an indispensable role in the AUG's mission of collecting oceanographic data, highlighting its critical importance. To address this issue, this research aims to apply Computational Fluid Dynamics (CFD) numerical simulations to predict the glider's trajectory under the influence of ocean currents. This analysis will help construct an appropriate operational mode for the underwater glider in various oceanic environments. Regarding the application of CFD to predict the underwater glider's trajectory influenced by ocean currents, the preliminary flow field simulation analysis and feasibility study have been completed. From the simulation results, it is evident that variations in ocean current velocity will have a substantial impact on the glider's initial motion attitude, horizontal speed, as well as the distance covered during each diving and ascending phase. The research findings are expected to significantly contribute to the design and development of a new domestic underwater glider. © 2023 Taiwan Society of Naval Architects and Marine Engineers. All rights reserved.

关键词： Ocean currents

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Metaheuristic Approach to Artificial Neural Network Optimization

Metaheuristic Approach to Artificial Neural Network Optimiza...

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International Conference on Social Networks Analysis, Management and Security (SNAMS)

作者： Alhassan M. Aldabbagh Mujahid N. Syed Industrial and Systems Engineering Department KFUPM Dhahran Saudi Arabia Industrial and Systems Engineering Department Interdisciplinary Research Center for Intellegent Secure Systems KFUPM Dhahran Saudi Arabia

The performance of Artificial Neural Networks (ANNs) depends on the tuning quality of the parameters, such as weights, learning rate, hyperparameters, number of layers and number of neurons. Typical tuning approaches include gradient descent based methods, which are applicable for smooth functions and perform at their best for convex problems. However, ANNs are non-convex and they may benefit from non-smooth functions. Thus, finding new innovative techniques to overcome these limitations is a priority for researchers in the field. Metaheuristic (MH) algorithms can be an alternate option to estimate the optimal parameters of ANNs. Since most MH algorithms have a high capability in exploration or exploitation of non-convex problems, developing customized MH algorithms will be a fruitful area for parameter search of ANNs. In this work, our focus is on developing a Variable Neighborhood Search (VNS) approach that overcomes the limitations of conventional methods in the parameter search of ANNs.

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Muon-induced collisional flavor instability in core-collapse supernova

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Physical Review D 2024年第4期110卷 043039页

作者： Jiabao Liu Hiroki Nagakura Ryuichiro Akaho Akira Ito Masamichi Zaizen Shun Furusawa Shoichi Yamada Department of Physics and Applied Physics School of Advanced Science & Engineering Division of Science Faculty of Science and Engineering College of Science and Engineering Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS) RIKEN Wako Saitama 351-0198 Japan Department of Physics School of Advanced Science & Engineering Research Institute for Science and Engineering

Neutrinos are known to undergo flavor conversion among their three flavors. In the theoretical modeling of core-collapse supernova, there has been a great deal of attention to recent discoveries of a new type of neutrino flavor conversions, namely collisional flavor instability (CFI), in which the instability is induced by the flavor-dependent decoherence due to the disparity of neutrino-matter interactions among flavors. In this paper, we study how the appearance of on-shell muons and associated neutrino-matter interactions can impact CFIs based on linear stability analysis of flavor conversions. Some striking results emerge from the present study. First, we analytically show that breaking beta and pair equilibrium is a necessary condition to trigger CFIs. This also indicates that CFIs with on-shell muons could appear in eτ and μτ neutrino mixing sectors in very high-density region (≳1013 g/cm3), exhibiting a possibility of large impacts of CFIs on core-collapse supernova. Second, resonancelike CFIs, having a much higher growth rate than normal CFIs, can be triggered by muons. The resonance point of CFIs is different between eτ and μτ sectors; the former (latter) occurs at μe(μ)=μn−μp, where μi denotes the chemical potential of i constitute (n and p represent neutrons and protons, respectively). Our result suggests that the nonlinear evolution of CFI with on-shell muons would induce flavor conversions with the complex interplay among all three different neutrino-mixing sectors.

关键词： Neutrino mixing Neutrino oscillations Novae & supernovae Neutrinos

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Detection of Alzheimer's Disease and Frontotemporal Dementia: An Explainable Machine Learning Approach Using EEG Signals

Detection of Alzheimer's Disease and Frontotemporal Dementia...

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International Winter Workshop on Brain-Computer Interface (BCI)

作者： Hwa-Yeon Lee Min-Kyung Jung Choel-Hui Lee Hakseung Kim Dong-Joo Kim Department of Brain and Cognitive Engineering Interdisciplinary Program in Precision Public Health Korea University Seoul South Korea Department of Brain and Cognitive Engineering Korea University Seoul South Korea

ISBN: (数字)9798331521929

ISBN: (纸本)9798331521936

Alzheimer's disease and frontotemporal dementia are among the most prevalent neurodegenerative diseases worldwide. With the absence of definitive treatments, early detection and precise diagnosis remain crucial for alleviating patient suffering and reducing healthcare costs. This study aimed to differentiate Alzheimer's disease, frontotemporal dementia and normal cognition using electroencephalography biomarkers. Significant power spectral density and functional connectivity features were identified via one-way analysis of variance and Scheffe's post-hoc test. A three-class classification was performed by a support vector machine classifier and explainable artificial intelligence technique was employed to investigate feature importance. This classifier achieved an average accuracy of 84.09%, and linear shapley additive explanation model identified T5-Fpl connectivity in alpha band as the most important feature, consistent with findings from previous studies. Further clinical research and brain network analysis using advanced deep learning models could enhance our understanding of the cognitive functions and neural mechanisms underlying these dementias.

关键词： Support vector machines Deep learning Costs Network analyzers Medical services Brain modeling Electroencephalography Cognition Brain-computer interfaces Alzheimer's disease

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Explainable Rip Current Detection and Visualization with XAI EigenCAM 26

Explainable Rip Current Detection and Visualization with XAI...

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26th International Conference on Advanced Communications Technology, ICACT 2024

作者： Choi, Juno Rajendran, Muralidharan Cheol Suh, Yong Pukyong National University Ur Interdisciplinary Program of Hydrography Busan48513 Korea Republic of GreenBlue Inc. Research and Development Team Busan48934 Korea Republic of Pukyong National University Department of Civil Engineering Busan48513 Korea Republic of

ISBN: (纸本)9791188428120

Rip currents have long posed a serious threat to beachgoers and swimmers. Despite numerous preventive measures throughout the period, the fatality rate [1] underscores the need for a robust rip current detection system. Recently deep learning models have shown promising results in rip current detection, outperforming traditional methods. However, these models still exhibit some accuracy limitations due to insufficient data distribution. To address this challenge, we incorporate a novel largest dataset [2] comprising over 110,215 Korean coastline images. Through the comparative study of the state-of-the-art models, we aim to analyze the detection accuracy of each model and gain a deeper understanding of their intensity over rip current detection. In comparison to the other rip current datasets, the evaluation results on our proposed dataset demonstrate a remarkable elevation in accuracy, reaching 79.4 mAP. Further, we employ the EigenCAM (Eigen Class Activation Maps) to interpret the intense regions of the rip currents and to gain a deeper comprehension of rip current explainability. This comprehensive analysis marks a significant step toward improving rip current safety and understanding. © 2024 Global IT Research Institute - GIRI.

关键词： Computer vision

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