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Defective Sic Nanotube Based Single-Atom Catalysts for Electrocatalytic Nitrogen Fixation with Curvature Effect

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SSRN

SSRN 2023年

作者： Wang, Zhiwei Gao, Shuaishuai Liu, Xiaojing Chen, Xin Zhang, Xintao Sa, Rongjian Li, Qiaohong Sun, Chenghua Ma, Zuju School of Environmental and Materials Engineering Yantai University Yantai264005 China School of Computer and Control Engineering Yantai University Yantai264005 China College of Materials and Chemical Engineering Minjiang University Fuzhou350108 China State Key Laboratory of Structural Chemistry Fujian Institute of Research the Structure of Matter Chinese Academy of Sciences Fuzhou350002 China Department of Chemistry and Biotechnology Faculty of Science Engineering & Technology Swinburne University of Technology HawthornVIC3122 Australia

The production of fertilizers, explosives, and various other chemicals relies heavily on ammonia (NH3). Electrochemical reduction of nitrogen to ammonia, also known as the nitrogen reduction reaction (NRR), is a potential alternative to the Haber-Bosch process that can be carried out at ambient conditions. However, many NRR catalysts suffer from low selectivity and require a large overpotential to drive the reaction, limiting their practical application. In this study, we used density functional theory (DFT) calculations to investigate the mechanistic aspects of the NRR and the effect of curvature variation on the catalytic activity of silicon carbide nanotubes (SiCNTs) decorated with 3d-5dtransition metal single-atom catalysts. Our results suggest that the Os@SiCNT catalyst exhibits promising activity as an eNRR catalyst with an overpotential of 0.47 V and high selectivity over hydrogen evolution reaction (HER) competition. The electronic "acceptance-donation" interaction between N2 and Os promotes the adsorption and activation of N2 molecules on the catalyst surface. Additionally, our findings demonstrate that as the nanotube diameter decreases, the energy barrier for the NRR reaction decreases as well. However, this decrease in diameter also leads to a weaker capacity for *N2 adsorption, which may ultimately reduce the selectivity of the NRR reaction. These findings offer valuable insights that can aid in the rational design of nanotube-based electrocatalysts for eNRR. © 2023, The Authors. All rights reserved.

关键词： Density functional theory

Automated Leukemia Screening and Sub-types Classification Using Deep Learning

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computer Systems science & engineering 2023年第9期46卷 3541-3558页

作者： Chaudhary Hassan Abbas Gondal Muhammad Irfan Sarmad Shafique Muhammad Salman Bashir Mansoor Ahmed Osama M.Alshehri Hassan H.Almasoudi Samar M.Alqhtani Mohammed M.Jalal Malik A.Altayar Khalaf F.Alsharif Department of Computer Science COMSATS University Islamabad44000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Control Automotive and Robotics LabNational Center of Robotics and Automation(NCRA HEC)MirpurPakistan Mirpur University of Science and Technology(MUST)MirpurPakistan Department of Computer Science Virtual University of PakistanLahore54000Pakistan Department of Clinical Laboratory Sciences College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Medical Laboratory Technology Faculty of Applied Medical SciencesUniversity of TabukTabukSaudi Arabia Department of Clinical Laboratory Sciences College of Applied Medical SciencesTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

Leukemia is a kind of blood cancer that damages the cells in the blood and bone marrow of the human *** produces cancerous blood cells that disturb the human’s immune system and significantly affect bone marrow’s production ability to effectively create different types of blood cells like red blood cells(RBCs)and white blood cells(WBC),and *** can be diagnosed manually by taking a complete blood count test of the patient’s blood,from which medical professionals can investigate the signs of leukemia ***,two other methods,microscopic inspection of blood smears and bone marrow aspiration,are also utilized while examining the patient for ***,all these methods are labor-intensive,slow,inaccurate,and require a lot of human experience and *** authors have proposed automated detection systems for leukemia diagnosis to overcome these *** have deployed digital image processing and machine learning algorithms to classify the cells into normal and blast ***,these systems are more efficient,reliable,and fast than previous manual diagnosing ***,more work is required to classify leukemia-affected cells due to the complex characteristics of blood images and leukemia cells having much intra-class variability and inter-class *** this paper,we have proposed a robust automated system to diagnose leukemia and its *** have classified ALL into its sub-types based on FAB classification,i.e.,L1,L2,and L3 types with better *** have achieved 96.06%accuracy for subtypes classification,which is better when compared with the state-of-the-art methodologies.

关键词： Healthcare cancer detection deep learning convolutional neural network

On the selection of appropriate control system design methodologies

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On the selection of appropriate control system design method...

作者： Van Willigenburg, L.G. De Koning, W.L. Chalabi, Z.S. Tchamitchian, M. Van Straten, G. Systems and Control Group Wageningen University P.O. Box 17 6700 AA Wageningen Netherlands Faculty of Electrical Engineering Delft University of Technology Mathematics and Computer Science Mekelweg 4 2628 CD Delft Netherlands Public and Environmental Health Research Unit London School of Hygiene and Tropical Medicine University of London Keppel Street London WC1E 7HT United Kingdom INRA Bioclimatologie Domaine StPaul Site Agroparc Cedex 9 84914 Avignon France

ISBN: (纸本)008045108X

We will argue in this paper that the nature and magnitude of model uncertainty dictate the appropriateness of the control system design methodology. To obtain these arguments, we will pursue optimality of the control system design. Note this is a philosophical paper, in which we present our arguments in qualitative terms. We will identify the circumstances under which several control system design methodologies are appropriate. The design methodologies that will be considered are (1) optimal control and optimal feedback design, (2) model predictive control (receding horizon control), (3) active and passive adaptive control and (4) robust control. Robust control strategies are conservative and limit the possible improvements that can be obtained over say classical PID control. However, it will turn out that for certain types of control problems, improvements in performance are indeed limited. Roughly speaking, the area where we may expect (significant) improvement from advanced (optimal) control system design is very much limited by the uncertainty of the systems model. Miracles are not to be expected from advanced control. What can be expected is reflected in an active adaptive optimal control scheme introduced and discussed in this paper. Copyright © 2005 IFAC.

关键词： Robust control

Distributed Event-Triggered Bandit Convex Optimization with Time-Varying Constraints

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arXiv 2024年

作者： Zhang, Kunpeng Yi, Xinlei Wen, Guanghui Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China The Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States The Department of Mathematics Southeast University Nanjing210096 China The Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violation. Existing distributed online algorithms require that each agent broadcasts its decision to its neighbors at each iteration. To better utilize the limited communication resources, we propose a distributed event-triggered online primal-dual algorithm with two-point bandit feedback. Under several classes of appropriately chosen decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. These bounds are comparable to the results achieved by distributed event-triggered online algorithms with full-information feedback. Finally, a numerical example is provided to verify the theoretical results. Copyright © 2024, The Authors. All rights reserved.

关键词： Convex optimization

Shape and Style GAN-based Multispectral Data Augmentation for Crop/Weed Segmentation in Precision Farming

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arXiv 2024年

作者： Fawakherji, Mulham Suriani, Vincenzo Nardi, Daniele Bloisi, Domenico Daniele Department of Built Environment College of Science and Technology North Carolina A&T University 1601 E Market St Greensboro27411 United States Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Via Ariosto 25 Roma00185 Italy Faculty of Political Science and Sociopsychological Dynamics UNINT University Via Cristoforo Colombo 200 Roma00147 Italy

The use of deep learning methods for precision farming is gaining increasing interest. However, collecting training data in this application field is particularly challenging and costly due to the need of acquiring information during the different growing stages of the cultivation of interest. In this paper, we present a method for data augmentation that uses two GANs to create artificial images to augment the training data. To obtain a higher image quality, instead of re-creating the entire scene, we take original images and replace only the patches containing objects of interest with artificial ones containing new objects with different shapes and styles. In doing this, we take into account both the foreground (i.e., crop samples) and the background (i.e., the soil) of the patches. Quantitative experiments, conducted on publicly available datasets, demonstrate the effectiveness of the proposed approach. The source code and data discussed in this work are available as open source. © 2024, CC BY-NC-ND.

关键词： Crops

Multi-model least squares-based recomputation framework for large data analysis

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arXiv 2021年

作者： Zhang, Wandong Wu, Q.M. Jonathan Yang, Yimin Zhao, W.G. Will Wang, TianLei Zhang, Hui Department of Electrical and Computer Engineering University of Windsor Windsor Canada Department of Computer Science Lakehead University Thunder Bay Canada Vector Institute for Artificial Intelligence Toronto Canada Faculty of Business Administration Lakehead University Canada Artificial Intelligence Group CEGEP de Ste Foy Canada Institute of Information and Control Hangzhou Dianzi University Hangzhou China School of Robotics Hunan University Changsha China

Most multilayer least squares (LS)-based neural networks, such as deep random vector functional link (RVFL), are structured with two separate stages: unsupervised feature encoding and supervised pattern classification. Once the unsupervised learning is finished, the latent encoding would be fixed without supervised fine-tuning. However, in complex tasks such as handling the ImageNet dataset, there are often many more clues that can be directly encoded, while the unsupervised learning, by definition, cannot know exactly what is useful for a certain task. There is a need to retrain the latent space representations in the supervised classification stage to learn some clues that unsupervised learning has not yet learned. In particular, the error matrix from the output layer is pulled back to each hidden layer, and the parameters of the hidden layer are recalculated with Moore-Penrose (MP) inverse for more generalized representations. In this paper, a recomputation-based multilayer network using MP inverse (RML-MP) is developed. A sparse RML-MP (SRML-MP) model to boost the performance of RML-MP is then proposed. The experimental results with varying training samples (from 3 K to 1.8 M) show that the proposed models provide better generalization performance than most representation learning algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal encoding

Decentralized Nonconvex Robust Optimization over Unsafe Multiagent Systems: System Modeling, Utility, Resilience, and Privacy Analysis

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arXiv 2024年

作者： Hu, Jinhui Chen, Guo Li, Huaqing Cheng, Huqiang Guo, Xiaoyu Huang, Tingwen School of Automation Central South University Changsha410083 China Department of Biomedical Engineering City University of Hong Kong Kowloon Hong Kong School of Electrical Engineering and Telecommunications University of New South Wales SydneyNSW2052 Australia Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China Key Laboratory of Dependable Services Computing in Cyber Physical Society Ministry of Education College of Computer Science Chongqing University Chongqing400044 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen518055 China

Privacy leakage and Byzantine failures are two adverse factors to the intelligent decision-making process of multiagent systems (MASs). Considering an unsafe MAS with these two issues, this paper targets the resolution of a class of nonconvex optimization problems under the Polyak-Lojasiewicz (P-L) condition. To address this problem, we first identify and construct the unsafe MAS model. Under this kind of unfavorable MASs, we mask the local gradients with Gaussian noises and adopt a resilient aggregation method self-centered clipping (SCC) to design a differentially private (DP) decentralized Byzantine-resilient algorithm, namely DP-SCC-PL, which simultaneously achieves differential privacy and Byzantine resilience. The convergence analysis of DP-SCC-PL is challenging since the convergence error can be contributed jointly by privacy-preserving and Byzantine-resilient mechanisms, as well as the nonconvex relaxation, which is addressed via seeking the contraction relationships among the disagreement measure of reliable agents before and after SCC aggregation, together with the optimal gap. Theoretical results reveal that DP-SCC-PL achieves consensus among all reliable agents and sublinear (inexact) convergence with well-designed step-sizes. It has also been proved that if there are no privacy issues and Byzantine agents, then the asymptotic exact convergence can be recovered. Numerical experiments verify the utility, resilience, and differential privacy of DP-SCC-PL by tackling a nonconvex optimization problem satisfying the P-L condition under various Byzantine attacks. Copyright © 2024, The Authors. All rights reserved.

关键词： Differential privacy

Energy-Saving Practice of Variable Frequency Drive Technology in Data Center HVAC System

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Energy-Saving Practice of Variable Frequency Drive Technolog...

International Conference on Power and Energy Technology (ICPET)

作者： Chuanxian Ai Jinpeng Yang Rui Chen Faculty of Information Engineering and Automation Kunming University of Science and Technology Yunnan Branch The National Computer Network Emergency Response Technical Team/Coordination Center of China Kunming China Power Dispatch Control Center Guizhou Power Grid Co. Ltd. China Southern Power Grid Co. Ltd Guiyang China

The variable-frequency drive technology (VFD) can modify the motor speed or torque by varying the frequency and voltage of the AC motor input power according to the load demand as a way to save energy. To analyse the energy saving effect of variable-frequency drive technology applied to data centre heating, ventilation, and air conditioning (HVAC) systems, this paper applies VFD technology to data centre fluorine pump-compressor composite air conditioning systems, implements monitoring and analysis of the operational energy efficiency of this system before and after retrofit, and combines the actual application of this technology. The findings indicate that the VFD technology can substantially reduce the number of compressor starts and stops, reduce the compressor start-up inrush current, and improve the power system’s stability. Furthermore, utilising this technology, the HVAC system can effectively synchronise with the load and fluctuations in outdoor temperature and humidity, resulting in accurate temperature regulation and optimal utilisation of outdoor cooling resources. This approach can lead to significant energy conservation of up to 42.95% when compared to extreme hot and cold weather conditions. The findings of the study indicate that the utilisation of VFD technology exhibits commendable adaptability and yields favourable outcomes in regions with varying temperature ranges. The minimum PUE value recorded was 1.228.

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Learning Dictionaries from Physical-Based Interpolation for Water Network Leak Localization

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arXiv 2023年

作者： Irofti, Paul Romero-Ben, Luis Stoican, Florin Puig, Vicenç Department of Computer Science Faculty of Mathematics and Computer Science University of Bucharest 010014 Romania The Institute for Logic and Data Science Popa Tatu 18 Bucharest010805 Romania The Institut de Robòtica i Informàtica Industrial CSIC-UPC Llorens i Artigas 4-6 Barcelona08028 Spain The Universitat Politècnica de Catalunya Campus de Terrassa Gaia Building Rambla Sant Nebridi 22 Terrassa Barcelona08222 Spain The Deptartment of Automation Control and Systems Engineering Politehnica University of Bucharest 060042 Romania

This article presents a leak localization methodology based on state estimation and learning. The first is handled by an interpolation scheme, whereas dictionary learning is considered for the second stage. The novel proposed interpolation technique exploits the physics of the interconnections between hydraulic heads of neighboring nodes in water distribution networks. Additionally, residuals are directly interpolated instead of hydraulic head values. The results of applying the proposed method to a well-known case study (Modena) demonstrated the improvements of the new interpolation method with respect to a state-of-the-art approach, both in terms of interpolation error (considering state and residual estimation) and posterior localization. Copyright © 2023, The Authors. All rights reserved.

关键词： Interpolation