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arXiv 2022年

作者： Kristiansen, Kristian Uldall Pedersen, Morten Gram Department of Applied Mathematics and Computer Science Technical University of Denmark Kgs. Lyngby2800 Denmark Department of Information Engineering University of Padova Padova35131 Italy

In this paper, we use geometric singular perturbation theory and blowup, as our main technical tool, to study the mixed-mode oscillations (MMOs) that occur in two coupled FitzHugh-Nagumo units with symmetric and repulsive coupling. In particular, we demonstrate that the MMOs in this model are not due to generic folded singularities, but rather due to singularities at a cusp - not a fold - of the critical manifold. Using blowup, we determine the number of SAOs analytically, showing - as for the folded nodes - that they are determined by the Weber equation and the ratio of eigenvalues. We also show that the model undergoes a (symmetric) saddle-node bifurcation in the desingularized reduced problem, which - although resembling a folded saddle-node (type II) at this level - also occurs on a cusp, and not a fold. We demonstrate that this bifurcation is associated with the emergence of an invariant cylinder, the onset of SAOs, as well as SAOs of increasing amplitude. We relate our findings with numerical computations and find excellent *** Codes 34C15, 34D15, 37E17 Copyright © 2022, The Authors. All rights reserved.

关键词： Bifurcation (mathematics)

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Modelling and Economic Optimal Control for a Laboratory-scale Continuous Stirred Tank Reactor for Single-cell Protein Production

arXiv

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arXiv 2022年

作者： Nielsen, Marcus Krogh Dynesen, Jens Dragheim, Jess Christensen, Ib Jørgensen, Sten Bay Huusom, Jakob Kjøbsted Gernaey, Krist V. Jørgensen, John Bagterp Department of Applied Mathematics and Computer Science Denmark Department of Chemical and Biochemical Engineering the Technical University of Denmark Kgs. Lyngby Denmark Unibio A/S Roskilde Denmark

In this paper, we present a novel kinetic growth model for the micro-organism Methylococcus capsulatus (Bath) that couples growth and pH. We apply growth kinetics in a model for single-cell protein production in a laboratory-scale continuous stirred tank reactor inspired by a physical laboratory fermentor. The model contains a set of differential algebraic equations describing growth and pH-dynamics in the system. We present a method of simulation that ensures non-negativity in the state and algebraic variables. Additionally, we introduce linear scaling of the algebraic equations and variables for numerical stability in Newton’s method. Finally, we conduct a numerical experiment of economic optimal control for single-cell protein production in the laboratory-scale reactor. The numerical experiment shows non-trivial input profiles for biomass growth and pH tracking. Copyright © 2022, The Authors. All rights reserved.

关键词： Laboratories

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Generative AI Enables Medical Image Segmentation in Ultra Low-Data Regimes

arXiv

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arXiv 2024年

作者： Zhang, Li Jindal, Basu Alaa, Ahmed Weinreb, Robert Wilson, David Segal, Eran Zou, James Xie, Pengtao Department of Electrical and Computer Engineering University of California La Jolla San DiegoCA United States Bakar Computational Health Sciences Institute University of California San Francisco San FranciscoCA United States Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA United States Hamilton Glaucoma Center Shiley Eye Institute Viterbi Family Department of Ophthalmology University of California La Jolla San DiegoCA United States Division of Pulmonary Allergy and Critical Care Medicine Department of Medicine University of Pittsburgh PittsburghPA United States Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot Israel Department of Molecular Cell Biology Weizmann Institute of Science Rehovot Israel Department of Biomedical Data Science Stanford University School of Medicine StanfordCA United States Department of Computer Science Stanford University StanfordCA United States Department of Medicine University of California La Jolla San DiegoCA United States

Semantic segmentation of medical images is pivotal in applications like disease diagnosis and treatment planning. While deep learning has excelled in automating this task, a major hurdle is the need for numerous annotated segmentation masks, which are resource-intensive to produce due to the required expertise and time. This scenario often leads to ultra low-data regimes, where annotated images are extremely limited, posing significant challenges for the generalization of conventional deep learning methods on test images. To address this, we introduce a generative deep learning framework, which uniquely generates high-quality paired segmentation masks and medical images, serving as auxiliary data for training robust models in data-scarce environments. Unlike traditional generative models that treat data generation and segmentation model training as separate processes, our method employs multi-level optimization for end-to-end data generation. This approach allows segmentation performance to directly influence the data generation process, ensuring that the generated data is specifically tailored to enhance the performance of the segmentation model. Our method demonstrated strong generalization performance across 9 diverse medical image segmentation tasks and on 16 datasets, in ultra-low data regimes, spanning various diseases, organs, and imaging modalities. When applied to various segmentation models, it achieved performance improvements of 10-20% (absolute), in both same-domain and out-of-domain scenarios. Notably, it requires 8 to 20 times less training data than existing methods to achieve comparable results. This advancement significantly improves the feasibility and cost-effectiveness of applying deep learning in medical imaging, particularly in scenarios with limited data availability. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Correction to: Optimal Location Identification of Solar PV Systems in Distributed Generators Based on Prediction of Load Flow and Factor Using Rule Based Deep Learning Algorithm (Journal of Electrical engineering & Technology, (2025), 20, 3, (1269-1281), 10.1007/s42835-024-02063-8)

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Journal of Electrical engineering and Technology 2025年 1-1页

作者： Kolanchinathan, V.P. Aswini, K.R.N. Rajendran, Narayanasamy Chinthamani, B. Bhuvana, S. Deepa, S.N. Mohan, S.B. Shanker, N.R. Gayathri, J. Department of Electronics and Communication Engineering Veltech Hightech Dr. Rangarajan Dr. Sagunthula Engineering College Avadi Chennai India Department of Electronics and Communication Chinmaya Vishwa Vidyapeeth Kerala Ernakulam India College of Computing and Information Sciences University of Technology and Applied Sciences Nizwa United Arab Emirates Department of Electronics and Instrumentation Engineering Easwari Engineering College Ramapuram Chennai India Dr. MGR Educational and Research Institute Chennai India Department of Electrical and Electronics Engineering NIT Calicut Kerala Kozhikode India Department of Electronics and Communication Engineering S.A. Engineering College Chennai India Department of Computer Science and Engineering Alim Muhammed Salegh College of Engineering Chennai India Department of Electronics and Communication Engineering Veltech Multitech DR.RR & SR Engineering College Avadi Chennai India

In this article the affiliation details for Author J. Gayathri were incorrectly given as both affiliations 1 and 9 but should have been only affiliation 9 " department of Electronics and Communication engineering, Veltech Multitech ***& SR engineering College, Avadi, Chennai, India". The original article has been corrected. © The Author(s) under exclusive licence to The Korean Institute of Electrical Engineers 2025.

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Matching Game for Optimized Association in Quantum Communication Networks

Matching Game for Optimized Association in Quantum Communica...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Mahdi Chehimi Bernd Simon Walid Saad Anja Klein Don Towsley Mérouane Debbah Bradley Department of Electrical and Computer Engineering Wireless@VT Virginia Tech Arlington VA USA Communication Engineering Lab Technische Universität Darmstadt Darmstadt Germany Cyber Security Systems and Applied AI Research Center Lebanese American University Lebanon College of Information and Computer Sciences University of Massachusetts Amherst Amherst MA USA Electrical Engineering and Computer Science Department Khalifa University of Science and Technology Abu Dhabi UAE

Enabling quantum switches (QSs) to serve requests submitted by quantum end nodes in quantum communication networks (QCNs) is a challenging problem due to the heterogeneous fidelity requirements of the submitted requests and the limited resources of the QCN. Effectively determining which requests are served by a given QS is fundamental to foster developments in practical QCN applications, like quantum data centers. However, the state-of-the-art on QS operation has overlooked this association problem, and it mainly focused on QCNs with a single QS. In this paper, the request-QS association problem in QCNs is formulated as a matching game that captures the limited QCN resources, heterogeneous application-specific fidelity requirements, and scheduling of the different QS operations. To solve this game, a swap-stable request-QS association (RQSA) algorithm is proposed while considering partial QCN information availability. Extensive simulations are conducted to validate the effectiveness of the proposed RQSA algorithm. Simulation results show that the proposed RQSA algorithm achieves a near-optimal (within 5%) performance in terms of the percentage of served requests and overall achieved fidelity, while outperforming benchmark greedy solutions by over 13%. Moreover, the proposed RQSA algorithm is shown to be scalable and maintain its near-optimal performance even when the size of the QCN increases.

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Interferometric Purcell suppression of spontaneous emission in a superconducting qubit

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Physical Review applied 2025年第2期23卷 024068-024068页

作者： Alec Yen Yufeng Ye Kaidong Peng Jennifer Wang Gregory Cunningham Michael Gingras Bethany M. Niedzielski Hannah Stickler Kyle Serniak Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Research Laboratory of Electronics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Harvard John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge Massachusetts 02138 USA MIT Lincoln Laboratory Lexington Massachusetts 02421 USA

In superconducting qubits, suppression of spontaneous emission is essential to achieve fast dispersive measurement and reset without sacrificing qubit lifetime. We show that resonator-mediated decay of the qubit mode to the feedline can be suppressed using destructive interference, where the readout resonator is coupled to the feedline at two points. This “interferometric Purcell filter” does not require dedicated filter components or impedance mismatch in the feedline, making it suitable for applications such as all-pass readout. We design and fabricate a device with the proposed scheme and demonstrate suppression of resonator-mediated decay that exceeds 2 orders of magnitude over a bandwidth of 400MHz for a resonator linewidth of 13.8 MHz.

关键词： Qubits

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Web Server Attack Detection using Machine Learning 1

Web Server Attack Detection using Machine Learning

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1st Annual International Conference on Cyber Warfare and Security, ICCWS 2020

作者： Saleem, Saima Sheeraz, Muhammad Hanif, Muhammad Farooq, Umar Pakistan Institute of Engineering and Applied Sciences Department of Computer and Information Science Islamabad Pakistan

ISBN: (纸本)9781728168401

Today, every single organization is utilizing web applications for extension of its business as a result of the high accessibility of web and simple access. With the expansion of web use, the danger of attacks has increased likewise. An efficient monitoring software which can detect these attacks timely is required. HTML, PHP and Java script are used for websites development and SQL is used for database management extensively. Most common web server attacks include SQL injection, DOS (Denial of Service) and XSS (Cross Site Scripting). Rule based intrusion detection systems work on keywords and patterns and are unable to detect unknown attacks. This paper proposes machine learning based model for intrusion detection using web server logs. This model detects whether a specific log is normal or an attack log and also specifies the type of attack. Web server logs are generated and collected by creating a private network using an Apache WAMP server. © 2020 IEEE.

关键词： Denial-of-service attack

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Applications in Home Improvement Retailer, Koctas

Applications in Home Improvement Retailer, Koctas

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Business Analytics for Technology and Security (ICBATS), International Conference on

作者： Nahia Mourad Hammad Raza Muhamamd Amjad Muhammed Ubaid Ullah Nouh Sabri Elmitwally College of Engineering & IT British University in Dubai Dubai United Arab Emirates Department of Computer Science National College of Business Administration and Economics Lahore Pakistan School of Computer Science NCBA&E Lahore Pakistan Applied Science Research Center Applied Science Private University Amman Jordan Minhaj University Lahore Paksitan School of Computing and Digital Technology Birmingham City University Birmingham B4 7XG UK Department of Computer Science Faculty of Computers and Artifcial Intelligence Cairo University Giza

It sounds like Koçtaş is a leader in the home improvement sector in Turkey, and they are focused on providing the best service and customer experience possible. They are also actively working to accelerate their digital investments and use their vast amount of customer data to innovate in the industry. One way they are using this data is by collecting and analyzing video camera images using AI. This allows them to detect humans and identify which products and shelves are most viewed in their stores. This information can then be used to optimize store layout and product placement for a better customer experience. Another way Koçtaş is innovating is through the implementation of kiosks that use Natural Language Processing (NLP) to interact with customers. These kiosks can understand and respond to questions asked by customers using AI, providing a more personalized and human-like ***, Koçtaş is using Dynamic Creative Optimization to create personalized advertisements for their customers. This method allows them to optimize the content and format of their ads based on the individual preferences and behavior of their customers, leading to more effective ***, Koçtaş is using technology and data to drive innovation and provide a better customer experience in the home improvement industry.

关键词： Industries Technological innovation Layout Cameras Natural language processing Security Artificial intelligence

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Non-Hermitian selective thermal emitter for thermophotovoltaics

Non-Hermitian selective thermal emitter for thermophotovolta...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Ciril S. Prasad Samuel C. Raphaelson Gururaj V. Naik Department of Electrical and Computer Engineering Rice University Houston TX USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA Department of Material Science and NanoEngineering Rice University Houston TX USA

Selective thermal emitters can boost the efficiency of heat-to-electricity conversion in thermophotovoltaic systems only if their spectral selectivity is high. We demonstrate a non-Hermitian metasurface-based selectiv... 详细信息

ISBN: (纸本)9781957171258

关键词： Emissivity Light intensity Optical constants Silicon Temperature Thermal emission

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Multiband highly sensitive metamaterial-based THz absorber for edible oil adulteration sensing

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Optik 2024年 307卷

作者： Anowarul Haque, S.M. Sohayeb Hossain, Md Alqahtani, Abdulrahman Islam, Mohammad Tariqul Moniruzzaman, Md. Samsuzzaman, Md. Dept. of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia Dept. of Electrical and Electronic Engineering Mymensingh Engineering College Bangladesh Department of Biomedical Technology College of Applied Medical Sciences in Al-Kharj Prince Sattam Bin Ab-dulaziz University Al-Kharj11942 Saudi Arabia Department of Medical Equipment Technology College of Applied Medical Science Majmaah University Majmaah City11952 Saudi Arabia Dept. of Electrical and Electronic Engineering College of Engineering and Technology International University of Business Agriculture and Technology Dhaka Uttara1230 Bangladesh Dept. of Computer and Communication Engineering Faculty of Computer Science and Engineering Patuakhali Science and Technology University Bangladesh Faculty of Graduate Studies Daffodil International University Daffodil Smart City Birulia Dhaka Savar1216 Bangladesh

A terahertz (THz) wave technology is very appealing for applications in detection in biomedicine, biological spectroscopy, material characterization, detection, imaging, sensing, and other convenient applications. Metamaterials (MMs) are artificial structures that have structures in a regular periodic arrangement and don't exist in nature. By utilizing a proposed terahertz metamaterial absorber, a broad spectrum of adulterated lubricants can be detected. It is an efficient detection process that enables the development of a THz detection approach by making use of the metamaterial as a sensor. The proposed terahertz absorber is analyzed and optimized using the CST Microwave Studio 2019 software. The article proposed a multiband THz metamaterial absorber with a unit size of 70 µm. According to the demonstrated results, we can achieve five narrow absorption peaks with perfect absorption within the frequency range between (0.2–4.2) Terahertz. Also, the result shows that, the average absorbance of 99.07% at the resonance frequencies of 0.56, 1.42, 2.676, 3.14, and 3.89 THz. The E (electric) and H (magnetic)-field distributions on the resonator at different resonance frequencies were also analyzed as well as. The recommended metamaterial absorber has a good sensing capability at different resonant frequencies, with refractive index sensitivities of 80 GHz/RIU, 240 GHz/RIU, 480 GHz/RIU, 480 GHz/RIU, and 520 GHz/RIU obtained by modifying the refractive index of the sample holder or the analytic layer, respectively. As a result, the proposed detector has a high refractive index sensitivity, high Q-factor, and high FOM, making it suitable for detecting oil adulteration. © 2024 Elsevier GmbH

关键词： Metamaterials

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