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Conference on Lasers and Electro-Optics (CLEO)

作者： Swarnava Sanyal Yoshitomo Okawachi Yun Zhao Bok Young Kim Karl J. McNulty Michal Lipson Alexander L. Gaeta Department of Applied Physics and Applied Mathematics Columbia University New York USA Department of Electrical Engineering Columbia University New York USA

We demonstrate a deterministic and repeatable pathway to access single and multi-free-spectral range states with normal-GVD Kerr combs. A key component to stabilizing the high-power comb states is implementation of a ... 详细信息

ISBN: (纸本)9781957171258

关键词： Coupled resonators Frequency combs Optical resonators Pulse shaping Transmission measurement Wavelength division multiplexers

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SSABA:Search Step Adjustment Based Algorithm

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Computers, Materials & Continua 2022年第6期71卷 4237-4256页

作者： Fatemeh Ahmadi Zeidabadi Ali Dehghani Mohammad Dehghani Zeinab Montazeri Stepán Hubálovsky Pavel Trojovsky Gaurav Dhiman Department of Mathematics and Computer Sciences Sirjan University of TechnologySirjanIran Department of Civil Engineering Islamic Azad UniversityEstahban BranchEstahbanIran Department of Mathematics Faculty of ScienceUniversity of Hradec KrálovéHradec Králové50003Czech Republic Department of Electrical and Electronics Engineering Shiraz University of TechnologyShirazIran Department of Applied Cybernetics Faculty of ScienceUniversity of Hradec KrálovéHradec Králové50003Czech Republic Department of Computer Science Government Bikram College of CommercePatialaPunjabIndia

Finding the suitable solution to optimization problems is a fundamental challenge in various *** algorithms are one of the effective stochastic methods in solving optimization *** this paper,a new stochastic optimization algorithm called Search StepAdjustment Based Algorithm(SSABA)is presented to provide quasi-optimal solutions to various optimization *** the initial iterations of the algorithm,the step index is set to the highest value for a comprehensive search of the search ***,with increasing repetitions in order to focus the search of the algorithm in achieving the optimal solution closer to the global optimal,the step index is reduced to reach the minimum value at the end of the algorithm *** is mathematically modeled and its performance in optimization is evaluated on twenty-three different standard objective functions of unimodal and multimodal *** results of optimization of unimodal functions show that the proposed algorithm SSABA has high exploitation power and the results of optimization of multimodal functions show the appropriate exploration power of the proposed *** addition,the performance of the proposed SSABA is compared with the performance of eight well-known algorithms,including Particle Swarm Optimization(PSO),Genetic Algorithm(GA),Teaching-Learning Based Optimization(TLBO),Gravitational Search Algorithm(GSA),Grey Wolf Optimization(GWO),Whale Optimization Algorithm(WOA),Marine Predators Algorithm(MPA),and Tunicate Swarm Algorithm(TSA).The simulation results show that the proposed SSABA is better and more competitive than the eight compared algorithms with better performance.

关键词： Optimization population-based optimization problem search step optimization algorithm minimization maximization

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Triple-Band Metamaterial Inspired Antenna for Future Terahertz(THz)Applications

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Computers, Materials & Continua 2022年第7期72卷 1071-1087页

作者： Adel Y.I.Ashyap S.Alamri S.H.Dahlan Z.Z.Abidin M.Inam Abbasi Huda A.Majid M.R.Kamarudin Y.A.Al-Gumaei M.Hashim Dahri Center for Applied Electromagnetic(EMCenter) Faculty of Electrical and Electronic EngineeringUniversiti Tun Hussein Onn Malaysia(UTHM)Batu Pahat86400JohorMalaysia Faculty of Engineering Electrical Engineering Dep. Al Baha UniversityAlaqiq65799Al-BahaSaudi Arabia Advanced Telecommunication Research Center(ATRC) Faculty of Electrical and Electronic EngineeringUniversiti Tun Hussein Onn Malaysia(UTHM)Batu Pahat86400JohorMalaysia Faculty of Electrical and Electronic Engineering Technology Universiti Teknikal Malaysia MelakaHang Tua Jaya76100Durian TunggalMelakaMalaysia Department of Mathematics Physicsand Electrical EngineeringNorthumbria UniversityNE18ST Newcastle Upon TyneUK Department of Electronic Engineering Dawood University of Engineering and TechnologyKarachi74800Pakistan

For future healthcare in the terahertz(THz)band,a triple-band microstrip planar antenna integrated with metamaterial(MTM)based on a polyimide substrate is *** frequencies of operation are 500,600,and 880 *** triple-band capability is accomplished by etching metamaterial on the patch without affecting the overall antenna *** of a partial ground plane,a full ground plane is used as a buffer to shield the body from back radiation emitted by the *** overall dimension of the proposed antenna is 484×484μm^(2).The antenna’s performance is investigated based on different crucial factors,and excellent results are *** gain for the frequencies 500,600,880GHz is 6.41,6.77,10.1 dB,respectively while the efficiency for the same frequencies is 90%,95%,96%,*** research has been conducted by mounting the presented antenna on a single phantom layer with varying dielectric *** results show that the design works equally well with and without the phantom model,in contrast to a partially ground antenna,whose performance is influenced by the presence of the phantom *** a result,the presented antenna could be helpful for future healthcare applications in the THz band.

关键词： THz metamaterial triple-band wireless body area networks(WBAN)

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DCNet: Densely Connected Neural Network with Global Context for Abnormalities Prediction in Bronchoscopy Images

DCNet: Densely Connected Neural Network with Global Context ...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Wang, Ying Tie, Yun Liu, Fenghui Qi, Lin Hu, Ziqing Zhengzhou University School of Electrical and Information Engineering Zhengzhou China Zhengzhou University The First Affiliated Hospital of Zhengzhou University Zhengzhou China University of Notre Dame Department of Applied and Computational Mathematics and Statistics Notre Dame United States

ISBN: (纸本)9798350337488

Bronchoscopy plays an important role in the examination of lower respiratory tract diseases. However, the large number of medical images produced by bronchoscopy makes it a time-consuming and labor-intensive task for doctors to analyze. Therefore, developing computer-aided diagnostic algorithms to assist doctors in lung image analysis is of great *** this paper, we propose a novel densely connected convolutional network called DCNet with local and global receptive fields for the automatic prediction of bronchoscopy images. Our experimental results on the clinical bronchoscopy image analysis dataset demonstrate that our proposed method outperforms state-of-the-art algorithms in distinguishing malignant bronchoscopy images, with an accuracy rate of 92.81%. And DCNet achieved 99.31% accuracy on the public data set called Kvasir-Capsule. This model may be a valuable tool to assist medical staff in the analysis of bronchoscopy images. © 2023 IEEE.

关键词： bronchoscopy images prediction deep learning dense connection self-attention

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Photoluminescence and photovoltaic properties of cesium lead bromide nanocrystals with linoleic acid ligand 14

Photoluminescence and photovoltaic properties of cesium lead...

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14th International Symposium on Modern Optics and Its Applications, ISMOA 2023

作者： Rizki Yandri, Valdi Debora, Rima Asma Nurunnizar, Adhita Wulandari, Priastuti Maulani Nursam, Natalita Hidayat, Rahmat Yamashita, Yoshiyuki Photonics and Magnetism Physics Research Group Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Indonesia Research Center of Electronics and Telecommunication National Research and Innovation Agency Bandung Indonesia Tsukuba Japan Department of Applied Chemistry Faculty of Engineering Kyushu University Kyushu Japan Power Electronics Laboratory Electrical Engineering Department Polytechnic State of Padang Indonesia

Cesium lead bromide (CsPbBr3) nanocrystals (NCs) were synthesized using the ligand-assisted reprecipitation (LARP) method, with linoleic acid (LA) and oleylamine (OlAm) as ligands. The crystal structures of the samples depend on the ligand used in the synthesis. Sample-1, with LA-OlAm as the ligand, showed an orthorhombic crystal structure, whereas Sample-2, with OlAm only, showed a tetragonal crystal structure. These samples exhibited slightly different photoluminescence (PL) characteristics, where the PL peak of Sample-1 appeared at 521.4 nm, whereas the PL peak of Sample-2 appeared at 524.1 nm. Sample-1 showed brighter PL than that of Sample-2. These differences are strongly related to their crystal structures and degree of crystallization, which is also evident from the differences in the chemical states of the Br and Pb ions on the NCs surface, as depicted by the X-Ray Photoelectron Spectroscopy (XPS) spectra. In addition, despite exhibiting PL characteristics, these CsPbBr3 NCs also exhibit photovoltaic properties. © Published under licence by IOP Publishing Ltd.

关键词： Bromine compounds

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An Optimal Framework for SDN Based on Deep Neural Network

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Computers, Materials & Continua 2022年第10期73卷 1125-1140页

作者： Abdallah Abdallah Mohamad Khairi Ishak Nor Samsiah Sani Imran Khan Fahad RAlbogamy Hirofumi Amano Samih M.Mostafa Department of Industrial Engineering School of Applied Technical Sciences German Jordanian UniversityAmman35247Jordan School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal14300Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyThe National University of Malaysia(UKM)Bangi43600SelangorMalaysia Department of Electrical Engineering University of Engineering and TechnologyPeshawar814Pakistan Turabah University College Computer Sciences ProgramTaif UniversityTaif21944Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-Mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Software-defined networking(SDN)is a new paradigm that promises to change by breaking vertical integration,decoupling network control logic from the underlying routers and switches,promoting(logical)network control centralization,and introducing network ***,the controller is similarly vulnerable to a“single point of failure”,an attacker can execute a distributed denial of service(DDoS)attack that invalidates the controller and compromises the network security in *** address the problem of DDoS traffic detection in SDN,a novel detection approach based on information entropy and deep neural network(DNN)is *** approach contains a DNN-based DDoS traffic detection module and an information-based entropy initial inspection *** initial inspection module detects the suspicious network traffic by computing the information entropy value of the data packet’s source and destination Internet Protocol(IP)addresses,and then identifies it using the DDoS detection module based on *** assaults were found when suspected irregular traffic was *** reveal that the algorithm recognizes DDoS activity at a rate of more than 99%,with a much better accuracy *** false alarm rate(FAR)is much lower than that of the information entropy-based detection ***,the proposed framework can shorten the detection time and improve the resource utilization efficiency.

关键词： Deep neural network computer networks data security optimization

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How to beat a Bayesian adversary

arXiv

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arXiv 2024年

作者： Ding, Zihan Jin, Kexin Latz, Jonas Liu, Chenguang Department of Electrical and Computer Engineering Princeton University United States Department of Mathematics Princeton University United States Department of Mathematics University of Manchester United Kingdom Delft Institute of Applied Mathematics Technische Universiteit Delft Netherlands

Deep neural networks and other modern machine learning models are often susceptible to adversarial attacks. Indeed, an adversary may often be able to change a model’s prediction through a small, directed perturbation of the model’s input – an issue in safety-critical applications. Adversarially robust machine learning is usually based on a minmax optimisation problem that minimises the machine learning loss under maximisation-based adversarial attacks. In this work, we study adversaries that determine their attack using a Bayesian statistical approach rather than maximisation. The resulting Bayesian adversarial robustness problem is a relaxation of the usual minmax problem. To solve this problem, we propose Abram – a continuous-time particle system that shall approximate the gradient flow corresponding to the underlying learning problem. We show that Abram approximates a McKean-Vlasov process and justify the use of Abram by giving assumptions under which the McKean-Vlasov process finds the minimiser of the Bayesian adversarial robustness problem. We discuss two ways to discretise Abram and show its suitability in benchmark adversarial deep learning *** Codes 90C15, 65C35, 68T07 © 2024, CC BY.

关键词： Deep neural networks

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Topological Machine Learning: Integrating Topological Data Analysis with Machine Learning to Enhance Breast Cancer Classification

Topological Machine Learning: Integrating Topological Data A...

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Sustainable Technology and engineering (i-COSTE), International Conference on

作者： Rabelani Netshifhire Maria Vivien Visaya Department of Electrical and Electronic Engineering Science University of Johannesburg Johannesburg South Africa Department of Mathematics and Applied Mathematics University of Johannesburg and DSI-NRF CoE-MaSS Johannesburg South Africa

ISBN: (数字)9798331517335

ISBN: (纸本)9798331517342

Accurate classification tools are essential for improving patient outcomes in breast cancer diagnosis and treatment. Oncologists face the challenge of interpreting diverse patientspecific datasets such as mammograms, ultrasounds, and biopsy reports. Manual assessment of datasets is time-consuming and error-prone, complicating breast cancer classification. To address these issues, we explore the integration of Topological Data Analysis (TDA) with Machine Learning (ML), known as Topological Machine Learning (TML). TDA provides a systematic framework to uncover topological structures in highdimensional datasets, while ML offers powerful classification tools to analyze complex data. We present a comprehensive overview of TDA and ML, highlighting their individual strengths and the synergistic benefits of their integration. Topological features extracted through TDA are fed into ML models, including K-Nearest Neighbors (KNN), Random Forest (RF), Decision Tree (DT), Gaussian Naive Bayes (GNB), Logistic Regression (LR), and Support Vector Machine (SVM), to improve classification accuracy. Results show significant classification accuracy compared to traditional ML methods.

关键词： Support vector machines Accuracy Data analysis Machine learning algorithms Clustering algorithms Machine learning Nearest neighbor methods Feature extraction Breast cancer Classification algorithms

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Local Sequential MCMC for Data Assimilation with Applications in Geoscience

arXiv

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arXiv 2024年

作者： Ruzayqat, Hamza Knio, Omar Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

This paper presents a new data assimilation (DA) scheme based on a sequential Markov Chain Monte Carlo (SMCMC) DA technique [36] which is provably convergent and has been recently used for filtering, particularly for high-dimensional non-linear, and potentially, non-Gaussian state-space models. Unlike particle filters, which can be considered exact methods and can be used for filtering non-linear, non-Gaussian models, SMCMC does not assign weights to the samples/particles, and therefore, the method does not suffer from the issue of weight-degeneracy when a relatively small number of samples is used. We design a localization approach within the SMCMC framework that focuses on regions where observations are located and restricts the transition densities included in the filtering distribution of the state to these regions. This results in immensely reducing the effective degrees of freedom and thus improving the efficiency. We test the new technique on high-dimensional (d ∼ 104 − 105) linear Gaussian model and non-linear shallow water models with Gaussian noise with real and synthetic observations. For two of the numerical examples, the observations mimic the data generated by the Surface Water and Ocean Topography (SWOT) mission led by NASA, which is a swath of ocean height observations that changes location at every assimilation time step. We also use a set of ocean drifters' real observations in which the drifters are moving according the ocean kinematics and assumed to have uncertain locations at the time of assimilation. We show that when higher accuracy is required, the proposed algorithm is superior in terms of efficiency and accuracy over competing ensemble methods and the original SMCMC *** Codes 62M20, 60G35, 60J20, 94A12, 93E11, 65C40 © 2024, CC BY.

关键词： Markov chains

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Efficient Power Transfer via Induced Virtual Critical Coupling in an Overcoupled Silicon Nitride Microresonator

Efficient Power Transfer via Induced Virtual Critical Coupli...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Hinney, Jakob Kim, Seunghwi Flatt, Graydon J.K. Datta, Ipshita Alii, Andrea Lipson, Michal Department of Electrical Engineering Columbia University New YorkNY10027 United States Photonics Advanced Science Research Catm City University of New Yor New YorkNY10031 United States Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States

We induce virtual critical coupling in an overcoupled photonic microresonator using complex-frequency pulses. We observe efficient cavity storage as an incident pulse of time constant 138 ps suppresses the resonant tr... 详细信息

ISBN: (纸本)9781957171258

关键词： Microresonators

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