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Conference on Lasers and Electro-Optics (CLEO)

作者： J. Cheng I. Komissarov G. Chen D. Chakraborty S. Kutcher H. Chen S. Trivedi Roman Sobolewski Materials Science Graduate Program University of Rochester Rochester New York USA Laboratory for Laser Energetics University of Rochester Rochester New York USA Department of Electrical and Computer Engineering University of Rochester Rochester New York USA Brimrose Technology Corp Sparks Maryland USA

We developed a dual optical/x-ray ultrafast photodetector based on in-house grown Cd 0.97 Mg 0.03 Te single crystals. The detector is characterized by ~200 ps full-width-at-half-maximum, readout-electronics limited p... 详细信息

ISBN: (纸本)9781957171258

关键词： Femtosecond lasers Photodetectors Photon counting Pump probe spectroscopy Radiation detectors Ti:sapphire lasers

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Improving Candle Direction Classification in Forex Market Using Support Vector Machine with Hyperparameters Tuning

Improving Candle Direction Classification in Forex Market Us...

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international Conference on Informatics and Computing (ICIC)

作者： Raymond Sunardi Oetama Yaya Heryadi Lukas Wayan Suparta Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Indonesia

ISBN: (纸本)9798350345728

Foreign Exchange market is the world's largest daily currency turnover. Two of the popular currencies Euro and Pound sterling traded against the US Dollar. Since the Russia and Ukraine war started in February 2022, their exchange rates decrease to the lowest rate ever. Even though the general trend is bearish, several daily candles increase for some days making challenges for forex analysts. To solve this problem, classification is applied. The data is labeled downward and upward. By utilizing Linear Kernel and Radial Basis Function (RBF) Kernel-based Support Vector Machines (SVM), the candle direction can be classified and optimized by tuning the Hyperparameters. The accuracy of candle direction classifications are highly improved. After tuning, in general, classification using Linear Models can outperform RBF Models. The best accuracy found on the Pound sterling against US Dollar by using the Linear model is 98.11% and the accuracy becomes 100% on data testing at a ratio of 70:30. Whilst for the Euro against the US Dollar, the best accuracy found the same for both Linear and RBF models on a ratio of 80:20 at 97.53%. However, on data testing, it decreases to 94.51% for Linear Model and 93.41% using RBF Model. The implication of this study is SVM can successfully classify candle direction on pairs in the Forex Market that are affected by a big event that comes for such a long period as long as the hyperparameter is tuned.

关键词： Support vector machines Training Exchange rates Market research Data models Kernel Informatics

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CLINICAL DETERIORATION PREDICTION IN BRAZILIAN HOSPITALS BASED ON ARTIFICIAL NEURAL NETWORKS AND TREE DECISION MODELS

arXiv

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arXiv 2022年

作者： Yazdanpanah, Hamed Silva, Augusto C.M. Guedes, Murilo Morales, Hugo M.P. Coelho, Leandro dos S. Moro, Fernando G. Department of Research Robô Laura PR Curitiba Brazil Department of Computer Science University of São Paulo SP São Paulo Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana PR Curitiba Brazil Electrical Engineering Graduate Program Federal University of Parana PR Curitiba Brazil

Early recognition of clinical deterioration (CD) has vital importance in patients' survival from exacerbation or death. Electronic health records (EHRs) data have been widely employed in Early Warning Scores (EWS) to measure CD risk in hospitalized patients. Recently, EHRs data have been utilized in Machine Learning (ML) models to predict mortality and CD. The ML models have shown superior performance in CD prediction compared to EWS. Since EHRs data are structured and tabular, conventional ML models are generally applied to them, and less effort is put into evaluating the artificial neural network's performance on EHRs data. Thus, in this article, an extremely boosted neural network (XBNet) is used to predict CD, and its performance is compared to eXtreme Gradient Boosting (XGBoost) and random forest (RF) models. For this purpose, 103,105 samples from thirteen Brazilian hospitals are used to generate the models. Moreover, the principal component analysis (PCA) is employed to verify whether it can improve the adopted models' performance. The performance of ML models and Modified Early Warning Score (MEWS), an EWS candidate, are evaluated in CD prediction regarding the accuracy, precision, recall, F1-score, and geometric mean (G-mean) metrics in a 10-fold cross-validation approach. According to the experiments, the XGBoost model obtained the best results in predicting CD among Brazilian hospitals' data. © 2022, CC BY-NC-SA.

关键词： Machine learning

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Coherent Acoustic Phonons in Bi2Se3 Ultrathin Films Probed by Femtosecond, Optical Pump-Probe Spectroscopy

Coherent Acoustic Phonons in Bi2Se3 Ultrathin Films Probed b...

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CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Cheng, Jing Niherysh, Kiryl A. Francis, Peter Chakraborty, Debamitra Lombardi, Floriana Erts, Donats Prischepa, Serghej L. Laszcz, Adam Komissarov, Ivan V. Sobolewski, Roman Materials Science Graduate Program University of Rochester RochesterNY14627 United States Laboratory for Laser Energetics University of Rochester RochesterNY14623-1299 United States Department of Microtechnology and Nanoscience Chalmers University of Technology Gothenburg Sweden Institute of Chemical Physics University of Latvia Riga Latvia Department of Electrical and Computer Engineering University of Rochester RochesterNY14627 United States Dipartimento di Fisica "E.R. Caianiello" Università degli Studi di Salerno Sa FiscianoI-84084 Italy Lukasiewicz Research Network Institute of Microelectronics and Photonics WarszawaPL-02668 Poland

ISBN: (纸本)9781957171395

The dynamics of coherent acoustic phonons in the Bi2Se3 layered crystal system are investigated. The findings reveal that the frequency evolution of breathing modes with the number of the material quintuple layers and the dispersion relation both can be explained by a modified chain model with a nonuniform coupling force. © Optica Publishing Group 2024, © 2024 The Author(s)

关键词： Ultrathin films

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New Frontiers for Wave engineering Using Metamaterials

New Frontiers for Wave Engineering Using Metamaterials

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2022年全国微波毫米波会议

作者： Andrea Alù Photonics Initiative Advanced Science Research Center City University of New York Physics Program Graduate Center City University of New York Department of Electrical and Computer Engineering City College of New York

Metamaterials are engineered materials with properties that go well beyond what offered by nature, providing unprecedented opportunities to tailor and enhance the control of waves. In this talk, I discuss our recent activity at microwaves and THz frequencies, showing how suitably tailored meta-atoms and their arrangements open exciting avenues for wave manipulation, including metasurfaces with enhanced wavefront manipulation, and magnet-free nonreciprocity and topological phenomena. Insights into the underlying physics and new devices based on these concepts will be presented.

关键词： New Frontiers for Wave engineering Using Metamaterials

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Fast Tracking of Maximum Power in a Shaded Photovoltaic System Using Ali Baba and the Forty Thieves (AFT) Algorithm

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Processes 2023年第10期11卷

作者： Rehman, Khalil Ur Sajid, Injila Lu, Shiue-Der Ahmad, Shafiq Liu, Hwa-Dong Bakhsh, Farhad Ilahi Tariq, Mohd Sarwar, Adil Lin, Chang-Hua Department of Electrical Engineering ZHCET Aligarh Muslim University Aligarh202002 India Department of Electrical Engineering National Chin-Yi University of Technology Taichung411 Taiwan Industrial Engineering Department College of Engineering King Saud University Riyadh11421 Saudi Arabia Undergraduate Program of Vehicle and Energy Engineering National Taiwan Normal University Taipei106 Taiwan Department of Electrical Engineering National Institute of Technology Srinagar190006 India Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States Department of Electrical Engineering National Taiwan University of Science and Technology Taipei106 Taiwan

Photovoltaic (PV) generation systems that are partially shaded have a non-linear operating curve that is highly dependent on temperature and irradiance conditions. Shading from surrounding objects like clouds, trees, and buildings creates partial shading conditions (PSC) that can cause hot spot formation on PV panels. To prevent this, bypass diodes are installed in parallel across each panel, resulting in a global maximum power point (GMPP) and multiple local maximum power points (LMPPs) on the power-voltage (P-V) curve. Traditional methods for maximum power point tracking (MPPT), such as perturb and observe (P&O) and incremental conductance (INC), converge for LMPPs on the P-V curve, but metaheuristic algorithms can track the GMPP effectively. This paper proposes a new, efficient, and robust GMPP tracking technique based on a nature-inspired algorithm called Ali Baba and the Forty Thieves (AFT). Utilizing the AFT algorithm for MPPT in PV systems has several novel features and advantages, including its adaptability, exploration-exploitation balance, simplicity, efficiency, and innovative approach. These characteristics make AFT a promising choice for enhancing the efficiency of PV systems under varied circumstances. The performance of the proposed method in tracking the GMPP is evaluated using a simulation model under MATLAB/Simulink environment, the achieved simulation results are compared to particle swarm optimization (PSO). The proposed method is also tested in real-time using the Hardware-in-the-loop (HIL) emulator to validate the achieved simulation results. The findings indicate that the proposed AFT-based GMPP tracking method performs better under complex partial irradiance conditions than PSO. © 2023 by the authors.

关键词： Efficiency

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Energy Efficiency Optimization for NOMA-based Multi-cell VLC System with Optical IRS

Energy Efficiency Optimization for NOMA-based Multi-cell VLC...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Zehao Liu Fang Yang Shiyuan Sun Jian Song Zhu Han Department of Electronic Engineering Beijing National Research Center for Information Science and Technology Tsinghua University Beijing P. R. China Research Institute of Tsinghua University Shenzhen P. R. China Shenzhen International Graduate School Tsinghua University Shenzhen P. R. China Department of Electrical and Computer Engineering University of Houston Houston TX USA

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Considering that optical intelligent reflecting surface (OIRS) can change the optical channel, the enhancement performance of OIRS on the energy efficiency (EE) of the non-orthogonal multiple access (NOMA)-based visible light communication (VLC) system is investigated. Specifically, a multi-cell VLC system is modelled with both line-of-sight (LoS) and OIRS-reflected paths, and then the problem is formulated to optimize the OIRS configuration and power allocation for the maximization of the overall EE while adhering to various constraints. Moreover, the original task is decomposed into two sub-problems, and is solved iteratively by the proposed algorithm. In addition, the convergence of the proposed algorithm and enhancement in EE achieved by OIRS are illustrated by simulation results, which offer beneficial insights on resource allocation for the NOMAbased VLC systems with OIRS.

关键词： Wireless communication NOMA Simulation Line-of-sight propagation Energy efficiency Numerical models Optical reflection Resource management Optimization Visible light communication

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AVTENet: Audio-Visual Transformer-based Ensemble Network Exploiting Multiple Experts for Video Deepfake Detection

arXiv

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arXiv 2023年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min The Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Academia Sinica Taipei11529 Taiwan The Institute of Information Systems and Applications National Tsing Hua University Hsinchu30013 Taiwan The Department of Computer Science National Chengchi University Taipei11605 Taiwan The Department of Electrical Engineering The Institute of Communications Engineering National Tsing Hua University Hsinchu300044 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan The Institute of Information Science Academia Sinica Taipei11529 Taiwan

Forged content shared widely on social media platforms is a major social problem that requires increased regulation and poses new challenges to the research community. The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous work on detecting AI-generated fake videos only utilizes visual modality or audio modality. While there are some methods in the literature that exploit audio and visual modalities to detect forged videos, they have not been comprehensively evaluated on multi-modal datasets of deepfake videos involving acoustic and visual manipulations. Moreover, these existing methods are mostly based on CNN and suffer from low detection accuracy. Inspired by the recent success of Transformer in various fields, to address the challenges posed by deepfake technology, in this paper, we propose an Audio-Visual Transformer-based Ensemble Network (AVTENet) framework that considers both acoustic manipulation and visual manipulation to achieve effective video forgery detection. Specifically, the proposed model integrates several purely transformer-based variants that capture video, audio, and audio-visual salient cues to reach a consensus in prediction. For evaluation, we use the recently released benchmark multi-modal audio-video FakeAVCeleb dataset. For a detailed analysis, we evaluate AVTENet, its variants, and several existing methods on multiple test sets of the FakeAVCeleb dataset. Experimental results show that our best model outperforms all existing methods and achieves state-of-the-art performance on Testset-I and Testset-II of the FakeAVCeleb dataset. © 2023, CC BY.

关键词： Statistical tests

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!MESS: A modular, efficient speaker verification system

!MESS: A modular, efficient speaker verification system

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Workshop on Speaker Recognition and its Commercial and Forensic Applications, RLA2C 1998

作者： van Vuuren, Sarel Hermansky, Hynek Department of Electrical and Computer Engineering Oregon Graduate Institute of Science and Technology PO Box 91000 PortlandOR97291-1000 United States International Computer Science Institute BerkeleyCA United States

We describe a text-independent speaker verification system !MESS that was designed to be highly modular and efficient. The system incorporates an extension of the Tel script language that facilitates rapid prototyping and high overall execution speed. We provide an overview of the system and its implementation, detailing its applicability as a flexible research environment. Using the system we investigate the importance of parts of the modulation spectrum for speaker verification. We find that higher modulation frequencies are not particularly important for verification - removing them improves verification performance. On the 1997 Switchboard evaluation set, for test segments of 30 seconds, a relatively small system with lowpass filtering at 10Hz cutoff gives a 12% reduction in EER. Copyright © RLA2C 1998 - Speaker Recognition and its Commercial and Forensic *** rights reserved.

关键词： Low pass filters

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Astrophysical expedition: Transit search heuristics for fractional Hammerstein control autoregressive models

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Modern Physics Letters B 2025年第7期39卷

作者： Altaf, Faisal Chang, Ching-Lung Chaudhary, Naveed Ishtiaq Ali Khan, Taimoor Khan, Zeshan Aslam Shu, Chi-Min Raja, Muhammad Asif Zahoor Graduate School of Engineering Science and Technology National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou 64002 Taiwan Department of Computer Science and Information Engineering National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou 64002 Taiwan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou 64002 Taiwan International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou 64002 Taiwan Department of Electrical and Computer Engineering International Islamic University Islamabad Capital Territory Islamabad 44000 Pakistan Department of Safety Health and Environmental Engineering National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou 64002 Taiwan

This study presents an astrophysics-inspired transit search optimization (TSO) algorithm based on exoplanet search divided into five phases: galaxy phase, star phase, transit phase, neighbor phase and exploitation phase for effective parameter estimation of fractional Hammerstein control autoregressive (Fr-HCAR) systems. Various physical phenomena and real processes can be modeled with Fr-HCAR systems and estimating the Fr-HCAR parameters becomes a vital task. The mean-square error (MSE)-based criterion function is developed, and efficacy of the TSO for Fr-HCAR identification is deeply analyzed for different fractional orders, disturbance levels and degrees of freedom. The TSO remained accurate, convergent, robust and stable for all variations in Fr-HCAR but the accuracy level degrades a little bit for high disturbance and increased degrees of freedom. The reliability and trustworthiness of the TSO for Fr-HCAR identification are endorsed through statistical analyses conducted on sufficient autonomous executions of the scheme. © 2025 World Scientific Publishing Company.

关键词： Astrophysics fractional calculus Hammerstein model nonlinear systems transit search optimization

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