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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Tang, Haoning Wang, Yiting Ni, Xueqi Watanabe, Kenji Taniguchi, Takashi Fan, Shanhui Mazur, Eric Yacoby, Amir Cao, Yuan School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Department of Electrical Engineering and Computer Science University of California at Berkeley BerkeleyCA94720 United States National Institute for Materials Science Namiki 1-1 Ibaraki Tsukuba305-0044 Japan Department of Applied Physics Ginzton Laboratory Stanford University StanfordCA94305 United States

ISBN: (纸本)9781957171395

We introduce the first on-chip, microelectromechanical system for the in situ tuning of twisted 2D materials, enabling tunable interfacial properties, synthetic topological singularities, and adjustable-polarization light sources for advanced quantum material manipulation in 2D-3D devices. © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： Degrees of freedom (mechanics)

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Not so griddy: Internal representations of RNNs path integrating more than one agent 38

Not so griddy: Internal representations of RNNs path integra...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Redman, William T. Acosta, Francisco Acosta-Mendoza, Santiago Miolane, Nina Intelligent Systems Center Johns Hopkins Applied Physics Laboratory United States Department of Physics University of California Santa Barbara United States Dynamical Neuroscience University of California Santa Barbara United States Department of Electrical & Computer Engineering University of California Santa Barbara United States

Success in collaborative and competitive environments, where agents must work with or against each other, requires individuals to encode the position and trajectory of themselves and others. Decades of neurophysiological experiments have shed light on how brain regions [e.g., medial entorhinal cortex (MEC), hippocampus] encode the self's position and trajectory. However, it has only recently been discovered that MEC and hippocampus are modulated by the positions and trajectories of others. To understand how encoding spatial information of multiple agents shapes neural representations, we train a recurrent neural network (RNN) model that captures properties of MEC to path integrate trajectories of two agents simultaneously navigating the same environment. We find significant differences between these RNNs and those trained to path integrate only a single agent. At the individual unit level, RNNs trained to path integrate more than one agent develop weaker grid responses, stronger border responses, and tuning for the relative position of the two agents. At the population level, they develop more distributed and robust representations, with changes in network dynamics and manifold topology. Our results provide testable predictions and open new directions with which to study the neural computations supporting spatial navigation. © 2024 Neural information processing systems foundation. All rights reserved.

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HPC Application Parameter Autotuning on Edge Devices: A Bandit Learning Approach

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arXiv 2025年

作者： Hossain, Abrar Badawy, Abdel-Hameed A. Islam, Mohammad A. Patki, Tapasya Ahmed, Kishwar Department of Electrical Engineering and Computer Science The University of Toledo United States Department of Electrical and Computer Engineering New Mexico State University United States Department of Computer Science and Engineering The University of Texas Arlington United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory

The growing necessity for enhanced processing capabilities in edge devices with limited resources has led us to develop effective methods for improving high-performance computing (HPC) applications. In this paper, we introduce LASP (Lightweight Autotuning of Scientific Application Parameters), a novel strategy designed to address the parameter search space challenge in edge devices. Our strategy employs a multi-armed bandit (MAB) technique focused on online exploration and exploitation. Notably, LASP takes a dynamic approach, adapting seamlessly to changing environments. We tested LASP with four HPC applications: Lulesh, Kripke, Clomp, and Hypre. Its lightweight nature makes it particularly well-suited for resource-constrained edge devices. By employing the MAB framework to efficiently navigate the search space, we achieved significant performance improvements while adhering to the stringent computational limits of edge devices. Our experimental results demonstrate the effectiveness of LASP in optimizing parameter search on edge devices. © 2025, CC BY-NC-ND.

关键词： Edge computing

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Enhancing Strategic Marketing with AI-Driven Insights into Dynamic Preferences and Decision Patterns

Enhancing Strategic Marketing with AI-Driven Insights into D...

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2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Raj, Vijilius Helena Shubhra Al-Rubaye, Taqi Mohammed Khattab Siri, Dharmapuri Sirisha, N. Dutt, Amit New Horizon College of Engineering Department of Applied Sciences Bangalore India Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India College of Medical Technologies The Islamic University Department of Medical Laboratory Technology Najaf Iraq Griet Department of Cse Bachupally Telangana Hyderabad India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Lovely Professional University Phagwara India

ISBN: (纸本)9798331527495

Once AI begins gathering client data, the marketing sector will alter drastically. This research uses sophisticated AI technologies to better understand how complex client behaviors might be. We examine pricing solutions, including social media mood monitoring, joint filtering algorithms for targeted marketing, and reinforcement learning-based dynamic pricing. Neural networks are being investigated for application in e-commerce predictive analytics and predicting subscription cancellations. This research examines clustering algorithms' performance to see whether they may be utilized for cross-channel marketing activities, including consumer segmentation and credit modeling. The article concludes by examining how virtual reality is affecting shop advertising and marketing. The study's findings encompass AI-powered marketing strategies' applications, advantages, and drawbacks. AI helps marketing, according to the findings. Businesses may improve their strategy, communicate with consumers, and meet client needs using this information. © 2025 IEEE.

关键词： Marketplaces

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A Novel Inherited Modeling Structure of Automatic Brain Tumor Segmentation from MRI

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computers, Materials & Continua 2022年第11期73卷 3983-4002页

作者： Abdullah AAsiri Tariq Ali Ahmad Shaf Muhammad Aamir Muhammad Shoaib Muhammad Irfan Hassan A.Alshamrani Fawaz F.Alqahtani Osama M.Alshehri Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Department of Informatics and Systems University of Management and TechnologyLahore54000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Clinical Laboratory Sciences Collage of Applied Medical ScienceNajran UniversityNajranSaudi Arabia

Brain tumor is one of the most dreadful worldwide types of cancer and affects people leading to *** resonance imaging methods capture skull images that contain healthy and affected *** checked the affected tissue in the slice-by-slice manner,which was timeconsuming and hectic ***,auto segmentation of the affected part is needed to facilitate ***,we have considered a hybrid model that inherits the convolutional neural network(CNN)properties to the support vector machine(SVM)for the auto-segmented brain tumor *** CNN model is initially used to detect brain tumors,while SVM is integrated to segment the tumor region *** proposed method was evaluated on a publicly available BraTS2020 *** statistical parameters used in this work for the mathematical measures are precision,accuracy,specificity,sensitivity,and dice ***,our method achieved an accuracy value of 0.98,which is most prominent than existing ***,the proposed approach is more suitable for medical experts to diagnose the early stages of the brain tumor.

关键词： Brain tumor support vector machine convolutional neural network BraTS classification

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Virtual Reality Support of Cognitive Processes in Firefighter Skills Training 1

Virtual Reality Support of Cognitive Processes in Firefighte...

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1st IEEE International Conference on Cognitive Aspects of Virtual Reality, CVR 2022

作者： Wijkmark, Cecilia Hammar Heldal, Ilona Metallinou, Maria Monika Western Norway University of Applied Sciences Chemistry and Biomedical Laboratory Sciences Department of Safety Haugesund Norway Western Norway University of Applied Sciences Electrical Engineering and Mathematical Sciences Department of Computer Science Bergen Norway

ISBN: (数字)9781665485166

ISBN: (纸本)9781665485166

Practice-based training in realistic settings is necessary to acquire and retain competence as a firefighter. Hot-Fire Live Simulation (HF-LS) training in real fire and smoke, using training buildings, vehicles, and equipment, has been the only available practice-based training format available, and therefore accepted despite its limitations. Virtual Reality (VR) development has provided possibilities for supplementing HF-LS training. However, hesitation exists, often because of doubt regarding the represented realism of virtual fire situations. This paper investigates how immersive VR supports cognitive processes and affects fidelity in firefighter training, compared with HF-LS. Data were collected from firefighter recruits, experienced firefighters, and instructors at a Fire and Rescue Service in Sweden, 33 persons in total, during VR and HF-LS training. VR experiences were compared with previous experiences of HF-LS. The results emphasize the current benefits and limitations of VR versus HF-LS training in relation to the support of cognitive processes and the representations' fidelity. © 2022 IEEE.

关键词： Fires

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Control of Chirality and Directionality of Nonlinear Metasurface Light Source via Moiré engineering

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Physical Review Letters 2025年第4期134卷 043801-043801页

作者： Huanyu Zhou Xueqi Ni Beicheng Lou Shanhui Fan Yuan Cao Haoning Tang Department of Electrical Engineering and Computer Science University of California at Berkeley Berkeley California 94720 USA Department of Physics National University of Singapore Singapore 119077 Department of Applied Physics and Ginzton Laboratory Stanford University Stanford California 94305 USA School of Engineering and Applied Sciences Harvard University Cambridge Massachusetts 02138 USA

Metasurfaces have revolutionized nonlinear and quantum light manipulation in the past decade, enabling the design of materials that can tune polarization, frequency, and direction of light simultaneously. However, tuning of metasurfaces is traditionally achieved by changing their microscopic structure, which does not allow in situ tuning and dynamic optimization of the metasurfaces. In this Letter, we explore the concept of twisted bilayer and tetralayer nonlinear metasurfaces, which offer rich tunability in its effective nonlinear susceptibilities. Using gold-based metasurfaces, we demonstrate that a number of different singularities of nonlinear susceptibilities can exist in the parameter space of twist angle and interlayer gap between different twisted layers. At the singularities, reflected or transmitted light from the nonlinear process (such as second-harmonic generation) can either become circularly polarized (for C points), or entirely vanish (for V points). By further breaking symmetries of the system, we can independently tune all aspects of the reflected and transmitted nonlinear emission, achieving unidirectional emission with full-Poincaré polarization tunability, a dark state (V−V point), or any other bidirectional output. Our work paves the way for multidimensional control of polarization and directionality in nonlinear light sources, opening new avenues in ultrafast optics, optical communication, sensing, and quantum optics.

关键词： Quantum optics

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Evaluating Electric Vehicle Charging Impacts on Distribution Grid Stability and Efficiency Through Adaptive Load Management Strategies

Evaluating Electric Vehicle Charging Impacts on Distribution...

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2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Janakiraman, V. Ahmad, Sabbir Revathi, V. Dutt, Amit Rani, K.Pushpa Al-Rubaye, Taqi Mohammed Khattab Bobba, Phaneendra Babu Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India University Polytechnic Jamia Millia Islamia Department of Electronics Engineering F/O Engineering & Tech India New Horizon College of Engineering Department of Applied Sciences Bangalore India Lovely Professional University Phagwara India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India College of Medical Technologies The Islamic University Department of Medical Laboratory Technology Najaf Iraq Griet Department of Eee Telangana Hyderabad India

ISBN: (纸本)9798331527495

The high growth rates of the EV market create complex issues for distribution grids, forcing a detailed examination of grid responses at high rates of EV deployment. This paper seeks to elucidate the effects of EV charging on the distribution grid stability With this, the impact of the pod on voltage fluctuations, line load, and power loss is assessed using the IEEE 37-bus system. Load patterns of EV charging stations are consequently simulated successfully by a number of real and statistically created synthetic data sources, which truly represent averaged fluctuations in load. The study looks at several charging methods of the EV, such as time of use and smart charging, to determine their impact on the grids. Furthermore, the utilization of renewable energy sources for improving the aspects of grid reliability is explored. Regarding performance aspects related to the expansion of widespread EV charging and the efficiency of the applied measures for grid stabilization, the results of this study offer beneficial information. © 2025 IEEE.

关键词： Electric buses

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Assessment of Energy Management Strategies in Buildings Equipped with Modulating Heat Pumps 2

Assessment of Energy Management Strategies in Buildings Equi...

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2nd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2022

作者： Efkarpidis, Nikolaos A. Christoforidis, Georgios C. Papagiannis, Grigoris K. University of Applied Sciences and Arts Northwestern Switzerland Institute of Electric Power Systems Windisch Switzerland University of Western Macedonia Department of Electrical and Computer Engineering Kozani Greece Aristotle University of Thessaloniki Power Systems Laboratory School of Electrical & Computer Engineering Thessaloniki Greece

ISBN: (数字)9781665461078

ISBN: (纸本)9781665461078

Buildings equipped with battery energy storages (BES), thermal energy storages (TES), Photovoltaics (PV), solar thermal collectors (STC) and modulating heat pumps (HP) can significantly enhance the energy management potential. The energy management systems are mainly based on self-consumption maximization (SCM) and time-of-use arbitrage (ToUA). In terms of electricity pricing, dynamic pricing policies with two, three tariff zones or real-time pricing (RTP) are mostly applied. In this study, different control algorithms based on the concepts of SCM and ToUA are evaluated for a complex energy system consisted of BES, TES, PV, STC and HPs with variable-speed compressors. The performance of the proposed energy management strategies is assessed under ToU and RTP pricing regimes. © 2022 IEEE.

关键词： Costs

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Power Wavelet Cepstral Coefficients (PWCC): An Accurate Auditory Model-Based Feature Extraction Method for Robust Speaker Recognition

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IEEE Access 2025年 13卷 102323-102338页

作者： Zouhir, Youssef Zarka, Mohamed Ouni, Kais Amraoui, Lilia El University of Carthage Research Laboratory Smart Electricity & ICT SE&ICT Lab. National Engineering School of Carthage LR18ES44 Tunis 2035 Tunisia King Khalid University Applied College in Tanumah Computer Science Department Abha 61421 Saudi Arabia Princess Nourah bint Abdulrahman University College of Engineering Department of Electrical Engineering P.O. Box 84428 Riyadh 11671 Saudi Arabia

Human capability for Speaker Recognition (SR) exceeds recent machine learning approaches, even in noisy environments. To bridge this gap, researchers investigate the human auditory system to support machine learning algorithm performance. The paper introduces a novel feature extraction method, named “Power Wavelet Cepstral Coefficients” (PWCC), for enhancing SR accuracy. This method is derived from the “Normalized Wavelet FilterBank” (NWFB), which utilizes an “Equivalent Rectangular Bandwidth” rate (ERB-rate) scale and additionally integrates a "Noise Suppression Module" (NSM). The NWFB imitates the cochlea’s frequency selectivity using “Morlet Wavelet filters” alongside an ERB-rate scale. The NSM applies a medium-duration power analysis, an asymmetrical noise-suppression module incorporating a temporal masking component, and a spectral smoothing module to reduce the impact of noisy signal. To assess the performance of the proposed PWCC method, experiments were conducted using clean speech signals from the TIMIT database, corrupted with various noises from the AURORA dataset. Using a “Gaussian Mixture Model-Universal Background Model” (GMM-UBM) classifier, the PWCC method demonstrated superior SR accuracy in noisy environments compared to traditional methods such as PNCC and MFCC. Furthermore, PWCC maintained higher precision, recall, and F1-scores than PNCC and MFCC under overall noise conditions. For instance, with babble noise at 15dB SNR, PWCC achieved a recognition rate of 92.06%, compared to 75.24% for PNCC and 68.33% for MFCC. © 2013 IEEE.

关键词： Auditory Models Biometric Authentication Cochlear Filtering Feature Extraction GMM-UBM Machine Learning MFCC Noise Robustness PNCC Power Wavelet Cepstral Coefficients (PWCC) Speaker Recognition Wavelet Transform

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