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programmable threshold sensing in wireless devices using Ising dynamics

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Nature Electronics 2025年 1-8页

作者： Nicolas Casilli Hussein M. E. Hussein Ryan Tetro Luca Colombo Matteo Rinaldi Cristian Cassella Seunghwi Kim Andrea Alù Philip X.-L. Feng Institute for Nano Systems Innovation (NanoSI) Department of Electrical and Computer Engineering Northeastern University Boston MA USA Photonics Initiative Advanced Science Research Center City University of New York New York City NY USA Physics Program Graduate Center City University of New York New York City NY USA Department of Electrical and Computer Engineering University of Florida Gainesville FL USA

Ising machines—comprising dissipatively coupled nodes capable of emulating the behaviour of ferromagnetic spins—can form analogue computing engines that surpass the sequential processing constraints of von Neumann architectures. However, the incorporation of Ising dynamics into radio-frequency wireless technologies remains limited, especially in terms of their potential to enhance wireless sensing capabilities. Here we report a passive wireless sensor that uses Ising dynamics to accurately implement threshold sensing. The device correlates the occurrence of violations in a sensed parameter with transitions in the coupling state of two parametric oscillators acting as Ising spins. As a result, the accuracy of the device is unaffected by distortions in its input and output signals due to multipath and is less prone to clutter caused by co-site interference. We illustrate the potential of the approach in temperature threshold sensing using a microfabricated lithium niobate microelectromechanical temperature sensor to couple two radio-frequency parametric oscillators, and show that such a system allows the sensor threshold to be wirelessly reprogrammed.

关键词： Ising model

Topological Metamaterials

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arXiv 2022年

作者： Ni, Xiang Yves, Simon Krasnok, Alex Alu, Andrea Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States Department of Electrical Engineering City College The City University of New York 160 Convent Avenue New York10031 United States Physics Program The Graduate Center The City University of New York 365 Fifth Avenue New York10016 United States

Unlike geometrical features, such as shape or volume, the topological properties of an object do not change continuously, but only due to abrupt transitions associated with a change in the integer quantities that describe these properties - known as topological invariants. In turn, this resilience of topological features is associated with intrinsic robustness. For example, the topological invariant known as the Chern number, associated with the quantization of the Hall conductance in a two-dimensional electron gas, supports disorder-immune electron transport at the surface of topological insulators (TIs). One of the most significant breakthroughs in physics of the last decade has been the discovery that materials with non-trivial topological properties for electronic, electromagnetic, acoustic and mechanical responses can be designed and manufactured at our will through engineered metamaterials (MMs). Here, we review the foundation and the state-of-the-art advances of topological photonics, acoustics and mechanical MMs. We discuss how topological MMs enable nontrivial wave phenomena in physics, engineering, of great interest for a broad range of interdisciplinary science disciplines such as classical and quantum chemistry. We first introduce the foundations of topological materials and the main concepts behind their peculiar features, including the concepts of topological charge and geometric phase. We then discuss the topology of electronic band structures in natural topological materials, like topological insulators and gapless Dirac and Weyl semimetals. Based on these concepts, we review the concept, design and response of topologically nontrivial MMs in photonics and phononics, including topological phases in 2D MMs with and without time-reversal symmetry, Floquet TIs based on spatial and temporal modulation, topological phases in 3D MMs, higher-order topological phases in MMs, non-Hermitian and nonlinear topological MMs and the topological features of scatteri

关键词： Metamaterials

Beyond Bounds on Light Scattering with Complex Frequency Excitations

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arXiv 2022年

作者： Kim, Seunghwi Lepeshov, Sergey Krasnok, Alex Alù, Andrea Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States DTU Electro Department of Electrical and Photonics Engineering Technical University of Denmark Ørsteds Plads 343 Kgs. LyngbyDK-2800 Denmark Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States

Light scattering is one of the most established wave phenomena in optics, lying at the heart of light-matter interactions and of crucial importance for nanophotonic applications. Passivity, causality and energy conservation imply strict bounds on the degree of control over scattering from small particles, with implications on the performance of many optical devices. Here, we demonstrate that these bounds can be surpassed by considering excitations at complex frequencies, yielding extreme scattering responses as tailored nanoparticles reach a quasi-steady-state regime. These mechanisms can be used to engineer light scattering of nanostructures beyond conventional limits for noninvasive sensing, imaging, and nanoscale light manipulation. Copyright © 2022, The Authors. All rights reserved.

关键词： Light scattering

Learning management system for oil palm smallholder-owned plantations

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AIP Conference Proceedings 2023年第1期2594卷

作者： E. Firmansyah D. Nurjannah S. I. Dinarti D. Sudigyo T. Suparyanto B. Pardamean Department of Agrotechnology Institute of Agriculture STIPER Yogyakarta Indonesia 55281 Departement of Agricultural Economics Institute of Agriculture STIPER Yogyakarta Indonesia 55281 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Departement of Agriculture Engineering Institute of Agriculture STIPER Yogyakarta Indonesia 55281 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

The production gap between oil palm smallholder-owned plantations and corporations shows a real problem in the national palm oil industry. To reduce the gap, user-friendly assistance for smallholder-owned plantations is needed for the cultivation of sustainable palm oil production. Android-based software can be a platform for bridging the transfer of knowledge and technology, transfer of problems, and transfer of solutions between planters and experts. The platform development was formulated in five stages which began with Learning Management System (LMS) application development, identification of Good Agricultural Practices (GAP) and Best Management Practices (BMP) materials, development of digital contents, uploading the digital content to the LMS server, and dissemination. The curriculum in the application platform was prepared based on the needs of the growers according to the identification results of the farmers' profiles. The curriculum consists of GAP and BMP material blocks. Each block was divided into discussion topics. The digital contents related to GAP and BMP were set in the LMS, which was built using Moodle platform.

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Applying mobility business intelligence concept in analyzing oil palm plantation productivity

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AIP Conference Proceedings 2024年第1期3026卷

作者： Andreas Wahyu Krisdiarto Irya Wisnubhadra Anzaludin Samsinga Perbangsa Teddy Suparyanto Bens Pardamean Faculty of Agricultural Technology STIPER Institute of Agriculture Yogyakarta Indonesia Informatics Engineering Department Atma Jaya Yogyakarta University Yogyakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia BDSRC Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

The palm oil business employs almost 20 million people, generates USD 21 billion in revenue, and plays a vital role in Indonesia’s social economy. The Fresh Fruit Bunches (FFB) to Palm Oil Mills (POM) distribution system is one important aspect of fruit quality. Three steps are involved in getting Oil Palm FFB from the plantation to the POM. The first part of the procedure involves cutting FFB from the tree, the second stage involves gathering the fruit at a fruit collection point (FCP), and the third stage involves transporting the fruit to the palm oil mill (POM). As of now, the cost of the FFB transportation is still considerable, accounting for roughly 15% to 20% of the FFB pricing. The use of the Business Intelligence (BI) idea in the oil palm harvesting system is presented in this study as a foundation for creating web-based applications.

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Drum-aware ensemble architecture for improved joint musical beat and downbeat tracking

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arXiv 2021年

作者： Chiu, Ching-Yu Su, Alvin Wen-Yu Yang, Yi-Hsuan The Graduate Program of Multimedia Systems and Intelligent Computing National Cheng Kung University Academia Sinica Taiwan The Department of Computer Science and Information Engineering National Cheng Kung University Taiwan Yating Music Team Taiwan AI Labs Taiwan Research Center for IT Innovation Academia Sinica Taiwan

This paper presents a novel system architecture that integrates blind source separation with joint beat and downbeat tracking in musical audio signals. The source separation module segregates the percussive and non-percussive components of the input signal, over which beat and downbeat tracking are performed separately and then the results are aggregated with a learnable fusion mechanism. This way, the system can adaptively determine how much the tracking result for an input signal should depend on the input's percussive or non-percussive components. Evaluation on four testing sets that feature different levels of presence of drum sounds shows that the new architecture consistently outperforms the widely-adopted baseline architecture that does not employ source separation. Copyright © 2021, The Authors. All rights reserved.

关键词： Blind source separation

CNN-based cardiac motion extraction to generate deformable geometric left ventricle myocardial models from Cine MRI

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arXiv 2021年

作者： Upendra, Roshan Reddy Wentz, Brian Jamison Simon, Richard Shontz, Suzanne M. Linte, Cristian A. Center for Imaging Science Rochester Institute of Technology RochesterNY United States Biomedical Engineering Rochester Institute of Technology RochesterNY United States Bioengineering Graduate Program University of Kansas LawrenceKS United States Electrical Engineering and Computer Science University of Kansas LawrenceKS United States Information and Telecommunication Technology Center University of Kansas LawrenceKS United States

Patient-specific left ventricle (LV) myocardial models have the potential to be used in a variety of clinical scenarios for improved diagnosis and treatment plans. Cine cardiac magnetic resonance (MR) imaging provides high resolution images to reconstruct patient-specific geometric models of the LV myocardium. With the advent of deep learning, accurate segmentation of cardiac chambers from cine cardiac MR images and unsupervised learning for image registration for cardiac motion estimation on a large number of image datasets is attainable. Here, we propose a deep leaning-based framework for the development of patient-specific geometric models of LV myocardium from cine cardiac MR images, using the Automated Cardiac Diagnosis Challenge (ACDC) dataset. We use the deformation field estimated from the VoxelMorph-based convolutional neural network (CNN) to propagate the isosurface mesh and volume mesh of the end-diastole (ED) frame to the subsequent frames of the cardiac cycle. We assess the CNN-based propagated models against segmented models at each cardiac phase, as well as models propagated using another traditional nonrigid image registration technique. © 2021, CC BY.

关键词： Image registration

Passive Bias-Free Nonreciprocal Metasurfaces Based on Nonlinear Quasi-Bound States in the Continuum

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arXiv 2022年

作者： Cotrufo, Michele Cordaro, Andrea Sounas, Dimitrios L. Polman, Albert Alù, Andrea Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Van der Waals-Zeeman Institute Institute of Physics University of Amsterdam Science Park 904 Amsterdam1098 XH Netherlands Center for Nanophotonics AMOLF Science Park 104 Amsterdam1098 XG Netherlands Department of Electrical and Computer Engineering Wayne State University DetroitMI48202 United States Physics Program Graduate Center of the City University of New York New YorkNY10016 United States

Nonreciprocal devices – in which light is transmitted with different efficiencies along opposite directions – are key technologies for modern photonic applications, yet their compact and miniaturized implementation remains an open challenge. Among different avenues, nonlinearity-induced nonreciprocity has attracted significant attention due to the absence of external bias and integrability within conventional material platforms. So far, nonlinearity-induced nonreciprocity has been demonstrated only in guided platforms using high-Q resonators. Here, we demonstrate ultrathin optical metasurfaces with large nonreciprocal response for free-space radiation based on silicon third-order nonlinearities. Our metasurfaces combine an out-of-plane asymmetry – necessary to obtain nonreciprocity – with in-plane broken symmetry, which finely tunes the radiative linewidth of quasi-bound states in the continuum (q-BICs). Third-order nonlinearities naturally occurring in silicon, engaged by q-BICs, are shown to enable over 10 dB of nonreciprocal transmission while maintaining less than 3 dB in insertion loss. The demonstrated devices merge the field of nonreciprocity with ultrathin metasurface technologies, offering an exciting functionality for signal processing and routing, communications, and protection of high-power laser cavities. © 2022, CC BY.

关键词： High power lasers

Radar Occupancy Prediction with Lidar Supervision while Preserving Long-Range Sensing and Penetrating Capabilities

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arXiv 2021年

作者： Kung, Pou-Chun Wang, Chieh-Chih Lin, Wen-Chieh The Graduate Degree Program of Robotics National Yang Ming Chiao Tung University Hsinchu Taiwan The Department of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan The Mechanical and Mechatronics Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan The Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan

Radar shows great potential for autonomous driving by accomplishing long-range sensing under diverse weather conditions. But radar is also a particularly challenging sensing modality due to the radar noises. Recent works have made enormous progress in classifying free and occupied spaces in radar images by leveraging lidar label supervision. However, there are still several unsolved issues. Firstly, the sensing distance of the results is limited by the sensing range of lidar. Secondly, the performance of the results is degenerated by lidar due to the physical sensing discrepancies between the two sensors. For example, some objects visible to lidar are invisible to radar, and some objects occluded in lidar scans are visible in radar images because of the radar's penetrating capability. These sensing differences cause false positive and penetrating capability degeneration, respectively. In this paper, we propose training data preprocessing and polar sliding window inference to solve the issues. The data preprocessing aims to reduce the effect caused by radar-invisible measurements in lidar scans. The polar sliding window inference aims to solve the limited sensing range issue by applying a near-range trained network to the long-range region. Instead of using common Cartesian representation, we propose to use polar representation to reduce the shape dissimilarity between long-range and near-range data. We find that extending a near-range trained network to long-range region inference in the polar space has 4.2 times better IoU than in Cartesian space. Besides, the polar sliding window inference can preserve the radar penetrating capability by changing the viewpoint of the inference region, which makes some occluded measurements seem non-occluded for a pretrained network. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical radar