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arXiv 2024年

作者： Ota, Rikuto Kobayashi, Keito Hayakawa, Keisuke Kanai, Shun Çamsarı, Kerem Y. Ohno, Hideo Fukami, Shunsuke Laboratory for Nanoelectronics and Spintronics Research Institute of Electrical Communication Tohoku University Sendai980-8577 Japan Graduate School of Engineering Tohoku University Sendai980-0845 Japan Center for Science and Innovation in Spintronics Tohoku University Sendai980-8577 Japan WPI-Advanced Institute for Materials Research Tohoku University Sendai980-8577 Japan PRESTO Japan Science and Technology Agency Kawaguchi332-0012 Japan Division for the Establishment of Frontier Sciences Tohoku University Sendai980-8577 Japan National Institutes for Quantum Science and Technology Takasaki370-1207 Japan Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States Center for Innovative Integrated Electronic Systems Tohoku University Sendai980-0845 Japan Inamori Research Institute for Science Kyoto600-8411 Japan

Stochastic magnetic tunnel junctions (s-MTJ) is a promising component of probabilistic bit (p-bit), which plays a pivotal role in probabilistic computers. For a standard cell structure of the p-bit, s-MTJ is desired to be insensitive to voltage across the junction over several hundred millivolts. In conventional s-MTJs with a reference layer having a fixed magnetization direction, however, the stochastic output significantly varies with the voltage due to spin-transfer torque (STT) acting on the stochastic free layer. In this work, we study a s-MTJ with a "double-free-layer" design theoretically proposed earlier, in which the fixed reference layer of the conventional structure is replaced by another stochastic free layer, effectively mitigating the influence of STT on the stochastic output. We show that the key device property characterized by the ratio of relaxation times between the high- and low-resistance states is one to two orders of magnitude less sensitive to bias voltage variations compared to conventional s-MTJs when the top and bottom free layers are designed to possess the same effective thickness. This work opens a pathway for reliable, nanosecond-operation, high-output, and scalable spintronics-based p-bits. © 2024, CC BY.

关键词： Tunnel junctions

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Sensitive and selective ozone sensor based on CuCo2O4 synthesized by a facile solution combustion method

SSRN

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SSRN 2022年

作者： Zhao, Zhongyao Deng, Zanhong Zhang, Ruofan Klamchuen, Annop He, Yong Horprathum, Mati Chang, Junqing Mi, Longqing Li, Meng Wang, Shimao Fang, Xiaodong Meng, Gang School of Environmental Science and Optoelectronic Technology University of Science and Technology of China Hefei230026 China Anhui Provincial Key Laboratory of Photonic Devices and Materials Anhui Institute of Optics and Fine Mechanics Key Lab of Photovoltaic and Energy Conservation Materials Chinese Academy of Sciences Hefei230031 China Advanced Laser Technology Laboratory of Anhui Province Hefei230037 China National Nanotechnology Center National Science and Technology Development Agency Pathum Thani 12120 Thailand Key Laboratory of Optoelectronic Technology and Systems The Education Ministry of China College of Optoelectronic Engineering Chongqing University Chongqing400044 China Opto-Electrochemical Sensing Research Team Spectroscopic and Sensing Devices Research Group National Electronics and Computer Technology Center Pathum Thani 12120 Thailand College of New Materials and New Energies Shenzhen Technology University Shenzhen518118 China Shenzhen Shengfang Technology Company Limited Shenzheng518116 China

In this study, p-type spinel CuCo2O4 nanomaterials with abundant oxygen vacancies were synthesized by a facile one-step solution combustion method, and their sensing characteristics have been investigated. The p-type CuCo2O4 sensor shows a high response of 11 to 1 ppm O3 and low responses (3, NO2, SO2, and 1000 ppm ethanol, methanol and acetone) at 90 °C in dry air, indicating a superior selectivity. The sensor also possesses a wide O3 detection range from 10 to 3000 ppb and good repeatability. More importantly, the relative humidity (RH) could promote the electrical response to O3, and the response to 1 ppm O3 only deviates from 24 to 27 as the RH increases from 50% to 90%, benefitting for practical applications in ambient humid air atmospheres. The humidity enhanced response for p-type CuCo2O4 could be ascribed to the competition of hole carrier reduction, O2− active sites reduction and O3 decomposition promotion induced by the hydroxyl groups. © 2022, The Authors. All rights reserved.

关键词： Copper compounds

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Efficient Pyramid Channel Attention Network for Pathological Myopia Recognition

arXiv

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arXiv 2023年

作者： Zhang, Xiaoqing Zhao, Jilu Li, Yan Wu, Hao Zhou, Xiangtian Liu, Jiang Research Institute of Trustworthy Autonomous Systems Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Center for High Performance Computing Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China National Clinical Research Center for Ocular Diseases Eye Hospital Wenzhou Medical University Wenzhou325027 China State Key Laboratory of Ophthalmology Optometry and Visual Science Eye Hospital Wenzhou Medical University Wenzhou325027 China Research Unit of Myopia Basic Research and Clinical Prevention and Control Chinese Academy of Medical Sciences Wenzhou325027 China Singapore Eye Research Institute 169856 Singapore

Pathological myopia (PM) is the leading ocular disease for impaired vision worldwide. Clinically, the characteristic of pathology distribution in PM is global-local on the fundus image, which plays a significant role in assisting clinicians in diagnosing PM. However, most existing deep neural networks focused on designing complex architectures but rarely explored the pathology distribution prior of PM. To tackle this issue, we propose an efficient pyramid channel attention (EPCA) module, which fully leverages the potential of the clinical pathology prior of PM with pyramid pooling and multi-scale context fusion. Then, we construct EPCA-Net for automatic PM recognition based on fundus images by stacking a sequence of EPCA modules. Moreover, motivated by the recent pretraining-and-finetuning paradigm, we attempt to adapt pre-trained natural image models for PM recognition by freezing them and treating the EPCA and other attention modules as adapters. In addition, we construct a PM recognition benchmark termed PM-fundus by collecting fundus images of PM from publicly available datasets. The comprehensive experiments demonstrate the superiority of EPCA-Net over state-of-the-art methods in the PM recognition task. For example, EPCA-Net achieves 97.56% accuracy and outperforms ViT by 2.85% accuracy on the PM-fundus dataset. The results also show that our method based on the pretraining-and-finetuning paradigm achieves competitive performance through comparisons to part of previous methods based on traditional fine-tuning paradigm with fewer tunable parameters, which has the potential to leverage more natural image foundation models to address the PM recognition task in limited medical data regime. Copyright © 2023, The Authors. All rights reserved.

关键词： Pathology

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Application-level Benchmarking of Quantum computers using Nonlocal Game Strategies

arXiv

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arXiv 2023年

作者： Furches, Jim Chehade, Sarah Hamilton, Kathleen Wiebe, Nathan Marrero, Carlos Ortiz College of Computing Georgia Institute of Technology AtlantaGA30332 United States Physical Detection Systems and Deployment Division Pacific Northwest National Laboratory RichlandWA99354 United States Quantum Computational Science Group Oak Ridge National Laboratory Oak RidgeTN37830 United States Department of Computer Science University of Toronto ONM5S 1A1 Canada High Performance Computing Group Pacific Northwest National Laboratory RichlandWA99354 United States Canadian Institute for Advanced Research TorontoONM5G 1M1 Canada Department of Electrical & Computer Engineering North Carolina State University RaleighNC27607 United States

In a nonlocal game, two noncommunicating players cooperate to convince a referee that they possess a strategy that does not violate the rules of the game. Quantum strategies allow players to optimally win some games by performing joint measurements on a shared entangled state, but computing these strategies can be challenging. We present a variational quantum algorithm to compute quantum strategies for nonlocal games by encoding the rules of a nonlocal game into a Hamiltonian. We show how this algorithm can generate a short-depth optimal quantum strategy for a graph coloring game with a quantum advantage. This quantum strategy is then evaluated on fourteen different quantum hardware platforms to demonstrate its utility as a benchmark. Finally, we discuss potential sources of errors that can explain the observed decreased performance of the executed task and derive an expression for the number of samples required to accurately estimate the win rate in the presence of noise. Copyright © 2023, The Authors. All rights reserved.

关键词： Hamiltonians

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Incorporating Multiple Features to Predict Bug Fixing Time with Neural Networks

Incorporating Multiple Features to Predict Bug Fixing Time w...

引用

International Conference on Software Maintenance (ICSM)

作者： Wei Yuan Yuan Xiong Hailong Sun Xudong Liu SKLSDE Lab School of Computer Science and Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China SKLSDE Lab School of Software Beihang University Beijing China

Debugging is a well-known time-consuming task, and knowing how long it would take to resolve bugs is of great importance for allocating the limited resources in a software development team. However, it is challenging to predict bug fixing time since fixing bugs is subject to a plethora of uncertain factors such as types of bugs, program complexity and developers' abilities. Existing work mainly focuses on developers' activities in a bug lifecycle and ignores other important factors. In light of the limitations of existing work, we propose a novel approach to predicting the bug fixing time by incorporating a comprehensive set of relevant features. Specifically, we consider four types of features including developers' activities, developers' sentiments, semantics of bugs, and efforts caused by understanding and analyzing source code, and design particular neural networks to take advantage of these features and make them work efficiently. Experimental results on four real application datasets demonstrate that on the one hand, our approach outperforms the state-of-the-art by over 5% in accuracy and 7.3% in F1-score on average; on the other hand, each type of the features considered in our approach plays an important part in the prediction.

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NAS-Count: Counting-by-Density with Neural Architecture Search 16th

NAS-Count: Counting-by-Density with Neural Architecture Sear...

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16th European Conference on computer Vision, ECCV 2020

作者： Hu, Yutao Jiang, Xiaolong Liu, Xuhui Zhang, Baochang Han, Jungong Cao, Xianbin Doermann, David School of Electronic and Information Engineering Beihang University Beijing China Key Laboratory of Advanced Technologies for Near Space Information Systems Ministry of Industry and Information Technology Beijing China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beijing China YouKu Cognitive and Intelligent Lab Alibaba Group Hangzhou China Beihang University Beijing China Computer Science Department Aberystwyth University AberystwythSY23 3FL United Kingdom Department of Computer Science and Engineering University at Buffalo New York United States

ISBN: (纸本)9783030585419

Most of the recent advances in crowd counting have evolved from hand-designed density estimation networks, where multi-scale features are leveraged to address the scale variation problem, but at the expense of demanding design efforts. In this work, we automate the design of counting models with Neural Architecture Search (NAS) and introduce an end-to-end searched encoder-decoder architecture, Automatic Multi-Scale Network (AMSNet). Specifically, we utilize a counting-specific two-level search space. The encoder and decoder in AMSNet are composed of different cells discovered from micro-level search, while the multi-path architecture is explored through macro-level search. To solve the pixel-level isolation issue in MSE loss, AMSNet is optimized with an auto-searched Scale Pyramid Pooling Loss (SPPLoss) that supervises the multi-scale structural information. Extensive experiments on four datasets show AMSNet produces state-of-the-art results that outperform hand-designed models, fully demonstrating the efficacy of NAS-Count. © 2020, Springer Nature Switzerland AG.

关键词： Decoding

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Walkability assessment for the elderly through simulations: The LONGEVICITY project 4

Walkability assessment for the elderly through simulations: ...

引用

4th Italian Workshop on Artificial Intelligence for Ambient Assisted Living, AI*AAL.it 2018

作者： Bandini, Stefania Crociani, Luca Gorrini, Andrea Nishinari, Katsuhiro Vizzari, Giuseppe Complex Systems and Artificial Intelligence Research Center Department of Computer Science University of Milan-Bicocca Milan Italy Research Center for Advanced Science and Technology University of Tokyo Tokyo Japan

In the context of global progressive urbanization and ageing of the population, the LONGEVICITY Project has the objective to study advanced solutions to assess and enhance the walkability of urban environments. This is aimed at sustaining the social inclusion of the elderly citizens. The paper introduces one of the research activities of the project, focused on the design of innovative agent-based model for the simulation of pedestrian circulation dynamics and street crossing behavior for the assessment of the level of walkability of the City of Milan (Italy). This is based on the possibility to model age-driven pedestrian dynamics while crossing as characterized by heterogeneous behaviors in terms of speeds and crossing decision. This is aimed at providing applicative design solutions to enhance the level of comfort and safety of the elderly while walking through the city and to sustain their active ageing. © 2019 CEUR-WS. All Rights Reserved.

关键词： Computational methods

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Rate-Splitting Multiple Access for Uplink Massive MIMO With Electromagnetic Exposure Constraints

arXiv

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arXiv 2022年

作者： Jiang, Hanyu You, Li Elzanaty, Ahmed Wang, Jue Wang, Wenjin Gao, Xiqi Alouini, Mohamed-Slim The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The Purple Mountain Laboratories Nanjing211100 China The 5GIC & 6GIC Institute for Communication Systems University of Surrey GuildfordGU2 7XH United Kingdom School of Information Science and Technology Nantong University Nantong226019 China Nantong Research Institute for Advanced Communication Technologies Nantong226019 China The Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Makkah Province Thuwal Saudi Arabia

Over the past few years, the prevalence of wireless devices has become one of the essential sources of electromagnetic (EM) radiation to the public. Facing with the swift development of wireless communications, people are skeptical about the risks of long-term exposure to EM radiation. As EM exposure is required to be restricted at user terminals, it is inefficient to blindly decrease the transmit power, which leads to limited spectral efficiency and energy efficiency (EE). Recently, rate-splitting multiple access (RSMA) has been proposed as an effective way to provide higher wireless transmission performance, which is a promising technology for future wireless communications. To this end, we propose using RSMA to increase the EE of massive MIMO uplink while limiting the EM exposure of users. In particularly, we investigate the optimization of the transmit covariance matrices and decoding order using statistical channel state information (CSI). The problem is formulated as non-convex mixed integer program, which is in general difficult to handle. We first propose a modified water-filling scheme to obtain the transmit covariance matrices with fixed decoding order. Then, a greedy approach is proposed to obtain the decoding permutation. Numerical results verify the effectiveness of the proposed EM exposure-aware EE maximization scheme for uplink RSMA. © 2022, CC BY-NC-ND.

关键词： Energy efficiency

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Brain multigraph prediction using topology-aware adversarial graph neural network

arXiv

引用

arXiv 2021年

作者： Bessadok, Alaa Mahjoub, Mohamed Ali Rekik, Islem BASIRA Lab Faculty of Computer and Informatics Istanbul Technical University Istanbul Turkey Higher Institute of Informatics and Communication Technologies University of Sousse Tunisia National Engineering School of Sousse University of Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia School of Science and Engineering Computing University of Dundee United Kingdom

Brain graphs (i.e, connectomes) constructed from medical scans such as magnetic resonance imaging (MRI) have become increasingly important tools to characterize the abnormal changes in the human brain. Due to the high acquisition cost and processing time of multimodal MRI, existing deep learning frameworks based on Generative Adversarial Network (GAN) focused on predicting the missing multimodal medical images from a few existing modalities. While brain graphs help better understand how a particular disorder can change the connectional facets of the brain, synthesizing a target brain multigraph (i.e, multiple brain graphs) from a single source brain graph is strikingly lacking. Additionally, existing graph generation works mainly learn one model for each target domain which limits their scalability in jointly predicting multiple target domains. Besides, while they consider the global topological scale of a graph (i.e., graph connectivity structure), they overlook the local topology at the node scale (e.g., how central a node is in the graph). To address these limitations, we introduce topology-aware graph GAN architecture (topoGAN), which jointly predicts multiple brain graphs from a single brain graph while preserving the topological structure of each target graph. Its three key innovations are: (i) designing a novel graph adversarial auto-encoder for predicting multiple brain graphs from a single one, (ii) clustering the encoded source graphs in order to handle the mode collapse issue of GAN and proposing a cluster-specific decoder, (iii) introducing a topological loss to force the prediction of topologically sound target brain graphs. The experimental results using five target domains demonstrated the outperformance of our method in brain multigraph prediction from a single graph in comparison with baseline approaches. © 2021, CC BY-NC-SA.

关键词： Graphic methods

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Ab initio informed 20Ne(p, pα)16O reaction elucidates the emergence of alpha clustering from chiral potentials

arXiv

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arXiv 2024年

作者： Sargsyan, G.H. Yoshida, Kazuki Ogata, Kazuyuki Launey, K.D. Escher, J.E. Langr, D. Dytrych, T. Facility for Rare Isotope Beams Michigan State University East LansingMI48824 United States Advanced Science Research Center Japan Atomic Energy Agency Ibaraki Tokai319-1195 Japan Department of Physics Kyushu University Fukuoka819-0395 Japan Osaka University Ibaraki Osaka567-0047 Japan Department of Physics and Astronomy Louisiana State University Baton RougeLA70803 United States Lawrence Livermore National Laboratory LivermoreCA94550 United States Department of Computer Systems Faculty of Information Technology Czech Technical University in Prague Prague16000 Czech Republic Nuclear Physics Institute The Czech Academy of Sciences Řež250 68 Czech Republic

We report on the first ab initio informed α knock-out reaction in the intermediate-mass region, with the aim to probe the underlying chiral potential and its impact on the emergence of alpha clustering in this mass region. The theoretical predictions of the α+16O clustering in the 20Ne ground state, based on the ab initio symmetry-adapted no-core shell model with continuum, yield a triple differential cross section for 20Ne(p, pα)16O that is in a remarkable agreement with the data. This allows us to examine predictions of surface and in-medium α-cluster features from a chiral potential and to compare these to the successful antisymmetrized molecular dynamics approach. © 2024, CC BY.

关键词： Molecular dynamics

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