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arXiv 2025年

作者： Snapp-Childs, Winona G. Hancock, David Y. Smith, Preston M. Towns, John Stewart, Craig A. Pervasive Technology Institute Office of the VP for IT Indiana University BloomingtonIN47408 United States Research Technologies Office of the VP for IT Indiana University BloomingtonIN47408 United States Rosen Center for Advanced Computing Purdue University West LafayetteIN47906 United States National Center for Supercomputing Applications University of Illinois Urbana-Champaign UrbanaIL61801 United States Department of Computer Science Indiana University BloomingtonIN47408 United States

Purpose: How much to invest in research facilities has long been a question in research policy and practice in higher education. This matter is time-sensitive due to critical financial challenges at institutions in the USA, with signs of significant problems in Europe. The purpose of this report is to present new techniques for assessment of one particular type of research infrastructure - computing facilities and staff that support research. These new approaches are timely because of the ongoing financial crises which may make it essential for institutions of higher education to make difficult decisions regarding research infrastructure. Principal results: We present recently developed methods for assessment of the economic and scientific value of investment in advanced computing facilities and services. Existing examples of these tools in use show that investment in advanced computing facilities and services contributes importantly to positive financial and academic outcomes for institutions of higher education. We present a format based on the Balanced Scorecard concept for summarizing such information. Conclusion: The methods presented here enable quantitative assessment of the relationship between investment in computing facilities and research and education outcomes. These methods should be of interest to research policy investigators and practitioners. The analysis methods described may be applied retroactively, making this report of potentially immediate value in setting research policies. © 2025, CC BY.

关键词： Decentralized finance

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Artificial Intelligence-Enhanced Health Monitoring System via with Disease Prediction

Artificial Intelligence-Enhanced Health Monitoring System vi...

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Innovative computing, Intelligent Communication and Smart Electrical Systems (ICSES), International Conference on

作者： Aathithya J Mohammed Basil Abdulkareem Abdulnaser A. Hagar Saliha Bathoo l Dexter Woodward MaajidMohiUd Din Malik Research Officer-Medicine Siddha Central Research Institute Central Council for Research in Siddha (Ministry of Ayush) Government of India Chennai Tamil Nadu India Department of Business Administration College of Administration and Economic University of Anbar Iraq Faculty of Administrative and Computer Sciences Albaydha University Albaydha Yemen Department of Computer Science and Engineering Alliance School of Advanced Computing Alliance University Bangalore India Institute of Management and Rural Development Administration Sangli Maharashtra Dr. D.Y. Patil School of Allied Health Sciences Dr.D.Y Patil Vidyapeeth Pimpri Pune Maharashtra

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

Internationally, coronary infection is the main source of mortality. This technique's results incorporate the capacity to anticipate earlier cardiovascular illness. The task utilizes an Arduino to control an IOT sensor (a heartbeat sensor to screen beat), and the outcomes might be seen on a successive screen. The therapeutic parameters that are also used for information preparation and testing are used to categorise the datasets. This approach uses the information preparation order technique to evaluate those parameters. with the aid of categorization and AI computations. The dataset is first separated, inspected, and screened. The data that is then accumulated is then handled in Python programming utilizing AI calculations, to be specific Choice Tree and Arbitrary Boondocks Classifier calculations. Concerning exactness, SVM (Backing Vector Machine) delivers improved results when used to analyze coronary illness. It is consequently shown that the recommended system is a solid one for foreseeing cardiovascular sickness previously. The proposed equipment and programming arrangement helps patients in the early identification of heart illness.

关键词： Support vector machines Heart Mortality Programming Solids Vectors Internet Random forests Monitoring Testing

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Advancing quantum imaging through learning theory

arXiv

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arXiv 2025年

作者： Wang, Yunkai Oh, Changhun Liu, Junyu Jiang, Liang Zhou, Sisi Perimeter Institute for Theoretical Physics WaterlooONN2L 2Y5 Canada Department of Applied Mathematics University of Waterloo ONN2L 3G1 Canada Institute for Quantum Computing University of Waterloo ONN2L 3G1 Canada Department of Physics Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of Department of Computer Science The University of Pittsburgh PittsburghPA15260 United States Pritzker School of Molecular Engineering The University of Chicago ChicagoIL60637 United States Department of Physics and Astronomy University of Waterloo ONN2L 3G1 Canada

We quantify performance of quantum imaging by modeling it as a learning task and calculating the Resolvable Expressive Capacity (REC). Compared to the traditionally applied Fisher information matrix approach, REC provides a single-parameter interpretation of overall imaging quality for specific measurements that applies in the regime of finite samples. We first examine imaging performance for two-point sources and generally distributed sources, referred to as compact sources, both of which have intensity distributions confined within the Rayleigh limit of the imaging system. Our findings indicate that REC increases stepwise as the sample number reaches certain thresholds, which are dependent on the source’s size. Notably, these thresholds differ between direct imaging and superresolution measurements (e.g., spatial-mode demultiplexing (SPADE) measurement in the case of Gaussian point spread functions (PSF)). REC also enables the extension of our analysis to more general scenarios involving multiple compact sources, beyond the previously studied scenarios. For closely spaced compact sources with Gaussian PSFs, our newly introduced orthogonalized SPADE method outperforms the naively separate SPADE method, as quantified by REC. Copyright © 2025, The Authors. All rights reserved.

关键词： Fisher information matrix

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FedVQCS: Federated Learning via Vector Quantized Compressed Sensing

arXiv

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arXiv 2022年

作者： Oh, Yongjeong Jeon, Yo-Seb Chen, Mingzhe Saad, Walid The Department of Electrical Engineering POSTECH Gyeongbuk Pohang37673 Korea Republic of The Institute for Convergence Research and Education in Advanced Technology Yonsei University Incheon21983 Korea Republic of The Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States The Wireless@VT Bradley Department of Electrical and Computer Engineering Virginia Tech ArlingtonVA22203 United States

In this paper, a new communication-efficient federated learning (FL) framework is proposed, inspired by vector quantized compressed sensing. The basic strategy of the proposed framework is to compress the local model update at each device by applying dimensionality reduction followed by vector quantization. Subsequently, the global model update is reconstructed at a parameter server by applying a sparse signal recovery algorithm to the aggregation of the compressed local model updates. By harnessing the benefits of both dimensionality reduction and vector quantization, the proposed framework effectively reduces the communication overhead of local update transmissions. Both the design of the vector quantizer and the key parameters for the compression are optimized so as to minimize the reconstruction error of the global model update under the constraint of wireless link capacity. By considering the reconstruction error, the convergence rate of the proposed framework is also analyzed for a non-convex loss function. Simulation results on the MNIST and FEMNIST datasets demonstrate that the proposed framework provides more than a 2.4% increase in classification accuracy compared to state-of-the-art FL frameworks when the communication overhead of the local model update transmission is 0.1 bit per local model entry. Copyright © 2022, The Authors. All rights reserved.

关键词： Vector quantization

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Pre-Equalization Aided Grant-Free Massive Access in Massive MIMO System

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IEEE Transactions on Vehicular Technology 2025年

作者： Wang, Yueqing Mei, Yikun Gao, Zhen Wan, Ziwei Ning, Boyu Mi, De Muhaidat, Sami School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology MIIT Key Laboratory of Complex-Field Intelligent Sensing Beijing100081 China Yangtze Delta Region Academy Jiaxing314019 China Beijing Institute of Technology Advanced Technology Research Institute Jinan250307 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Birmingham City University School of Computing and Digital Technology BirminghamB55JU United Kingdom Khalifa University KU 6 G Research Center Department of Computer and Information Engineering Abu Dhabi United Arab Emirates

The spatial diversity and multiplexing advantages of massive multi-input-multi-output (mMIMO) can significantly improve the capacity of massive non-orthogonal multiple access (NOMA) in machine type communications. However, state-of-the-art grant-free massive NOMA schemes for mMIMO systems require accurate estimation of random access channels to perform activity detection and the following coherent data demodulation, which suffers from excessive pilot overhead and access latency. To address this, we propose a pre-equalization aided grant-free massive access scheme for mMIMO systems, where an iterative detection scheme is conceived. Specifically, the base station (BS) firstly activates one of its antennas (i.e., beacon antenna) to broadcast a beacon signal, which facilitates the user equipment (UEs) to perform downlink channel estimation and pre-equalize the uplink random access signal with respect to the channels associated with the beacon antenna. During the uplink transmission stage, the BS detects UEs' activity and data by using the proposed iterative detection algorithm, which consists of three modules: coarse data detection (DD), data-aided channel estimation (CE), and fine DD. In the proposed algorithm, the joint activity and DD is firstly performed based on the signals received by the beacon antenna. Subsequently, the DD is further refined by iteratively performing data-aided CE module and fine DD module using signals received by all BS antennas. Our simulation results demonstrate that the proposed scheme outperforms state-of-the-art mMIMO-based grant-free massive NOMA schemes with the same access latency. © 1967-2012 IEEE.

关键词： Channel estimation

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Hollywood’s misrepresentation of death: A comparison of overall and by-gender mortality causes in film and the real world

arXiv

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arXiv 2024年

作者： Beauregard, Calla Danforth, Christopher M. Dodds, Peter Sheridan Computational Story Lab Vermont Advanced Computing Center University of Vermont BurlingtonVT05405 United States Vermont Complex Systems Center MassMutual Center of Excellence for Complex Systems and Data Science University of Vermont BurlingtonVT05405 United States Department of Mathematics & Statistics University of Vermont BurlingtonVT05405 United States Department of Computer Science University of Vermont BurlingtonVT05405 United States Santa Fe Institute 1399 Hyde Park Rd Santa FeNM87501 United States

The common phrase ‘representation matters’ asserts that media has a measurable and important impact on civic society’s perception of self and others. The representation of health in media, in particular, may reflect and perpetuate a society’s disease burden. Here, for the top 10 major causes of death in the United States, we examine how cinematic representation of overall and by-gender mortality diverges from reality. Using crowd-sourced data on film deaths from Cinemorgue Wiki, we employ natural language processing (NLP) techniques to analyze shifts in representation of deaths in movies versus the 2021 National Vital Statistic Survey (NVSS) top ten mortality causes. Overall, movies strongly overrepresent suicide and, to a lesser degree, accidents. In terms of gender, movies overrepresent men and underrepresent women for nearly every major mortality cause, including heart disease and cerebrovascular disease. The two exceptions for which women are overrepresented are suicide and accidents. We discuss the implications of under- and over-representing causes of death overall and by gender, as well as areas of future research. © 2024, CC BY-SA.

关键词： Natural language processing systems

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SRCBT: Secure Regeneration of Corrupted Blocks by TPA in Cloud

SRCBT: Secure Regeneration of Corrupted Blocks by TPA in Clo...

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2020 IEEE Region 10 Symposium, TENSYMP 2020

作者： C M, Geeta K S, Tejashwinishivaram R G, Shreyas Raju Buyya, Rajkumar K R, Venugopal Iyengar, S S Patnaik, L M Uvce Bangalore University Department of Computer Science and Engineering Bengaluru India Clouds Lab School of Computing and Information Systems University of Melbourne Australia Bangalore University Bengaluru India Florida International University Department of Computer Science and Engineering United States Insa National Institute of Advanced Studies Indian Institute of Science Campus Bengaluru India

ISBN: (纸本)9781728173665

To conserve the deployed information in cloud repository contrary to adulterations, including fault toleration to cloud repository together with information integrity verification and failure restoration becomes important. Belatedly, reconstructing codes acquire recognition because of their reduced reparation bandwidth while ensuring fault toleration. Prevailing distant auditing schemes for reconstructing-coded information authorizes an intermediary to reconstruct authenticators and information blocks on the suspended servers in the course of the reparation process. To address this issue, we propose Secure Regeneration of Corrupted Blocks by TPA in Cloud (SRCBT). We eliminate the semi-trusted proxy and allow the TPA to reconstruct authenticators and information chunks on the suspended servers in the course of the reparation process. Thus, our mechanism can totally relinquish information proprietors from online burden. The proposed scheme preserves privacy, TPA efficiently reconstructs authenticators and information chunks on the suspended servers in the course of the reparation process and also effectively performs batch auditing. The performance analysis shows that our mechanism is extremely effective and can be conceivably blended into the reconstructing-code-based distributed repository. © 2020 IEEE.

关键词： Codes (symbols)

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PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN with Dual-Discriminators

arXiv

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arXiv 2023年

作者： Cong, Runmin Yang, Wenyu Zhang, Wei Li, Chongyi Guo, Chun-Le Huang, Qingming Kwong, Sam Institute of Information Science Beijing Jiaotong University Beijing100044 China School of Control Science and Engineering Shandong University Jinan250061 China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan250061 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China College of Computer Science Nankai University Tianjin300350 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Peng Cheng Laboratory Shenzhen518055 China Department of Computer Science City University of Hong Kong Hong Kong City University of Hong Kong Shenzhen Research Institute Shenzhen51800 China

Due to the light absorption and scattering induced by the water medium, underwater images usually suffer from some degradation problems, such as low contrast, color distortion, and blurring details, which aggravate the difficulty of downstream underwater understanding tasks. Therefore, how to obtain clear and visually pleasant images has become a common concern of people, and the task of underwater image enhancement (UIE) has also emerged as the times require. Among existing UIE methods, Generative Adversarial Networks (GANs) based methods perform well in visual aesthetics, while the physical model-based methods have better scene adaptability. Inheriting the advantages of the above two types of models, we propose a physical model-guided GAN model for UIE in this paper, referred to as PUGAN. The entire network is under the GAN architecture. On the one hand, we design a Parameters Estimation subnetwork (Par-subnet) to learn the parameters for physical model inversion, and use the generated color enhancement image as auxiliary information for the Two-Stream Interaction Enhancement subnetwork (TSIE-subnet). Meanwhile, we design a Degradation Quantization (DQ) module in TSIE-subnet to quantize scene degradation, thereby achieving reinforcing enhancement of key regions. On the other hand, we design the Dual-Discriminators for the style-content adversarial constraint, promoting the authenticity and visual aesthetics of the results. Extensive experiments on three benchmark datasets demonstrate that our PUGAN outperforms state-of-the-art methods in both qualitative and quantitative metrics. The code and results can be found from the link of https://***/proj_***. © 2023, CC BY-NC-SA.

关键词： Discriminators

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Patients’ and Health Care Professionals’ Expectations of Virtual Therapeutic Agents in Outpatient Aftercare: Qualitative Survey Study

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JMIR Formative Research 2025年 9卷 e59527页

作者： Immel, Diana Hilpert, Bernhard Schwarz, Patricia Hein, Andreas Gebhard, Patrick Barton, Simon Hurlemann, René Department of Psychiatry School of Medicine and Health Sciences Carl von Ossietzky Universität Oldenburg Oldenburg Germany Affective Computing Group Deutsches Forschungszentrum für Künstliche Intelligenz GmbH German Research Center for Artificial Intelligence Kaiserslautern Germany Leiden Institute of Advanced Computer Science Leiden University Snellius Gebouw Leiden Netherlands Department of Computer Science Vrije Universiteit Amsterdam Amsterdam Netherlands Assistance Systems and Medical Device Technology Department for Health Services Research School of Medicine & Health Sciences Carl von Ossietzky Universität Oldenburg Oldenburg Germany

Background: Depression is a serious mental health condition that can have a profound impact on the individual experiencing the disorder and those providing care. While psychotherapy and medication can be effective, there are gaps in current approaches, particularly in outpatient care. This phase is often associated with a high risk of relapse and readmission, and patients often report a lack of support. Socially interactive agents represent an innovative approach to the provision of assistance. Often powered by artificial intelligence, these virtual agents can interact socially and elicit humanlike emotions. In health care, they are used as virtual therapeutic assistants to fill gaps in outpatient aftercare. Objective: We aimed to explore the expectations of patients with depression and health care professionals by conducting a qualitative survey. Our analysis focused on research questions related to the appearance and role of the assistant, the assistant-patient interaction (time of interaction, skills and abilities of the assistant, and modes of interaction) and the therapist-assistant interaction. Methods: A 2-part qualitative study was conducted to explore the perspectives of the 2 groups (patients and care providers). In the first step, care providers (n=30) were recruited during a regional offline meeting. After a short presentation, they were given a link and were asked to complete a semistructured web-based questionnaire. Next, patients (n=20) were recruited from a clinic and were interviewed in a semistructured face-to-face interview. Results: The survey findings suggested that the assistant should be a multimodal communicator (voice, facial expressions, and gestures) and counteract negative self-evaluation. Most participants preferred a female assistant or wanted the option to choose the gender. In total, 24 (80%) health care professionals wanted a selectable option, while patients exhibited a marked preference for a female or diverse assistant. Regrading

关键词： artificial intelligence depression digital health care digital intervention digital technology e-mental health major depressive disorder mental disorder mental illness outpatient aftercare public health socially interactive agent suicidal ideation suicide prevention virtual therapeutic assistant

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qSWIFT: High-order randomized compiler for Hamiltonian simulation

arXiv

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arXiv 2023年

作者： Nakaji, Kouhei Bagherimehrab, Mohsen Aspuru-Guzik, Alán Chemical Physics Theory Group Department of Chemistry University of Toronto TorontoON Canada 1-1-1 Umezono Ibaraki Tsukuba305-8568 Japan Quantum Computing Center Keio University 3-14-1 Hiyoshi Kohoku-ku Kanagawa Yokohama223-8522 Japan Department of Computer Science University of Toronto TorontoON Canada Vector Institute for Artificial Intelligence TorontoON Canada Department of Chemical Engineering & Applied Chemistry University of Toronto TorontoON Canada Department of Materials Science & Engineering University of Toronto TorontoON Canada Canadian Institute for Advanced Research TorontoON Canada

Hamiltonian simulation is known to be one of the fundamental building blocks of a variety of quantum algorithms such as its most immediate application, that of simulating many-body systems to extract their physical properties. In this work, we present qSWIFT, a high-order randomized algorithm for Hamiltonian simulation. In qSWIFT, the required number of gates for a given precision is independent of the number of terms in Hamiltonian, while the systematic error is exponentially reduced with regards to the order parameter. In this respect, our qSWIFT is a higher-order counterpart of the previously proposed quantum stochastic drift protocol (qDRIFT), in which the number of gates scales linearly with the inverse of the precision required. We construct the qSWIFT channel and establish a rigorous bound for the systematic error quantified by the diamond norm. qSWIFT provides an algorithm to estimate given physical quantities using a system with one ancilla qubit, which is as simple as other product-formula-based approaches such as regular Trotter-Suzuki decompositions and qDRIFT. Our numerical experiment reveals that the required number of gates in qSWIFT is significantly reduced compared to qDRIFT. Particularly, the advantage is significant for problems where high precision is required;for example, to achieve a systematic relative propagation error of 10−6, the required number of gates in third-order qSWIFT is 1000 times smaller than that of qDRIFT. © 2023, CC BY.

关键词： Hamiltonians

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