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A residual attention-based privacy-preserving biometrics model of transcriptome prediction from genome

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A residual attention-based privacy-preserving biometrics mod...

IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Cheng Tian Song Liu Jinbao Li Guangchen Wang Luyue Kong Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Department of Medicine Shandong Medical College Jinan China

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Transcriptome prediction from genetic variation data is an important task in the privacy-preserving and biometrics field, which can better protect genomic data and achieve biometric recognition through transcriptome. Many transcriptome prediction methods have achieved good accuracy from genetic variation data. However, these traditional transcriptome prediction methods have the problems of linear assumption, overfitting, expose personal privacy, and extensive manual optimization. To solve these shortcomings, we propose an attention-based transcriptome prediction model from genetic variation named RATPM that improves the accuracy of transcriptome prediction and protects participant genomic data. In RATPM, we introduce and improve the deep learning model with multi-head self-attention into the transcriptome prediction stage of Predixcan, which uncovers the non-linear relationship between genetic variation and transcriptome. Moreover, we introduce a residual attention module to generate attention-aware features and extract more accurate features at different levels from genetic variation. Furthermore, we introduce the BERT pre-training module to encode genetic variation fully utilizing their contextual information. Our research enables scientific institutions to publish only predicted transcriptomic data for biometric purposes, thus protecting the genomic information of the subjects. Finally, we evaluated our model on the 1000 Genomes and Geuvadis projects datasets to compare with other baseline models.

关键词： Privacy Biometrics (access control) Biological system modeling Genomics Predictive models Feature extraction Gene expression

Schwarz methods by domain truncation

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arXiv 2022年

作者： Gander, Martin J. Zhang, Hui Department of Mathematics University of Geneva CP64 Geneva 41211 Switzerland Department of Applied Mathematics Laboratory for Intelligent Computing & Financial Technology Xi'an Jiaotong-Liverpool University Suzhou215123 China

Schwarz methods use a decomposition of the computational domain into subdomains and need to put boundary conditions on the subdomain boundaries. In domain truncation one restricts the unbounded domain to a bounded computational domain and also needs to put boundary conditions on the computational domain boundaries. In both fields there are vast bodies of literature and research is very active and ongoing. It turns out to be fruitful to think of the domain decomposition in Schwarz methods as truncation of the domain onto subdomains. Seminal precursors of this fundamental idea are Hagstrom, Tewarson and Jazcilevich (1988), Després (1990) and Lions (1990). The first truly optimal Schwarz method that converges in a finite number of steps was proposed in Nataf (1993) and used precisely transparent boundary conditions as transmission conditions between subdomains. Approximating these transparent boundary conditions for fast convergence of Schwarz methods led to the development of optimized Schwarz methods - a name that has become common for Schwarz methods based on domain truncation. Compared to classical Schwarz methods which use simple Dirichlet transmission conditions and have been successfully used in a wide range of applications, optimized Schwarz methods are much less well understood, mainly due to their more sophisticated transmission *** Codes 65Y05 © 2022, CC BY.

关键词： Boundary conditions

LSN:Long-Term Spatio-Temporal Network for Video Recognition

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LSN:Long-Term Spatio-Temporal Network for Video Recognition

作者： Zhenwei Wang Wei Dong Bingbing Zhang Jianxin Zhang School of Computer Science and Engineering Dalian Minzu University SEAC Key Laboratory of Big Data Applied Technology Dalian Minzu University Institute of Machine Intelligence and Bio-Computing Dalian Minzu University School of Information and Communication Engineering Dalian University of Technology

Although recurrent neural networks(RNNs) are widely leveraged to process temporal or sequential data,they have attracted too little attention in current video action recognition ***,this work attempts to model the long-term spatio-temporal information of the video based on a variant of RNN,i.e.,higher-order ***,we propose a novel long-term spatio-temporal network(LSN) for solving this video task,the core of which integrates the newly constructed high-order ConvLSTM(HO-ConvLSTM) modules with traditional2D convolutional ***,each HO-Conv LSTM module consists of an accumulated temporary state(ATS) module as well as a standard Conv LSTM module,and several previous hidden states in the ATS module are accumulated to one temporary state that will enter the standard Conv LSTM to determine the output together with the current *** HO-Conv LSTM module can be inserted into different stages of the 2D convolutional neural network(CNN) in a plug-andplay manner,thus well characterizing the long-term temporal evolution at various spatial *** results on three commonly used video benchmarks demonstrate that the proposed LSN model can achieve competitive performance with the representative models.

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IoT Urban River Water Quality System Using Federated Learning via Knowledge Distillation

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IoT Urban River Water Quality System Using Federated Learnin...

IEEE International Conference on Communications (ICC)

作者： Amine Dahane Rabaie Benameur Manel Naloufi Sami Souihi Thiago Abreu Francoise S. Lucas Abdelhamid Mellouk Laboratory of Industrial Computing and Networks (RIIR) University of Oran 1 Oran Algeria Institute of Applied Science and Technology ISTA Oran Algeria Image Signal and Intelligent Systems (LiSSi) Laboratory TincNET Research Team Univ. Paris-Est Créteil France Laboratoire Eau Environnement et Systèmes Urbains (Leesu) Univ. Paris-Est Créteil École des Ponts ParisTech France

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

In the past decades, the use of urban rivers for recreational and sporting activities has gained increasing interest. However, bathing in urban surface waters is not without health risks due to short-term pollution of fecal origin, which may have an important impact on the overall population health within a region where bathing in water streams is possible. Therefore, EU member states are required to lower the contamination risk of such areas through active water quality management, as defined by the Bathing Water directory (BWD, 2006/7/EC). This paper develops and evaluates a cost-effective IoT-based water quality monitoring system, based on low-cost water quality sensors coupled with machine-learning approaches. By monitoring spatiotemporal dynamics of several physical and chemical parameters correlated with bacterial indicators, managers can more easily decide if the water quality of a bathing site is enough for usage. To determine the water suitability at particular river sites, the system employs a convolutional neural network (CNN) deep learning classifier, integrating federated learning (FL) with knowledge distillation (FedKD) to streamline model architecture, reduce communication costs, and preserve data privacy. The system is tested on the Seine and the Marne rivers (Paris area, France) and results demonstrate that FedKD outperforms centralized knowledge distillation (KD) and FL algorithms such as FedAvg and UFedAVG. Using the current features, it achieves a satisfactory average accuracy of 90.74% at Marne station.

关键词： Federated learning Surface contamination Water quality Water pollution Rivers Spatiotemporal phenomena Convolutional neural networks

Exploration of core concepts required for mid- and domain-level ontology development to facilitate explainable-AI-readiness of data and models 4

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Exploration of core concepts required for mid- and domain-le...

4th International Workshop on Data meets Ontologies in Explainable AI, DAO-XAI 2024

作者： Horsch, Martin T. Chiacchiera, Silvia Todorov, Ilian T. Correia, Ana Teresa Dey, Aditya Konchakova, Natalia A. Scholze, Sebastian Stephan, Simon Tøndel, Kristin Sarkar, Arkopaul Karray, M. Hedi Al Machot, Fadi Schembera, Björn Norwegian University of Life Sciences Department of Data Science Postboks 5003 Ås1432 Norway UKRI Science and Technology Facilities Council Scientific Computing Department DaresburyWA4 4AD United Kingdom ATB Institut für Angewandte Systemtechnik Bremen GmbH Wiener Str. 1 Bremen28359 Germany Helmholtz-Zentrum Hereon Institute of Surface Science Max-Planck-Str. 1 Geesthacht21502 Germany RPTU Kaiserslautern Laboratory of Engineering Thermodynamics Kaiserslautern67663 Germany University of Technology Tarbes Occitanie Pyrénées Production Engineering Lab. 47 av. d’Azereix Tarbes France University of Stuttgart Institute of Applied Analysis and Numerical Simulation Stuttgart70569 Germany

This position paper reports on the initial discussions within the Knowledge Graph Alliance’s working group on explainable-AI-ready data and metadata principles, which was created in March 2024. At present, we are taking initial steps toward capturing core concepts related to explanation, grounding, reliance, and trust;the scope also extends to potential dual notions such as explainability, verifiability/reproducibility, reliability, and trustworthiness. These initial steps consist in reviewing core concepts as they are discussed in the literature and exploring what could be practically useful definitions of these most central concepts. One of the conclusions is that the metadata standards will need to be suitable for documenting three kinds of grounding: Grounding of knowledge, grounding of reliance, and grounding of trust. Pre-existing metadata standards at the mid and domain level are presently undergoing a redesign in order to become more modular, computationally tractable, intelligible to humans, and adjustable, which will be needed as we continue our work toward actionable recommendations. The development of this system of lite (OWL 2 EL) ontologies, called MSO-EM: Ontologies for modelling, simulation, optimization (MSO) and epistemic metadata (EM), is carried out on a public repository. © 2024 Copyright for this paper by its authors.

关键词： applied ontology epistemic metadata explainable-AI-ready (XAIR) ontology redesign reliability reproducibility

Optimizing Neighborhood Area Network Topology for Enhanced Communication in Smart Grid

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IEEE Transactions on Consumer Electronics 2025年

作者： Li, Jian-Hui Ding, Yuemin Yu, Zu-Guo Zhang, Weizhe Ren, Honglin Tian, Yu-Chu Xiangtan University National Center for Applied Mathematics in Hunan Key Laboratory of Intelligent Computing and Information Processing of the Ministry of Education of China Xiangtan University Hunan 411105 China Queensland University of Technology School of Computer Science BrisbaneQLD Australia University of Navarra Ikerbasque Foundation Tecnun School of Engineering San Sebastián Spain Bilbao Spain Harbin Institute of Technology School of Computer Science and Technology Shenzhen China

In modern power grids, smart meters, as a type of consumer electronics, act as metering and communication nodes, which form Neighborhood Area Networks (NANs) spanning electricity distribution networks from substations to energy producers and consumers. In smart meter communication, wireless technologies have been widely adopted due to their inherent advantages of easier installation, flexibility, and low cost. For achieving low-latency communications in NANs, it is crucial to optimize the existing topology to enhance communication efficiency. However, optimizing the NAN topology is a challenging task due to the computational infeasibility of obtaining the optimal solution. To tackle this challenge, topology optimization in NANs is first formulated into a combinatorial optimization problem. After that, a heuristic solution driven by complex network theory is presented to solve the formulated optimization problem. The proposed heuristic solution consists of an effective network rewiring scheme and a long-range edge connection strategy. The rewiring optimizes the topology of wireless NANs to reduce local network length, whilst the long-range edge connection best pairs a small number of NAN nodes to reduce global network length. Numerical studies are conducted on diverse case studies to demonstrate the presented solution to enhance communication efficiency in smart grid NANs, outperforming the benchmark schemes. © 1975-2011 IEEE.

关键词： Combinatorial optimization

Period Variation Rates of Four Radial Single-Mode High-Amplitude Delta Scuti Stars

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arXiv 2025年

作者： Ma, Tian-Fang Niu, Jia-Shu Xue, Hui-Fang Institute of Theoretical Physics Shanxi University Taiyuan030006 China State Key Laboratory of Quantum Optics Technologies and Devices Shanxi University Taiyuan030006 China Collaborative Innovation Center of Extreme Optics Shanxi University Taiyuan030006 China Department of Physics Taiyuan Normal University Jinzhong030619 China Institute of Computational and Applied Physics Taiyuan Normal University Jinzhong030619 China Shanxi Key Laboratory for Intelligent Optimization Computing and Blockchain Technology Jinzhong030619 China

In this work, we present a study on the long time-scale period variations of four single-mode high-amplitude delta Scuti stars (HADS) via the classical O − C analysis. The target HADS are (i) XX Cygni, (ii) YZ Bootis, (iii) GP Andromedae, and (iv) ZZ Microscopii. The newly determined times of maximum light came from the Transiting Exoplanet Survey Satellite (TESS), American Association of Variable Star Observers (AAVSO), and Bundesdeutsche Arbeitsgemeinschaft für Veränderliche Sterne (BAV) projects. Together with the times of maximum light obtained in the historical literature, the O − C analysis was performed on these HADS, in which we obtained the linear period variation rates P/P as (9.2 ± 0.2) × 10−9 yr−1, (3.2 ± 0.2) × 10−9 yr−1, (4.22 ± 0.03) × 10−8 yr−1, and (−2.06 ± 0.02) × 10−8 yr−1, respectively. Based on these results and some earlier research, we also discuss the evolutionary stages and the mechanisms of the period variation of these four HADS. © 2025, CC BY.

关键词： Pulsars

vailá: VERSATILE ANARCHO INTEGRATED LIBERATION ÁNALYSIS IN MULTIMODAL TOOLBOX

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arXiv 2024年

作者： Santiago, Paulo Roberto Pereira Chinaglia, Abel Gonçalves Flanagan, Kira Bedo, Bruno L.S. Mochida, Ligia Yumi Aceros, Juan Bononi, Aline Cesar, Guilherme Manna Biomechanics and Motor Control Laboratory School of Physical Education and Sport USP Brazil Graduate Program in Rehabilitation and Functional Performance Medical School USP Brazil Technology and Sports Performance Analysis Laboratory School of Physical Education USP Brazil Laboratory of Applied Biomechanics and Engineering Brooks College of Health UNF United States Department of Physical Therapy Brooks College of Health UNF United States College of Computing Engineering and Construction UNF United States Municipal Pharmacy Ribeirão Preto Brazil

Human movement analysis is crucial in health and sports biomechanics for understanding physical performance, guiding rehabilitation, and preventing injuries. However, existing tools are often proprietary, expensive, and function as "black boxes", limiting user control and customization. This paper introduces vailá—Versatile Anarcho Integrated Liberation Ánalysis in Multimodal Toolbox—an open-source, Python-based platform designed to enhance human movement analysis by integrating data from multiple biomechanical systems. vailá supports data from diverse sources, including retroreflective motion capture systems, inertial measurement units (IMUs), markerless video capture technology, electromyography (EMG), force plates, and GPS/GNSS systems, enabling comprehensive analysis of movement patterns. Developed entirely in Python 3.11.9, which offers improved efficiency and long-term support, and featuring a straightforward installation process, vailá is accessible to users without extensive programming experience. In this paper, we also present several workflow examples that demonstrate how vailá allows the rapid processing of large batches of data, independent of the type of collection method. This flexibility is especially valuable in research scenarios where unexpected data collection challenges arise, ensuring no valuable data point is lost. We demonstrate the application of vailá in analyzing sit-to-stand movements in pediatric disability, showcasing its capability to provide deeper insights even with unexpected movement patterns. By fostering a collaborative and open environment, vailá encourages users to innovate, customize, and freely explore their analysis needs, potentially contributing to the advancement of rehabilitation strategies and performance optimization. For more details in GitHub repository: https://***/vaila-multimodaltoolbox/vaila and the online documentation: https://*** Codes 92C10, 68U10, 65D18, 65K10 © 2024, CC BY-SA.

关键词： Electromyography

Discovery of resonating integration modes in triple-mode high-amplitude δ Scuti stars: a new evolutionary phase indicator

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arXiv 2025年

作者： Niu, Jia-Shu Xue, Hui-Fang Institute of Theoretical Physics Shanxi University Taiyuan030006 China State Key Laboratory of Quantum Optics Technologies and Devices Shanxi University Taiyuan030006 China Collaborative Innovation Center of Extreme Optics Shanxi University Taiyuan030006 China Department of Physics Taiyuan Normal University Jinzhong030619 China Institute of Computational and Applied Physics Taiyuan Normal University Jinzhong030619 China Shanxi Key Laboratory for Intelligent Optimization Computing and Blockchain Technology Jinzhong030619 China

High-amplitude δ Scuti stars (HADS) that pulsate in their first three radial modes are rare in current samples. Here, we analyse five such triple-mode HADS observed by the Transiting Exoplanet Survey Satellite (TESS) and report that the previously considered second overtone mode (f2) is actually the non-radial component of a resonating integration mode (RI mode, resulting from resonance between a radial p-mode and a non-radial p-g mixed mode), which shows significant amplitude and frequency variations over short timescales (approximately 20 days). This RI mode appears to be widespread among these stars. Notably, all five stars are in the post-main sequence evolutionary phase, actively crossing the Hertzsprung gap. These stars offer valuable insights into stellar evolution during the Hertzsprung gap, which is one of the most rapid evolutionary stages in a star’s life. © 2025, CC BY.

关键词： Image retrieval