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19th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2024

作者： Amato, Domenico Calderaro, Salvatore Lo Bosco, Giosué Vella, Filippo Rizzo, Riccardo Department of Mathematics and Computer Science University of Palermo Palermo90123 Italy Institute for High-Performance Computing and Networking National Research Council of Italy Palermo90146 Italy

ISBN: (纸本)9783031897030

A transcription factor is a regulatory protein that modulates the transcriptional velocity of genetic information from DNA to mRNA. This protein orchestrates the activation and deactivation of specific genes, thereby regulating their expression to coincide precisely with requisite phases and quantities throughout the cellular lifecycle. This paper introduces an innovative deep-learning methodology designed to ascertain the presence of transcription factors within protein sequences. This method, through a graph-based representation of the sequence, employs a Graph Neural Network for protein classification. We evaluated this novel approach across four datasets derived from the Swiss-Prot database;we achieved promising results that surpass those obtained through traditional fixed-length encodings and conventional machine-learning techniques and are comparable with state-of-the-art deep models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Transcription factors

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Transformers for Interpretable Classification of Histopathological Images 18th

Transformers for Interpretable Classification of Histopath...

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18th International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2023

作者： Amato, Domenico Calderaro, Salvatore Lo Bosco, Giosué Marino, Giuseppe Vella, Filippo Rizzo, Riccardo Department of Mathematics and Computer Science University of Palermo Palermo90123 Italy Institute for High-Performance Computing and Networking National Research Council of Italy Palermo90146 Italy

ISBN: (纸本)9783031907135

Recent studies have shown how machine learning techniques can help and support the analysis of expert physicians’ digitalized biopsy images. In particular, these techniques can improve the process related to some repetitive tasks, provide information, and speed up physician decision-making. Classifiers based on neural networks, particularly those that use Vision Transformers, have proven to be state-of-the-art in several classification tasks. In this paper, we apply vision transformers to classify histological images provided in the BreakHis and GasHisSDB datasets, which collect images from breast and gastric biopsies, respectively. The transformer architecture allows classification performances close to the state-of-the-art, also providing an explainable mechanism based on attention maps that localize and highlight the image regions relevant to the classifier’s decision. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Biopsy

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Online Optimization in Power Systems With high Penetration of Renewable Generation:Advances and Prospects

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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On Error-Based Step Size Control for Discontinuous Galerkin Methods for Compressible Fluid Dynamics

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应用数学与计算数学学报 2025年第1期7卷 3-39页

作者： Hendrik Ranocha Andrew R.Winters Hugo Guillermo Castro Lisandro Dalcin Michael Schlottke-Lakemper Gregor J.Gassner Matteo Parsani Applied Mathematics University of HamburgBundesstr.5520146 HamburgGermany Department of Mathematics Applied Mathematics Linköping UniversityLinköpingSweden Extreme Computing Research Center(ECRC) Computer Electrical and Mathematical Science and Engineering Division(CEMSE)King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Applied and Computational Mathematics RWTH Aachen UniversityAachenGermany High-Performance Computing Center Stuttgart University of StuttgartStuttgartGermany Department of Mathematics and Computer Science University of CologneCologneGermany Center for Data and Simulation Science University of CologneCologneGermany Extreme Computing Research Center(ECRC) Computer Electrical and Mathematical Science and Engineering Division(CEMSE)King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Physical Science and Engineering Division(PSE) King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia

We study a temporal step size control of explicit Runge-Kutta(RK)methods for com-pressible computational fluid dynamics(CFD),including the Navier-Stokes equations and hyperbolic systems of conservation laws such as the Euler *** demonstrate that error-based approaches are convenient in a wide range of applications and compare them to more classical step size control based on a Courant-Friedrichs-Lewy(CFL)*** numerical examples show that the error-based step size control is easy to use,robust,and efficient,e.g.,for(initial)transient periods,complex geometries,nonlinear shock captur-ing approaches,and schemes that use nonlinear entropy *** demonstrate these properties for problems ranging from well-understood academic test cases to industrially relevant large-scale computations with two disjoint code bases,the open source Julia pack-ages *** with *** and the C/Fortran code SSDC based on PETSc.

关键词： Explicit Runge-Kutta(RK)methods Step size control Compressible fluid dynamics Adaptivity in space and time Shock capturing

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Automatic APT Attack Reconstruction Supporting Lateral Movement 2nd

Automatic APT Attack Reconstruction Supporting Lateral Movem...

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2nd International Conference on Security and Information Technologies with AI, Internet computing and Big-data Applications, SITAIBA 2023

作者： Fan, Chun-I Wu, Wei-Chen Shie, Cheng-Han Kuo, Hsin-Nan Lee, Bo-Yi Department of Computer Science and Engineering National Sun Yat-sen University Kaohsiung Taiwan National Center for High-Performance Computing Hsinchu Taiwan Information Security Research Center National Sun Yat-sen University Kaohsiung Taiwan

ISBN: (纸本)9789819777853

This work proposes a framework for generating datasets that allows users to adjust the APT attack techniques within it. The framework utilizes the MITRE ATT&CK framework to label the attack traffic based on the Tactics, Techniques, and Procedures (TTP), which facilitating researchers in using the datasets for model training. Meanwhile, this work uses the framework to reconstruct the APT29 attack process and collect a dataset to validate the framework’s feasibility. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Advanced Persistent Threat (APT) dataset generation The APT29 attack Threat intelligence

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Understanding the catalytic performance and deactivation behaviour of second-promoter doped Pt/WO_(χ)/γ-Al_(2)O_(3) catalysts in the glycerol hydrogenolysis for selective and cleaner production of 1,3-propanediol

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Journal of Energy Chemistry 2024年第7期94卷 486-507页

作者： Rafik Rajjak Shaikh Sittichai Damruang Rais Ahmad Khan Supareak Praserthdam Piyasan Praserthdam Center of Excellence on Catalysis and Catalytic Reaction Engineering(CECC) Department of Chemical EngineeringFaculty of EngineeringChulalongkorn UniversityBangkok 10330Thailand Department of Chemistry College of ScienceKing Saud UniversityP.O.Box 2455Riyadh 11451Saudi Arabia High-Performance Computing Unit(CECC-HCU) Centre of Excellence on Catalysis and Catalytic Reaction Engineering(CECC)Department of Chemical EngineeringFaculty of EngineeringChulalongkorn UniversityBangkok 10330Thailand

The selective aqueous-phase glycerol hydrogenolysis is a promising reaction to produce commercially useful 1,3-propanediol(1,3-PDO).The Pt-WOx bifunctional catalyst can catalyse the glycerol hydrogenol-ysis but the catalyst deactivation via sintering,metal leaching,and coking can predominantly occur in the aqueous phase *** this work,the effect of reaction temperature,pressure and second promoter(Cu,Fe,Rh,Mn,Re,Ru,Ir,Sn,B,and P)on catalytic performance and deactivation behaviour of Pt/WOx/-Al2O3 was *** doped with Rh,Mn,Re,Ru,Ir,B,and P,the second promoter boosts catalytic activity by promoting great dispersion of Pt on support and increasing Pt surface *** increased Bronsted acid sites lead to selective synthesis of 1,3-PDO than 1,2-propanediol(1,2-PDO).The characterization studies of fresh and spent catalysts reveal that the main cause of catalyst deactivation is the Pt sintering,as interpreted based on XRD,CO chemisorption,and TEM *** Pt sintering is affected depending on the second promoter that can either or reduce the interaction between Pt,WO_(χ)/γ and Al_(2)O_(3).As an electron acceptor of Pt in Pt/WO_(χ)/γ-Al_(2)O_(3),Re and Mn as second promoters resulted in increased Pt^(2+) on the catalytic surface,which strengthens the contact between Pt andγ-Al_(2)O_(3) and WO_(χ),resulting in a decrease in Pt *** metal leaching and coking are not affected by the presence of second *** catalyst modified with a second promoter possesses improved catalytic activity and 1,3-PDO production,however the stability continues to remain a *** present work unrav-elled the determining parameters of catalytic activity and deactivation,thus providing a promising pro-tocol toward effective catalysts for glycerol hydrogenolysis.

关键词： Glycerol hydrogenolysis 1,3-propanediol Metal-support interaction Second promoter Liquid phase Catalyst deactivation

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Customisable sound absorption properties of functionally graded metallic foams

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Journal of Materials science & Technology 2022年第13期108卷 196-207页

作者： Jun Wei Chua Xinwei Li Tao Li Beng Wah Chua Xiang Yu Wei Zhai Department of Mechanical Engineering National University of Singapore117575Singapore Agency for Science Technology and Research(A^(*)STAR)Singapore Institute of Manufacturing Technology138634Singapore Agency for Science Technology and Research(A^(*)STAR)Engineering MechanicsInstitute of High-Performance Computing1 Fusionopolis Way138632Singapore

In this study,functionally graded foam made of Inconel 625 superalloy was successfully produced using the template replication method,with open-cell polyurethane foams as a *** products have a similar pore morphology as the templates and adjacent layers were successfully sintered together by particle *** absorption experiments on graded metallic foams reveal that the sound absorption at particular frequency ranges can be improved by various permutations of foam *** graded foam of two distinct pore sizes,a mathematical equation was proposed to predict the location of the intersection point of the sound absorption curves,thereby aiding in graded foam *** increase in sound absorption coefficients by resonance-like effects can be introduced before the intersection points by placing the foam layer of smaller pore size nearer to the sound *** sound absorption performances can be further customized when the thickness proportion of the pore sizes is changed and when the number of distinct pore sizes used is *** sound absorption performance at lower frequencies is generally boosted by resonance-like effects when the layer of foam with the largest pore size is placed furthest from the sound *** the same composition of foam with a fixed thickness proportion of pore sizes,one can introduce resonance-like effects to improve the sound absorption performance compared to other permutations while possibly satisfying weight requirements in practical *** study provides valuable insights and mathematical guidelines in the design and manufacturing of functionally graded metallic foam for specific applications.

关键词： Template replication method Functionally graded foam Sound absorption Transfer matrix method Composite metal foam

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Research on key technologies of edge cache in virtual data space across WAN

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Frontiers of Computer science 2023年第1期17卷 15-34页

作者： Jiantong HUO Yaowen XU Zhisheng HUO Limin XIAO Zhenxue HE State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China High Performance Computing Center Beihang UniversityBeijing 100191China College of Software Beihang UniversityBeijing 100191China Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China College of Computer Science and Technology Zhejiang UniversityHangZhou 310013China

The authors of this paper have previously proposed the global virtual data space system (GVDS) to aggregate the scattered and autonomous storage resources in China’s national supercomputer grid (National Supercomputing Center in Guangzhou, National Supercomputing Center in Jinan, National Supercomputing Center in Changsha, Shanghai Supercomputing Center, and Computer Network Information Center in Chinese Academy of sciences) into a storage system that spans the wide area network (WAN), which realizes the unified management of global storage resources in China. At present, the GVDS has been successfully deployed in the China National Grid environment. However, when accessing and sharing remote data in the WAN, the GVDS will cause redundant transmission of data and waste a lot of network bandwidth resources. In this paper, we propose an edge cache system as a supplementary system of the GVDS to improve the performance of upper-level applications accessing and sharing remote data. Specifically, we first designs the architecture of the edge cache system, and then study the key technologies of this architecture: the edge cache index mechanism based on double-layer hashing, the edge cache replacement strategy based on the GDSF algorithm, the request routing based on consistent hashing method, and the cluster member maintenance method based on the SWIM protocol. The experimental results show that the edge cache system has successfully implemented the relevant operation functions (read, write, deletion, modification, etc.) and is compatible with the POSIX interface in terms of function. Further, it can greatly reduce the amount of data transmission and increase the data access bandwidth when the accessed file is located at the edge cache system in terms of performance, i.e., its performance is close to the performance of the network file system in the local area network (LAN).

关键词： virtual data space system wide area network edge cache redundant data transmission

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Traffic Object Detection System Based on YOLOv5 for V2V Communications

Traffic Object Detection System Based on YOLOv5 for V2V Comm...

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2023 International Russian Automation Conference, RusAutoCon 2023

作者： Abdulnagimov, Ansaf Klyavlin, Nail Alektorov, Gleb Ufa University of Science and Technology Automated Control and Management Department Ufa Russia Ufa University of Science and Technology Department of High-Performance Computing Technologies and Systems Ufa Russia Ufa University of Science and Technology Department of Computational Mathematics and Cybernetics Ufa Russia

ISBN: (纸本)9798350345551

The deep learning techniques on the base of YOLOv5 architecture have been shown to make a traffic objects detection system for V2V communications to ensure traffic safety and traffic flows prediction. According to the detection data the detector allows to estimate the traffic object speed and the coordinates of movement. To improve the accuracy of calculations, the distortion correction algorithm (in geometric optics), the Chang method and the Kalman filter are used. To set the detector to work in online operation mode, an algorithm has been developed that receives video stream from open city surveillance cameras with the processing of a m3u8 playlist. The developed detector can be used on "connected"vehicles to assess the situation on the roads and ensure safety traffic. © 2023 IEEE.

关键词： Object detection

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Mobility-Aware Deep Reinforcement Learning with Seq2seq Mobility Prediction for Offloading and Allocation in Edge computing

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IEEE Transactions on Mobile computing 2024年第6期23卷 6803-6819页

作者： Wu, Chao-Lun Chiu, Te-Chuan Wang, Chih-Yu Pang, Ai-Chun Academia Sinica Research Center for Information Technology Innovation Taipei115 Taiwan National Tsing Hua University Department of Computer Science Hsinchu300 Taiwan National Taiwan University Institute of Networking and Multimedia Taipei10617 Taiwan National Taiwan University High Performance and Scientific Computing Center Taipei10617 Taiwan

Mobile/multi-access edge computing (MEC) is developed to support the upcoming AI-aware mobile services, which require low latency and intensive computation resources at the edge of the network. One of the most challenging issues in MEC is service provision with mobility consideration. It has been known that the offloading decision and resource allocation need to be jointly handled to optimize the service provision efficiency within the latency constraints, which is challenging when users are in mobility. In this paper, we propose Mobility-Aware Deep Reinforcement Learning (M-DRL) framework for mobile service provision in the MEC system. M-DRL is composed of two parts: glimpse, a seq2seq model customized for mobility prediction to predict a sequence of locations just like a 'glimpse' of the future, and a DRL specialized in supporting offloading decisions and resource allocation in MEC. By integrating the proposed DRL and glimpse mobility prediction model, the proposed M-DRL framework is optimized to handle the MEC service provision with average 70% performance improvements. © 2002-2012 IEEE.

关键词： Reinforcement learning

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