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检索条件"任意字段=International Conference on Embedded Computer Systems Architectures Modeling and Simulation"

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Autism Disease Prediction Using Deep Learning & Transfer Learning

Autism Disease Prediction Using Deep Learning & Transfer Lea...

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international conference on Networking, embedded and Wireless systems (ICNEWS)

作者： Abhishek Das Towhidul Alam Md. Zihad Hossain Habiba Rashid Lamiya Department of Electrical and Computer Engineering North South University Dhaka Bangladesh

ISBN: (数字)9798350367461

ISBN: (纸本)9798350367478

The neurological disease known as autism spectrum disorder (ASD) is characterized by impaired social interaction, communication issues, and constrained and repetitive behavior patterns. For the benefit of early interventions and support for afflicted persons, timely and accurate ASD prognosis is essential. Deep learning methods have become effective tools for predictive modeling across a range of industries, including healthcare. This study examines the use of deep learning and transfer learning to forecast ASD using a large dataset of clinical and behavioral variables. In this study, the effectiveness of three well-known deep learning architectures VGG16, DenseNet121, and MobileNetv2 in predicting ASDs is compared. A sizable dataset with a variety of ASD-related variables, such as demographic data, medical histories, and behavioral assessments, is used to train the models. To take use of pre-learned weights from models trained on extensive generic image recognition tasks, transfer learning is used. With accuracy rates of 97% apiece, the experimental results show remarkable prediction performance for VGG16 and DenseNet121. These models have significant generalization abilities that make it possible to make reliable predictions for identifying those who are at risk for ASD. In contrast to the other architectures, MobileNetv2 only obtains an accuracy of 73%. The results show that deeper architectures like VGG16 and DenseNet121 capture the rich patterns and fine details of the input data, resulting in more precise predictions. Additionally, thorough investigations are carried out to look into the models' learned representations and pinpoint the primary features that influence ASD prediction. These revelations aid in a better comprehension of the underlying causes and potential biomarkers of ASD. The information gleaned from these studies can direct ongoing research projects and support the creation of individualized interventions and therapies. Overall, the study empha

关键词： Deep learning Wireless communication Autism Accuracy Biological system modeling Transfer learning Predictive models Biomarkers Reliability Prognostics and health management

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HelioCubed: A High Order Inner Heliosphere simulation Code with a Mapped Cubed Sphere Grid and Adaptive Mesh Refinement 16

HelioCubed: A High Order Inner Heliosphere Simulation Code w...

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16th international conference on Numerical modeling of Space Plasma Flows, ASTRONUM 2024

作者： Singh, Talwinder Colella, Phillip Van-Straalen, Brian Bozhart, Chris Pogorelov, Nikolai V. Department of Physics & Astronomy Georgia State University AtlantaGA30303 United States Applied Numerical Algorithms Group Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Electrical Engineering and Computer Science Department University of California Berkeley BerkeleyCA94720 United States Department of Space Science The University of Alabama in Huntsville HuntsvilleAL35805 United States Center for Space Plasma and Aeronomic Research The University of Alabama in Huntsville HuntsvilleAL35805 United States

We present the HelioCubed, a high-order magnetohydrodynamic (MHD) code designed for modeling the inner heliosphere. The code is designed to achieve 4th order accuracy both in space and in time. In addition, HelioCubed can perform simulations on mapped grids, such as those based on cubed spheres, which makes it possible to overcome stability limitations caused by the geometrical singularity at the polar axis of a spherical grid, thus enabling substantially larger time steps. HelioCubed has been developed using the high-level Proto library, ensures performance portability across CPU and GPU architectures, and supports back-end implementations, e.g., CUDA, HIP, OpenMP, and MPI. The code is compatible with the HDF5 library, which facilitates seamless data handling for simulations and boundary conditions derived from semi-empirical and MHD models of the solar corona. While presenting the results of preliminary simulations, we demonstrate that our simulations are indeed performed with 4th order of accuracy. Our approach ensures that HelioCubed solves the MHD equations preserving the radial flow to machine round-off error even on cubed-sphere grids. Solar wind simulations are performed using the boundary conditions provided by the Wang-Sheeley-Arge coronal model of the ambient solar wind. It also allows us to to simulate coronal mass ejections using observation-driven flux rope models. These capabilities make HelioCubed a versatile and powerful tool to advance heliophysics research and space weather forecasting. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Mesh generation

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Systematic Synthesis of Energy-Aware Timing Models in Automotive Software systems 8th

Systematic Synthesis of Energy-Aware Timing Models in Automo...

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8th international conference on Model-Driven Engineering and Software Development (MODELSWARD)

作者： Iyenghar, Padma Univ Osnabrueck Software Engn Res Grp Osnabruck Germany

ISBN: (纸本)9783030674441;9783030674458

In automotive embedded software, functions have several performance requirements such as timing, energy, safety and reliability. For such complex software architectures, an early evaluation and decision on the best set of performance configuration (e.g. timing vs energy trade-offs) could save costly corrections of potential errors in the design. For example, appropriate performance analysis workflows and frameworks if employed already during early design stages, allow us to understand the performance aspects and behavior of the system depending on software and hardware characteristics. The main input required for such analysis is the performance-analysis model based on the underlying design model. In this context, this chapter presents a workflow for synthesis of energy-aware timing analysis models for AUTOSAR-based embedded software systems developed using the Unified modeling Language (UML)/systems modeling Language (SysML) domains. A prototype of the model transformations for the synthesis of the energy-aware timing models and its evaluation in an automotive use case is presented.

关键词： Energy-aware timing model AUTOSAR Unified modeling language (UML) Synthesis Meta-model Model transformation

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Memristor-based High Speed and Area Efficient Comparators in IMPLY Logic

Memristor-based High Speed and Area Efficient Comparators in...

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international conference on VLSI Design

作者： Nandit Kaushik B. Srinivasu School Of Computing & Electrical Engineering Indian Institute of Technology Mandi Mandi India

Because of its In-Memory-Computation (IMC) capacity and low area footprint, memristive technology is a rapidly growing alternative to traditional computer architectures. Using IMPLY logic, this research proposes an efficient multi-bit comparator architecture in memristor technology. This article proposes three one-bit comparator designs, two of which conduct serial computations and the other performs parallel computations. An area efficient comparator design takes only four memristors to make the comparison in thirteen computational steps by reusing the input memristors. When the number of memristors that are reused decreases, the design speed increases. This is seen in the second serial comparator design, which computes the result in only eight steps using six memristors. A comparator design with seven memristors that performs the parallel computations takes only six steps to compute the output. The proposed method can be extended to multi-bit designs. A two-bit high speed comparator is also proposed, which takes twenty-two steps to perform the magnitude comparison. The proposed comparator designs were simulated in the Cadence Virtuoso using the VTEAM model.

关键词： embedded systems Computational modeling Memristors computer architecture Very large scale integration Computational efficiency

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Towards Web Platform for Cloud-Based Virtual Commissioning of IEC 61499 Distributed Automation systems

Towards Web Platform for Cloud-Based Virtual Commissioning o...

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international conference on Emerging Technologies and Factory Automation (ETFA)

作者： Tuojian Lyu Tung Nguyen Roman Rumiantsev Mikhail Kolesnikov Hansani Perera Udayanto Dwi Atmojo Valeriy Vyatkin Department of Electrical Engineering and Automation Aalto University Espoo Finland Department of Computer Science Computer and Space Engineering Luleå Tekniska Universitet Sweden

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

In this paper, we propose a cloud-based virtual commissioning Web platform for IEC 61499 compliant distributed automation systems that support Create-Read-Update-Delete operations for SoftPLC containers from various versions and provide a remote engineering workstation with an embedded web Integrated Development Environment (IDE), Human Machine Interface (HMI), and 3D simulation models. A water tank use case demonstrates the platform's flexibility, enabling control software testing entirely via a Web browser without local installations.

关键词： Water Software testing Cloud computing Solid modeling Three-dimensional displays Human-machine systems Storage management Workstations IEC Standards Manufacturing automation

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WE-HML: hybrid WCET estimation using machine learning for architectures with caches 27

WE-HML: hybrid WCET estimation using machine learning for ar...

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27th IEEE international conference on embedded and Real-Time Computing systems and Applications (RTCSA)

作者： Amalou, Abderaouf N. Puaut, Isabelle Muller, Gilles Univ Rennes Rennes France Inria Paris Rennes France

ISBN: (纸本)9781665441889

Modern processors raise a challenge for WCET estimation, since detailed knowledge of the processor micro-architecture is not available. This paper proposes a novel hybrid WCET estimation technique, WE-HML, in which the longest path is estimated using static techniques, whereas machine learning (ML) is used to determine the WCET of basic blocks. In contrast to existing literature using ML techniques for WCET estimation, WE-HML (i) operates on binary code for improved precision of learning, as compared to the related techniques operating at source code or intermediate code level;(ii) trains the ML algorithms on a large set of automatically generated programs for improved quality of learning;(iii) proposes a technique to take into account data caches. Experiments on an ARM Cortex-A53 processor show that for all benchmarks, WCET estimates obtained by WE-HML are larger than all possible execution times. Moreover, the cache modeling technique of WE-HML allows an improvement of 65 percent on average of WCET estimates compared to its cache-agnostic equivalent.

关键词： Maximum likelihood estimation Program processors Pollution Machine learning computer architecture Benchmark testing Prediction algorithms

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Stability Analysis for Frequency Tunable Bandpass Delta-Sigma ADC architectures

Stability Analysis for Frequency Tunable Bandpass Delta-Sigm...

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international conference on Synthesis, modeling, Analysis and simulation Methods and Applications to Circuit Design (SMACD)

作者： Jesko Flemming Bernhard Wicht Pascal Witte Department of Integrated Circuits and Embedded Systems University of Applied Sciences and Arts Hanover Germany Institute of Microelectronic Systems Leibniz Universitat Hannover Hanover Germany Laboratory of Nano and Quantum Engineering Leibniz Universitat Hannover Hanover Germany

This paper presents bandpass delta-sigma modulator (BP-Δ∑M) structures, which are specifically suited for frequency tuning. The structures are identified through stability analyses and comparisons between chain of resonators feedforward (CRFF) and chain of resonators feedback (CRFB) delta-sigma modulator (Δ∑M) configurations. Frequency tuning is predominantly achieved through altering the resonator coefficients. Therefore, the paper guides designers though the analysis process for identifying suitable tunable BP-Δ∑M structures. When moderately changing the resonators the structures perform almost identical to a non-tunable modulator optimized for the same frequency. For large frequency shifts, the out-of-band gain (OOBG) of the signal transfer function (STF) and noise transfer function (NTF) in the CRFF structure, drastically increases and the control loop becomes unstable. It is shown how utilizing CRFB structures is advantageous for frequency tuning and that the OOBG in CRFF structures can be compensated through a unity STF (USTF) Δ∑M structure.

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Floating-Point Number Scalar Product Hardware Implementation for embedded systems

Floating-Point Number Scalar Product Hardware Implementation...

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international conference on CAD systems in Microelectronics (CADSM)

作者： Ivan Tsmots Vasyl Rabyk Vasyl Teslyuk Yurii Opotyak Department of Automated Control Systems Lviv Polytechnic National University Lviv Ukraine Department of Radiophysics and Computer Technologies Ivan Franko National University of Lviv Lviv Ukraine

An algorithm for calculating the scalar product of operands in floating-point format using a table-algorithmic method and an algorithm for forming tables of macro-partial products are proposed. The Calc_T_MPP program, which forms tables of macropartial products, was implemented in the C language on a Raspberry Pi 4 based embedded system. The structure of the scalar product calculation component was developed and implemented using the hardware programming language VHDL in the development environment Quartus II ver. 13.1. The simulation of the Block _ SP component and the estimation of the time of calculation of the scalar product by it were carried out.

关键词： Solid modeling embedded systems VHDL Estimation C languages Hardware

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16th international conference on Parallel Computational Technologies, PCT 2022

16th International Conference on Parallel Computational Tech...

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16th international conference on Parallel Computational Technologies, PCT 2022

ISBN: (纸本)9783031116223

The proceedings contain 22 papers. The special focus in this conference is on Parallel Computational Technologies. The topics include: High-Performance Calculations for modeling the Propagation of Allergenic Plant Pollen in an Atmospheric Boundary Layer;simulation of Nonstationary Thermal Fields in Permafrost Using Multicore Processors;HPC TaskMaster – Task Efficiency Monitoring System for the Supercomputer Center;modeling of Two-Phase Fluid Flow Processes in a Fractured-Porous Type Reservoir Using Parallel Computations;MPI-Based PFEM-2 Method Solver for Convection-Dominated CFD Problems;construction of a Parallel Algorithm for the Numerical modeling of Coke Sediments Burning from the Spherical Catalyst Grain;parallel simulations of Dynamic Interaction Between Train Pantographs and an Overhead Catenary Line;a New Approach to the Supercomputer simulation of Carbon Burning Sub-grid Physics in Ia Type Supernovae Explosion;visualizing Multidimensional Linear Programming Problems;Tuning of a Matrix-Matrix Multiplication Algorithm for Several GPUs Connected by Fast Communication Links;Measuring the Effectiveness of SAT-Based Guess-and-Determine Attacks in Algebraic Cryptanalysis;Implementation of the Algebraic Multigrid Solver Designed for Graphics Processing Units Based on the AMGCL Framework;VGL Rating: A Novel Benchmarking Suite for Modern Supercomputing architectures;kinetic modeling of Isobutane Alkylation with Mixed C4 Olefins and Sulfuric Acid as a Catalyst Using the Asynchronous Global Optimization Algorithm;quantum-Chemical Calculations of the Enthalpy of Formation of Some Tetrazine Derivatives;preface;Analysis of Block Stokes-Algebraic Multigrid Preconditioners on GPU Implementations;Compact LRnLA Algorithms for Flux-Based Numerical Schemes;parallel Methods for Solving Saddle Type systems;optimization of the Computational Process for Solving Grid Equations on a Heterogeneous Computing System.

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modeling of resource allocation in industrial organizations 13th

Modeling of resource allocation in industrial organizations

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13th Annual Meeting of the BICA Society: 2022 Annual international conference on Brain-Inspired Cognitive architectures for Artificial Intelligence, BICA*AI 2022

作者： Petrosov, D.A. Pleshakova, E.S. Osipov, A.V. Ivanov, M.N. Zelenina, A.N. Lvovich, I.Ya. Preobrazhenskiy, Yu. P. Petrosova, N.V. Lopatnuk, L.A. Kupriyanov, D.Y. Roga, S.N. Financial University under the Government of the Russian Federation 49 Leningradsky ave. Moscow125993 Russia Voronezh Institute of High Technologies Lenina st. 73 A Voronezh394043 Russia Belgorod State Agricultural University Named after V. Gorin 1 Vavilova Street Mayskiy308503 Russia Nesavisimosti av.99 Minsk220023 Belarus National Research Nuclear University mEPHI 31 Kashirskoe Shosse Moscow115409 Russia Belgorod State Technological University Named after V. G. Shuhova 46 Kostyukova street Belgorod308012 Russia

The paper analyzes the possibilities of modeling the distribution of resources in organizations. A methodology has been developed on the basis of which stocks of parts of heating equipment are managed. An adaptive model with dynamic parameter adjustment has been developed;A simulation model with algorithmization of the search engine optimization system has been developed. A simulation model with unplanned needs for spare parts for heating equipment has been developed. The results of the simulation demonstrated the efficiency of the proposed approach. © 2022 The Author(s).

关键词： Intelligent systems

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