the proceedings contain 21 papers. the topics discussed include: fast ART algorithm based on simplified weighting factor calculation;advances in the application of magnetic resonance imaging in the diagnosis of brain ...
ISBN:
(纸本)9781450396691
the proceedings contain 21 papers. the topics discussed include: fast ART algorithm based on simplified weighting factor calculation;advances in the application of magnetic resonance imaging in the diagnosis of brain diseases;semi-supervised learning with double head approach for carotid artery detection;framework of unsupervised based denoising for optical coherence tomography;determination of resolution limitation of sonography used in diagnosis of cleft lips and palates;study on fatty liver based on pseudotime analysis;an incremental unsupervised feature extraction method based on infomax;learning-induced neural plasticity in the primary motor cortex during the motor imagery task and the speech task;evaluation of different cutoff frequencies of high-pass filter for online spike sorting;and enhance decoding of functional lower-limb movements by combining sensory motor rhythm and movement-related cortical potential features.
Traditional power load management terminals lack precision and flexibility in controlling customer power loads, hindering efficient energy use. Developing intelligent energy terminals is essential to meet national dem...
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Convex optimization is at the heart of many performance-critical applications across a wide range of domains. Although many high-performance hardware accelerators have been developed for specific optimization problems...
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ISBN:
(纸本)9798400700958
Convex optimization is at the heart of many performance-critical applications across a wide range of domains. Although many high-performance hardware accelerators have been developed for specific optimization problems in the past, designing such accelerator is a challenging task and the resulting computing architecture is often so specific to the targeted application that they can hardly be reused even in a related application within the same domain. To accelerate general-purpose optimization solvers that must operate on diverse user input during run time, an ideal hardware solver should be able to adapt to the provided optimization problem dynamically while achieving high performance and power-efficiency. In this work, a hardware-accelerated general-purpose quadratic program solver, called RSQP, with reconfigurable functional units and data paththat facilitate problem-specific customization is presented. RSQP uses a string-based encoding to describe the problem structure with fine granularity. Based on this encoding, functional units and datapath customized to the sparsity pattern of the problem are created by solving a dictionary-based lossless string compression problem and a mixed integer linear program respectively. RSQP has been integrated to accelerate the general-purpose quadratic programming solver OSQP and has been tested using an extensive benchmark with 120 optimization problems from 6 application domains. through architectural customization, RSQP achieves up to 7x performance improvement over its baseline generic design. Furthermore, when compared with a CPU and a GPU-accelerated implementation, RSQP achieves up to 31.2x and 6.9x end-to-end speedup on these benchmark programs, respectively. Finally, the FPGA accelerator operates at up to 6.6x lower dynamic power consumption and up to 22.7x higher power efficiency over the GPU implementation, making it an attractive solution for power-conscious datacenter applications.
the social accounting matrix model is an accounting method based on the direct correlation analysis of various elements. It reflects the relationship between input and output and various departments, which is convenie...
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To achieve the ambitious goal of net-zero by 2050, the power sector in many countries has been increasingly using renewable energy sources (RES). the power system balance will be significantly challenged due to the in...
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To achieve the ambitious goal of net-zero by 2050, the power sector in many countries has been increasingly using renewable energy sources (RES). the power system balance will be significantly challenged due to the intermittency of RES. Lithium-ion battery energy storage systems (BESS) can effectively address the challenge by providing flexibility to fill the mismatch between the intermittent supply and the varying demand, generating revenues for BESS to payback the initial investment. However, every grid participation also results in an inevitable lifetime loss. From the asset owner's perspective, therefore, it is important to balance the short-term revenue from the fluctuating electrical market withthe long-term battery life loss. To achieve this in this study, first, a novel online-applied battery life model is established, which is computationally efficient to comprehensively consider the battery's historical aging, state of charge (SOC), charge-discharge rate (Crate). then, an online-applied sliding-window dynamic programming (SWDP) strategy is proposed to optimize short-term grid service revenues and long-term battery life losses. the SWDP is also compared with an offline-applied dynamic programming (DP) strategy. the simulation results show that the cost due to battery life decay is significant, which indicates the importance of tracking the battery life loss in the battery asset management. Additionally, the prediction accuracy of electricity price significantly influences the performance of SWDP strategy. the BESS's total profit can reduce by half in the considered case study if the electricity prediction error is 12.5%. (C) 2022 the Author(s). Published by Elsevier Ltd.
Computer programming is one of the critical competencies that engineering students should have. Meanwhile, not all engineering students have enough prior experience and knowledge in programming, especially for student...
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ISBN:
(纸本)9781665432320
Computer programming is one of the critical competencies that engineering students should have. Meanwhile, not all engineering students have enough prior experience and knowledge in programming, especially for students in Industrial Engineering majors. there is an opportunity to develop an interactive learning and teaching approach as the growing interactive online learning system, which could facilitate students achieving their programming competencies to solve practical problems. this paper presents the design of a web-based learning module using interactive coding to enhance students learning process. the system was developed using the SDLC method with 3-tier architecture. It is also equipped with students' data, text and video learning materials, assessments, and an "interactive coding". through interactivity, "interactive coding" could facilitate students to deepen their understanding of coding practice from the online tutorials provided by the instructors. the text and video materials could add and drop as needed regarding the curriculum. the design result is promising to extend for any programming course in higher education.
Cloud-edge collaborative computing has become an emerging computing paradigm due to its ability in fully utilizing the computing power for cloud and edge servers. However, in the process of task offloading, it is face...
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this paper presents a novel traffic control action referring to virtual moving of the internal boundary of bi-directional highways for lane-free traffic of automated vehicles. Since capacity of lane-free traffic is ro...
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ISBN:
(纸本)9781728189956
this paper presents a novel traffic control action referring to virtual moving of the internal boundary of bi-directional highways for lane-free traffic of automated vehicles. Since capacity of lane-free traffic is roughly proportional to the road width, the total cross-road capacity may be shared flexibly (in space and time) between the two opposite directions according to the current bi-directional demand. In order to determine the control input, which is the road width or capacity sharing factor, an appropriate QP (Quadratic programming) problem formulation employing the macroscopic CTM (Cell Transmission Model) is developed. Simulation results with and without control are analyzed and compared to demonstrate the potential of the proposed scheme in exploiting the available road infrastructure at unprecedented levels.
the proceedings contain 13 papers. the special focus in this conference is on Network Science. the topics include: HyperNetVec: Fast and Scalable Hierarchical Embedding for Hypergraphs;constructing Provably Robust Sca...
ISBN:
(纸本)9783030972394
the proceedings contain 13 papers. the special focus in this conference is on Network Science. the topics include: HyperNetVec: Fast and Scalable Hierarchical Embedding for Hypergraphs;constructing Provably Robust Scale-Free Networks;using Localized Attacks with Probabilistic Failures to Model Seismic Events over Physical-Logical Interdependent Networks;hunting for Dual-Target Set on a Class of Hierarchical Networks;functional Characterization of Transcriptional Regulatory Networks of Yeast Species;preface;generalized Linear Models Network Autoregression;competitive Information Spreading on Modular Networks;vessel Destination Prediction Using a Graph-Based Machine Learning Model;modularity-Based Backbone Extraction in Weighted Complex Networks;deep Topological Embedding with Convolutional Neural Networks for Complex Network Classification.
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