In this paper we propose a dynamic model of a software market for component reuse. We investigate the market dynamics using experiments with economically motivated human subjects. Our results suggest that the introduc...
详细信息
How can parallel computing topics be incorporated into core courses that are taken by the majority of undergraduate students? this paper reports our experiences adding GPU computing with CUDA into the core undergradua...
详细信息
Energy harvesting technologies offer a promising solution to sustainably power an ever-growing number of Internet of things (IoT) devices. However, due to the weak and transient natures of energy harvesting, IoT devic...
详细信息
ISBN:
(纸本)9781665421355
Energy harvesting technologies offer a promising solution to sustainably power an ever-growing number of Internet of things (IoT) devices. However, due to the weak and transient natures of energy harvesting, IoT devices have to work intermittently rendering conventional routing policies and energy allocation strategies impractical. To this end, this paper, for the very first time, developed a distributed multi-agent reinforcement algorithm known as global actor-critic policy (GAP) to address the problem of routing policy and energy allocation together for the energy harvesting powered IoT system. At the training stage, each IoT device is treated as an agent and one universal model is trained for all agents to save computing resources. At the inference stage, packet delivery rate can be maximized. the experimental results show that the proposed GAP algorithm achieves similar to 1.28x and similar to 1.24x data transmission rate than that of the Q-table and ESDSRAA algorithm, respectively.
Many advanced gaze visualization techniques have been developed continuously based on the fundamental gaze visualizations such as scatter plots, attention map, and scanpath. However, it is not easy to locate challengi...
详细信息
On-road vehicle detection is one of the key techniques in intelligent driver systems and has been an active research area in the past years. Considering the high demand for real-time and robust vehicle detection metho...
详细信息
the proceedings contain 43 papers. the topics discussed include: a novel particle swarm-based approach for 3D motif matching and protein structure classification;rhetorical figuration as a metric in text summarization...
ISBN:
(纸本)9783319064826
the proceedings contain 43 papers. the topics discussed include: a novel particle swarm-based approach for 3D motif matching and protein structure classification;rhetorical figuration as a metric in text summarization;empirical evaluation of intelligent mobile user interfaces in healthcare;learning to measure influence in a scientific social network;filtering personal queries from mixed-use query logs;analysis of feature maps selection in supervised learning using convolutional neural networks;inconsistency versus accuracy of heuristics;VMSP: efficient vertical mining of maximal sequential patterns;a comparison of multi-label feature selection methods using the random forest paradigm;analyzing user trajectories from mobile device data with hierarchical dirichlet processes;and use of ontology and cluster ensembles for geospatial clustering analysis.
this paper proposes a new algorithm that improves the complexity bound for solving parity games. Our approach combines McNaughton's iterated fixed point algorithm with a preprocessing step, which is called prior t...
详细信息
ISBN:
(纸本)9783540770497
this paper proposes a new algorithm that improves the complexity bound for solving parity games. Our approach combines McNaughton's iterated fixed point algorithm with a preprocessing step, which is called prior to every recursive call. the preprocessing uses ranking functions similar to Jurdzinski's, but with a restricted codomain, to determine all winning regions smaller than a predefined parameter. the combination of the preprocessing step withthe recursive call guarantees that McNaughton's algorithm proceeds in big steps, whose size is bounded from below by the chosen parameter. Higher parameters result in smaller call trees, but to the cost of an expensive preprocessing step. An optimal parameter balances the cost of the recursive call and the preprocessing step, resulting in an improvement of the known upper bound for solving parity games from approximately O(mn(1/2c)) to O(mn(1/3c)).
Least-squares fitting (LSF) is a fundamental statistical method that is widely used in linear regression problems, such as modeling, data fitting, predictive analysis, etc. For large-scale data sets, LSF is computatio...
详细信息
ISBN:
(纸本)9781665421355
Least-squares fitting (LSF) is a fundamental statistical method that is widely used in linear regression problems, such as modeling, data fitting, predictive analysis, etc. For large-scale data sets, LSF is computationally complex and poorly scaled due to the O(N-2)-O(N-3) computational complexity. the computingin-memory technique has potential to improve the performance and scalability of LSF. In this paper, we propose a computing-inmemory accelerator based on resistive random-access memory (RRAM) devices. We not only utilize the conventional idea of accelerating matrix-vector multiplications by RRAM-based crossbar arrays, but also elaborate the hardware and the mapping strategy. Our approach has a unique feature that it can finish a complete LSF problem in O(1) time complexity. We also propose a scalable and configurable architecture such that the problem scale that can be solved is not restricted by the crossbar array size. Experimental results have demonstrated the superior performance and energy efficiency of our accelerator.
the proceedings contain 43 papers. the topics discussed include: the low power and wide tuning range advantages of Armstrong VCOs in 180 nm Si-Ge HBT technology;a back-to-back series varactor configuration minimizing ...
ISBN:
(纸本)9781509034093
the proceedings contain 43 papers. the topics discussed include: the low power and wide tuning range advantages of Armstrong VCOs in 180 nm Si-Ge HBT technology;a back-to-back series varactor configuration minimizing the amplitude-to-phase noise conversion in Si-Ge HBT technology VCOs;comparison of the simulated performance of two divider controllers in a fractional-n frequency synthesizer with a piecewise-linear charge-pump nonlinearity;nonlinear forward selection component analysis for optical emission spectroscopy wavelength selection;evaluation of requirements for the development of a bench test system to test PTC heater in-situ automotive HVAC case units;experimental evaluation of memory configurations of Hadoop in docker environment;decomposition of surface electromyograms reveals changes in motor control after 14-day bed rest;investigating brain signal peaks vs electroencephalograph electrode placement using multicolour 10Hz flickering graphics stimulation for brain-computer interface development;design of an auto-gain control transimpedance amplifier for optical sensing applications;design and test of W-band passive circuit components in 28nm bulk CMOS technology;and input variables selection of dynamic fuzzy models by genetic algorithm.
the goal of this paper is to provide a technique to estimate the input parameters for a waveguide physical model. this work is motivated by the fact that the input parameters strongly influence the quality of the synt...
详细信息
暂无评论