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This code is provided here for research purpose(s) only. You are allowed to use this code/data provided that you cite the following paper:
U. Lotrič, R. Pilipović, and P. Bulić, “A Hybrid Radix-4 and Approximate Logarithmic Multiplier for Energy Efficient Image Processing,” Electronics, vol. 10, no. 10, p. 1175, May 2021 [Online]. Available: http://dx.doi.org/10.3390/electronics10101175
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The dataset is contains the dataset and results of 10 genes, 20 genes, 30 genes, 40 genes, 100-300 genes, and DREAM4.
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Comparison of specific experimental data
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The data package contains 4 folders. The corresponding contents of each folder are as follows:
Fitting code for Ti-Pd-HfO2-Ag-Au device: Test data and fitting code for Ti-Pd-HfO2-Ag-Au device.
Matlab code: Model code that can be used in Matlab.
SPICE-like code: Model schematic and code that can be used in LTspice.
Verilog-a code: Model code that can be used for Hspice and Cadance.
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Dataset used in experiments reported in the paper "Scalable Energy Games Solvers on GPUs" accepted for publication in IEEE-TPDS
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The dataset contains high bandwidth voltage and current measurements of the main inverter of an electric vehicle. They were acquired from a Mercedes-Benz E-Vito on a testing ground in many different Operation Points (OP) listed in the following table:
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<p>The dataset comprises 2035 images from 14 different software architectural patterns (100+ images each), viz., Broker, Client Server, Microkernel, Repository, Publisher-Subscriber, Peer-to-Peer, Event Bus, Model View Controller, REST, Layered, Presentation Abstraction Controller, Microservices, and Space-based patterns.</p>
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Instructions for authors submitting to TNS
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· 9/11 hijackers network dataset [20]: The 9/11 hijackers network incorporates 61 nodes (each node is a terrorist involved in 9/11 bombing at World Trade Centers in 2011). Dataset was prepared based on some news report, and ties range from ‘at school with’ to ‘on the same plane’. The Data consists of a mode matrix with 19*19 terrorist by terrorist having trusted prior contacts with 1 mode matrix of 61 edges of other involved associates.
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1134 Views
Twitter is one of the most popular social networks for sentiment analysis. This data set of tweets are related to the stock market. We collected 943,672 tweets between April 9 and July 16, 2020, using the S&P 500 tag (#SPX500), the references to the top 25 companies in the S&P 500 index, and the Bloomberg tag (#stocks). 1,300 out of the 943,672 tweets were manually annotated in positive, neutral, or negative classes. A second independent annotator reviewed the manually annotated tweets.
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11446 Views