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This repository includes the data collected from the aocl profile and the Jupyter notebooks with the memory model equations proposed. Application folder contains a set of benchmarks to validate the proposed model.
The model was developed using the Quartus aocl version 18.1 for Stratix10 GX and 19.4 for Stratix10MX
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This dataset is the recorded data for a Dissipative Particle Dynamics simulator which is designed to run on an event-driven high performance computing platform, POETS (poets-project.org).
This is in support of an article submitted to IEEE Transactions on Parallel and Distributed Systems, entitled "An event-driven approach to Dissipative Particle Dynamics".
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The Python Packaging Index is an invaluable resource that is used by developers to improve their projects; however, there are glaring issues in its implementation that will hinder development until resolved. The Python Packaging Index (PyPI) is the official third-party software repository for Python where the majority of open-source Python packages are published. Each package has wheel and egg files accessible from the Python package management system PIP, as well as queryable metadata that contains important package information.
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This paper introduces a low profile wideband Planar Inverted-F antenna (PIFA) for vehicular applications in the 5G systems (below 6GHz) and Vehicle-to-Everything (V2X) communications. The antenna covers a wide range of bandwidth that operates from 617MHz to 6GHz while having an acceptable filtering on the GNSS bands. This design’s physical dimensions and electrical performance makes it suitable for low profile wireless applications in the automotive field.
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This is a large Chinese taxonomic knowledge base, which is translated from Probase by the neural network.
It has 11,292,493 IsA pairs with an accuracy of 86.6%.
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This is a large Chinese commonsense knowledge base, which is translated from ConceptNet 5.6, with around 2 million triples and an accuracy of 89.6%.
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This dataset presents the results obtained for Ingestion and Reporting layers of a Big Data architecture for processing performance management (PM) files in a mobile network. Flume was used in the Ingestion layer. Flume collected PM files from a virtual machine that replicates PM files from a 5G network element (gNodeB). Flume transferred PM files to High Distributed File System (HDFS) in XML format. Hive was used in the Reporting layer. Hive queries the raw data from HDFS. Hive queries a view from HDFS.
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The current maturity of autonomous underwater vehicles (AUVs) has made their deployment practical and cost-effective, such that many scientific, industrial and military applications now include AUV operations. However, the logistical difficulties and high costs of operating at-sea are still critical limiting factors in further technology development, the benchmarking of new techniques and the reproducibility of research results. To overcome this problem, we present a freely available dataset suitable to test control, navigation, sensor processing algorithms and others tasks.
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This dataset is a set of eighteen directed networks that represents message exchanges among Twitter accounts during eighteen crisis events. The dataset comprises 645,339 anonymized unique user IDs and 1,396,709 edges that are labeled with respect to Plutchik's basic emotions (anger, fear, sadness, disgust, joy, trust, anticipation, and surprise) or "neutral" (if a tweet conveys no emotion).
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