1,358 Works

SNU-B36-50E: an inter-floor noise dataset

Hwiyong Choi, Haesang Yang, Seungjun Lee & Woojae Seong
SNU-B36-50 is an inter-floor noise dataset collected in building 36 at Seoul National University.It is designed for evaluation of an inter-floor noise type/position classifier.The dataset is a part of the conference paper:https://ieeexplore.ieee.org/abstract/document/8521392And a convolutional neural networks-based inter-floor noise type/position classifier is evaluated with the expanded version (SNU-B36-50E) in a paper titled "Classification of inter-floor noise type/position via convolutional neural network-based supervised learning” (submitted to Applied Sciences).The inter-floor noises included in the dataset can be classified...

Modeling of Maximum Power Point Tracking Algorithm for Photovoltaic Systems

Ioan Viorel Banu & Marcel Istrate
Modeling of Maximum Power Point Tracking Algorithm for Photovoltaic SystemsThis work presents the performance evaluation of incremental conductance maximum power point tracking (MPPT) algorithm for solar photovoltaic (PV) systems under rapidly changing irradiation condition. The simulation model, carried out in Matlab and Simulink, includes the PV solar panel, the dc/dc buck converter and the MPPT controller. This model provides a good evaluation of performance of MPPT control for PV systems. The incremental conductance algorithm was...

Load-Independent Voltage Control for Multiple-Receiver Inductive Power Transfer Systems

Quoc-Trinh Vo
This paper proposes a multiple-receiver inductive power transfer platformwhich is capable of controlling the load voltages to satisfy individually rated values andstabilizing the load voltages against the load variations.In the proposed charging platform, multiple transmitting resonators are employed to supporta voltage-driven source resonator in manipulating the energy flows toward individual receivers.This structure also helps the voltage source induce constant currents into the transmittingresonators, and therefore, is able to deliver load-independent voltages to the loads.As a...

The Opinions of the decision makers

zhang Hengshan
There are 3 data files in total for this data set, 1 for Experiment 1 and 2 for Experiment 2. The File Experiment 1.csv contains 12 matrices for Experiment 1, which are the opinions of the decision makers with the pairwise comparison of alternatives in the form of the linguistic preference relations. The File Experiment 2-1.csv contains 51 matrices, which denote the opinions of the decision makers with the pairwise comparison of alternatives in the...

Four arff multivariate time-series

Zhi-Heng Zhang
The original AirQuality dataset is downloaded from UCI\footnote{http://archive.ics.uci.edu/ml/datasets/Air+Quality}. CentralAirConditioning is a semi-open access dataset for Chinese National Contest of Maths Models\footnote{http://www.tipdm.org/bdrace/index.html}. The last two oilwell maintenance datasets are provided by China National Offshore Oil Corporation (CNOOC)\footnote{http://www.cnooc.com.cn/en/}.

Four arff multivariate time-series

Zhi-Heng Zhang
The original AirQuality dataset is downloaded from UCI\footnote{http://archive.ics.uci.edu/ml/datasets/Air+Quality}. CentralAirConditioning is a semi-open access dataset for Chinese National Contest of Maths Models\footnote{http://www.tipdm.org/bdrace/index.html}. The last two oilwell maintenance datasets are provided by China National Offshore Oil Corporation (CNOOC)\footnote{http://www.cnooc.com.cn/en/}.

Binary classifiers' outputs for ensemble creation

Attila Tiba, Andras Hajdu, Henrietta Toman & Gyorgy Terdik
This dataset was created based on the paper 'Andras Hajdu, Gyorgy Terdik, Attila Tiba, and Henrietta Toman:A stochastic approach to handle knapsack problems in the creation of ensembles'.To summarize our experimental setup for UCI binary classification problems, we have considered baseclassifiers perceptron, decision tree, Levenberg-Marquardt feedforward neural network, random neural network,and discriminative restricted Boltzmann machine classifier for the 5 UCI datasets MAGIC Gamma Telescope, HIGGS, EEG EyeState,Musk (Version 2), and Spambase; datasets of large cardinalities...

Proprioceptive Sensor Dataset for Quadruped Robots

Geoff Fink
These datasets are of the hydraulically actuated robot HyQ’s proprioceptive sensors. They include absolute and relative encoders, force and torque sensors, and MEMS-based and fibre optic-based inertial measurement units (IMUs). Additionally, a motion capture system recorded the ground truth data with millimetre accuracy. In the datasets HyQ was manually controlled to trot in place or move around the laboratory. The sequence includes: forward and backwards motion, side-to-side motion, zig-zags, yaw motion, and a mix of...

Audio Steganalysis Dataset

Yuntao Wang, Kun Yang, Yunzhao Yang, Zhenyu Zhang, Xiaowei Yi & Xianfeng Zhao
Audio steganography and steganalysis have drawn increasing attention in recent years, however, there is no standard public dataset. To promote this study field, we construct a dataset including 33038 stereo WAV audio clips with a sampling rate of 44.1 kHz and duration of 10s, and this dataset is aimed at MP3 steganalysis at this stage. All audio files are from Internet through data crawling, which is for a better simulation of real detection environment. We...

Proprioceptive Sensor Dataset for Quadruped Robots

Geoff Fink
These datasets are of the hydraulically actuated robot HyQ’s proprioceptive sensors. They include absolute and relative encoders, force and torque sensors, and MEMS-based and fibre optic-based inertial measurement units (IMUs). Additionally, a motion capture system recorded the ground truth data with millimetre accuracy. In the datasets HyQ was manually controlled to trot in place or move around the laboratory. The sequence includes: forward and backwards motion, side-to-side motion, zig-zags, yaw motion, and a mix of...

SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities

Zhen Li, Deqing Zou, Shouhuai Xu, Hai Jin, Yawei Zhu, Zhaoxuan Chen, Sujuan Wang & Jialai Wang
We propose a general framework for using deep learning to detect vulnerabilities, named SySeVR. For evaluate the SySeVR, we collect the Semantics-based Vulnerability Candidate (SeVC) dataset, which contains all kinds of vulnerabilities that are available from the National Vulnerability Database (NVD) and the Software Assurance Reference Dataset (SARD). At a high level, the Syntax-based Vulnerability Candidate (SyVC) representation corresponds to a piece of code in a program that may be vulnerable based on a syntax...

Sussex-Huawei Locomotion and Transportation Dataset

Hristijan Gjoreski, Mathias Ciliberto, Lin Wang, Francisco Javier Ordoñez Morales, Sami Mekki, Stefan Valentin & Daniel Roggen
This dataset is a highly versatile and precisely annotated large-scale dataset of smartphone sensor data for multimodal locomotion and transportation analytics of mobile users.The dataset comprises 7 months of measurements, collected from all sensors of 4 smartphones carried at typical body locations, including the images of a body-worn camera, while 3 participants used 8 different modes of transportation in the southeast of the United Kingdom, including in London.In total 28 context labels were annotated, including...

FSGS for Data Transaction

Yuexin Xiang
Our proposed solution is to solve the big data transaction problem, which is based on smart contracts, digital watermarks and blockchains. Through the solution we proposed, we can solve some problems in the current big data transaction.This code mainly implements all the functions of the smart contract proposed in our paper.The image shows the FSGS we designed. The left area shows the operation interface, the lower right area shows the block information (including transaction information),...

FSGS for Data Transaction

Yuexin Xiang
Our proposed solution is to solve the big data transaction problem, which is based on smart contracts, digital watermarks and blockchains. Through the solution we proposed, we can solve some problems in the current big data transaction.This code mainly implements all the functions of the smart contract proposed in our paper.The image shows the FSGS we designed. The left area shows the operation interface, the lower right area shows the block information (including transaction information),...

FSGS for Data Transaction

Yuexin Xiang
Our proposed solution is to solve the big data transaction problem, which is based on smart contracts, digital watermarks and blockchains. Through the solution we proposed, we can solve some problems in the current big data transaction.This code mainly implements all the functions of the smart contract proposed in the paper.The image shows the FSGS we designed. The left area shows the operation interface, the lower right area shows the block information (including transaction information),...

FSGS for Data Transaction

Yuexin Xiang
Our proposed solution is to solve the big data transaction problem, which is based on smart contracts, digital watermarks and blockchains. Through the solution we proposed, we can solve some problems in the current big data transaction.This code mainly implements all the functions of the smart contract proposed in the paper.The image shows the FSGS we designed. The left area shows the operation interface, the lower right area shows the block information (including transaction information),...

Supplementary Material for “EEG Signal Processing in MI-BCI Applications with Improved Covariance Matrix Estimators”

Javier Olias, Ruben Martin-Clemente, M. Auxiliadora Sarmiento-Vega & Sergio Cruces
This material is associated with the PhD Thesis of Javier Olias (which is supervised by Sergio Cruces) and the article: “EEG Signal Processing in MI-BCI Applications with Improved Covariance Matrix Estimators” by J.Olias, R. Martin-Clemente, M.A. Sarmiento-Vega and S. Cruces, which was accepted in the journal IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2019.

Date Fruit Dataset

Syed Umar Amin, Mansour Alsulaiman & Ghulam Muhammad
Date fruit data sets are not publicly available. Previous studies have collected and used their own data set. Almost all these studies have few hundred images per class. As our motive was robust date fruit classification, we did not use the camera to take images of a particular size, angle or images with a particular background, instead to add robustness, we built our date fruit database using Google search engine. Hence the images had the...

MaliciousML: MovieLens dataset attacked with diverse profile injection attacks

Santiago Alonso, Jesús Bobadilla, Fernando Ortega & Ricardo Moya
The MovieLens 1M dataset has been extended introducing diverse shilling profiles to push or nuke a target item. Shilling profiles has been generated using different shilling attack methods: random, average, bandwagon, reverse-bandwagon, love-hate and perfect-knowledge. Each file contains the 1M original MovieLens ratings plus the added votes for the shilling profiles. Each shilling profile rates as many items as the mean number of ratings from each user in the original dataset. The dataset is divided...

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