The measurement and diagnosis of the severity of failures in rotating machines allow the execution of predictive maintenance actions on equipment. These actions make it possible to monitor the operating parameters of the machine and to perform the prediction of failures, thus avoiding production losses, severe damage to the equipment, and safeguarding the integrity of the equipment operators. This paper describes the construction of a dataset composed of vibration signals of a rotating machine.

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This paper introduces a compact Multiple input Multiple output (MIMO) antenna system for vehicular application in the sub-6GHz 5G systems that operates in the middle and high frequency bands from 1.71GHz to 5GHz. The proposed design consists of two symmetrical raised printed monopoles on Flame Retardant 4 (FR4) dielectric material with Electromagnetic Band Gap shape (EBG) to provide defected ground to improve bandwidth impedance and higher isolation across the operating frequency range.

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This dataset consists of the training and the evaluation datasets for the LiDAR-based maritime environment perception presented in our journal publication "Maritime Environment Perception based on Deep Learning." Within the datasets, LiDAR raw data are processed using Deep Neural Networks (DNN). In the training dataset, we introduce the method for generating training data in Gazebo simulation. In the evaluation datasets, we provide the real-world tests conducted by two research vessels, respectively.

 

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356 Views

Recently, surface electromyogram (EMG) has been proposed as a novel biometric trait for addressing some key limitations of current biometrics, such as spoofing and liveness. The EMG signals possess a unique characteristic: they are inherently different for individuals (biometrics), and they can be customized to realize multi-length codes or passwords (for example, by performing different gestures).

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528 Views

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The data set collected using a self-designed electronic nose (e-nose) involved eight Chinese liquor types, which are LanJinJiu with 38% alcohol concentration (LJJ38), LanJinJiu with 48% alcohol concentration (LJJ48), DaoHuaXiang with 42% alcohol concentration (DHX), LuZhouLaoJiao with 38% alcohol concentration (LZLJ), MianZhuDaQu with 38% alcohol concentration (MZDQ), QingJiu with 38% alcohol concentration (QJ), ShiLiXiang (SLX) with 40% alcohol concentration and BianFengHu with 40% alcohol concentration (BFH).

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The name of the data set is changed to 'Electronic nose dataset for recogniton of eight liquor types'.

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Representative videos of dMRI data from the numerical tests of the paper: "Kernel Regression Imputation in Manifolds via Bi-Linear Modeling: The Dynamic-MRI Case," by K. Slavakis, G. N. Shetty, L. Cannelli, G. Scutari,  U. Nakarmi, and L. Ying. 

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