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A Public Domain Dataset for Human Activity Recognition using Smartphones
TLDR
We introduced a new publicly available dataset for Human Activity Recognition using smartphones and acknowledged some results using a multiclass Support Vector Machine approach. Expand
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Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine
TLDR
In this paper, we present a system for human physical Activity Recognition (AR) using smartphone inertial sensors. Expand
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Energy Efficient Smartphone-Based Activity Recognition using Fixed-Point Arithmetic
TLDR
We propose a novel energy efficient approach for the recognition of human activities using smartphones as wearable sensing devices, targeting assisted living applications such as remote patient activity monitoring for the disabled and the elderly. Expand
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Advances in learning analytics and educational data mining
TLDR
The growing interest in recent years towards Learning Analytics (LA) and Educational Data Mining (EDM) has enabled novel ap- proaches and advancements in educational settings. Expand
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Corporate Disclosure in Family Firms
This Chapter attempts to provide a systematic review of the possible relations between mandatory and voluntary disclosure and of financial and non-financial reporting on the one hand, and familyExpand
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Human Activity Recognition on Smartphones with Awareness of Basic Activities and Postural Transitions
TLDR
We present a novel smartphone-based online HAR system for the classification of activities, which deals with the occurrence of postural transitions. Expand
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In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines
TLDR
In-sample approaches to model selection and error estimation of support vector machines (SVMs) are not as widespread as out-of-sample methods, where part of the data is removed from the training set for validation and testing purposes, mainly because their practical application is not straightforward and the latter provide questionable results. Expand
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Energy Load Forecasting Using Empirical Mode Decomposition and Support Vector Regression
TLDR
In this paper we focus our attention on the long-term load forecasting problem, that is the prediction of energy consumption for several months ahead (up to one or more years). Expand
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Energy Efficient Smartphone-Based Activity Recognition Using Fixed-Point Arithmetic
TLDR
We propose a novel energy efficient approach for the recognition of human activities using smartphones as wearable sensing devices, targeting assisted living applications such as remote patient activity monitoring for the disabled and the elderly. Expand
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A Hardware-friendly Support Vector Machine for Embedded Automotive Applications
TLDR
We present here a hardware-friendly version of the support vector machine (SVM), which is useful to implement its feed-forward phase on limited-resources devices such as field programmable gate arrays (FPGAs) or microcontrollers, where a floating-point unit is seldom available. Expand
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