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Chinese liquors from different plants have unique flavors attributable to the use of various bacteria and fungi, raw materials, and production processes. Accurately identifying the flavor of Chinese liquors is not always possible through the subjective consciousness of a taster. A quartz crystal microbalance (QCM)-based electronic nose (e-nose) can perform this task because of its keen ability to...
This paper presents a supervised data imputation based on the class-dependent matrix factors, which are generated during matrix factorization. The proposed ridge alternating least squares imputation uses class information to create substituted values, which approximate the characteristics of their corresponding classes, for missing entries. In the training phase, the incomplete data with label information...
This paper presents a novel WLAN-based indoor localization algorithm (i.e., HED) to combat the environmental dynamics by tolerating the sequence disorders caused by AP (access point) changes, while harvesting from the bursting number of available wireless resources. Via extensive real-world experiments lasting for over 6 months, we show the superiority of our HED algorithm in terms of accuracy and...
Indoor localization remains a hot topic and receives tremendous research efforts during the last few decades. While most previous efforts focus on the designing issue, little effort has been paid to the impact of different environmental parameters on the system performance. To this end, we present an extensive empirical study with real-world experiments to provide sufficient data for analysis. By...
This paper studies the methods of speech bandwidth extension (BWE) using artificial neural networks. Several types of neural networks, including bidirectional neural networks such as restricted Boltzmann machines (RBM) and bidirectional associative memories (BAM), and feedforward deep neural networks (DNNs), are employed to restore high frequency spectral envelopes from low frequency ones. Compared...
Human action recognition is very important in human computer interaction. In this article, we present a new method of recognizing human actions by using Microsoft Kinect sensor, k-means clustering and Hidden Markov Models (HMMs). Kinect is able to generate human skeleton information from depth images, in addition, features representing specific body parts are generated from the skeleton information...
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