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In this study, we propose a two-stage method for material segmentation in hyperspectral images. The first stage employs a Convolutional Neural Network (CNN) to predict the material label at individual pixels. The second stage further refines the segmentation by a fully-connected Conditional Random Field (CRF) framework. For the first stage, we experimented with two different network architectures...
The current animal sperm morphology analysis is mostly achieved through computer vision technology. By using image processing technique, the parameters of each sperm such as ellipticity, elongation of the head, mid-piece angle and percentage of acrosome can be calculated, then the quality of sperm can be evaluated. This system uses K-means algorithim to segment the sperm images, thinning algorithm...
How a grain ahead affecting a dolphin's transmitting performance is examined. A finite element approach was applied to numerically simulate the acoustic field around a dolphin with a small grain ahead of it. Acoustic intensity distribution, beam pattern, angle of strong beam and 3dB beam width are compared to investigate the differences caused by the small grain ahead of the dolphin. Although the...
To prove to a customer that a new or overhauled gas turbine satisfies its contractual performance, mechanical and emissions target, an acceptance test is normally performed by the manufacturer. Such acceptance tests typically involve running the turbine through its operational envelope based on a predefined test schedule, with information regarding the thermodynamic and mechanical performance as well...
In this paper, an off-design performance prediction model for a single shaft industrial gas turbine (IGT) using Microsoft Excel with Visual Basic for Applications (VBA) programming is presented. The modelling architecture is comprised of fundamental thermodynamic equations describing the performance of IGTs. A graphical user interface has been constructed to allow an easy interaction of the model...
Fault diagnosis of incipient crack failure in rotating shafts allows the detection and identification of performance degradation as early as possible in industrial plants, such as downtime and potential injury to personnel. The present work studies the performance and effectiveness of crack fault detection by means of applying wavelet packet decomposition (WPD) and empirical mode decomposition (EMD)...
In ultra-dense cellular networks, research works on enhancing cell edge performance receive considerable attention. Based on interlaced clustering, we propose a heuristic sparse beamforming strategy to improve the cell edge throughput effectively in distributed antenna systems (DASs). In our scheme, each cluster pattern (CP) is divided into several adaptive cells, where all the remote antenna units...
Temperature has a considerable influence on the shallow water. Due to important economic value and relation to human activity, the on-line and real-time water temperature monitoring is of great scientific and practical significance. This paper has performed an experiment of a high frequency acoustic temperature measurement. Reciprocal sound transmission and the signal cross-correlation method were...
Fault diagnosis of roller bearings in rotating machinery is of great significance to identify latent abnormalities and failures in industrial plants. This paper presents a new self-adaptive fault diagnosis system for different conditions of roller bearings using InfraRed Thermography (IRT). In the first stage of the proposed system, 2-Dimensional Discrete Wavelet Transform (2D-DWT) and Shannon entropy...
Recent works have identified hybrid analog-digital processing as a cost-effective alternative to conventional full-digital processing in massive multiple-input multiple-output (MIMO) systems owing to the deployment of far less number of radio frequency (RF) chains. In this paper, we analyze the impact of oscillator phase noise on hybrid precoding in massive MIMO systems. Relying on the time division...
The objective of this paper is to estimate the compressor discharge temperature measurements on an industrial gas turbine that is undergoing commissioning at site, using a data-driven model which is built using the test bed measurements of the engine. This paper proposes a Bayesian neuro-fuzzy modelling (BNFM) approach, which combines the adaptive neuro-fuzzy inference system (ANFIS) and variational...
Lightning invaded over-voltage is the main cause of insulation fault of electric apparatus. To acquire the actual substation lightning invaded over-voltage, a monitoring system based on arrester valve divider is proposed in this paper. The working principle and advantages of the proposed monitoring system is analyzed firstly. And then, the actual overvoltage waveforms are presented, which are recorded...
Mobility impaired individuals need the wheelchair to support their independent life, so monitor activities performed on the wheelchair can provide significant insights on their general health status. Activity recognition related to healthy people is a well established research area; however, only few works addressed this problem for wheelchair users. This paper proposes a novel approach based on dynamic...
Wireless Access in Vehicular Environments (WAVE) is designed for VANETs to provide safety services and infotainment services through contention-based medium access control (MAC) mechanism. However, the collision probability may increase dramatically in the case of high density of vehicles, due to the contention-based MAC mechanism. To address this issue, we propose a spectrum penetration (i.e., transmit...
LKB1(Liver Kinase B1) gene is a tumor suppressor gene, which regulates the pathophysiological function of many cells, but the mechanism of LKB1 gene is still unclear. The double transgenic mice with positive homozygous and negative homozygous were screened by PCR amplification technique and gel electrophoresis technique. The expression level of LKB1 gene in smooth muscle cells was detected by Westernblot...
In light of the powerful learning capability of deep neural networks (DNNs), deep (convolutional) models have been built in recent years to address the task of salient object detection. Although training such deep saliency models can significantly improve the detection performance, it requires large-scale manual supervision in the form of pixel-level human annotation, which is highly labor-intensive...
This paper considers the impulsive H∞ control problem for a class of discrete-time Markovian jump delay systems for the first time. Some sufficient conditions are given in terms of matrix inequalities. A numerical example is presented to show the effectiveness of the theoretical results.
The classification of different odontocetes using écholocation clicks plays a significant role in tracking and detecting animals for research and protection purposes. Echolocation clicks were detected by an automatic method based on the Teager-Kaiser Energy Operator (TKEO). Then, these clicks were represented by their FFT magnitude spectrum. To reduce the influence of high similar clicks among species,...
The problem of simultaneous polarimetrie measurement of moving targets is eonsidered in this paper. A seheme of eombining a eompressed sensing algorithm and the interleaved orthogonal frequeney division multiplexing (OFDM) radar signal is proposed to aehieve better aeeuraey in polarimetrie measurement. The interleaved OFDM waveform pair is introdueed beeause of its outstanding orthogonality features...
A novel two dimension direction-of-arrival (2D-DOA) estimation method for L-shaped array using atomic norm minimization based on the cross-correlation matrix is proposed in this paper. We first reconstruct the autocorrelation matrix of observed signals in the Toeplitz structure by cross-correlation matrix-based atomic norm minimization (CCMANM), and then employ the reconstructed autocorrelation matrix...
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