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Many real-world problems involve multi-view high-dimension-small-sample-size data analysis, such as multi-omics data. The combination of multi-view databases is supposed to provide a better biological significance. However, the multi-view data always contain noise and outlying entries that result in inaccurate and unreliable. It has become an urgent need how to effectively analyze these data. We proposed...
In order to compensate for the effects of supply voltage, process and temperature on the oscillator frequency, we design a ring oscillator with digital calibration. By comparing the frequency deviation between the ring oscillator and the external reference clock source, adjusting the state of the control word, and then changing the number of resistors in the analog circuit to adjust the output frequency...
We fabricate a Fabry-Perot resonator in a LiNbO3 subwavelength slab and investigate the spatiotemporal evolution of terahertz pulses in the structure via time-resolved imaging system. The wave confinement and standing wave modes are clearly observed.
The inductively coupled coil in wireless power transfer (WPT) system is the key to optimizing the power transfer efficiency. Based on an iterative printed spiral coil (PSC) design procedure, this paper proposes a load-based design method to improve the efficiency stability for a load-variable system. The efficiency stability coefficient is defined to choose the optimal PSCs. Several pairs of PSCs...
An ultra-wideband metasurface is designed for suppressing the specular electromagnetic wave reflection or backward radar cross section (RCS). Square ring structure is chosen as the basic meta-atoms. A new physical mechanism based on size adjustment of the basic meta-atoms is proposed for ultrawideband manipulation of electromagnetic (EM) waves. Based on hybrid array pattern synthesis (APS) and particle...
A new metaheuristic intelligent algorithms—flower pollination algorithm (FPA) and a novel differential evolution mutation strategy—Target Mutation(TM) strategy are introduced. An improved FPA based on mutation strategy—MFPA algorithm, is proposed to overcome the low accuracy computation, low speed convergence, and easy to fall into local optimization. The MFPA improves the TM, and introduces the strategy...
The rapid advances of transportation infrastructure have led to a dramatic increase in the demand for smart systems capable of monitoring traffic and street safety. Fundamental to these applications are a community-based evaluation platform and benchmark for object detection and multi-object tracking. To this end, we organize the AVSS2017 Challenge on Advanced Traffic Monitoring, in conjunction with...
Triggered by several head-mounted display (HMD) devices that have come to the market recently, such as Oculus Rift, HTC Vive, and Samsung Gear VR, significant interest has developed in virtual reality (VR) systems, experiences and applications. However, the current HMD devices are still very heavy and large, negatively affecting user experience. Moreover, current VR approaches perform rendering locally...
This paper proposes a fully automatic pipeline to generate accurate object segment proposals in realistic videos. Our approach first detects generic object proposals for all video frames and then learns to rank them using a Convolutional Neural Networks (CNN) descriptor built on appearance and motion cues. The ambiguity of the proposal set can be reduced while the quality can be retained as highly...
We perform fast vehicle detection from traffic surveillance cameras. A novel deep learning framework, namely Evolving Boxes, is developed that proposes and refines the object boxes under different feature representations. Specifically, our framework is embedded with a light-weight proposal network to generate initial anchor boxes as well as to early discard unlikely regions; a fine-turning network...
In order to improve the starting torque of the soft start of the asynchronous motor and reduce the starting current, a soft starting method from the second frequency to the power frequency starting is proposed. On the basis of this theory, the simulation model of soft start system of asynchronous motor graded frequency conversion control is built by Simulink simulation function of MATLAB. The simulation...
Aiming at the starting problem of motor equipment, this paper studied a large of existing soft start modes and their starting characteristics. Then, using MATLAB/Simulink tool to build common soft start simulation models, this paper got a lot of simulation waveforms. These helped to identify the applicable occasions of these soft starters and their respective advantages and disadvantages. We designed...
Chronic disease self-management contains many aspects of knowledge, such as disease, nutrition, exercise, pharmacy and medical guidelines. This study aims to integrate the knowledge from various domains and develop a chronic disease self-management knowledge base (CDSMKB) using web ontology language (OWL) and semantic rules in Jena rule format. A mobile chronic disease self-management system (CDSMS)...
In this paper, we explore the possibility of enabling cloud-based virtual classroom applications providing the advantages of computational scalability and access from any end device. In particular, we investigate a virtual classroom application in which the classroom including teacher, students and activities are rendered on the cloud, with each student view captured and streamed to students' end...
Sparse Principal Component Analysis (SPCA) is a method that can get the sparse loadings of the principal components (PCs), and it may formulate PCA as a regression-type optimization problem by using the elastic net. But the selected features are different with each PC and generally independent. A new method named SPCA has been proposed for removing these detect, which replaces the elastic net with...
Tumor clustering based on biomolecular data plays a very important role for cancer classifications discovery. To further improve the robustness, stability and accuracy of tumor clustering, we develop a novel dimension reduction method named p-norm singular value decomposition (PSVD) to seek a low-rank approximation matrix to the bimolecular data. To enhance the robustness to outliers, the Lp-norm...
Based on various genomic information of chimeric transcript, recent studies used machine-learning methods to predict the oncogenic potentials for chimeric transcripts, however these works ignored transcriptional signature of those chimeric transcripts. Based on clonal evolution theory, we hypothesized that a chimeric transcript is more likely to be an oncogenic ‘driver’ mutation, if the neoplastic...
Soccer video semantic analysis has attracted a lot of researchers in the last few years. Many methods of machine learning have been applied to this task and have achieved some positive results, but the neural network method has not yet been used to this task from now. Taking into account the advantages of Convolution Neural Network(CNN) in fully exploiting features and the ability of Recurrent Neural...
Deep learning methods have been successfully used in many areas of computer vision, including super resolution. However, all of the previous deep learning methods have been proposed for generic image super resolution. In this paper, we proposed to use convolutional neural network for face hallucination (FH) by combining the domain specific prior knowledge of face images and properties of deep learning...
In this paper, a design of memory built-in self-test based on JTAG interface circuit applied in Power line communication chip is implemented with SMIC 0.18um CMOS 1P5M process. The memory built-in self-test circuit mainly includes JTAG interface and memory test circuits. Test data and test instruction can be sent and received through only 5 JTAG interface pins. It can also complete memory test with...
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