关键词： 建筑测绘   地面激光扫描模式   方法研究  

摘要： 对于理论研究来说,测绘是一门高度专业化的学科。使用地面激光扫描方法可以准确快速地获得室内外环境中特定的三维数据信息。近年来,地面激光扫描这种特定的识别方法已被公认并广泛应用于建筑测绘研究和工程实践领域。能准确呈现建筑实体的状态,从而提高建筑工程测绘的效率和水平。本文主要探讨建筑测绘领域激光扫描模式的具体识别方法及相关内容,仅供参考。

关键词： 光通信系统   信号调制   识别方法   模式识别  

摘要： 当前光通信系统调制识别方法存在识别正确率低、速度慢等缺陷,难以获得理想的光通信系统信号调制识别结果。为了对光通信系统信号调制方法进行准确识别,设计了基于模式识别的光通信系统信号调制识别方法。首先对当前光通信系统信号调制识别研究现状进行分析,找到引起识别效果差的因素,然后采集光通信系统信号调制识别的数据,并采用模式识别技术对光通信系统信号调制方式的特点进行拟合,实现光通信系统信号调制识别,最后进行了光通信系统信号调制识别的验证性实验。结果表明,本文方法提高了光通信系统信号调制识别的正确率,光通信系统信号调制的误识率差小于其它光通信系统信号调制识别方法,获得了比较满意的光通信系统信号调制识别结果。

关键词： 变频空调   模式识别   数据挖掘   能耗分析   优化运行  

摘要： 变频空调的长期运行数据是空调在实际环境中运行状态最直接的反映,空调运行的内在规律潜藏在其长期的运行数据中,分析其长期运行数据时,由于数据冗余、存在异常数据等原因,需要采用数据挖掘的方法进行研究。采用聚类算法进行分析,空调的运行模式可总结为三种模式,即上午高负荷模式、下午高负荷模式以及低频平稳模式,三种模式下空调的送风温度都比较接近,但室外温度有所区别。上午(下午)高负荷模式中,室外温度在上午(下午)最高,功率及制冷性能系数(Energy efficiency ratio, EER)分别处于峰值及谷值,低频平稳模式下,室外温度并不高,开机后空调运行比较稳定,运行参数变化不大。此后,采用控制变量法和多项式拟合来分析环境工况参数对空调性能的影响,室外侧环境温度、空调回风温度的升高均导致空调的功率增加,而空调的EER随着回风温度的升高而增加,随着室外温度及空调的功率(运行频率)的增加而下降。采用神经网络算法,研究基于空调送风侧参数预测变频空调性能的方法,并建立神经网络预测模型,该方法的预测误差在15%以内,可以通过控制空调运行时的送风侧参数,达到控制空调性能的目的。最后,根据以上研究成果,提出变频空调控制优化方法,提高空调在线长期运行能效。

关键词： French Massif Central   Morphostructural zoning   Pattern recognition   Seismogenic nodes  

摘要： The goal of this work is to identify seismogenic nodes capable of generating I (0) ae VI earthquakes in the French Massif Central, an intraplate region of low-to-moderate seismicity in the Mediterranean. For this purpose, we apply a phenomenological approach based on the pattern recognition. Recognition objects-morphostructural nodes-have been delineated with the morphostructural zoning method enabling to outline the hierarchical block-structure of the region, the network of morphostructural lineaments bounding blocks, and the loci of the nodes that are formed at the intersections of the lineaments. The epicenters of I (0) ae VI earthquakes nucleate at some of the delineated nodes. The CORA-3 recognition algorithm pinpointed the other capable nodes, where the target earthquakes have not yet been recorded. The recognized seismogenic nodes are situated mainly in the eastern part of the Massif and correlate with high ranks lineaments dividing the larger blocks of the Massif Central. An assemblage of geomorphic features typical of seismogenic nodes was also defined. The work provides information on the potential earthquake sources which is very important for knowledgeable long-term seismic hazard assessment.

关键词： Machine learning   Artificial intelligence   Pesticide   Smoking   Hearing loss   Farmer  

摘要： The use of pesticides has been increasing in agriculture, leading to a public health problem. The aim of this study was to evaluate ototoxic effects in farmers who were exposed to cigarette smoke and/or pesticides and to identify possible classification patterns in the exposure groups. The sample included 127 participants of both sexes aged between 18 and 39, who were divided into the following four groups: control group (CG), smoking group (SG), pesticide group (PG), and smoking + pesticide group (SPG). Meatoscopy, pure tone audiometry, logoaudiometry, high-frequency thresholds, and immittance testing were performed. Data were evaluated by artificial neural network (ANN), K-nearest neighbors (K-NN), and support vector machine (SVM). There was symmetry between the right and left ears, an increase in the incidence of hearing loss at high frequency and of downward sloping audiometric curve configuration, and alteration of stapedial reflex in the three exposed groups. The machine-learning classifiers achieved good classification performance (control and exposed). The best classification results occur in high type (I and II) datasets (about 90% accuracy) in k-NN test. It is concluded that both xenobiotic substances have ototoxic potential;however, their combined use does not present additive or potentiating effects recognizable by the algorithms.

关键词： Particle size   Jackfruit flesh flour   Microstructure   Loss factor   XRD   Pasting characteristics  

摘要： Jackfruit flour was significantly (p<.05) different from other flours due to its highest water absorption capacity (WAC) (1.57g/g), particle size (PS) (384.984 mu m) and lowest loss factor (tan), foaming stability (FS) (32.6%). The different blends consisting of jackfruit flour at 0.5%, 1%, 5%, 10%, 20%, 30% levels with equal proportions of rice and pigeonpea flour were prepared. The higher the substitution of jackfruit flour in blends, PS and WAC were increased whereas peak viscosity, trough viscosity, relative crystallinity, oil absorption capacity, foaming properties were decreased. A mixture of spherical, polyhedral and irregular shaped starch granules with less smooth granule surfaces can be observed using scanning electron microscopy. Micrographs of blends showed swollen and slightly elongated starch granules with distorted structure. Pattern recognition methods such as principal component analysis and linear discriminate analysis were performed to classify jackfruit flesh flour, rice flour and pigeonpea flour based blends on the basis of rheological, functional, microstructural and pasting properties. The variables like setback viscosity, FS, tan, final viscosity and WAC exhibited higher discrimination power.

关键词： Polar microstructure   Computer vision   Ultra-precision machining   Nanoscale measurement   Pattern recognition  

摘要： Due to the low resolution of pattern recognition and disorganized textures of the surfaces of most natural objects observed under a microscope, computer vision technology has not been widely applied in precision positioning measurement on machine tools, which needs high resolution and accuracy. This paper presents a systematic method to solve the surface recognition problem which makes use of ultra-precision diamond machining to produce a functional and polar-coordinate surface named 'polar microstructure'. The unique characteristic of a polar microstructure is the distinctive pattern of any locations including rotation in the global surface which provides the feasibility of achieving precise absolute positions by matching the patterns by utilizing computer vision technology. A polar microstructure which possesses orientation characteristics is also able to measure the displacement of rotation angle. A series of simulation experiments including feature point extraction, orientation detection as well as resolution of pattern recognition was conducted, and the results show that a polar microstructure can achieve a resolution of 9.35 nm which is capable of providing a novel computer vision-based nanometric precision measurement method which can be applied in positioning on machine tools in the future.

关键词： Neuromorphic   Hardware neural network   Artificial synapse  

摘要： To achieve high pattern recognition accuracy by using an analog input voltage scheme, we have confirmed that the conductance linearity (CL), conductance uniformity (CU) and multi-levels conductance (MLC) characteristics are the key factors for synapse devices. We analyze the CL, CU and MLC characteristics of WOx-based resistive device (RD) for hardware neural network applications. Our findings show that excellent CL of RD is achieved by engineering the WOx composition and Schottky barrier height. Further, by adjusting top electrode materials, the RD exhibits improved CU due to the uniform W-WOx contact leading to discrete MLC states of RD with varying the device area. Finally, we have successfully demonstrated the potential of WOx-based RD for synapse application of hardware inference system through neural network simulation and the hardware implementation.

关键词： Surface roughness   Machine interactive learning   Statistical pattern recognition   Robot laser hardening   SEM images  

摘要： Performance characteristics of the products made of metallic materials such as wear resistance, fatigue strength, stability of gaps and strain between the connections, corrosion resistance, etc., depend to a large extent by the quality of their surfaces roughness. An interactive control of the manufacturing parameters which influence the surface roughness is particularly crucial in the construction of many mechanical components. The present paper devises a new method for statistical pattern recognition on samples produced by the process of robot laser hardening using network theory and describes its application to the determination of surface roughness. The method is based on the analysis of SEM images. Indeed the data characterizing the state of surface irregularities detected as extremely small segments contain indicators of surface roughness. Different methods of machine learning techniques designed to predict the surface roughness of robot laser hardened material are discussed.

关键词： Radon transform   Mellin transform   invariant   Radon-Mellin transform (RMT)   Radon-Fourier descriptor (RFD)  

摘要： Radon transform is not only robust to noise, but also independent on the calculation of pattern centroid. In this paper, Radon-Mellin transform (RMT), which is a combination of Radon transform and Mellin transform, is proposed to extract invariant features. RMT converts any object into a closed curve. Radon-Fourier descriptor (RFD) is derived by applying Fourier descriptor to the obtained closed curve. The obtained RFD is invariant to scaling and rotation. (Generic) R-transform and some other Radon-based methods can be viewed as special cases of the proposed method. Experiments are conducted on some binary images and gray images.