基于嵌入式的电网自动调度信息分级采集系统设计

传统系统在电网调度信息采集的过程中,未对其进行分级,导致系统采集数据误差较大,准确度较低.为了提高电网自动调度信息分级采集能力,提出基于嵌入式的电网自动调度信息分级采集系统.构建电网自动调度信息的大数据挖掘模型,结合嵌入式调度方法,实现电网自动调度信息分级采集和优化检索.仿真结果表明,电网自动调度信息分集采集的准确度较高,自适应性较好,具有一定可行性,数据准确性满足系统设计需要,达到实用效果.     

FORMATION OF μ-PHASE AND ITS EFFECT ON MECHANICAL PROPERTIES OF CAST NICKEL-BASE SUPERALLOYS

本文研究了铸造镍基高温合金中沉淀的片状μ相,揭示了μ相的形成规律、化学成份、TTT曲线、断裂特征和对力学性能的影响。研究结果表明,μ相的形成温度范围很宽,从800—1140℃。片状μ相的宽面是六方指数的{0001},它沿基体γ的{111}面板出。在760℃以下冲击,拉伸和持久的断裂特征是沿μ相{0001},面解理断裂,电子空位数N_v值不是控制μ相形成的唯一因素,还与(Mo+W)at.-％和Mo(Mo+W)有关。此外,硼也是抑制μ相的有效因素。     

射线检测中运动模糊图像的恢复

X射线实时成像检测中,若曝光时间内工件和X射线图像采集设备有相对线性运动,会造成图像运动模糊降质。提出利用运动模糊点扩展函数的频域特征和Hough变换得到模糊图像的运动方向,并将之旋转到水平轴方向,利用差分法求解运动模糊点扩展函数的长度。并用Wiener滤波的方法,恢复降质的图像,取得了较好的效果。     

A new image fusion performance metric based on visual information fidelity

Because subjective evaluation is not adequate for assessing work in an automatic system, using an objective image fusion performance metric is a common approach to evaluate the quality of different fusion schemes. In this paper, a multi-resolution image fusion metric using visual information fidelity (VIF) is presented to assess fusion performance objectively. This method has four stages: (1) Source and fused images are filtered and divided into blocks. (2) Visual information is evaluated with and without distortion information in each block. (3) The visual information fidelity for fusion (VIFF) of each sub-band is calculated. (4) The overall quality measure is determined by weighting the VIFF of each sub-band. In our experiment, the proposed fusion assessment method is compared with several existing fusion metrics using the subjective test dataset provided by Petrovic. We found that VIFF performs better in terms of both human perception matching and computational complexity.     

Test frame updating in CPM testing of Prolog programs

Category Partition Method (CPM) is a general approach to specification-based program testing, where test frame reduction and refinement are two important issues. Test frame reduction is necessary since too many test frames may be produced, and test frame refinement is important since during CPM testing new information about test frame generation may be achieved and considered incrementally. Besides the information provided by testers or users, implementation related knowledge offers alternative information for reducing and refining CPM test frames. This paper explores the idea by proposing a call patterns semantics based test frame updating method for Prolog programs, in which a call patterns analysis is used to collect information about the way in which procedures are used in a program. The updated test frames will be represented as constraints. The effect of our test frame updating is two-fold. On one hand, it removes “uncared” data from the original set of test frames; on the other hand, it refines the test frames to which we should pay more attention. The first effect makes the input domain on which a procedure must be tested a subset of the procedure’s input domain, and the latter makes testers stand more chance to find out the faults that are more likely to show their presence in the use of the program under consideration. Our test frame updating method preserves the effectiveness of CPM testing with respect to the detection of faults we care. The test case generation from the updated set of test frames is also discussed. In order to show the applicability of our method an approximation call patterns semantics is proposed, and the test frame updating on the semantics is illustrated by an example.

谈电子产品中的色彩设计

本文通过对色彩设计在电子产品设计中的应用的分析研究,说明不同的色彩给人不同的感受,并进一步说明色彩设计对电子产品设计产生不同的影响作用以及色彩设计的发展.     

Fiducial markers for increasing the versatility of optical correlation in the measurement of faults on integrated-circuit wafers

A microscope-coherent optical processor is used for the measurement of the registration errors on integrated-circuit wafers. The measurements are obtained from the optical correlation of wafers with reference wafer patterns by use of matched spatial filters. Previously, the intricate pattern of the active circuit area of wafers has been used in the correlation process, and a new matched spatial filter had to be created for each different integrated circuit. Here, the results of using comparatively plain fiducial markers on a wafer for the registration-error measurement are presented, and these show that the measurements can be made independent of the design of the integrated circuit while maintaining the advantages and accuracy of the optical correlation technique.     

Surface Control and Electrical Tuning of MXene Electrode for Flexible Self-Powered Human–Machine Interaction

MXene materials emerge as promising candidates for energy harvesting and storage application. In this study, the effect of the surface chemistry on the work function of MXenes, which determines the performance of MXene-based triboelectric nanogenerator (TENG), is elucidated. First-principles calculations reveal that the surface functional group greatly influences MXene work function:  OH termination reduces the work function with respect to that of bare surface, while  F and  Cl increase it. Then, work functions are experimentally determined by Kelvin probe force microscopy. The MXene prepared by gentle etching at 40 °C for 48 h (GE_40/48) has the largest work function. Furthermore, an electron-cloud potential-well model is established to explain the mechanism of electron emission-dominated charge transfer and assemble a triboelectric device to verify experimentally its conclusions. It is found that GE_40/48 has the best performance with a 281 V open-circuit voltage, 9.7 µA short-current current, and storing 1.019 µC of charge, which is consistent with the model. Last, a patterned TENG is demonstrated for self-powered human–machine interaction application. This finding enhances the understanding of the inherent mechanism between the surface structure and the output performance of MXene-based TENG, which can be applied to other TENG based on 2D materials.     

An SPH-based mass transfer model for simulating hydraulic characteristics and mass transfer process of dammed rivers

Engineering with Computers - Aerated flow characterized by complex mass transfer processes with multiple hydraulic properties is a common enviro-hydraulics phenomenon, which have a variety of...     

Application of intelligent real-time image processing in fitness motion detection under internet of things

The purpose is to study the applicability of digital and intelligent real-time Image Processing (IP) in fitness motion detection under the environment of the Internet of Things (IoT). Given the absence of real-time training standards and possible workout injury problems during fitness activities, an intelligent fitness real-time IP system based on Deep Learning (DL) is implemented. Specifically, the keyframes of the real-time images are collected from the fitness monitoring video, and the DL algorithm is introduced to analyze the fitness motions. Afterward, the performance of the proposed system is evaluated through simulation. Subsequently, the Noise Reduction (NR) performance of the proposed algorithm is evaluated from the Peak Signal-to-Noise Ratio (PSNR), which remains above 20 dB for seriously noisy images (with a noise density reaching up to 90%). By comparison, the PSNR of the Standard Median Filter (SMF) and Ranked-order Based Adaptive Median Filter (RAMF) algorithms are not higher than 10 dB. Meanwhile, the proposed algorithm outperforms other DL algorithms by over 2.24% with a detection accuracy of 97.80%; the proposed system can adaptively detect the fitness motion, with a transmission delay no larger than 1 s given a maximum of 750 keyframes. Therefore, the proposed DL-based intelligent fitness real-time IP algorithm has strong robustness, high detection accuracy, and excellent real-time image diagnosis and processing effect, thus providing an experimental reference for sports digitalization and intellectualization.