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.

多重链路网络分区与QoS度量两级并行QoSR算法

在多重链路上联网络环境下,采用并行路由搜索的思想寻找最优路径,能够获得较好的路径寻优结果,并且算法的时间复杂度较低.给出一种两级并行QoSR算法,将多重链路环境按一定规则划分为若干分区,为每个分区分配一定数量的QoS度量并行处理器和1个分区处理器,在各个分区分别采用QPAS算法,由QoS度量并行处理器并行计算出各分区内的QoS度量Pareto最佳路径,最终由分区处理器调用最短路径并行算法完成分区间代价最小路径的计算.     

基于WSNs的脉搏血氧饱和度中央监护系统设计

设计了基于无线传感器网络(WSNs)的脉搏血氧饱和度中央监护系统;系统利用WSNs的各节点位置随机分布,自组织网络等特性,结合脉搏血氧饱和度监测仪,应用无线的方式完成了病人脉搏血氧饱和度监测的任务;其中一个传感器节点与血氧仪相连进行数据采集;其它的节点组成多跳路由通讯网络,把血氧仪采集到的数据传到中央监控站(host computer)里;最后通过一个友好的图形用户界面来接收和显示所有的监测患者的实时监测数据,并经分析、处理后实现自动报警,自动记录;试验结果表明具有很高的测量精确度,且在设备的实用性、方便性、可管理性等方面有了极大提高。     

基于SD卡的低功耗多通道内记系统设计

给出一种应用于低功耗数据采集仪的SD卡设计方案,该方案选用高性能单片机C8051F020作为主控制器,采用SPI总线接口方式与SD卡相连,引入了FAT16文件系统来管理存储在SD卡上的数据。讨论了系统硬件接口和软件设计。     

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.