Moist-Electric Generator with Efficient Output and Scalable Integration Based on Carbonized Polymer Dot and Liquid Metal Active Electrode

Moisture-enabled electricity generation (MEG) is highly promising in next-generation energy conversion. However, the practical applications of existing MEG devices are limited due to their low current and voltage outputs, strong dependence on high moisture, and inflexible nature. Herein, an efficient MEG integrated with flexible, all-weather, and scalable fabrication characteristics based on the rational combination of carbonized polymer dots (CPDs) and liquid metal (LM) active electrodes is developed for the first time. Remarkably, the fabricated MEG device can produce a stable voltage output of 800 mV and a record high current density of 1640 µA cm⁻². Even at a low air humidity of 15%, the MEG device can provide a high voltage output of 0.65 V and a considerable current density of 12 µA cm⁻². The prompted diffusion of hydrogen ions in CPDs and the additional metal ions ionized from the LM electrode contribute synergistically to the high electricity generation. Additionally, the device can be easily integrated on various flexible substrates and generate an ultrahigh voltage of 210 V to power commercial electronics, showing great potential in large-scale fabrication and application.     

Classification of Imagined Speech EEG Signals with DWT and SVM

With the development of human–computer interaction technology, brain–computer interface (BCI) has been widely used in medical, entertainment, military, and other fields. Imagined speech is the latest paradigm of BCI and represents the mental process of imagining a word without making a sound or making clear facial movements. Imagined speech allows patients with physical disabilities to communicate with the outside world and use smart devices through imagination. Imagined speech can meet the needs of more complex manipulative tasks considering its more intuitive features. This study proposes a classification method of imagined speech Electroencephalogram (EEG) signals with discrete wavelet transform (DWT) and support vector machine (SVM). An open dataset that consists of 15 subjects imagining speaking six different words, namely, up, down, left, right, backward, and forward, is used. The objective is to improve the classification accuracy of imagined speech BCI system. The features of EEG signals are first extracted by DWT, and the imagined words are classified by SVM with the above features. Experimental results show that the proposed method achieves an average accuracy of 61.69%, which is better than those of existing methods for classifying imagined speech tasks.     

M2OVQA: Multi-space signal characterization and multi-channel information aggregation for quality assessment of compressed omnidirectional videos

Considering the high requirements for omnidirectional video compression, we propose an objective quality evaluation method to assess quality loss in encoding omnidirectional videos. According to characteristics of 360° videos, we consider multi-space signal characterization (MSSC) to fully characterize the distortions of video signals from spatial/image domains to frequency domains and from image content to motion information, and further consider multi-channel information aggregation (MCIA) to fuse scores from multiple projection planes and temporal divided groups. The main innovation of our method is to establish a universal framework in bridging the connection between typical quality assessment and 360° quality assessment to measure 360° video quality effectively and efficiently. Experimental results show that our method outperforms state-of-the-art 2D quality metrics and quality metrics for omnidirectional images.     

直流调速系统不用测速机实现速度反馈探索

分析了实现速度反馈的几种途径,提出了一种不用测速机实现速度反馈的新思想,通过对一实验装置的研究证实了这一思想的可行性。     

基于MATLAB的同步发电机PSS与励磁系统仿真

在分析同步发电机励磁控制系统模型的基础上,研究了以电力系统稳定器（Power System Stabilizer—PSS）为辅助控制的同步发电机励磁控制方式,并基于MATLAB／SIMULINK构建了包含PSS的励磁控制系统的仿真模型。根据仿真结果分析在电力系统出现不同故障（三线短路以及断线故障）情况下带有PSS的励磁控制系统的控制性能,并与不加载PSS的励磁系统进行了比较,得到了在同步机励磁系统中加载PSS的必要性,为励磁系统的设计提供了依据。     

并网系统逆变器锁相环的研究

在太阳能光伏发电系统中,并网逆变器是实现光伏电能馈送电网的重要环节,并网光伏逆变器的控制目标为：控制逆变电路的输出为稳定的、高品质的正弦波,且与电网电压同频、同相。鉴于此,本文提出了一种数字电流锁相的方法,并且进行了系统仿真。仿真结果表明,TMS320C2000系列DSP芯片适用于该数字锁相技术,其并网输出电流波形良好...     

多路信号采集系统设计

信号采集器是信号和和控制器之间的枢纽,采集信号的质量和采集速度与控制质量密切相关。然而,自然界中的信号各种各样,环境复杂,而且控制器对信号的要求亦各不相同,这些都使得信号采集一直以来都存在技术难点。本文基于C8051F020单片机设计了一款多路信号采集系统,与传统的数据采集器相比,C8051F020具有集成度高、逻辑实...     

ADC系统性能测试及提高

本文简介了一种基于FPGA和DSP,对ADC系统进行性能分析并对其转换后的数字进行数据采集的方法。其中性能分析主要是针对ADC的信噪比和无杂散动态范围。同时,主要介绍了ADC系统中时钟、电源、模拟信号输入等方面性能改善的方法。并以此来提高SNR,实现对有效位数和整体性能的提高。     

Enabling energy-efficient and lossy-aware data compression in wireless sensor networks by multi-objective evolutionary optimization

Nodes of wireless sensor networks (WSNs) are typically powered by batteries with a limited capacity. Thus, energy is a primary constraint in the design and deployment of WSNs. Since radio communication is in general the main cause of power consumption, the different techniques proposed in the literature to improve energy efficiency have mainly focused on limiting transmission/reception of data, for instance, by adopting data compression and/or aggregation. The limited resources available in a sensor node demand, however, the development of specifically designed algorithms. To this aim, we propose an approach to perform lossy compression on single node based on a differential pulse code modulation scheme with quantization of the differences between consecutive samples. Since different combinations of the quantization process parameters determine different trade-offs between compression performance and information loss, we exploit a multi-objective evolutionary algorithm to generate a set of combinations of these parameters corresponding to different optimal trade-offs. The user can therefore choose the combination with the most suitable trade-off for the specific application. We tested our lossy compression approach on three datasets collected by real WSNs. We show that our approach can achieve significant compression ratios despite negligible reconstruction errors. Further, we discuss how our approach outperforms LTC, a lossy compression algorithm purposely designed to be embedded in sensor nodes, in terms of compression rate and complexity.