基于Cortex-M的嵌入式设备固件更新方法研究

本文提出了一种基于分散加载技术实现Boot程序和用户应用程序在同一个工程编写开发的固件更新方法 .通过编写分散加载规范文件在工程中实现代码存储区分区.为了保证固件更新的稳定性和可靠性,在固件下载过程中引入CRC校验、丢包错包重传等容错技术.实验结果 验证了方法的有效性和可靠性.     

Cross-Layer Optimization of Dynamic Packet Assignment for Video Transmission Over IEEE 802.11e Networks

Video transmission over IEEE 802.11e wireless networks still shows poor performance for large bandwidth demand and frequently changed environments. Thus, several enhancements of IEEE 802.11e were proposed. On the other hand, big frames and simultaneous sending of adjacent frames always cause packet dropping for buffer overflow. In the past, we proposed an IEEE 802.11e enhancement named DFAA and a content aware mechanism to solve the above problems. The motivation of this paper is to find a proper way to integrate these two mechanisms. A DFAA enhancement (DFAA-E) is proposed to make up the insufficiency of content aware mechanism. Experiments results show that the combination of DFAA-E and content aware mechanism improves the video decoded quality greatly. And its performance can be further enhanced by selecting the suitable settings of certain parameters.     

Properties of high reinforcement-content aluminum matrix composite for electronic packages

Aluminum matrix composites reinforced by a high volume fraction of ceramic particles provide a novel solution to electronic packaging technology, because of their high thermal conductivity, compatible and tailorable coefficient of thermal expansion (CTE) with chips or substrates, low weight, enhanced specific stiffness, and low cost. In this paper, SiC-particle-reinforced aluminum matrix composites are fabricated by the cost-effective squeeze-casting technology, and their microstructure characteristics, thermo-physical, and mechanical properties are investigated. The reinforcement volume fraction is as high as 70% and composites with linear CTE of 6.9–9.7×10^–6 °C^–1 and thermal conductivity of 120–170 W m^–1 °C^–1 are produced. The composites can be electric-discharge machined, ground, and electric-spark drilled. An electroless nickel layer is plated on the composite by the conventional procedures. Finally, their potential applications in electronic packaging and thermal management are illustrated via prototype examples.     

基于多源多维度用能数据的用户标签萃取方法研究

随着电力行业数字化、智能化水平稳步提升,电力公司利用大数据技术精准识别用户需求、掌握用户用能规律,进而满足用户多样化的用能需求成为营造良好用电体验的关键.为此提出一种基于多源多维度用能数据的用户标签萃取方法,旨在通过采用模糊C均值聚类算法进行标签聚类、用户智能画像,更好支撑用户用电行为掌握、精准营销策略执行,辅助制定电力需求侧响应策略,推动电力服务质效提升.     

Real-time and robust hand tracking with a single depth camera

In this paper, we introduce a novel, real-time and robust hand tracking system, capable of tracking the articulated hand motion in full degrees of freedom (DOF) using a single depth camera. Unlike most previous systems, our system is able to initialize and recover from tracking loss automatically. This is achieved through an efficient two-stage k-nearest neighbor database searching method proposed in the paper. It is effective for searching from a pre-rendered database of small hand depth images, designed to provide good initial guesses for model based tracking. We also propose a robust objective function, and improve the Particle Swarm Optimization algorithm with a resampling based strategy in model based tracking. It provides continuous solutions in full DOF hand motion space more efficiently than previous methods. Our system runs at 40 fps on a GeForce GTX 580 GPU and experimental results show that the system outperforms the state-of-the-art model based hand tracking systems in terms of both speed and accuracy. The work result is of significance to various applications in the field of human–computer-interaction and virtual reality.     

干式变压器铁芯接地故障分析

本文通过对20kV及以下系统干式变压器铁芯接地故障进行分析,从定期检查、检修维护、设备管理方面提出了相应的防范措施,可为水电站机组安全运行提供借鉴。     

Contrastive Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation

In recommender systems, the cold-start issue is challenging due to the lack of interactions between users or items. Such an issue can be alleviated via data-level and model-level strategies. Traditional data-level methods employ auxiliary information like feature information to enhance the learning of user and item embeddings. Recently, Heterogeneous Information Networks (HINs) have been incorporated into the recommender system as they provide more fruitful auxiliary information and meaningful semantics. However, these models are unable to capture the structural and semantic information comprehensively and neglect the unlabeled information of HINs during training. Model-level methods propose to apply the meta-learning framework which naturally fits into the cold-start issue, as it learns the prior knowledge from similar tasks and adapts to new tasks quickly with few labeled samples. Therefore, we propose a contrastive meta-learning framework on HINs named CM-HIN, which addresses the cold-start issue at both data level and model level. In particular, we explore meta-path and network schema views to describe the higher-order and local structural information of HINs. Within meta-path and network schema views, contrastive learning is adopted to mine the unlabeled information of HINs and incorporate these two views. Extensive experiments on three benchmark datasets demonstrate that CM-HIN outperforms all state-of-the-art baselines in three cold-start scenarios.     

基于Micro830的异步电动机控制系统设计

为解决异步电动机的控制问题,本文利用Micro830PLC控制器和PowerFlex 4M变频器,构建了异步电动机控制系统,结合RsLinx和FactoryTalk View Studio软件,实现了上位机对整套电机控制系统的实时监控。同时利用RsLinx建立OPC通讯,并在FactoryTalk View Studio上利用已建立的OPC数据服务器进行上位机操作。经过对控制系统进行调试及运行,结果表明,监控软件可以实现电动机启动、停止、正反转的自由切换,响应速度快,能够实现有效地控制,整个控制系统稳定性和精确度较高,操作方便,上位机监控软件能实现转速和方向的实时显示和有效控制。该系统实现了异步电动机方向和转速的准确控制,具有良好的应用前景。     

Fast and effective color-based object tracking by boosted color distribution

In this paper, we propose a novel tracking algorithm, boosted color distribution (BCD), for tracking color objects. There exist three contributions in this paper. First, we propose a novel online gentle boost (OGB) algorithm for online learning. The essential idea of OGB is composed of two aspects: online updating candidate weak classifiers, and then choosing and combining them in a boosting way. Second, we design a novel weak classifier, log color feature distribution ratio, which focuses on the difference of color distributions rather than individual samples and provides a simple yet effective manner of mining color features for object tracking. Third, by combining our OGB algorithm and our log color features, we develop a fast yet effective color-based object tracking algorithm. Numerous experiments demonstrate that our tracking algorithm is better than or not worse than some state-of-the-art tracking algorithms on some public sequences.Overall, this paper presents a novel BCD algorithm for color object tracking that achieves good results at a fast speed.