直升机发动机超转实验系统的测频设计

本文采用FPGA技术测量直升机发动机转速,介绍了双通道等精度测频的原理,设计了信号调理电路,并在FPGA上设计了Verilog代码,在实际应用中测量直升机发动机转速表现了良好的系统实时性能。     

企业信息安全事件控制方案研究

结合企业信息突发事件应急响应的实际情况,分析了目前常见的信息安全事件,提出了在事件控制中采用的关键技术及有效的防范措施。     

基于车联网的隐私保护数据聚合研究综述

随着智能网联汽车的普及,用户数据的隐私问题成为了车联网发展中亟待解决的问题。针对车联网聚合方案的研究现状,对当前方案中存在的问题进行分析总结。首先,系统地介绍了车联网中主流系统模型和车联网中常见的攻击模型;其次,对当前国内外应用在车联网中的聚合方案的安全性、效率和优劣进行分析总结,分别从签名阶段聚合方案、用户数据收集和传输阶段聚合方案和云平台处理数据阶段聚合方案三方面对其进行讨论;最后,阐述了车联网聚合方案中存在的问题及解决方法,展望了车联网聚合方案未来的研究方向。     

金沙江中游梯级水电站联合优化调度实践

分析了金沙江中游区域梯级水电站联合调度的特殊性及复杂性,从电调的角度介绍了金中集控中心自成立以来对受控梯级水电站联合调度的具体实施,总结了梯级水电站联合优化调度的措施,并分析了梯级水电站联合优化调度的综合效益,发现优化调度成效明显。     

Design of composite data acquisition gateway based on 5G network

The integrated data collection system hasn't changed much over the years. Their growth is dominated by digital filtering, and they get a new avionics bus. Time division multiplexing is still used to communicate with the system's data collector. These schemes make use of commands and data buses. While this method works, it has many drawbacks. These shortcomings are overwhelming the strict system architecture, system bandwidth limits, and expertise to only obtain an avionics bus, otherwise system bandwidth and one-way flow of data and control. This lead for high-end video recorders. To quietly monitor our actions and valuable information provides important warnings. However, it is usually completed by a device with this small processing power, which tracks the device, stores the data of the user's data, and is limited in processing. Therefore, it is important to store and process user data in the cloud to track 5 G network activity. This article proposes a simple 5G network gateway solution for custom user monitoring equipment. Collects charge data on Network 5G and Charging-aware multi-mode based routing protocol (CMRP). The CMRP routing mechanism is not yet stable, but the changes depend on the state of the energy charge sensor. This cannot be complemented by energy-efficient sensors and routing protocols that consume less energy.     

Data monitoring and sports injury prediction model based on embedded system and machine learning algorithm

Managing sports performance is very important in the sports industry. Performance, the executives, centers on boosting competitor execution and decreasing the danger of injury. Several factors contribute to these goals, including player health, emotional status, exercise load and physical intensity requirements. Generally speaking, injury prediction is an essential component of injury prevention, and successful identification of injury prediction is a primary indicator for effective prevention. The proposed Artificial Neural Network (ANN) objective is to develop and use early-doing ability and exercise load data to validate a hierarchical machine learning prediction system with accurate detection of player injuries. The physical and workload that requires detection of this early personalized damage can be avoided with specific help. The framework is used to test 21 soccer players’ sports information from various sources, including gathered and inside burden information, outside burden information, and review information. The entirety of this information is fused into the proposed framework to improve the exactness of harm expectation. This calculation distinguishes competitors in danger of injury, with their early intervention available.     

The ability of eye-tracking metrics to classify and predict the perceived driving workload

Traffic safety is directly related to the mental and physical condition of the driver. Performing regular secondary tasks while driving is an additional activity that dissipates attention and adds to the drivers' workload. Identifying driver fatigue and workload based on gaze behavior is one way to ensure a safe driving experience. The purpose of this paper is to classify and predict driving perceived workload using a set of eye-tracking metrics (gaze fixation, duration, pointing, and pupil diameter). The ability of eye-tracking metrics to predict driving workload has been investigated. As a result, frustration, performance, and temporal load showed a correlation with gaze metrics. Gaze point, duration, fixation, and pupil diameter significantly influence driving workload.Relevance to industry: Results will supply the specialists in eye-tracking/sensor technologies and traffic safety with new knowledge to improve the design of the driving performance and safety monitoring systems and efficiency of the driving process.     

Software defect prediction model based on LASSO–SVM

Neural Computing and Applications - A software defect report is a bug in the software system that developers and users submit to the software defect library during software development and...     

采空区自然发火监测系统的设计

针对现有的采空区自然发火监测方式成本高、易出现故障、维护困难且有线传输方式不可靠的问题,采用无线射频技术和CAN总线技术设计了一种采空区自然发火监测系统,详细介绍了系统的整体架构,主要硬件部分的设计,以及无线通信频率、探头工作时序、无线接收分站工作流程、无线路由控制协议等关键技术的实现等。测试结果表明,该系统组网快速,当两探头间距小于150 m时能够对各监测节点处的温度数据进行实时采集及可靠传输,工作寿命达90 d。     

A delay‐dependent bounded real lemma for singular LPV systems with time‐variant delay

This paper is concerned with establishing a delay‐dependent bounded real lemma (BRL) for singular linear parameter‐varying (LPV) systems with time‐variant delay. In terms of linear matrix inequality, a delay‐dependent BRL is presented to ensure singular time‐delay LPV systems to be admissible and satisfy a prescribed H_∞ performance level. The BRL is obtained based on the construction of a parameter‐dependent Lyapunov–Krasovskii functional. The effectiveness of the proposed approach is shown by several numerical examples. Copyright © 2011 John Wiley & Sons, Ltd.