A Fuzzy Trust Management Mechanism with Dynamic Behavior Monitoring for Wireless Sensor Networks

Traditional wireless sensor networks(WSNs)are typically deployed in remote and hostile environments for information collection.The wireless communication methods adopted by sensor nodes may make the network highly vulnerable to various attacks.Traditional encryption and authentication mechanisms cannot prevent attacks launched by internal malicious nodes.The trust-based security mechanism is usually adopted to solve this problem in WSNs.However,the behavioral evidence used for trust estimation presents some uncertainties due to the open wireless medium and the inexpensive sensor nodes.Moreover,how to efficiently collect behavioral evidences are rarely discussed.To address these issues,in this paper,we present a trust management mechanism based on fuzzy logic and a cloud model.First,a type-II fuzzy logic system is used to preprocess the behavioral evidences and alleviate uncertainty.Then,the cloud model is introduced to estimate the trust values for sensor nodes.Finally,a dynamic behavior monitoring protocol is proposed to provide a balance between energy conservation and safety assurance.Simulation results demonstrate that our trust management mechanism can effectively protect the network from internal malicious attacks while enhancing the energy efficiency of behavior monitoring.

In-situ Monitoring the Setting Behavior of Foamed Concrete Using Ultrasonic Pulse Velocity Method

The applicability of ultrasonic pulse velocity （UPV） method to in-situ monitor setting and hardening process of foamed concrete （FC） was systematically investigated. The UPVs of various FC pastes were automatically and continuously measured by a specially designed ultrasonic monitoring apparatus （UMA）. Ultrasonic tests were performed on FC mixtures with different density （300, 500, 800 and 1 000 kg/m3）, and different fly ash contents （0%, 20%, 40% and 60%）. The influence of curing temperatures （20, 40, 60 and 80~C） was also studied. The experimental results show that three characteristic stages can be clearly identified during the setting process of an arbitrary FC paste： dormant stage, acceleration stage, and deceleration stage. Wet density, fly ash content, and curing temperature have great impact on setting behavior. A stepwise increase of the wet density results in shorter dormant stage and larger final UPV. Hydration reaction rate is obviously promoted with an increase in curing temperature. However, the addition fly ash retards the microstn,lcture formation. To aid in comparing with the ultrasonic results, the consistence spread test and Vicat needle test （VNT） were also conducted. A correlation between ultrasonic and VNT results was also established to evaluate the initial and final setting time of the FC mixtures. Finally, certain ranges of UPV with reasonable widths were suggested for the initial and final setting time, respectively.

蛋鸡养殖智能巡检机器人设计概述与应用

为改善规模化蛋鸡养殖中人工巡检效率低、劳动强度大等问题,研究设计了一种适用于叠层笼养蛋鸡舍的智能巡检机器人。该巡检机器人配备电源动力系统、控制主机系统、无线通信系统、导航避障系统以及参数采集系统。同时,巡检机器人基于射频识别(RFID)和磁导航技术构建巡检地图并规划路径,实现自主移动和避障;利用EfficientNet-Lite0等深度学习算法识别死弱鸡和绝产鸡,以监测鸡只健康状态;通过SQL Server技术开发数据集成管理系统整合分析舍内采集数据,实现对鸡舍养殖环境、鸡只健康等信息的实时感知与预警。在福建光阳蛋业渔溪养殖基地示范应用结果表明,巡检机器人能根据指令自主巡检,提高养殖人员巡检效率75%。研究表明,智能巡检机器人可有效降低劳动强度,并保障蛋鸡健康和生产性能,具有较好的应用和推广价值。

挡墙渗漏对富水砂层基坑变形性状的影响

针对深基坑漏水漏砂引发的灾害问题,探究基坑渗漏灾害发展规律及其控制方法对地下工程施工安全具有重要意义。结合某富水砂层排桩深基坑渗漏灾害实例,阐释了基坑漏水漏砂灾害发展特征及诱发原因,并采用现场监测和数值模拟方法对局部渗漏水下基坑变形性状及其控制措施进行了研究。研究结果表明:(1)基坑渗漏灾害发展是一个复杂的多场耦合作用过程,具有一定的隐蔽性和突发性;(2)挡墙水平位移曲线分布发展过程为“斜线”形—“锅底”形—浅“倒V”形—深“倒V”形,渗漏后挡墙最大水平位移为渗漏前的1.29~1.44倍;(3)墙后地表沉降曲线分布发展过程为“平勺底”形—“浅勺底”形—“深勺底”形,沉降槽敏感区范围为1.00h_e~1.20h_e(h_e为开挖深度),局部渗漏引起地表沉降槽加深变宽,渗漏后最大地表沉降为渗漏前的1.16~1.65倍;(4)地下水位“跳跃式”波动变化特征可作为评判基坑渗漏灾害的前兆信号;(5)支撑轴力变化随基坑开挖与支护过程动态调整从而协调变形发展,在基坑发生渗漏过程中支撑轴力出现小幅波动。采取“注浆+高压旋喷桩”联合处治措施可有效应对富水砂层基坑渗漏灾害控制难题,研究成果可为基坑工程渗漏灾害理论研究与控制提供参考。

基于神经网络算法的反间歇性窃电行为监测方法

针对当前反间歇性窃电行为监测方法准确性差用户用电数据识别平均精度较低等问题,提出基于神经网络算法的反间歇性窃电行为监测方法。构建基础窃电分析模型;使用中值滤波器剔除采集到的无用数据,完成用电数据采集及预处理;应用神经网络逆传播算法优化窃电行为监测神经网络模型,并设定间歇性窃电行为识别函数,实现对间歇性窃电行为的监测;构建实验环节,通过F_(1)值与平均精度2种指标分析应用效果。实验结果表明:该方法使数据分析能力得到提升,能提高反间歇性窃电行为监测准确性。

A Behavior-Based Remote Trust Attestation Model

While remote trust attestation is a useful concept to detect unauthorized changes to software, the current mechanism only ensures authenticity at the start of the operating system and cannot ensure the action of running software. Our approach is to use a behavior-based monitoring agent to make remote attestation more flexible, dynamic, and trustworthy. This approach was mostly made possible by extensive use of process information which is readily available in Unix. We also made use of a behavior tree to effectively record predictable behaviors of each process. In this paper, we primarily focus on building a prototype implementation of such framework, presenting one example built on it, successfully find potential security risks in the run time of a ftp program and then evaluate the performance of this model.

A model of unsafe behavior in coal mines based on game theory

Behavior choice, coal mine monitoring, and control intensity are combined in a general mathematical model established from the perspective of a behavioral game. A case study is provided with effective conditions of monitoring provided. This paper defines the expected value difference of control return and behavior cost difference and discusses the measurement and optimization of variable indexes, including the monitoring intensity and costs of control. The results imply that the control of unsafe behavior can be more effective when monitoring and control of coal mines are both improved. Monitoring will be useful when the rewards for displaying safe behavior, and the monitoring of unsafe behavior, are improved to a high level.

Analysis of working behavior of Jinping-I Arch Dam during initial impoundment

To study the stress, deformation, and seepage pressure during the initial impoundment of the Jinping-I Arch Dam, monitoring analysis and numerical calculation were used in a dam behavior analysis that focused on the working behavior of the dam during the late period of the initial impoundment up to the end of November 2014. The numerical calculation was performed based on feedback analysis of the deformation and stress of the arch dam through inversion of the elastic moduli(E) of the dam body and foundation, using a three-dimensional finite element model for the linear elastic material of the arch dam. The main monitoring indices presented insignificant changes in the late period of the initial impoundment, and the results of feedback analysis were consistent with monitoring results. Analysis results also show that the deformations of the dam body and dam foundation were within the design range; the dam stress distributions were normal, with values lower than the design control criteria; and the seepage flows through the dam body and dam foundation were lower than the design drainage capacity of the deep-well pump house, demonstrating that the Jinping-I Arch Dam was in good working condition, and the initial impoundment had been successfully completed. The results of the working behavior analysis of the Jinping-I hydropower project during the initial impoundment can provide references for safe operation of similar projects.

基于行为画像数据挖掘的异常流量监测技术

针对现有网络异常流量检测方法存在的识别率低、丢包率高的问题,基于行为画像数据挖掘算法,对异常流量监测技术展开研究。通过行为画像数据挖掘处理采集的流量数据,删除冗余数据对有效的特征数据进行映射,并经过融合计算得到新的特征数据集,设定一个异常行为阈值,引入显露模式建立异常规则,根据阈值的变化实现对异常流量的实时监测。实验结果表明:面对网络攻击情况,提出的基于行为画像数据挖掘的异常流量监测技术依然保持着高水平的识别正确率,并且数据丢包率低,说明该监测技术安全性得到了提升。

Mining pressure monitoring and analysis in fully mechanized backfilling coal mining face-A case study in Zhai Zhen Coal Mine

Fully mechanized solid backfill mining(FMSBM) technology adopts dense backfill body to support the roof. Based on the distinguishing characteristics and mine pressure control principle in this technology, the basic principles and methods for mining pressure monitoring were analyzed and established. And the characteristics of overburden strata movement were analyzed by monitoring the support resistance of hydraulic support, the dynamic subsidence of immediate roof, the stress of backfill body, the front abutment pressure, and the mass ratio of cut coal to backfilled materials. On-site strata behavior measurements of 7403 W solid backfilling working face in Zhai Zhen Coal Mine show that the backfill body can effectively support the overburden load, obviously control the overburden strata movement, and weaken the strata behaviors distinctly. Specific performances are as follows. The support resistance decreases obviously; the dynamic subsidence of immediate roof keeps consistent to the variation of backfill body stress, and tends to be stable after the face retreating to 120-150 m away from the cut. The peak value of front abutment pressure arises at 5-12 m before the operating face, and mass ratio is greater than the designed value of 1.15, which effectively ensures the control of strata movement. The research results are bases for intensively studying basic theories of solid backfill mining strata behaviors and its control, and provide theoretical guidance for engineering design in FMSBM.

Numerical simulation of the behaviors of test square for prehistoric earthen sites during archaeological excavation

During the process of archaeological excavation in the regions of Southeast China, collapse of test square usually occurs due to poor site-specific conditions. In this paper, the fast Lagrangian analysis of continua in three dimensions（FLAC3D） is employed to reveal the behaviors of test square. Taking the archaeological works in Liangzhu prehistoric earthen sites as the research background, the paper first introduces the geological setting, excavation procedure and monitoring scheme of the studied test square. Then, the deformation of four sides of the test square is modeled using FLAC3D. By comparison, it shows that the numerical results are consistent with the results from field monitoring. The result suggests that the numerical simulation can be effectively applied to representing the actual behaviors of the test square,which is helpful for determination of excavation scheme and stability evaluation of the test square during archaeological excavation.

基于计算机视觉的电力作业人员行为分析研究现状与展望

电力作业人员的有效监管是保障电力安全生产的基础。该文对电力视频中作业人员的行为识别研究进行了归类总结,涵盖静态行为分析(穿戴分析、动作分析和组合分析)和动态行为分析(复杂动作、时序行为和行为预测等);详细综述了电力作业行为分析中的核心算法模块,包括目标检测、姿态估计和视频跟踪等;论述了电力作业行为识别在算法高效性、鲁棒性、灵活性等方面所面临的应用难点和挑战,并展望了电力作业行为智能监控领域的未来发展方向,特别强调了在软硬件结合、通用大模型、生成式人工智能方面进行技术创新和改进所蕴含的潜在机会。

Research Note: A Multi-Method Approach to Monitor Recreational Trail Usage in Complex Spatial Settings

Trail use by pedestrians has become more popular in the United States over the last decade although few studies explore the use of technology to monitor high use trails. Monitoring trail users is an important part of trail management and an optimal monitoring system usually depends on site-specific characteristics. The objective of this study was to demonstrate how using a multi-methods system to monitor backcountry trail usage in complex spatial settings can be a useful approach for collecting the information that trail managers need. Given the national growth in recreational hiking, we were particularly interested in exploring these issues for highly visited trails close to urban areas and selected a portion of the Larch Trail leading to the top of Multnomah Falls for the study. The multi-methods approach that we used included a combination of automated infrared sensor counts, manual counts, parking lot data from an inductive loop, and travel time estimates collected with low-energy Bluetooth sensors. We found that using multiple methods allowed for a cost-effective and rich data set that considered the site characteristics and the specific need of the trail managers. We expect that many backcountry trail settings have complex landscape and physical design without robust pre-existing baseline data and hope that our insights will aid trail managers as they strive for a sustainable balance between human use and landscape impact.

机器视觉技术在奶牛精准化管理中的应用研究进展

近年来,随着我国奶牛养殖规模不断扩大,对奶牛场管理提出了更高的要求,通过传统的人工方式识别奶牛和统计奶牛数据已完全不能满足现代化、规模化牧场的需求。监测奶牛的行为变化有助于提高牧场的管理决策水平,而基于机器视觉技术可为奶牛养殖过程中的个体识别、健康监测、疾病预防等提供新的解决方案。本文主要从奶牛个体识别、体况评估、行为识别与监测3个方面进行综述,总结了目前机器视觉技术在奶牛精细化管理领域的研究成果以及存在的问题,旨在为现代化牧场的精准化管理和智能化发展提供新方法和新思路。

复合纸基柔性传感器力学性能及其对人体运动行为监测研究

纸基柔性传感器是一种具有极为广阔应用前景的新式传感器,但纸基制备的柔性传感器力学性能却普遍不佳。基于纸基柔性传感器的力学性能需求,以环氧大豆油、衣康酸等为基础材料制备了一种复合纸基柔性传感器,对该柔性传感器的力学性能进行了试验分析并对该传感器对人体运动行为监测的检测效果进行测试。结果表明:该复合纸基柔性传感器力学性能较一般纸基柔性传感器更为优异,可以非常精准、高效地对人体运动行为进行监测。

深部煤-岩组合体力学特征及裂隙扩展规律——以沁水盆地武乡区块为例

煤层及其顶、底板的岩石力学性质是影响煤储层压裂、起裂和裂缝延伸的关键因素,制约深部煤层气的规模效益开发。为研究煤-岩组合体破裂过程中的力学特征及其裂隙扩展行为,根据声发射信号监测,开展了沁水盆地中、东部武乡区块煤-岩组合体的单轴压缩实验和有限元数值模拟计算,研究了煤-岩组合体中不同厚度比、不同岩性类别和不同交界面倾角对组合体抗压强度、弹性模量、声发射信号特征和破裂特征的影响规律,探究不同组合配置下的裂缝扩展行为。研究结果表明:①煤-岩组合体的抗压强度和弹性模量随煤-岩厚度比和煤-岩交界面接触倾角的增大而减小,不同岩性的组合体弹性模量介于1.75~5.44 GPa,抗压强度为11.20~20.60 MPa,其中煤岩-泥页岩组合体力学性质最弱,煤岩-砂岩组合体最强。②煤-岩厚度比增大会加剧组合体的破坏程度和裂隙数量,当煤-岩厚度比达到一定程度时,煤体发生破裂后能量会继续扩散到邻层,使整个组合体破碎。在不同岩性的组合体中,破坏难易程度为煤岩-砂岩组合>煤岩-灰岩组合>煤岩-泥页岩组合。随着煤-岩组合体交界面接触倾角增大,整体更容易被破坏失稳、产生裂隙。③随着组合体中煤岩厚度增大,发育的裂缝由张性裂隙演变为X型剪切裂隙,且由只在煤岩内部扩展逐渐过渡到整个组合体。不同岩性组合体的力学强度愈大,其裂隙越倾向于从X型剪切裂隙演变为张性裂隙,展布范围由整个组合体变为局限于煤岩内部。煤-岩交界面接触倾角的增大使组合体内部的X型剪切裂隙尺度相应增加,加剧破坏程度。

母猪精准养殖智能感知技术研究进展

母猪的生长状况、繁殖性能与健康状况是猪场管理的重要生产要素,直接关系到猪场的经济效益。我国母猪养殖还存在生产管理智能化水平低、健康管理效率低、生产力水平低等突出问题,制约了我国养殖业的高质量发展。本文从母猪生长信息感知技术、繁殖行为监测技术、健康状态感知技术等3个方面,总结了母猪精准养殖管理中生长、生理、健康监测的研究和发展现状,分析了母猪精准养殖技术的薄弱环节,对母猪养殖智慧管控系统的建设提出了建议,并对未来的发展趋势进行了展望,以期为我国养猪业绿色高效智能转型升级与智能养猪工厂的建设提供参考。

政府与公众监管下外调水与地方水合规取用的演化博弈

针对调水工程受水区用水户使用外调水意愿不足,存在过度开采当地地下水或超量使用地表水等违规取用水行为的情况,基于社会共治理念,考虑引入社会公众监督力量,借助演化博弈理论,通过建立地方政府、用水户与社会公众的三方演化博弈模型,探讨不同情况下地方政府、用水户与社会公众的演化稳定策略以及实现系统稳定的条件,并通过系统动力学仿真分析研究模型中关键参数对三方利益主体演化策略的影响。结果表明:政府监管成本、补贴力度、处罚力度、违规取用水行为监管发现率以及社会公众监督举报成本是影响三方演化博弈的关键因素。其中,降低政府监管成本能够显著提升政府监管力度;提升政府水费补贴和惩罚力度能够促进用水户选择使用外调水,相较于政府处罚力度,用水户对于政府补贴力度更加敏感;降低监督举报成本能够提升社会公众参与监督的意愿。为此,建议政府从优化监管机制和措施、完善取用水奖惩制度与引导公众广泛参与3个方面推进调水工程受水区外调水的消纳与本地水的合规取用。

受载煤体微电流效应及煤岩动力灾害预警应用展望

利用建立的受载煤体微电流测试系统,开展不同加载条件下煤样微电流测试试验,研究揭示煤体受载变形微电流效应,分析煤体受载变形过程微电流响应特征,研究微电流与煤体力学行为间的定量关系,提出微电流法预测煤岩动力灾害的原理,结合现场实践结果,对微电流技术的应用前景进行展望。结果表明,煤体受载变形能够产生微电流,微电流变化与应力变化具有较好的一致性,微电流与煤体力学行为(应力、应变、应变率等)紧密相关,在压密阶段和塑性变形阶段,微电流随应变率增加而增加,在弹性变形阶段随应力和应变线性增加;煤体在扰动载荷下能够产生随应力周期性变化的微电流,即脉动直流电,其变化与应力变化一致。微电流对煤体破坏具有较好的前兆响应,微电流在加速增加过程(塑性变形阶段)中的异常波动可作为煤体渐进性破坏的前兆特征,微电流在衰减过程中的脉冲式波动可作为煤体蠕变破坏的前兆特征。煤体受载微电流效应及现场应力梯度的存在,是矿井微电流测试的重要基础;微电流与煤体力学行为间的紧密相关性,是利用微电流技术观测煤岩体应力的重要前提;微电流对煤体破坏具有明显的前兆响应,是利用微电流技术预测预报煤岩动力灾害的重要保障。微电流技术具有响应灵敏度高、前兆信息明显和抗干扰能力强的优点,在煤岩体应力观测及煤岩动力灾害预警中具有很好的应用前景。未来需进一步开展受载煤岩微电流基础理论及应用技术方面的研究,为发展煤岩动力灾害精准时空监测预警的微电流法提供支撑。

基于生成对抗网络的驾驶行为风险监测方法

针对真实驾驶场景下驾驶行为风险难以准确判断的问题,提出一种基于生成对抗网络的生成序列评估框架,旨在通过车辆行驶状态数据与驾驶场景信息匹配度评估来提高驾驶行为风险判断的准确性。构建真实驾驶场景数据匹配序列框架,利用生成对抗网络增加不同驾驶场景的数据量,提出一个驾驶员个性化情景感知样本数据集,对比分析真实数据和生成数据,并验证生成对抗网络检索与生成框架在匹配车辆行驶状态数据与驾驶场景信息方面的有效性和准确性。采用无监督学习生成评估框架,结合自回归模型中的监督训练控制策略来解决数据扩增问题,并通过迭代更新样本序列进行策略集成以保持模型鲁棒性。实验结果表明,相较于现有方法,所提研究框架在识别危险驾驶状态方面具有明显优势,为车辆行驶状态数据与驾驶场景信息的匹配评估提供了一种新的视角。