results: simulations 显示，使用 FlexRDZ 可以减少移动设备干扰的干扰强度达20dBm，同时保持测试发射机的通信能力和上线率。Abstract
FlexRDZ is an online, autonomous manager for radio dynamic zones (RDZ) that seeks to enable the safe operation of RDZs through real-time control of deployed test transmitters. FlexRDZ leverages Hierarchical Task Networks and digital twin modeling to plan and resolve RDZ violations in near real-time. We prototype FlexRDZ with GTPyhop and the Terrain Integrated Rough Earth Model (TIREM). We deploy and evaluate FlexRDZ within a simulated version of the Salt Lake City POWDER testbed, a potential urban RDZ environment. Our simulations show that FlexRDZ enables up to a 20 dBm reduction in mobile interference and a significant reduction in the total power of leaked transmissions while preserving the overall communication capabilities and uptime of test transmitters. To our knowledge, FlexRDZ is the first autonomous system for RDZ management.
摘要
flexrdz 是一个在线、自主的电台动态区域（rdz）管理器，旨在通过实时控制部署的测试发射器来确保rdz的安全运行。 flexrdz 利用层次任务网络和数字双子模型来在实时内计划和解决rdz 违反。我们使用gtpyhop 和 terrain 集成粗地模型（tirem）来详细描述flexrdz。我们在一个模拟的盐湖城powder测试环境中部署并评估flexrdz，我们的仿真结果表明，flexrdz 可以减少移动设备干扰的干扰范围，并减少泄漏的发射功率，同时保持测试发射器的通信能力和上线率。在我们所知道的情况下，flexrdz 是首个自主的rdz管理系统。
Variational Tracking and Redetection for Closely-spaced Objects in Heavy Clutter
results: 该论文的实验结果表明，VB-AbNHPP 跟踪器在具有高密度的 closely-spaced objects 和重重雷区域的情况下，比较高效和准确地跟踪目标。此外，该论文还提出了一种自动检测和恢复丢失跟踪的方法，可以在极大的监测区域中快速 rediscover 丢失的目标。Abstract
The non-homogeneous Poisson process (NHPP) is a widely used measurement model that allows for an object to generate multiple measurements over time. However, it can be difficult to efficiently and reliably track multiple objects under this NHPP model in scenarios with a high density of closely-spaced objects and heavy clutter. Therefore, based on the general coordinate ascent variational filtering framework, this paper presents a variational Bayes association-based NHPP tracker (VB-AbNHPP) that can efficiently perform tracking, data association, and learning of target and clutter rates with a parallelisable implementation. In addition, a variational localisation strategy is proposed, which enables rapid rediscovery of missed targets from a large surveillance area under extremely heavy clutter. This strategy is integrated into the VB-AbNHPP tracker, resulting in a robust methodology that can automatically detect and recover from track loss. This tracker demonstrates improved tracking performance compared with existing trackers in challenging scenarios, in terms of both accuracy and efficiency.
摘要
非均匀波恩斯过程（NHPP）是一种广泛使用的测量模型，允许对象在时间上产生多个测量。然而，在高密度的 closely-spaced 对象和重重干扰的情况下，可能difficult to efficiently and reliably track multiple objects under this NHPP model。因此，基于通用坐标征枢点升级滤波框架，这篇论文提出了一种基于变分浓 Bayes 协同跟踪（VB-AbNHPP）算法，可以高效地进行跟踪、数据协同和学习目标和干扰率的学习。此外，一种变分本地化策略也被提出，可以快速 rediscover 丢失的目标在极高干扰的情况下。这种策略被纳入 VB-AbNHPP 跟踪器中，导致了一种自动探测和恢复失踪的方法。这种跟踪器在复杂的情况下表现出了改善的跟踪性能，比如精度和效率。
Pupillary activity in areas of interest from visual stimuli for neonatal pain assessment
results: 研究结果表明，传统的视觉追踪指标可能并不直接关联到相应的认知负荷。两个样本组参与者在分析疼痛和无疼痛脸部图像时，视觉注意力反映在传统指标中可能不同。Abstract
This paper compares the pupillary activity index to traditional eye-tracking metrics like the fixation count and duration in assessing neonatal pain. It explores the benefits of incorporating pupillary activity measures to improve methods that lead to an understanding of cognitive processing and performance evaluation. The estimation of cognitive load using pupil diameter typically involves measures relative to a baseline. Instead, we conducted an eye-tracking study using the Low/High Index of Pupillary Activity to evaluate healthcare experts and non-experts analyzing the faces with and without pain from a dataset of newborn faces. This data was recorded by the Tobii TX300 eye-tracking system in a closed room with controlled lighting. Our contribution is to introduce the LHIPA calculation considering the areas of interest segments of the pupil diameter signal. The results suggest that the visual attention reflected by the traditional metrics may not correspond directly to the respective cognitive load for both sample groups of participants.
摘要
Translated into Simplified Chinese:这篇论文比较了腔Activity指数与传统的眼动跟踪指标，如fixation count和持续时间，以评估新生儿痛苦。它探讨了通过包含腔Activity测量来改进认知处理和性能评估方法的优点。通常来说，计算腔Activity需要相对于基准值进行估算。而我们则通过使用TX300眼动跟踪系统在控制的照明下录制了新生儿脸部图像，并使用低/高腔Activity指数来评估医疗专业人员和非专业人员对无痛和痛苦脸部图像的分析。我们的贡献在于在计算LHIPA时考虑了脸部图像中的区域关注段。结果表明，传统指标中的视觉注意力可能并不直接对应认知负荷的各个组合。
Output-only Modal Identification of beams with different boundary condition
paper_authors: M. R. Davoodi, S. A. Mostafavian, S. R. Nabavian, GH. R. Jahangiri
for: 本研究旨在evaluating the integrity of civil structures by observing their dynamic responses over time, specifically focusing on identifying the modal parameters of structures using output-only identification techniques.
methods: 该研究使用了Finite Element Method (FEM) and MATLAB software to model and analyze the behavior of four beams with different boundary conditions and arbitrary loading. The modal parameters were identified using Frequency Domain Decomposition (FDD) and Peak Picking (PP) methods, and the results were compared with the input-output method using Frequency Relation Function (FRF).
results: 研究结果显示了三种方法之间的好匹配，即FDD、PP和FRF方法对梁的动态特性具有良好的一致性。Abstract
Structural Health Monitoring (SHM) evaluates the integrity of a structure by observing its dynamic responses by an array of sensors over time to determine the current health state of the structure. The most important step of SHM is system identification which in civil structures is the identification of modal parameters of structures. Due to numerous limitations of input-output methods, system identification of ambient vibration structures using output-only identification techniques has become a key issue in structural health monitoring and assessment of engineering structures. In this paper, four beams with different boundary conditions and with arbitrary loading have been modeled in finite element software, ANSYS, and the responses (Acceleration of nodes) have been achieved. By using these data and the codes written in MATLAB software, the modal parameters (natural frequencies, mode shapes) of the beams are identified with FDD (frequency Domain Decomposition) and PP (Peak Picking) methods and then justified with the results of input-output method which was determined by frequency relation function (FRF). The results indicate a good agreement between the three methods for determining the dynamic characteristics of beams.
摘要
Structural Health Monitoring (SHM) 评估结构的完整性 by 观察其动态响应，通过数组传感器在时间上观察，以确定结构当前的健康状态。结构体系识别是结构体系的关键步骤，在 Civil 结构中最重要的是模式参数的识别。由于输入输出方法的限制，结构体系识别使用输出只识别技术在结构健康监测和工程结构评估中变得非常重要。在本文中，我们使用 ANSYS 软件模拟了四根不同边界条件的梁，并在这些梁上应用了任意的荷载。通过这些数据和 MATLAB 软件中写的代码，我们使用 FDD（频域分解）和 PP（峰挑出）方法来识别梁的模式参数（自然频率、模式形），并与输入输出方法确定的频率关系函数（FRF）的结果进行比较。结果表明，三种方法在梁的动态特性方面具有良好的一致性。
Direction-of-arrival estimation with conventional co-prime arrays using deep learning-based probablistic Bayesian neural networks
for: investigate the direction-of-arrival (DOA) estimation of narrow band signals with conventional co-prime arrays
methods: probabilistic Bayesian neural networks (PBNN) and a super resolution DOA estimation method based on Bayesian neural networks
results: enhances the generalization of untrained scenarios and provides robustness to non-ideal conditions, such as small angle separation, data scarcity, and imperfect arrays.Abstract
The paper investigates the direction-of-arrival (DOA) estimation of narrow band signals with conventional co-prime arrays by using probabilistic Bayesian neural networks (PBNN). A super resolution DOA estimation method based on Bayesian neural networks and a spatially overcomplete array output formulation overcomes the pre-assumption dependencies of the model-driven DOA estimation methods. The proposed DOA estimation method utilizes a PBNN model to capture both data and model uncertainty. The developed PBNN model is trained to do the mapping from the pseudo-spectrum to the super resolution spectrum. This learning-based method enhances the generalization of untrained scenarios, and it provides robustness to non-ideal conditions, e.g., small angle separation, data scarcity, and imperfect arrays, etc. Simulation results demonstrate the loss curves of the PBNN model and deterministic model. Simulations are carried out to validate the performance of PBNN model compared to a deterministic model of conventional neural networks (CNN).
摘要
文章 investigate 方向来源（DOA）估算窄频信号的传统伙 Prime 阵列上的应用，使用概率 Bayesian 神经网络（PBNN）。一种基于 Bayesian 神经网络的超解析 DOA 估算方法，扩展了模型驱动 DOA 估算方法的假设dependencies。提案的 DOA 估算方法利用 PBNN 模型捕捉数据和模型不确定性。开发的 PBNN 模型是将 pseudo-spectrum 与超解析 specturm 之间的映射执行。这个学习基于方法提高了无条件enario 的通用性，并提供了不IDEAL 状况下的Robustness，例如小角分离、数据缺乏、不完整阵列等等。在 Simulation 中，文章显示了 PBNN 模型和决定性模型的损失曲线。透过实验 validate PBNN 模型与传统神经网络（CNN）的决定性模型之间的表现差异。
Towards Robust Velocity and Position Estimation of Opponents for Autonomous Racing Using Low-Power Radar
results: 论文的结果表明，使用该系统可以在10个毫瓦特的电力消耗下实现距离估计的误差在0.21+-0.29米之间，速度估计的误差在0.39+-0.19米/秒之间。这个系统可以与其他感知器如LiDAR和摄像头结合使用，并可以在许多应用场景中使用。Abstract
This paper presents the design and development of an intelligent subsystem that includes a novel low-power radar sensor integrated into an autonomous racing perception pipeline to robustly estimate the position and velocity of dynamic obstacles. The proposed system, based on the Infineon BGT60TR13D radar, is evaluated in a real-world scenario with scaled race cars. The paper explores the benefits and limitations of using such a sensor subsystem and draws conclusions based on field-collected data. The results demonstrate a tracking error up to 0.21 +- 0.29 m in distance estimation and 0.39 +- 0.19 m/s in velocity estimation, despite the power consumption in the range of 10s of milliwatts. The presented system provides complementary information to other sensors such as LiDAR and camera, and can be used in a wide range of applications beyond autonomous racing.
摘要
Translation notes:* "infineon" is translated as " infinion" (因 Finland) in Simplified Chinese, as it is a German company.* "BGT60TR13D" is translated as "BGT60TR13D" in Simplified Chinese, as it is a product name and not a Chinese word.* "scaled race cars" is translated as "缩小赛车" (scaled down race cars) in Simplified Chinese.* "tracking error" is translated as "跟踪误差" (tracking error) in Simplified Chinese.* "power consumption" is translated as "能源消耗" (power consumption) in Simplified Chinese.* "milliwatts" is translated as "毫瓦" (milliwatts) in Simplified Chinese.
A balanced Memristor-CMOS ternary logic family and its application
results: 研究人员通过对两种设计方案的比较和分析，提供了后续三值逻辑电路的参考。Abstract
The design of balanced ternary digital logic circuits based on memristors and conventional CMOS devices is proposed. First, balanced ternary minimum gate TMIN, maximum gate TMAX and ternary inverters are systematically designed and verified by simulation, and then logic circuits such as ternary encoders, decoders and multiplexers are designed on this basis. Two different schemes are then used to realize the design of functional combinational logic circuits such as a balanced ternary half adder, multiplier, and numerical comparator. Finally, we report a series of comparisons and analyses of the two design schemes, which provide a reference for subsequent research and development of three-valued logic circuits.
摘要
“提出了基于抗阻门和CMOS设备的均衡三值逻辑电路设计。首先，设计了均衡三值最小门TMIN、最大门TMAX和三值逻辑滤波器，并通过仿真验证。然后，基于这些设计，设计了三值编码器、解码器和多路复用器。接着，采用了两种不同的实现方案，实现了功能 combinational 逻辑电路的设计，如均衡三值半加器、乘法器和数字比较器。最后，对两个设计方案进行了比较和分析，以供后续研究和发展三值逻辑电路的参考。”Note that the translation is in Simplified Chinese, which is the standard form of Chinese used in mainland China and Singapore. If you need Traditional Chinese, please let me know and I can provide that as well.
Half-Duplex APs with Dynamic TDD vs. Full-Duplex APs in Cell-Free Systems
results: 数值结果表明，论文的提案方法可以与多种 referential 相比，并且在相同的天线密度下，DTDD系统可以与FD系统具有相同的性能，而不需要进行内部基站干扰抑制。因此，DTDD与CF结合是一种可行的代替方案，可以在HD AP上实现类似的性能，而不需要进行FD系统的干扰抑制。Abstract
In this paper, we present a comparative study of half-duplex (HD) access points (APs) with dynamic time-division duplex (DTDD) and full-duplex (FD) APs in cell-free (CF) systems. Although both DTDD and FD CF systems support concurrent downlink transmission and uplink reception capability, the sum spectral efficiency (SE) is limited by various cross-link interferences. We first present a novel pilot allocation scheme that minimizes the pilot length required to ensure no pilot contamination among the user equipments (UEs) served by at least one common AP. Then, we derive the sum SE in closed form, considering zero-forcing combining and precoding along with the signal-to-interference plus noise ratio optimal weighting at the central processing unit. We also present a provably convergent algorithm for joint uplink-downlink power allocation and uplink/downlink mode scheduling of the APs (for DTDD) to maximize the sum SE. Our numerical results illustrate the superiority of the proposed algorithms over several benchmarks and show that the sum SE with DTDD can outperform an FD CF system with similar antenna density. Thus, DTDD combined with CF is a promising alternative to FD that attains the same performance using HD APs, while obviating the burden of intra-AP interference cancellation.
摘要
在这篇论文中，我们进行了半杂推测点（HD）接入点（AP）与动态时分多杂分多杂（DTDD）和全杂推测点（FD）CF系统的比较研究。虽然DTDD和FD CF系统都支持同时下行传输和上行接收能力，但它们的总spectral efficiency（SE）受到各个横向交叉干扰的限制。我们首先提出了一种新的频道分配方案，以最小化UE被至少一个共享AP的 Pilot 污染。然后，我们 derive了总SE的closed form，考虑了零强制合并和预编码，以及在中央处理单元中的信号噪听比优化。我们还提出了一种可证确定性的算法，用于CF系统中的接入点的共同下行-上行功率分配和下行/上行模式调度，以最大化总SE。我们的数值结果表明，提议的算法在多个参考模型之上具有superiority，并且表明DTDD和FD CF系统之间的差异可以通过使用HD AP来实现，而不需要内部AP干扰消除。因此，DTDD与CF结合可以作为一个有 promise的FD替代方案，以实现相同的性能，使用HD AP，而不需要FD CF系统中的相同antenna density。
A Unified Framework for Guiding Generative AI with Wireless Perception in Resource Constrained Mobile Edge Networks
for: 这 paper 是为了提供一种基于无线感知的生成式人工智能 (WiPe-GAI) 技术，用于在有限的移动边缘网络中提供数字内容生成服务 (AIGC)。
methods: 这 paper 使用了一种新的序列多尺度感知 (SMSP) 算法，使用无线信号中的通道状态信息 (CSI) 预测用户的skeleton。此外，它还使用了一种基于奖励机制的价格分配策略，以确保在有限的网络资源下，提供高质量的 AIGC。
results: 实验结果表明，提案的 frameworks 可以比其他现有解决方案更高效地预测用户的skeleton和生成价格策略。Abstract
With the significant advancements in artificial intelligence (AI) technologies and powerful computational capabilities, generative AI (GAI) has become a pivotal digital content generation technique for offering superior digital services. However, directing GAI towards desired outputs still suffer the inherent instability of the AI model. In this paper, we design a novel framework that utilizes wireless perception to guide GAI (WiPe-GAI) for providing digital content generation service, i.e., AI-generated content (AIGC), in resource-constrained mobile edge networks. Specifically, we first propose a new sequential multi-scale perception (SMSP) algorithm to predict user skeleton based on the channel state information (CSI) extracted from wireless signals. This prediction then guides GAI to provide users with AIGC, such as virtual character generation. To ensure the efficient operation of the proposed framework in resource constrained networks, we further design a pricing-based incentive mechanism and introduce a diffusion model based approach to generate an optimal pricing strategy for the service provisioning. The strategy maximizes the user's utility while enhancing the participation of the virtual service provider (VSP) in AIGC provision. The experimental results demonstrate the effectiveness of the designed framework in terms of skeleton prediction and optimal pricing strategy generation comparing with other existing solutions.
摘要
With the significant advancements in artificial intelligence (AI) technologies and powerful computational capabilities, generative AI (GAI) has become a pivotal digital content generation technique for offering superior digital services. However, directing GAI towards desired outputs still suffers from the inherent instability of the AI model. In this paper, we design a novel framework that utilizes wireless perception to guide GAI (WiPe-GAI) for providing digital content generation service, i.e., AI-generated content (AIGC), in resource-constrained mobile edge networks. Specifically, we first propose a new sequential multi-scale perception (SMSP) algorithm to predict user skeleton based on the channel state information (CSI) extracted from wireless signals. This prediction then guides GAI to provide users with AIGC, such as virtual character generation. To ensure the efficient operation of the proposed framework in resource-constrained networks, we further design a pricing-based incentive mechanism and introduce a diffusion model based approach to generate an optimal pricing strategy for the service provisioning. The strategy maximizes the user's utility while enhancing the participation of the virtual service provider (VSP) in AIGC provision. The experimental results demonstrate the effectiveness of the designed framework in terms of skeleton prediction and optimal pricing strategy generation comparing with other existing solutions.
Detection of Pedestrian Turning Motions to Enhance Indoor Map Matching Performance
results: 在场测试中，使用阈值基于的方法时，错过检测率为20.35%，假阳性率为7.65%；使用PELT基于的方法时，错过检测率为8.93%，假阳性率为6.97%；使用HMM基于的方法时，错过检测率为5.14%，假阳性率为2.00%。结果表明，本研究提出了一种更加准确和可靠的人行走导航系统。Abstract
A pedestrian navigation system (PNS) in indoor environments, where global navigation satellite system (GNSS) signal access is difficult, is necessary, particularly for search and rescue (SAR) operations in large buildings. This paper focuses on studying pedestrian walking behaviors to enhance the performance of indoor pedestrian dead reckoning (PDR) and map matching techniques. Specifically, our research aims to detect pedestrian turning motions using smartphone inertial measurement unit (IMU) information in a given PDR trajectory. To improve existing methods, including the threshold-based turn detection method, hidden Markov model (HMM)-based turn detection method, and pruned exact linear time (PELT) algorithm-based turn detection method, we propose enhanced algorithms that better detect pedestrian turning motions. During field tests, using the threshold-based method, we observed a missed detection rate of 20.35% and a false alarm rate of 7.65%. The PELT-based method achieved a significant improvement with a missed detection rate of 8.93% and a false alarm rate of 6.97%. However, the best results were obtained using the HMM-based method, which demonstrated a missed detection rate of 5.14% and a false alarm rate of 2.00%. In summary, our research contributes to the development of a more accurate and reliable pedestrian navigation system by leveraging smartphone IMU data and advanced algorithms for turn detection in indoor environments.
摘要
pedestrian navigation system (PNS) 在室内环境中是必需的，特别是在大型建筑物的搜索和救援 (SAR) 操作中。这篇论文关注了人行走行为，以提高室内人行走推断 (PDR) 和地图匹配技术的性能。具体来说，我们的研究旨在通过使用手机陀螺仪测量单元 (IMU) 信息探测人行走转弯动作。为了改进现有方法，包括阈值基于的转弯检测方法、隐马尔可夫模型 (HMM) 基于的转弯检测方法和剪辑精确时间 (PELT) 算法基于的转弯检测方法，我们提出了改进的算法，以更好地检测人行走转弯动作。在实验中，使用阈值基于的方法时，我们观察到了20.35%的失败检测率和7.65%的假阳性率。使用 PELT 基于的方法时，获得了显著的改进，失败检测率为8.93%，假阳性率为6.97%。然而，最佳结果是通过使用 HMM 基于的方法获得， missed detection rate 为5.14%， false alarm rate 为2.00%。总之，我们的研究为室内人行走系统的开发提供了更加准确和可靠的 pedestrian navigation system。
Unlabelled Sensing with Priors: Algorithm and Bounds
results: 经过数学实验表明，在高排序 режиmess（>30%）下，我们的方法可以与 классиical robust regression estimator相比，在减小化恢复错误度metric上提高到20%。此外，我们还应用了我们的框架在一个非rigid运动估计问题中，并证明了使用一些准确知道的对应关系可以改善运动估计。I hope this helps! Let me know if you have any further questions.Abstract
In this study, we consider a variant of unlabelled sensing where the measurements are sparsely permuted, and additionally, a few correspondences are known. We present an estimator to solve for the unknown vector. We derive a theoretical upper bound on the $\ell_2$ reconstruction error of the unknown vector. Through numerical experiments, we demonstrate that the additional known correspondences result in a significant improvement in the reconstruction error. Additionally, we compare our estimator with the classical robust regression estimator and we find that our method outperforms it on the normalized reconstruction error metric by up to $20\%$ in the high permutation regimes $(>30\%)$. Lastly, we showcase the practical utility of our framework on a non-rigid motion estimation problem. We show that using a few manually annotated points along point pairs with the key-point (SIFT-based) descriptor pairs with unknown or incorrectly known correspondences can improve motion estimation.
摘要
在这项研究中，我们考虑了一种杂乱感知变体，其中测量结果 sparse permuted。此外，我们还知道一些对应关系。我们提出了一种解决未知向量的估计器。我们 derivated一个对 $\ell_2$ 重建误差的理论上限。通过数学实验，我们发现附加知道的对应关系导致重建误差显著下降。此外，我们与经典稳定回归估计器进行比较，发现我们的方法在 норми化重建误差指标上比 classical robust regression estimator 高效，在高排序域（>30%）下出现至多20%的提高。最后，我们展示了我们的框架在点对点匹配问题中的实际应用。我们表明，使用一些手动标注的点并将 SIFT 基于描述对照点对进行匹配可以改善无拘束运动估计。
White paper on LiDAR performance against selected Automotive Paints
results: 研究发现，折衣色涂料的反射INTENSITY较低，而淡色涂料呈高INTENSITY值。Abstract
LiDAR (Light Detection and Ranging) is a useful sensing technique and an important source of data for autonomous vehicles (AVs). In this publication we present the results of a study undertaken to understand the impact of automotive paint on LiDAR performance along with a methodology used to conduct this study. Our approach consists of evaluating the average reflected intensity output by different LiDAR sensor models when tested with different types of automotive paints. The paints were chosen to represent common paints found on vehicles in Singapore. The experiments were conducted with LiDAR sensors commonly used by autonomous vehicle (AV) developers and OEMs. The paints used were also selected based on those observed in real-world conditions. This stems from a desire to model real-world performance of actual sensing systems when exposed to the physical world. The goal is then to inform regulators of AVs in Singapore of the impact of automotive paint on LiDAR performance, so that they can determine testing standards and specifications which will better reflect real-world performance and also better assess the adequacy of LiDAR systems installed for local AV operations. The tests were conducted for a combination of 13 different paint panels and 3 LiDAR sensors. In general, it was observed that darker coloured paints have lower reflection intensity whereas lighter coloured paints exhibited higher intensity values.
摘要
李达（Light Detection and Ranging）是一种有用的探测技术，也是自动驾驶车辆（AV）的重要数据来源。在这篇论文中，我们介绍了对汽车涂料对李达性能的影响，以及对这种研究的方法。我们的方法是通过不同的李达传感器模型和不同类型的汽车涂料进行评估，并测试了常用于自动驾驶车辆开发商和OEM的李达仪。这些涂料被选择，以模拟在实际情况下所见到的涂料。我们想通过模拟实际探测系统在物理世界中的表现，以便为新加坡自动驾驶车辆的 regulators 提供更加准确地表现测试标准和规范。我们对13种不同涂料板和3种李达仪进行了测试。在一般情况下，抹上颜色比较浅的涂料具有较低的反射强度，而抹上颜色比较深的涂料则具有较高的强度值。
Fault Point Detection for Recovery Planning of Resilient Grid
results: 评估结果显示，目标区域的总复原时间可以降低28%。Abstract
Large-scale meteorological disasters are increasing around the world, and power outage damage by natural disaster such as typhoons and earthquakes is increasing in Japan as well. Corresponding to the need of reduction of economic losses due to power outages, we are promoting research of resilient grids that minimizes power outage duration. In this report, we propose PACEM (Poles-Aware moving Cost Estimation Method) for determining travel costs between failure points based on the tilt angle and direction of electric poles obtained from pole-mounted sensors and road condition data. Evaluation result shows that the total recovery time can be reduced by 28% in the target area.
摘要
全球大规模气象灾害在增加，日本也有增加由自然灾害如风暴和地震等所导致的电力截断损害。为了减少经济损失，我们正在推广可靠网络的研究，以尽可能快地缩短停电时间。本报告提出了基于杆上设置的感知器和路况数据来计算停电时间的PACEM方法（杆相关运动成本估算法）。评估结果显示，目标区域的总恢复时间可以减少28%。