2022 IEEE International Symposium on Measurements & Networking (M&N)最新文献_第5页

Measurement of VHF Satellite Antennas using the Synthetic Probe Array Technique 利用合成探针阵列技术测量甚高频卫星天线

2022 IEEE International Symposium on Measurements & Networking (M&N) Pub Date : 2022-07-18 DOI: 10.1109/MN55117.2022.9887752

F. Saccardi, R. Tena-Sanchez, E. Tartaglino, A. Giacomini, L. Foged, P. Moseley, L. Rolo

引用次数: 3

Networks of EMF Area Monitor for Distributed Human Exposure Monitoring: Assessment of Performances in Simulated Realistic Scenarios 用于分布式人体暴露监测的电磁场区域监测网:模拟现实情景下的性能评估

2022 IEEE International Symposium on Measurements & Networking (M&N) Pub Date : 2022-07-18 DOI: 10.1109/MN55117.2022.9887704

R. Azaro, Roberto Franchelli, Alessandro Gandolfo

{"title":"Networks of EMF Area Monitor for Distributed Human Exposure Monitoring: Assessment of Performances in Simulated Realistic Scenarios","authors":"R. Azaro, Roberto Franchelli, Alessandro Gandolfo","doi":"10.1109/MN55117.2022.9887704","DOIUrl":"https://doi.org/10.1109/MN55117.2022.9887704","url":null,"abstract":"Multi-Band Area Monitors are currently employed by national authorities and agencies to implement monitoring networks able to evaluate the exposure generated by RF-EMF sources in a given geographical area. In most of the cases the focus is the evaluation of the exposure generated by sources operating in High Frequency Bands (f > 30 MHz), but in some particular case the sources operate in Low Frequency Bands (10 kHz–30 MHz), e.g. high power transmitters for long distance communications. Depending from the different applicative scenarios present in the different nodes of the network, an Area Monitor can be equipped or not with a cabling for the connection to an external power source. Since it is well known that low frequency electric fields are very sensitive to environmental boundary conditions, represented e.g. by interconnecting conductive cablings, some experimental activities have been performed to evaluate this kind of adverse phenomena and the effectiveness of possible countermeasures. The results of this experimental activity are described in the paper.","PeriodicalId":148281,"journal":{"name":"2022 IEEE International Symposium on Measurements & Networking (M&N)","volume":"45 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121002781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Some Notes on the Impact of the use of Dynamic Spectrum Sharing (DSS) on Maximum-Power Extrapolation techniques for Human Exposure Assessment to Electromagnetic Fields 关于使用动态频谱共享(DSS)对人体电磁场暴露评估的最大功率外推技术的影响的一些说明

2022 IEEE International Symposium on Measurements & Networking (M&N) Pub Date : 2022-07-18 DOI: 10.1109/MN55117.2022.9887686

S. Adda, T. Aureli, Tiziana Cassano, D. Franci, M. Migliore, N. Pasquino, S. Pavoncello, F. Schettino, Maddalena Schirone

引用次数: 1

Acoustic Monitoring of Environmental Noise Based on Sampling Approach 基于采样法的环境噪声声学监测

2022 IEEE International Symposium on Measurements & Networking (M&N) Pub Date : 2022-07-18 DOI: 10.1109/MN55117.2022.9887784

C. Liguori, V. Paciello, A. Ruggiero, D. Russo, P. Sommella, G. D. Leo

引用次数: 0

Reinforcement Learning applied to Network Synchronization Systems 强化学习在网络同步系统中的应用

2022 IEEE International Symposium on Measurements & Networking (M&N) Pub Date : 2022-07-18 DOI: 10.1109/MN55117.2022.9887533

Alessandro Destro, G. Giorgi

引用次数: 0

Development of a Cooperative Localization System using a UWB Network and BLE Technology 基于UWB网络和BLE技术的协同定位系统的开发

2022 IEEE International Symposium on Measurements & Networking (M&N) Pub Date : 2022-07-18 DOI: 10.1109/MN55117.2022.9887703

Valerio Brunacci, A. D. Angelis, G. Costante

引用次数: 2

RF Measurements for Future Communication Applications: an Overview 未来通信应用的射频测量:概述

2022 IEEE International Symposium on Measurements & Networking (M&N) Pub Date : 2022-07-18 DOI: 10.1109/MN55117.2022.9887740

D. Allal, R. Bannister, K. Buisman, D. Capriglione, G. D. Capua, Martín García-Patrón, Thomas Gatzweiler, Frauke K. H. Gellersen, T. Harzheim, H. Heuermann, J. Hoffmann, A. Izbrodin, K. Kuhlmann, K. Lahbacha, A. Maffucci, G. Miele, F. Mubarak, M. Salter, T. D. Pham, A. Sayegh, D. Singh, Friederike Stein, M. Zeier

引用次数: 2

An Efficient Bi-Polar Near-Field Far-Field Transformation for Flat AUTs 平面aut的有效双极近场远场变换

2022 IEEE International Symposium on Measurements & Networking (M&N) Pub Date : 2022-07-18 DOI: 10.1109/MN55117.2022.9887637

F. D’Agostino, F. Ferrara, C. Gennarelli, R. Guerriero, M. Migliozzi

{"title":"An Efficient Bi-Polar Near-Field Far-Field Transformation for Flat AUTs","authors":"F. D’Agostino, F. Ferrara, C. Gennarelli, R. Guerriero, M. Migliozzi","doi":"10.1109/MN55117.2022.9887637","DOIUrl":"https://doi.org/10.1109/MN55117.2022.9887637","url":null,"abstract":"This conference paper is devoted to an experimental assessment of a bi-polar near-field far-field (NFFF) transformation with probe compensation, which is particularly convenient from the data reduction standpoint when characterising a flat antenna under test (AUT). The proposed technique utilizes the non-redundant sampling representations of the electromagnetic fields for developing an efficient probe voltage sampling representation on the scan plane, which requires the knowledge of the NF bi-polar samples at a reduced number of sampling points. Then, these samples are suitably interpolated by a two-dimensional optimal sampling interpolation expansion to accurately reconstruct the plane-rectangular NF data needed by the standard Leach&Paris's NFFF transformation. To properly take into account the AUT geometry, a disc having diameter equal to the AUT largest dimension is adopted as modeling surface. Such a surface allows one a more effective AUT modeling from the NF data reduction stand-point than the other proposed modeling surfaces for quasi-planar AUTs (the oblate spheroid or the two-bowls), because it has the capability to reduce very significantly the related volumetric redundance, fitting very well the AUT geometry. Experimental results are shown to assess the efficacy of this NFFF transformation.","PeriodicalId":148281,"journal":{"name":"2022 IEEE International Symposium on Measurements & Networking (M&N)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130259242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hand-Arm Vibration Monitoring via Embedded Machine Learning on Low Power Wearable Devices 基于低功耗可穿戴设备的嵌入式机器学习手臂振动监测

2022 IEEE International Symposium on Measurements & Networking (M&N) Pub Date : 2022-07-18 DOI: 10.1109/MN55117.2022.9887747

A. Fort, Elia Landi, Riccardo Moretti, Lorenzo Parri, G. Peruzzi, A. Pozzebon

{"title":"Hand-Arm Vibration Monitoring via Embedded Machine Learning on Low Power Wearable Devices","authors":"A. Fort, Elia Landi, Riccardo Moretti, Lorenzo Parri, G. Peruzzi, A. Pozzebon","doi":"10.1109/MN55117.2022.9887747","DOIUrl":"https://doi.org/10.1109/MN55117.2022.9887747","url":null,"abstract":"This paper presents a new approach for the measurement of the Hand-Arm Vibration (HAV) exposure caused by the use of vibrating tools. In so doing, a wearable system can be designed in order to be embedded on personal protection equipment of workmen, so to preserve their health and to avoid injuries. In particular, a Machine Learning (ML) model is introduced, whose aim is to distinguish between the absence and the presence of harmful vibrations. In this way, vibration dose assessment systems can operate discarding acceleration signals related to body movements shocks or any other non-vibrational signal. The classifier is trained on a dataset composed of accelerometer data acquired in a real world scenario thus ensuring the classifier performances reliability. Moreover, the classifier is designed for its deployment on a microcontroller. The data processing technique presented in this work can be implemented in portable low cost and low power devices for the measurement of the vibration transmitted to the hand of an operator due to the use of drills, jackhammers, or other vibrating tools. Indeed, Internet of Things (IoT) sensor nodes powered with Artificial Intelligence (AI) capability can be designed by following this approach. Therefore, the brand new concept of the Artificial Intelligence of Things (AIoT) is met.","PeriodicalId":148281,"journal":{"name":"2022 IEEE International Symposium on Measurements & Networking (M&N)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115598378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Stateless ARE: Action Recommendation Engine without Network State Measurement 无状态ARE:没有网络状态度量的动作推荐引擎

2022 IEEE International Symposium on Measurements & Networking (M&N) Pub Date : 2022-07-18 DOI: 10.1109/MN55117.2022.9887710

Ayşe Rumeysa Mohammed, S. Mohammed, David Côté, S. Shirmohammadi

{"title":"Stateless ARE: Action Recommendation Engine without Network State Measurement","authors":"Ayşe Rumeysa Mohammed, S. Mohammed, David Côté, S. Shirmohammadi","doi":"10.1109/MN55117.2022.9887710","DOIUrl":"https://doi.org/10.1109/MN55117.2022.9887710","url":null,"abstract":"Network Operation Centers (NOC) are responsible for a communication network's efficient operation, traffic engineering, failure management, and network assurance. Due to the size and complexity of today's networks, the traditionally manual operations in an NOC are becoming more difficult to perform optimally. In response to that, in our previous work we showed that Artificial Intelligence (AI) can be utilized for autonomous action recommendation in an NOC. While in that work the network's state was measured, in this work we study if actions can be recommended without measuring the network's state, saving both time and processing power, reducing complexity, and avoiding mistakes in measuring network state. To that end, we design an AI-based action recommender that recommends actions for an NOC without first measuring the network state. Results show that although such a stateless action recommender does not initially outperform its stateful equivalent, it does significantly outperform a static network, leading to the conclusion that with more optimization and/or by choosing better AI methods, a stateless action recommender could potentially reach the same performance of a stateful action recommender.","PeriodicalId":148281,"journal":{"name":"2022 IEEE International Symposium on Measurements & Networking (M&N)","volume":"361 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115027178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0