2017 40th International Conference on Telecommunications and Signal Processing (TSP)最新文献_第2页

A high speed middle accuracy 9-bit SAR-ADC in 0.35-μm CMOS for sensor application in automotive industry 一种高速中等精度的9位SAR-ADC，采用0.35 μm CMOS，用于汽车传感器

2017 40th International Conference on Telecommunications and Signal Processing (TSP) Pub Date : 2017-07-05 DOI: 10.1109/TSP.2017.8075997

Zuzana Polesakova, J. Jerabek

引用次数: 2

Hardware and software implementation of an embedded metering webserver 嵌入式计量网络服务器的硬件和软件实现

2017 40th International Conference on Telecommunications and Signal Processing (TSP) Pub Date : 2017-07-05 DOI: 10.1109/TSP.2017.8075933

Sebastian Avram, Andreea-Mirela Safta, C. Căleanu, R. Vasiu

引用次数: 1

High impedance monopole antenna for indoor terahertz wireless communication systems 用于室内太赫兹无线通信系统的高阻抗单极天线

2017 40th International Conference on Telecommunications and Signal Processing (TSP) Pub Date : 2017-07-05 DOI: 10.1109/TSP.2017.8076103

A. Yazgan, J. Romeu, L. Jofre

引用次数: 2

Efficient and secure access control system based on programmable smart cards 基于可编程智能卡的高效安全门禁系统

2017 40th International Conference on Telecommunications and Signal Processing (TSP) Pub Date : 2017-07-05 DOI: 10.1109/TSP.2017.8075931

L. Malina, V. Benes, J. Hajny, Petr Dzurenda

引用次数: 2

TCP connection management through combined use of terrestrial and satellite IP-Based links 通过结合使用地面和卫星基于ip的链路来管理TCP连接

2017 40th International Conference on Telecommunications and Signal Processing (TSP) Pub Date : 2017-07-05 DOI: 10.1109/TSP.2017.8075932

A. Salam, M. Luglio, C. Roseti, F. Zampognaro

引用次数: 14

Resistorless electronically tunable grounded inductance simulator design 无电阻电子可调谐接地电感模拟器设计

2017 40th International Conference on Telecommunications and Signal Processing (TSP) Pub Date : 2017-07-05 DOI: 10.1109/TSP.2017.8075987

N. Herencsar, A. Kartci

引用次数: 0

Towards deep learning based estimation of fracture risk in osteoporosis patients 基于深度学习的骨质疏松患者骨折风险评估

2017 40th International Conference on Telecommunications and Signal Processing (TSP) Pub Date : 2017-07-05 DOI: 10.1109/TSP.2017.8076069

C. Ciușdel, A. Vizitiu, F. Moldoveanu, C. Suciu, L. Itu

{"title":"Towards deep learning based estimation of fracture risk in osteoporosis patients","authors":"C. Ciușdel, A. Vizitiu, F. Moldoveanu, C. Suciu, L. Itu","doi":"10.1109/TSP.2017.8076069","DOIUrl":"https://doi.org/10.1109/TSP.2017.8076069","url":null,"abstract":"Osteoporosis is a skeletal disorder which leads to bone mass loss and to an increased fracture risk. Recently, physics-based models, employing finite element analysis (FEA), have shown great promise in being able to non-invasively estimate biomechanical quantities of interest in the context of osteoporosis. However, these models have high computational demand, limiting their clinical adoption. In this manuscript, we present a deep learning model based on a convolutional neural network (CNN) for predicting average strain as an alternative to physics-based approaches. The model is trained on a large database of synthetically generated cancellous bone anatomies, where the target values are computed using the physics-based FEA model. The performance of the trained model was assessed by comparing the predictions against physics-based computations on a separate test data set. Correlation between deep learning and physics-based predictions was very good (0.895, p < 0.001), and no systematic bias was found in Bland-Altman analysis. The CNN model also performed better than the previously introduced Support Vector Machine (SVM) model which relied on handcrafted features (correlation 0.847, p < 0.001). Compared to the physics based computation, average execution time was reduced by more than 1000 times, leading to real-time assessment of average strain. Average execution time went down from 32.1 ± 3.0 seconds for the FE model to around 0.03 ± 0.005 seconds for the CNN model on a workstation equipped with 3.0 GHz Intel i7 2-core processor.","PeriodicalId":256818,"journal":{"name":"2017 40th International Conference on Telecommunications and Signal Processing (TSP)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128654208","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: 6

Sub-nanosecond Synchronization over 1G ethernet data links using white rabbit technologies on the WR-ZEN board 在WR-ZEN板上使用白兔技术在1G以太网数据链路上实现亚纳秒同步

2017 40th International Conference on Telecommunications and Signal Processing (TSP) Pub Date : 2017-07-01 DOI: 10.1109/TSP.2017.8076075

Jorge Sánchez-Garrido, A. M. Lopez-Antequera, M. Jiménez-López, Javier Díaz

{"title":"Sub-nanosecond Synchronization over 1G ethernet data links using white rabbit technologies on the WR-ZEN board","authors":"Jorge Sánchez-Garrido, A. M. Lopez-Antequera, M. Jiménez-López, Javier Díaz","doi":"10.1109/TSP.2017.8076075","DOIUrl":"https://doi.org/10.1109/TSP.2017.8076075","url":null,"abstract":"The White Rabbit (WR) technology has been introduced as an enhancement and next generation of the Precision Time Protocol (PTP, IEEE 1588), providing a boost in synchronization accuracy from the usual sub-microsecond range commonly found in PTPv2-based applications, down to the much more precise sub-nanosecond range. A number of White Rabbit-capable network nodes have been developed with the goal of allowing simultaneous deterministic time transfer and regular Ethernet data traffic to coexist on the same link without significant performance degradation over fiber links spanning tens of kilometers. The first SoC-based platform amongst these nodes is the WR-ZEN board, which implements a real-time White Rabbit stack in the Programmable Logic (PL) of the Zynq-7000 SoC; and features a hardened, ARM dual-core Processing System (PS) for running an embedded Linux environment. This paper presents the work carried out to upgrade the WR-ZEN board implementation, whose peak data throughput is limited just below 70 Mbps, so that a 1 Gbps data rate can be attained without impacting the performance of the White Rabbit synchronization. This goal is fulfilled by designing additional custom logic based on the Xilinx AXI DMA core, as well as an updated Linux network driver. This enhancement allows the widespread deployment of the WR-ZEN for major scientific infrastructure projects that require high-speed data transmission and deterministic timing transfer, as is the case of telescope arrays. Lastly, experimental results are presented comparing the synchronization performance of a baseline PTP-based setup to that achieved on the enhanced WR-ZEN board in the presence of high throughput data traffic. Conclusions are drawn and potential scientific and industrial applications that tap this increased bandwidth with deterministic timing transfer are discussed.","PeriodicalId":256818,"journal":{"name":"2017 40th International Conference on Telecommunications and Signal Processing (TSP)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117160453","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: 5

The control system of the mobile robot over a rought terrain 在崎岖地形上移动机器人的控制系统

2017 40th International Conference on Telecommunications and Signal Processing (TSP) Pub Date : 2017-07-01 DOI: 10.1109/TSP.2017.8075975

M. Chashchina, M. Evstigneev, Y. Litvinov, V. Mazulina

引用次数: 0

Perceptual feedback training for improving spatial acuity and resolving front-back confusion errors in virtual auditory environments 虚拟听觉环境中提高空间敏锐度和解决前后混淆错误的知觉反馈训练

2017 40th International Conference on Telecommunications and Signal Processing (TSP) Pub Date : 2017-07-01 DOI: 10.1109/TSP.2017.8075999

O. Balan, A. Moldoveanu, F. Moldoveanu, A. Morar, Silviu Ivascu

引用次数: 1