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arXiv 2020年

作者： Liu, Yuanwei Liu, Xiao Mu, Xidong Hou, Tianwei Xu, Jiaqi Di Renzo, Marco Al-Dhahir, Naofal The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom School of Artificial Intelligence Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications Beijing China The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China Université Paris-Saclay CNRS CentraleSupélec Laboratoire des Signaux et Systèmes 3 Rue Joliot-Curie Gif-sur-Yvette91192 France The Department of Electrical and Computer Engineering The University of Texas at Dallas RichardsonTX75080 United States

Reconfigurable intelligent surfaces (RISs), also known as intelligent reflecting surfaces (IRSs), or large intelligent surfaces (LISs)1, have received significant attention for their potential to enhance the capacity and coverage of wireless networks by smartly reconfiguring the wireless propagation environment. Therefore, RISs are considered a promising technology for the sixth-generation (6G) of communication networks. In this context, we provide a comprehensive overview of the state-of-the-art on RISs, with focus on their operating principles, performance evaluation, beamforming design and resource management, applications of machine learning to RIS-enhanced wireless networks, as well as the integration of RISs with other emerging technologies. We describe the basic principles of RISs both from physics and communications perspectives, based on which we present performance evaluation of multi-antenna assisted RIS systems. In addition, we systematically survey existing designs for RIS-enhanced wireless networks encompassing performance analysis, information theory, and performance optimization perspectives. Furthermore, we survey existing research contributions that apply machine learning for tackling challenges in dynamic scenarios, such as random fluctuations of wireless channels and user mobility in RIS-enhanced wireless networks. Last but not least, we identify major issues and research opportunities associated with the integration of RISs and other emerging technologies for applications to next-generation networks. Copyright © 2020, The Authors. All rights reserved.

关键词： Wireless networks

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112-Gb/s PAM4 with Joint Pre- and Post-Equalization for Data Center Interconnects

112-Gb/s PAM4 with Joint Pre- and Post-Equalization for Data...

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Asia communications and Photonics Conference

作者： Mengqi Guo Yaojun Qiao Xizi Tang Shuangyue Liu Zhongliang Sun Han Cui Xuekai Xu Leslie A. Rusch State Key Laboratory of Information Photonics and Optical Communications School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Computer Engineering COPL Université Laval Quebec Canada

A joint pre- and post-equalization method is proposed to compensate the bandwidth-limitation impairments in a 112-Gb/s PAM4 system. The experimental results show ～2.5-dB improvement in receiver sensitivity after appl... 详细信息

ISBN: (纸本)9781943580705

关键词： Analog to digital converters Fast Fourier transforms Signal processing Single mode fibers Variable optical attenuators Wavelength division multiplexing

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Performance Analysis of Large Intelligent Surfaces (LISs): Uplink spectral efficiency and pilot training

arXiv

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arXiv 2019年

作者： Jung, Minchae Saad, Walid Kong, Gyuyeol Advanced Communications Laboratory School of Electrical Electronic Engineering Yonsei University Seoul03722 Korea Republic of Wireless@VT Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24061 United States

Large intelligent surfaces (LISs) constitute a new and promising wireless communication paradigm that relies on the integration of a massive number of antenna elements over the entire surfaces of man-made structures. The LIS concept provides many advantages, such as the capability to provide reliable and space-intensive communications by effectively establishing line-of-sight (LOS) channels. In this paper, the system spectral efficiency (SSE) of an uplink LIS system is asymptotically analyzed under a practical LIS environment with a well-defined uplink frame structure. In order to verify the impact on the SSE of pilot contamination, the SSE of a multi-LIS system is asymptotically studied and a theoretical bound on its performance is derived. Given this performance bound, an optimal pilot training length for multi-LIS systems subjected to pilot contamination is characterized and, subsequently, the performance-maximizing number of devices that the LIS system must service is derived. Simulation results show that the derived analyses are in close agreement with the exact mutual information in presence of a large number of antennas, and the achievable SSE is limited by the effect of pilot contamination and intra/inter-LIS interference through the LOS path, even if the LIS is equipped with an infinite number of antennas. Additionally, the SSE obtained with the proposed pilot training length and number of scheduled devices is shown to reach the one obtained via a brute-force search for the optimal solution. Copyright © 2019, The Authors. All rights reserved.

关键词： Antennas

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GaNDLF: the generally nuanced deep learning framework for scalable end-to-end clinical workflows in Medical Imaging

arXiv

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arXiv 2021年

作者： Pati, Sarthak Thakur, Siddhesh P. Hamamcı, İbrahim Ethem Baid, Ujjwal Baheti, Bhakti Bhalerao, Megh Güley, Orhun Mouchtaris, Sofia Lang, David Thermos, Spyridon Gotkowski, Karol González, Camila Grenko, Caleb Getka, Alexander Edwards, Brandon Sheller, Micah Wu, Junwen Karkada, Deepthi Panchumarthy, Ravi Ahluwalia, Vinayak Zou, Chunrui Bashyam, Vishnu Li, Yuemeng Haghighi, Babak Chitalia, Rhea Abousamra, Shahira Kurc, Tahsin M. Gastounioti, Aimilia Er, Sezgin Bergman, Mark Saltz, Joel H. Fan, Yong Shah, Prashant Mukhopadhyay, Anirban Tsaftaris, Sotirios A. Menze, Bjoern Davatzikos, Christos Kontos, Despina Karargyris, Alexandros Umeton, Renato Mattson, Peter Bakas, Spyridon MLCommons Medical Working Group San FranciscoCA United States University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Informatics Technical University of Munich Bavaria Munich Germany International School of Medicine Istanbul Medipol University Marmara Istanbul Turkey Department of Bioengineering School of Engineering and Applied Science University of Pennsylvania PhiladelphiaPA United States Department of Mathematics School of Arts and Sciences University of Pennsylvania PhiladelphiaPA United States Institute for Digital Communications School of Engineering The University of Edinburgh Scotland United Kingdom Department of Computer Science Technical University of Darmstadt Hesse Darmstadt Germany Intel Corporation Santa ClaraCA United States Department of Computer Science Stony Brook University Stony Brook New YorkNY United States Department of Biomedical Informatics Stony Brook University Stony Brook New YorkNY United States Mallinckrodt Institute of Radiology Washington University School of Medicine St. LouisMO United States Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Institute of Image-Guided Surgery of Strasbourg Strasbourg France Department of Informatics & Analytics Dana-Farber Cancer Institute BostonMA United States Department of Pathology and Laboratory Medicine Weill Cornell Medicine New YorkNY United States Department of Biostatistics Harvard T.H. Chan School of Public Health BostonMA United States Department of Biological Engineering Department of Mechanical Engineering Massachusetts Institute of Technology BostonMA United States Google Menlo ParkCA United States

Deep Learning (DL) has the potential to optimize machine learning in both the scientific and clinical communities. However, greater expertise is required to develop DL algorithms, and the variability of implementations hinders their reproducibility, translation, and deployment. Here we present the community-driven Generally Nuanced Deep Learning Framework (GaNDLF), with the goal of lowering these barriers. GaNDLF makes the mechanism of DL development, training, and inference more stable, reproducible, interpretable, and scalable, without requiring an extensive technical background. GaNDLF aims to provide an end-to-end solution for all DL-related tasks in computational precision medicine. We demonstrate the ability of GaNDLF to analyze both radiology and histology images, with built-in support for k-fold cross-validation, data augmentation, multiple modalities and output classes. Our quantitative performance evaluation on numerous use cases, anatomies, and computational tasks supports GaNDLF as a robust application framework for deployment in clinical workflows. © 2021, CC BY.

关键词： Medical imaging

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Entropy minimization vs. diversity maximization for domain adaptation

arXiv

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arXiv 2020年

作者： Wu, Xiaofu Zhang, Suofei Zhou, Quan Yang, Zhen Zhao, Chunming Latecki, Longin Jan National Engineering Research Center of Communications and Networking Nanjing University of Posts and Telecommunications Nanjing210003 China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing210003 China National Mobile Commun. Research Lab. Southeast University Nanjing210096 China Department of Computer and Information Sciences Temple University PhiladelphiaPA United States

Entropy minimization has been widely used in unsupervised domain adaptation (UDA). However, existing works reveal that entropy minimization only may result into collapsed trivial solutions. In this paper, we propose to avoid trivial solutions by further introducing diversity maximization. In order to achieve the possible minimum target risk for UDA, we show that diversity maximization should be elaborately balanced with entropy minimization, the degree of which can be finely controlled with the use of deep embedded validation in an unsupervised manner. The proposed minimal-entropy diversity maximization (MEDM) can be directly implemented by stochastic gradient descent without use of adversarial learning. Empirical evidence demonstrates that MEDM outperforms the state-of-theart methods on four popular domain adaptation datasets. Copyright © 2020, The Authors. All rights reserved.

关键词： Entropy

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Dynamic Cache Placement, Node Association, and Power Allocation in Fog Aided Networks

Dynamic Cache Placement, Node Association, and Power Allocat...

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IEEE Global communications Conference

作者： Ruoguang Li Li Wang Yanmin Gong Mei Song Miao Pan Zhu Han School of Electronic Engineering Beijing University of Posts and Telecommunications Beijing China Ministry of Education Key Laboratory of the Universal Wireless Communications Beijing University of Posts and Telecommunications Beijing China School of Electrical and Computer Engineering University of Texas at San Antonio TX USA Department of Electrical and Computer Engineering University of Houston TX USA

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Proactively caching content at the edge is a promising way of alleviating the traffic load in the core networks, especially for latency sensitive video services. The content popularity herein is an effective measure for making efficient cache placement decisions. Most state-of-the-art works design the caching strategies under the assumption that video popularity is time-invariant. In practice, however, the popularity of different videos is constantly evolving over time, which will influence the quality of service and providers' operating efficiency. Therefore, in this paper, by considering a specified model of evolutionary video popularity, we investigate dynamic content placement, node association, and power allocation strategy in fog aided networks to maximize the time-average utility, meanwhile guaranteeing the queue in each edge node to remain stable. Utilizing the framework of the Lyapunov optimization, the formulated problem is transformed into an instantaneous mixed integer nonlinear programming problem at each time slot, which is then solved by our proposed iterative algorithm which jointly utilizes the greedy method and Generalized Benders decomposition. The simulation results demonstrate the effectiveness of our proposed algorithm and the tradeoff between the utility and average queue length.

关键词： Streaming media Optimization Resource management Wireless communication Dynamic scheduling Iterative methods Quality of service

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Design of Ultrasonic Wireless Power Transfer System

Design of Ultrasonic Wireless Power Transfer System

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IEEE Globecom Workshops

作者： Kensuke Nagaya Jiang Liu Shigeru Shimamoto Department of Communications and Computer Engineering Waseca University Tokyo Japan 8-01A R. J. Shipman hall 3-14-9 okubo Shinjuku Japan

ISBN: (数字)9781728109602

ISBN: (纸本)9781728109619

We designed a wireless power transmission (WPT) system using airborne ultrasonic waves and measured the received power characteristics of the system. Ultrasonic WPT is evaluated from these characteristics. We support the future development of ultrasonic WPT by presenting the details of the components (generator, amplifier, transducer, rectifier) that make up this system, with a detailed discussion. It has also been shown that when multiple transducer-rectifier circuits (passive sources) are used at the receiver, they can be connected in parallel to add all the signals and efficiently supply power to the load. Finally, we discussed the potential of near-field WPT as well as vibration energy harvesting.

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A suite of parallel algorithms for efficient band selection from hyperspectral images

A suite of parallel algorithms for efficient band selection ...

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作者： Fontanella, Alessandro Marenzi, Elisa Torti, Emanuele Danese, Giovanni Plaza, Antonio Leporati, Francesco Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy Department of Technology of Computers and Communications Escuela Politecnica de Caceres University of Extremadura Cáceres Spain

The analysis of hyperspectral images is usually very heavy from the computational point-of-view, due to their high dimensionality. In order to avoid this problem, band selection (BS) has been widely used to reduce the dimensionality before the analysis. The aim is to extract a subset of the original bands of the hyperspectral image, preserving most of the information contained in the original data. The BS technique can be performed by prioritizing the bands on the basis of a score, assigned by specific criteria;in this case, BS turns out in the so-called band prioritization (BP). This paper focuses on BP algorithms based on the following parameters: signal-to-noise ratio, kurtosis, entropy, information divergence, variance and linearly constrained minimum variance. In particular, an optimized C serial version has been developed for each algorithm from which two parallel versions have been derived using OpenMP and NVIDIA’s compute unified device architecture. The former is designed for a multi-core CPU, while the latter is designed for a many-core graphics processing unit. For each version of these algorithms, several tests have been performed on a large database containing both synthetic and real hyperspectral images. In this way, scientists can integrate the proposed suite of efficient BP algorithms into existing frameworks, choosing the most suitable technique for their specific applications. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Graphics processing unit

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Information support of daily scrum meetings 13

Information support of daily scrum meetings

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13th International Conference on Strategic Management and Its Support by Information Systems, SMSIS 2019

作者： Ministr, Jan Pitner, Tomas Danel, Roman Chaplyha, Vyacheslav VSB - Technical University of Ostrava Faculty of Economics Department of Applied Informatics 17. Listopadu 2172/15 Ostrava-Poruba70800 Czech Republic Masaryk University Faculty of Informatics Department of Computer Systems and Communications Botanická 68a Brno Czech Republic Technical and Economic University in Českś Budějovice Faculty of Technology Department of Civil Engineering Okružní 517/10 Českś Budějovice370 01 Czech Republic Lviv National Agrarian University Department Automatic Control and Computer-Integrated Technologies 1 V. Velykoho Str. Dublyany Lviv region80381 Ukraine

ISBN: (纸本)9788024843063

The vast majority of the software developers use the agile framework for project management. Agile approach provides more flexibility and adaption to the changes against classic software development approach. The key methodology of agile approach represents the scrum. The core of scrum management forms sprint, which represents a time shift activity and envelops all other events of scrum. The outcome of the sprint should be the increment in development of the project, which is possible to submit to the customers or the users. The paper maps the possibilities of visualization of the course of individual sprints at everyday meetings of the research team (stand up meetings), which have a decisive influence on the quality of communication of the research team and the overall success of the project. © 2019 VSB-Technical University of Ostrava. All rights reserved.

关键词： Project management

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Millimeter Wave Beam-Selection Using Out-of-Band Spatial Information

Millimeter Wave Beam-Selection Using Out-of-Band Spatial Inf...

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作者： Ali, Anum González-Prelcic, Nuria Heath, Robert W. Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712-1687 United States Signal Theory and Communications Department University of Vigo Vigo36310 Spain

Millimeter wave (mmWave) communication is one feasible solution for high data-rate applications like vehicular-to-everything communication and next generation cellular communication. Configuring mmWave links, which can be done through channel estimation or beam-selection, however, is a source of significant overhead. In this paper, we propose using spatial information extracted at sub-6 GHz to help establish the mmWave link. Assuming a fully digital architecture at sub-6 GHz;and an analog architecture at mmWave, we outline a strategy to extract spatial information from sub-6 GHz and its use in mmWave compressed beam-selection. Specifically, we formulate compressed beam-selection as a weighted sparse signal recovery problem, and obtain the weighting information from sub-6 GHz channels. In addition, we outline a structured precoder/combiner design to tailor the training to out-of-band information. We also extend the proposed out-of-band aided compressed beam-selection approach to leverage information from all active subcarriers at mmWave. To simulate multi-band frequency dependent channels, we review the prior work on frequency dependent channel behavior and outline a multi-frequency channel model. The simulation results for achievable rate show that out-of-band aided beam-selection can considerably reduce the training overhead of in-band only beam-selection. © 2017 IEEE.

关键词： Millimeter waves

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