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arXiv 2021年

作者： Liu, Fan Cui, Yuanhao Masouros, Christos Xu, Jie Han, Tony Xiao Eldar, Yonina C. Buzzi, Stefano Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen518055 China Department of Communication Engineering Beijing University of Posts and Telecommunications Beijing China Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom Shenzhen518172 China Shenzhen518172 China Huawei Technologies Co. Ltd Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel Department of Electrical and Information Engineering University of Cassino and Southern Lazio CassinoI-03043 Italy Consorzio Nazionale Interuniversitario per le Telecomunicazioni [CNIT ParmaI-43124 Italy GBB Wireless Research NapoliI-80143 Italy

—As the standardization of 5G is being solidified, researchers are speculating what 6G will be. Integrating sensing functionality is emerging as a key feature of the 6G Radio Access Network (RAN), allowing to exploit the dense cell infrastructure of 5G for constructing a perceptive network. In this paper, we provide a comprehensive overview on the background, range of key applications and state-of-the-art approaches of Integrated Sensing and Communications (ISAC). We commence by discussing the interplay between sensing and communications (S&C) from a historical point of view, and then consider multiple facets of ISAC and its performance gains. By introducing both ongoing and potential use cases, we shed light on industrial progress and standardization activities related to ISAC. We analyze a number of performance tradeoffs between S&C, spanning from information theoretical limits, tradeoffs in physical layer performance, to the tradeoff in cross-layer designs. Next, we discuss signal processing aspects of ISAC, namely ISAC waveform design and receive signal processing. As a step further, we provide our vision on the deeper integration between S&C within the framework of perceptive networks, where the two functionalities are expected to mutually assist each other, i.e., communication-assisted sensing and sensing-assisted communications. Finally, we summarize the paper by identifying the potential integration between ISAC and other emerging communication technologies, and their positive impact on the future of wireless networks. Copyright © 2021, The Authors. All rights reserved.

关键词： Waveform analysis

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Human-centered artificial intelligence in education: Seeing the invisible through the visible

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computers and Education: Artificial Intelligence 2021年 2卷

作者： Yang, Stephen J.H. Ogata, Hiroaki Matsui, Tatsunori Chen, Nian-Shing Department of Computer Science and Information Engineering National Central University No. 300 Zhongda Rd. Zhongli District Taoyuan City32001 Taiwan Academic Center for Computing and Media Studies Kyoto University Yoshidahonmachi Sakyo Ward Kyoto606-8501 Japan School of Human Sciences Waseda University 1-104 Totsukamachi Shinjuku-ku Tokyo169-8050 Japan Department of Applied Foreign Languages National Yunlin University of Science and Technology 123 University Road Section 3 Douliou CityYunlin64002 Taiwan

The inevitable rise and development of artificial intelligence (AI) was not a sudden occurrence. The greater the effect that AI has on humans, the more pressing the need is for us to understand it. This paper addresses research on the use of AI to evaluate new design methods and tools that can be leveraged to advance AI research, education, policy, and practice to improve the human condition. AI has the potential to educate, train, and improve the performance of humans, making them better at their tasks and activities. The use of AI can enhance human welfare in numerous respects, such as through improving the productivity of food, health, water, education, and energy services. However, the misuse of AI due to algorithm bias and a lack of governance could inhibit human rights and result in employment, gender, and racial inequality. We envision that AI can evolve into human-centered AI (HAI), which refers to approaching AI from a human perspective by considering human conditions and contexts. Most current discussions on AI technology focus on how AI can enable human performance. However, we explore AI can also inhibit the human condition and advocate for an in-depth dialog between technology- and humanity-based researchers to improve understanding of HAI from various perspectives. © 2021 The Author(s)

关键词： Artificial intelligence

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Random shifting intelligent reflecting surface for OTP encrypted data transmission

arXiv

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arXiv 2020年

作者： Ji, Zijie Yeoh, Phee Lep Chen, Gaojie Pan, Cunhua Zhang, Yan He, Zunwen Yin, Hao Li, Yonghui The School of Information and Electronics Beijing Institute of Technology Beijing100081 China The School of Electrical and Information Engineering University of Sydney SydneyNSW2006 Australia The Department of Engineering University of Leicester LeicesterLE1 7RH United Kingdom The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom Institute of China Electronic System Engineering Corporation Beijing100141 China

In this letter, we propose a novel encrypted data transmission scheme using an intelligent reflecting surface (IRS) to generate secret keys in wireless communication networks. We show that perfectly secure one-time pad (OTP) communications can be established by using a simple random phase shifting of the IRS elements. To maximize the secure transmission rate, we design an optimal time slot allocation algorithm for the IRS secret key generation and the encrypted data transmission phases. Moreover, a theoretical expression of the key generation rate is derived based on Poisson point process (PPP) for the practical scenario when eavesdroppers' channel state information (CSI) is unavailable. Simulation results show that employing our IRS-based scheme can significantly improve the encrypted data transmission performance for a wide-range of wireless channel gains and system parameters. Copyright © 2020, The Authors. All rights reserved.

关键词： Cryptography

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2-input/3-input all-optical switchable and/NOR logic gate

2-input/3-input all-optical switchable and/NOR logic gate

引用

Integrated Photonics Research, Silicon and Nanophotonics, IPRSN 2019

作者： Nabeyama, Akira Komatsu, Kosuke Hosoya, Gou Yashima, Hiroyuki Department of Management Science Faculty of Engineering Tokyo University of Science 6-3-1 Niijuku Katsushika-ku Tokyo125-8585 Japan Department of Management Science Graduate School of Engineering Graduate School of Tokyo University of Science 6-3-1 Niijuku Katsushika-ku Tokyo125-8585 Japan Department of Information and Computer Technology Faculty of Engineering Tokyo University of Science 6-3-1 Niijuku Katsushika-ku Tokyo125-8585 Japan

We propose a 2-input/3-input all-optical switchable AND/NOR logic gate. We perform a simulation to confirm that the output signal quality does not depend on the logical operators and the number of inputs. © 2019 ... 详细信息

ISBN: (纸本)9781943580644

关键词： Logic gates

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Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models

arXiv

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arXiv 2022年

作者： Aubry, Jean-Francois Bates, Oscar Boehm, Christian Pauly, Kim Butts Christensen, Douglas Cueto, Carlos Gélat, Pierre Guasch, Lluis Jaros, Jiri Jing, Yun Jones, Rebecca Li, Ningrui Marty, Patrick Montanaro, Hazael Neufeld, Esra Pichardo, Samuel Pinton, Gianmarco Pulkkinen, Aki Stanziola, Antonio Thielscher, Axel Treeby, Bradley Van't Wout, Elwin Physics for Medicine Paris INSERM U1273 ESPCI Paris PSL University CNRS UMR 8063 France Department of Bioengineering Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Institute of Geophysics ETH Zürich Sonneggstrasse 5 Zürich8092 Switzerland Department of Radiology Stanford University StanfordCA United States Department of Biomedical Engineering Department of Electrical and Computer Engineering University of Utah United States Department of Surgical Biotechnology Division of Surgery and Interventional Science University College London LondonNW3 2PF United Kingdom Earth Science and Engineering Department Imperial College London London United Kingdom Centre of Excellence IT4Innovations Faculty of Information Technology Brno University of Technology Bozetechova 2 Brno612 00 Czech Republic Graduate Program in Acoustics The Pennsylvania State University University Park PA16802 United States Joint Department of Biomedical Engineering University of North Carolina at Chapel Hill North Carolina State University NC United States Department of Electrical Engineering Stanford University StanfordCA United States Zurich Switzerland Laboratory for Acoustics / Noise control Empa Swiss Federal Laboratories for Materials Science and Technology Dubendorf Switzerland Zurich Switzerland Radiology and Clinical Neurosciences Departments Cumming School of Medicine University of Calgary Canada Department of Applied Physics University of Eastern Finland Kuopio70211 Finland Department of Medical Physics and Biomedical Engineering University College London Gower Street LondonWC1E 6BT United Kingdom Technical University of Denmark Denmark Danish Research Center for Magnetic Resonance Copenhagen University Hospital Hvidovre Denmark Institute for Mathematical and Computational Engineering School of Engineering and Faculty of Mathematics Pontificia Universidad Catolica de Chile Santiago Chile

Computational models of acoustic wave propagation are frequently used in transcranial ultrasound therapy, for example, to calculate the intracranial pressure field or to calculate phase delays to correct for skull distortions. To allow intercomparison between the different modeling tools and techniques used by the community, an international working group was convened to formulate a set of numerical benchmarks. Here, these benchmarks are presented, along with intercomparison results. Nine different benchmarks of increasing geometric complexity are defined. These include a single-layer planar bone immersed in water, a multi-layer bone, and a whole skull. Two transducer configurations are considered (a focused bowl and a plane piston), giving a total of 18 permutations of the benchmarks. Eleven different modeling tools are used to compute the benchmark results. The models span a wide range of numerical techniques, including the finite-difference time-domain method, angular-spectrum method, pseudospectral method, boundary-element method, and spectral-element method. Good agreement is found between the models, particularly for the position, size, and magnitude of the acoustic focus within the skull. When comparing results for each model with every other model in a cross comparison, the median values for each benchmark for the difference in focal pressure and position are less than 10% and 1 mm, respectively. The benchmark definitions, model results, and intercomparison codes are freely available to facilitate further comparisons. Copyright © 2022, The Authors. All rights reserved.

关键词： Bone

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Joint Task Assignment and Resource Allocation for D2D-Enabled Mobile-Edge Computing

Joint Task Assignment and Resource Allocation for D2D-Enable...

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作者： Xing, Hong Liu, Liang Xu, Jie Nallanathan, Arumugam College of Information Engineering Shenzhen University Shenzhen518060 China Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong Hong Kong School of Information Engineering Guangdong University of Technology Guangzhou510006 China School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom National Mobile Communications Research Laboratory Southeast University Nanjing211189 China

With the proliferation of computation-extensive and latency-critical applications in the 5G and beyond networks, mobile-edge computing (MEC) or fog computing, which provides cloud-like computation and/or storage capabilities at the network edge, is envisioned to reduce computation latency as well as to conserve energy for wireless devices (WDs). This paper studies a novel device-to-device (D2D)-enabled multi-helper MEC system, in which a local user solicits its nearby WDs serving as helpers for cooperative computation. We assume a time division multiple access (TDMA) transmission protocol, under which the local user offloads the tasks to multiple helpers and downloads the results from them over orthogonal pre-scheduled time slots. Under this setup, we minimize the computation latency by optimizing the local user's task assignment jointly with the time and rate for task offloading and results downloading, as well as the computation frequency for task execution, subject to individual energy and computation capacity constraints at the local user and the helpers. However, the formulated problem is a mixed-integer non-linear program (MINLP) that is difficult to solve. To tackle this challenge, we propose an efficient algorithm by first relaxing the original problem into a convex one, and then constructing a suboptimal task assignment solution based on the obtained optimal one. Furthermore, we consider a benchmark scheme that endows the WDs with their maximum computation capacities. To further reduce the implementation complexity, we also develop a heuristic scheme based on the greedy task assignment. Finally, the numerical results validate the effectiveness of our proposed algorithm, as compared against the heuristic scheme and other benchmark ones without either joint optimization of radio and computation resources or task assignment design. © 1972-2012 IEEE.

关键词： Resource allocation

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A Deep learning based wearable healthcare iot device for ai-enabled hearing assistance automation

arXiv

引用

arXiv 2020年

作者： Young, Fraser Zhang, Li Jiang, Richard Liu, Han Wall, Conor Department of Computer and Information Sciences Faculty of Engineering and Environment Northumbria University NewcastleNE1 8ST United Kingdom School of Computing and Communications Faculty of Science and Technology Lancaster University Lancaster United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom

With the recent booming of artificial intelligence (AI), particularly deep learning techniques, digital healthcare is one of the prevalent areas that could gain benefits from AI-enabled functionality. This research presents a novel AI-enabled Internet of Things (IoT) device operating from the ESP-8266 platform capable of assisting those who suffer from impairment of hearing or deafness to communicate with others in conversations. In the proposed solution, a server application is created that leverages Googles online speech recognition service to convert the received conversations into texts, then deployed to a micro-display attached to the glasses to display the conversation contents to deaf people, to enable and assist conversation as normal with the general population. Furthermore, in order to raise alert of traffic or dangerous scenarios, an urban-emergency classifier is developed using a deep learning model, Inception-v4, with transfer learning to detect/recognize alerting/alarming sounds, such as a horn sound or a fire alarm, with texts generated to alert the prospective user. The training of Inception-v4 was carried out on a consumer desktop PC and then implemented into the AI-based IoT application. The empirical results indicate that the developed prototype system achieves an accuracy rate of 92% for sound recognition and classification with real-Time performance. Copyright © 2020, The Authors. All rights reserved.

关键词： Internet of things

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Implementation of the algorithm for constructing homogeneous approximations of nonlinear control systems

arXiv

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arXiv 2021年

作者： Sklyar, Grigory Barkhayev, Pavel Ignatovich, Svetlana Rusakov, Viktor Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin Zolnierska 49 Szczecin71-210 Poland Institute of Mathematics University of Szczecin Wielkopolska 15 Szczecin70-451 Poland Department of Mathematical Sciences Norwegian University of Science and Technology Høgskoleringen 1 Trondheim7491 Norway B.Verkin Institute for Low Temperature Physics and Engineering Academy of Sciences of Ukraine Nauki Ave. 47 Kharkiv61103 Ukraine Department of Applied Mathematics V. N. Karazin Kharkiv National University Svobody Sq. 4 Kharkiv61022 Ukraine

We present a "calculator" for constructing a homogeneous approximation of nonlinear control systems, which is based on the algebraic approach developed by the authors in their previous papers. This approach mainly uses linear algebraic and combinatorial tools, so, it is perfectly adapted to computer realization. We describe the algorithm and discuss its capabilities and limitations. We present its implementation as a web application and show by example how this app works. © 2021, CC BY.

关键词： Algebra

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Cross-training scheme for an active learning program on space trials in the space education program of the Tokyo University of Science 70

Cross-training scheme for an active learning program on spac...

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70th International Astronautical Congress, IAC 2019

作者： Kimura, Shinichi Ueno, Ichiro Suzuki, Hideyuki Tatsukawa, Tomoaki Fujii, Kozo Yamamoto, Makoto Mukai, Chiaki Department of Electrical Engineering Tokyo University of Science 2641 Yamasaki Noda Chiba278-8510 Japan Department of Mechanical Engineering Tokyo University of Science 2641 Yamasaki Noda Chiba278-8510 Japan Department of Physics Tokyo University of Science 2641 Yamasaki Noda Chiba278-8510 Japan Department of Information and Computer Technology Tokyo University of Science 6-3-1 Niijuku Katsushika-kuTokyo125-8585 Japan Department of Information and Computer Technology Tokyo University of Science 6-3-1 Niijuku Katsushika-ku Tokyo125-8585 Japan Department of Mechanical Engineering Tokyo University of Science 6-3-1 Niijuku Katsushika-ku Tokyo125-8585 Japan Tokyo University of Science 1-3 Kagurazaka Shinjyuku Tokyo162-8601 Japan

Embodied learning is particularly important in science, technology, engineering, and mathematics (STEM) education. Space science and technology can strongly motivate students to proactively learn science. Giving students the possibility of conducting their own mission offers them a great opportunity to become strongly motivated to proactively learn and consider relating to science and technologies. Meanwhile, the process includes various aspects from which the students can benefit, such as system design and project management, as well as obtaining basic skills and knowledge in relating science and technologies. The Tokyo University of Science (TUS) has set up the TUS Space Education Program (T-SEP), funded by the Aerospace Science and technology Promotion Program of the Ministry of Education, Culture, Sports, Science, and technology (MEXT). In this paper, the outline of the T-SEP and its achievements are briefly presented. Copyright © 2019 by the International Astronautical Federation (IAF). All rights reserved.

关键词： Students

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Cost-effective search for lower-error region in material parameter space using multifidelity Gaussian process modeling

arXiv

引用

arXiv 2020年

作者： Takeno, Shion Tsukada, Yuhki Fukuoka, Hitoshi Koyama, Toshiyuki Shiga, Motoki Karasuyama, Masayuki Department of Computer Science Graduate School of Engineering Nagoya Institute of Technology Gokiso-cho Showa-ku Nagoya466-8555 Japan Department of Materials Design Innovation Engineering Graduate School of Engineering Nagoya University Furocho Chikusa-ku Nagoya464-8603 Japan JST PRESTO 4-1-8 Honcho Kawaguchi Saitama332-0012 Japan Department of Electrical Electronic and Computer Engineering Faculty of Engineering Gifu University 1-1 Yanagido Gifu501-1193 Japan Center for Advanced Intelligence Project RIKEN 1-4-1 Nihonbashi Chuo-ku Tokyo103-0027 Japan Center for Materials Research by Information Integration National Institute for Materials Science 1-2-1 Sengen TsukubaIbaraki305-0047 Japan

information regarding precipitate shapes is critical for estimating material parameters. Hence, we considered estimating a region of material parameter space in which a computational model produces precipitates having shapes similar to those observed in the experimental images. This region, called the lower-error region (LER), reflects intrinsic information of the material contained in the precipitate shapes. However, the computational cost of LER estimation can be high because the accurate computation of the model is required many times to better explore parameters. To overcome this difficulty, we used a Gaussian-process-based multifidelity modeling, in which training data can be sampled from multiple computations with different accuracy levels (fidelity). Lower-fidelity samples may have lower accuracy, but the computational cost is lower than that for higher-fidelity samples. Our proposed sampling procedure iteratively determines the most cost-effective pair of a point and a fidelity level for enhancing the accuracy of LER estimation. We demonstrated the efficiency of our method through estimation of the interface energy and lattice mismatch between MgZn2 and α-Mg phases in an Mg-based alloy. The results showed that the sampling cost required to obtain accurate LER estimation could be drastically reduced. Copyright © 2020, The Authors. All rights reserved.

关键词： Cost effectiveness

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