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IEEE International Workshop on computer-Aided Modeling, Analysis, and design of Communication Links and Networks, CAMAD

作者： Apostolos P. Fournaris Christos Tselios Evangelos Haleplidis Elias Athanasopoulos Antreas Dionysiou Dimitrios Mitropoulos Panos Louridas Georgios Christou Manos Athanatos George Hatzivasilis Konstantinos Georgopoulos Costas Kalogeros Christos Kotselidis Simon Vogl Francois Hamon Sotiris Ioannidis Research Center ATHENA Industrial Systems Institute Patras Greece University of Cyprus Nicosia Cyprus Department of Management Science and Technology Athens University of Economics and Business Athens Greece Department of Business Administration University of Athens Greece School of Electrical and Computer Engineering Technical University of Crete Greece AEGIS IT RESEARCH LTD Germany Pierer Innovation Austria University of Manchester UK VoXel Interaction Design Linz Austria GreenCitizen Marseille France

Rapid open-source software and hardware prototyping fueled by the significant expansion of the development community, led to the deployment of highly sophisticated frameworks, solutions and products. However, as the provided open-source solutions are managed in all aspects by their designers/engineers, they lack professional evaluation of their security level. The absence of comprehensive security assessment as well as a consolidated and ubiquitous roadmap for vulnerability patching and security hardening, makes open-source solution a risk for widespread enterprise use. This paper introduces a security assurance approach which addresses open-source hardware and software shortcoming in an end-to-end manner, by providing a logical decomposition of any such module into four distinct component layers: device, network, application and cognitive. This allows highly focused security assessment, taking into consideration the specific characteristics of each layer. In addition, the paper provides an approach on how open-source solution security can be improved, through decomposition, layered vulnerability mitigation and specialized security hardening techniques. The proposed framework which is the main research and innovation focus of the SecOPERA Project intends to transform an open source solution to a protected one, as well as provide security guarantees of its overall security status.

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Towards an Interaction Architecture for the iCub Robot: Social Gaze Space Model Adaptation for Social Interaction 23

Towards an Interaction Architecture for the iCub Robot: Soci...

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23rd IEEE-RAS International Conference on Humanoid Robots, Humanoids 2024

作者： Shaghaghi, Sahand Aliasghari, Pourya Tripp, Bryan Anderson, Britt Dautenhahn, Kerstin Nehaniv, Chrystopher L. Social & Intelligent Robotics Research Lab University of Waterloo 200 University Ave. W. WaterlooONN2L 3G1 Canada Dept. of Systems Design Enginering University of Waterloo 200 University Ave. W. WaterlooONN2L 3G1 Canada Dept. of Electrical & Computer Engineering University of Waterloo 200 University Ave. W. WaterlooONN2L 3G1 Canada Dept. of Psychology University of Waterloo 200 University Ave. W. WaterlooONN2L 3G1 Canada Centre for Theoretical Neuroscience University of Waterloo 200 University Ave. W. WaterlooONN2L 3G1 Canada

ISBN: (纸本)9798350373578

Gaze behaviour plays a crucial role in social interactions extending to Human-Robot Interactions. Humanoid robots equipped with anthropomorphic vision systems may be expected to employ natural gaze behaviour in interactions with humans. Here, we implemented a novel first-person human gaze state detection tool on the iCub robot and assessed its gaze detection accuracy. Using this tool, we then developed two social gaze interaction architectures for the iCub robot. The Social Gaze Space theory (SGS) of Jording and colleagues was the theoretical framework for building our first architecture, SGS Base (SGS-B). Our second architecture, SGS Interaction Architecture (SGS-IA), is the extended version of SGS Base that lets the robot take on different higher-level goals in an interaction, including being attentive to the interaction partner or attempting to direct their attention to an object. These architectures support dyadic social interactions involving initiating and responding to joint attention towards objects of interest, and are expected to allow the robot to interact in a more human-like manner in social interactions. The gaze detection accuracy of the iCub robot equipped with our choice of algorithms exceeded that of previously implemented methods. System validation trials confirmed that the robot detects the social gaze states correctly in the majority of the instances, allowing for behavioural control according to the Social Gaze Space theory. Validation tests presented in this article demonstrate the functionality of the SGS Interaction Architecture and also highlight the differences in personal interaction dynamics when the humanoid robot has no particular goals as opposed to when it has interactional goals appropriate to a teaching scenario. © 2024 IEEE.

关键词： Anthropomorphic robots

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Fast and Accurate Langevin Simulations of Stochastic Hodgkin-Huxley Dynamics

arXiv

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arXiv 2020年

作者： Pu, Shusen Thomas, Peter J. Case Western Reserve University Departments Mathematics Applied Mathematics and Statistics Biology Cognitive Science Electrical Computer and Systems Engineering

Fox and Lu introduced a Langevin framework for discrete-time stochastic models of randomly gated ion channels such as the Hodgkin-Huxley (HH) system. They derived a Fokker-Planck equation with state-dependent diffusion tensor D and suggested a Langevin formulation with noise coefficient matrix S such that SS| = D. Subsequently, several authors introduced a variety of Langevin equations for the HH system. In this paper, we present a natural 14-dimensional dynamics for the HH system in which each directed edge in the ion channel state transition graph acts as an independent noise source, leading to a 14 × 28 noise coefficient matrix S. We show that (i) the corresponding 14D system of ordinary differential equations is consistent with the classical 4D representation of the HH system;(ii) the 14D representation leads to a noise coefficient matrix S that can be obtained cheaply on each timestep, without requiring a matrix decomposition;(iii) sample trajectories of the 14D representation are pathwise equivalent to trajectories of Fox and Lu’s system, as well as trajectories of several existing Langevin models;(iv) our 14D representation (and those equivalent to it) give the most accurate interspike-interval distribution, not only with respect to moments but under both the L1 and L∞ metric-space norms;and (v) the 14D representation gives an approximation to exact Markov chain simulations that are as fast and as efficient as all equivalent models. Our approach goes beyond existing models, in that it supports a stochastic shielding decomposition that dramatically simplifies S with minimal loss of accuracy under both voltage- and current-clamp *** Codes 65C30 (Primary) 92C20, 37N25, 92B25 (Secondary) Copyright © 2020, The Authors. All rights reserved.

关键词： Stochastic systems

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Improving the accuracy of circuit quantization using the electromagnetic properties of superconductors

arXiv

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arXiv 2024年

作者： Park, Seong Hyeon Choi, Gahyun Kim, Eunjong Park, Gwanyeol Choi, Jisoo Choi, Jiman Chong, Yonuk Lee, Yong-Ho Hahn, Seungyong Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Center for Superconducting Quantum Computing Systems Korea Research Institute of Standards and Science Daejeon34113 Korea Republic of Department of Physics & Astronomy Institute of Applied Physics Seoul National University Seoul08826 Korea Republic of Quantum Devices Labs Korea Advanced Nano Fab Center Suwon16229 Korea Republic of Quantum Design Korea Seoul06272 Korea Republic of SKKU Adavanced Institute of Nanotechnology Sungkyunkwan University Suwon16419 Korea Republic of

Recent advances in quantum information processing with superconducting qubits have fueled a growing demand for scaling and miniaturizing circuit layouts. Despite significant progress, predicting the Hamiltonian of complex circuits remains a challenging task. Here, we propose an improved method for quantizing superconducting circuits that incorporates material- and geometry-dependent kinetic inductance. Our approach models superconducting films as reactive boundary elements, seamlessly integrating into the conventional circuit quantization framework without adding computational complexity. We experimentally validate our method using superconducting devices fabricated with 35 nm-thick disordered niobium films, demonstrating significantly improved accuracy in predicting the Hamiltonian based solely on the device layout and material properties of superconducting films and Josephson junctions. Specifically, conventional methods exhibit an average error of 5.4% in mode frequencies, while our method reduces it to 1.1%. Our method enables systematic studies of superconducting devices with disordered films or compact elements, facilitating precise engineering of superconducting circuits at scale. © 2024, CC BY-NC-ND.

关键词： Superconducting films

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Valley-polarized Exitonic Mott Insulator in WS2/WSe2 Moiré Superlattice

arXiv

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arXiv 2023年

作者： Lian, Zhen Meng, Yuze Ma, Lei Maity, Indrajit Yan, Li Wu, Qiran Huang, Xiong Chen, Dongxue Chen, Xiaotong Chen, Xinyue Blei, Mark Taniguchi, Takashi Watanabe, Kenji Tongay, Sefaattin Lischner, Johannes Cui, Yong-Tao Shi, Su-Fei Department of Chemical and Biological Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Departments of Materials The Thomas Young Centre for Theory and Simulation of Materials Imperial College London United Kingdom Department of Physics and Astronomy University of California RiversideCA92521 United States Department of Materials Science and Engineering University of California RiversideCA92521 United States Materials Science and Engineering Program School for Engineering of Matter Transport and Energy Arizona State University TempeAZ85287 United States International Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Research Center for Functional Materials National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Department of Electrical Computer & Systems Engineering Rensselaer Polytechnic Institute TroyNY12180 United States

Strongly enhanced electron-electron interaction in semiconducting moiré superlattices formed by transition metal dichalcogenides (TMDCs) heterobilayers has led to a plethora of intriguing fermionic correlated states1–7. Meanwhile, interlayer excitons in a type-II aligned TMDC heterobilayer moiré superlattice, with electrons and holes separated in different layers8,9, inherit this enhanced interaction and strongly interact with each other, promising for realizing tunable correlated bosonic quasiparticles10,11 with valley degree of freedom. We employ photoluminescence spectroscopy to investigate the strong repulsion between interlayer excitons and correlated electrons in a WS2/WSe2 moiré superlattice and combine with theoretical calculations to reveal the spatial extent of interlayer excitons and the band hierarchy of correlated states. We further find that an excitonic Mott insulator state emerges when one interlayer exciton occupies one moiré cell, evidenced by emerging photoluminescence peaks under increased optical excitation power. Double occupancy of excitons in one unit cell requires overcoming the energy cost of exciton-exciton repulsion of about 30-40 meV, depending on the stacking configuration of the WS2/WSe2 heterobilayer. Further, the valley polarization of the excitonic Mott insulator state is enhanced by nearly one order of magnitude. Our study demonstrates the WS2/WSe2 moiré superlattice as a promising platform for engineering and exploring new correlated states of fermion, bosons, and a mixture of both12 © 2023, CC BY.

关键词： Excitons

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Synergy of edge intelligence and blockchain: a comprehensive survey

TechRxiv

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TechRxiv 2021年

作者： Wang, Xiaofei Ren, Xiaoxu Qiu, Chao Xiong, Zehui Yao, Haipeng Leung, Victor C.M. College of Intelligence and Computing Tianjin University Tianjin300350 China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore487372 Singapore Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100088 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518061 China Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada

Edge intelligence (EI), as an emerging technology, has been attracting significant attention. It pushes the frontier of artificial intelligence (AI) from the cloud to the network edge, aiming to embrace and support the next-generation communications while unleashing AI services. However, it faces challenges in its decentralized management and security, which limit its capabilities to support services with numerous requirements. On the other side, blockchain (BC), as a promising decentralized technology, is beneficial to tackle the above issues. However, there exist some technical challenges for BC, such as transaction capacity, scalability, and fault tolerance. Motivated by significant current interest around EI and BC, this survey examines whether the synergy of EI and BC can make a powerful network with combined functionalities of both cutting-edge technologies. Accordingly, we develop EI-chain and Chain-intelligence to realize reliable computing-power management, data administration, and model optimization at the edges, while improving the functions of BC by leveraging complementary characteristics of EI and BC, further making up for their own limitations. In this survey, a wide spectrum of literature is carefully reviewed to enable the EI-chain and Chain-intelligence. Moreover, we cover the technological aspects of EI-chain and Chain-intelligence: overview, motivations, and frameworks. Finally, some challenges and future directions are explored. We believe this survey will provide developers and researchers a comprehensive view on the synergy of EI and BC, while accelerating the design of a powerful integrated network. © 2021, CC BY-NC-SA.

关键词： Blockchain

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A game-theoretic approach towards collaborative coded computation offloading

arXiv

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arXiv 2021年

作者： Ng, Jer Shyuan Lim, Wei Yang Bryan Xiong, Zehui Niyato, Dusit Leung, Cyril Kim, Dong In Zhang, Junshan Yang, Qiang Alibaba Group and Alibaba-NTU Joint Research Institute Nanyang Technological University Singapore Pillar of Information Systems Technology and Design Singapore University of Technology Design Singapore School of Computer Science and Engineering Nanyang Technological University Singapore Canada Sungkyunkwan University Korea Republic of School of Electrical Computer and Energy Engineering Arizona State University United States Hong Kong University of Science and Technology Hong Kong

Coded distributed computing (CDC) has emerged as a promising approach because it enables computation tasks to be carried out in a distributed manner while mitigating straggler effects, which often account for the long overall completion times. Specifically, by using polynomial codes, computed results from only a subset of edge servers can be used to reconstruct the final result. However, incentive issues have not been studied systematically for the edge servers to complete the CDC tasks. In this paper, we propose a tractable two-level game-theoretic approach to incentivize the edge servers to complete the CDC tasks. Specifically, in the lower level, a hedonic coalition formation game is formulated where the edge servers share their resources within their coalitions. By forming coalitions, the edge servers have more Central Processing Unit (CPU) power to complete the computation tasks. In the upper level, given the CPU power of the coalitions of edge servers, an all-pay auction is designed to incentivize the edge servers to participate in the CDC tasks. In the all-pay auction, the bids of the edge servers are represented by the allocation of their CPU power to the CDC tasks. The all-pay auction is designed to maximize the utility of the cloud server by determining the allocation of rewards to the winners. Simulation results show that the edge servers are incentivized to allocate more CPU power when multiple rewards are offered, i.e., there are multiple winners, instead of rewarding only the edge server with the largest CPU power allocation. Besides, the utility of the cloud server is maximized when it offers multiple homogeneous rewards, instead of heterogeneous rewards. © 2021, CC0.

关键词： Game theory

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MRI images, brain lesions and deep learning

arXiv

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arXiv 2021年

作者： Castillo, Darwin Lakshminarayanan, Vasudevan Rodríguez-Álvarez, Maria J. Departamento de Química y Ciencias Exactas Sección Fisicoquímica y Matemáticas Universidad Técnica Particular de Loja Loja11-01-608 Ecuador Theoretical and Experimental Epistemology Lab School of Optometry and Vision Science University of Waterloo Ontario Canada Departments of Physics Electrical and Computer Engineering and Systems Design Engineering University of Waterloo Ontario Canada Valencia Spain

Medical brain image analysis is a necessary step in the computers Assisted /Aided Diagnosis (CAD) systems. Advancements in both hardware and software in the past few years have led to improved segmentation and classification of various diseases. In the present work, we review the published literature on systems and algorithms that allow for classification, identification, and detection of White Matter Hyperintensities (WMHs) of brain MRI images specifically in cases of ischemic stroke and demyelinating diseases. For the selection criteria, we used the bibliometric networks. Out of a total of 140 documents we selected 38 articles that deal with the main objectives of this study. Based on the analysis and discussion of the revised documents, there is constant growth in the research and proposal of new models of deep learning to achieve the highest accuracy and reliability of the segmentation of ischemic and demyelinating lesions. Models with indicators (Dice Score, DSC: 0.99) were found, however with little practical application due to the uses of small datasets and lack of reproducibility. Therefore, the main conclusion is to establish multidisciplinary research groups to overcome the gap between CAD developments and their complete utilization in the clinical environment. © 2021, CC BY.

关键词： Magnetic resonance imaging

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eFAirWrite: Bringing energy efficient text entry to next generation smart devices

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Expert systems with Applications 2025年 289卷

作者： Muhammad Mohsin Ghaffar Ahmad Abdullah Junaid Younas Vladimir Rybalkin Jonas Ney Paul Lukowicz Norbert Wehn Microelectronic Systems Design Research Group University of Kaiserslautern-Landau Kaiserslautern 67663 Germany School of Electrical Engineering & Computer Science National University of Sciences & Technology Islamabad 44000 Pakistan German Research Centre for Artificial Intelligence Kaiserslautern 67663 Germany

Text entry tasks for emerging wireless Augmented Reality (AR) and Virtual Reality (VR) devices can be realized in many ways, one of the most promising methods is based on an Inertial Measurement Unit (IMU) sensor, which resembles a human writing style and is called air-writing. An existing air-writing Deep Neural Network (DNN) based algorithm called FAirWrite achieves state-of-the-art accuracy. However, this algorithm is optimized only for accuracy without considering the implementation constraints. State-of-the-art implementation executes the algorithm in a cloud, which is associated with large communication latency; privacy issues with respect to data transfer; and a need for reliable internet connection. A solution that tackles all three challenges is executing the algorithm locally at the edge in the closest proximity to the sensor. However, inference at the edge is challenging due to limited memory and computing resources, which can impact accuracy and increase latency. Additionally, battery-powered edge devices must adhere to strict power and energy consumption limits. All these constraints collectively restrict the model size and computational complexity that can be deployed near the sensor. In this work, we explore various optimizations required to enable state-of-the-art FAirWrite algorithm for a real-world deployment scenario, i.e. executing on an edge device. We perform a multi-layer design-space exploration considering multiple levels of design hierarchy spanning from optimizations applied on algorithmic level down to hardware level, considering various deployment run-times and edge platforms including embedded micro-controller, embedded Central Processing Unit (CPU), embedded Graphics Processing Unit (GPU), Neural Processing Unit (NPU), and Field-Programmable Gate Array (FPGA). The complexity reduction optimizations result in a 37 × smaller eFAirWrite model without any accuracy degradation. We propose and implement a custom hardware architecture of the

关键词： Human computer interaction Air-writing Convolution neural network inference Edge computing Energy efficient acceleration

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Spatial Suitability Analysis for Site Selection of Healthcare Facilities Using a Multimodal Machine Learning Approach

Spatial Suitability Analysis for Site Selection of Healthcar...

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IEEE International Workshop on Imaging systems and Techniques (IST)

作者： Nicolas Douard Joan LaRovere Matthew D. Harris Chandler McCann Allen Nasseri Vandan Parmar Daniel Straulino Corey Hanson Mohammed Bataglia Evan E. Afshin Mattia Filiaci Kim Azzarelli George Giakos Ebby Elahi Actionable Data Initiative Research Group Virtue Foundation New York NY USA Department of Electrical and Computer Engineering Manhattan College New York NY USA Department of Cardiology Boston Children’s Hospital Boston MA USA Department of Pediatrics Harvard Medical School Boston MA USA DataRobot Boston MA USA Department of Regional Planning and Urban Design University of Pennsylvania Weitzman School of Design Philadelphia PA USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Departments of Ophthalmology Otolaryngology and Global Health Icahn School of Medicine at Mount Sinai New York NY USA

This study proposes a novel end-to-end, geospatial and computer vision machine learning pipeline designed to estimate the suitability of geographic areas to affect community health through newly constructed healthcare facilities. The proposed multimodal model integrates several geographic features such as population density, landcover, elevation, and road networks along with the coordinates of current healthcare facilities to identify suitable locations through multi-scalar geospatial features. The proposed approach introduces novel transformations where features are passed as configurable images tiles to overcome the limitations of traditional geospatial analysis. The study utilizes an enhanced version of the OpenStreetMap humanitarian data layer for healthcare facilities, which was filtered based on building footprint, facility name, and online presence to focus on larger facilities and manually verified against government databases to ensure comprehensive coverage. Although the multimodal approach is model-agnostic, the proposed implementation utilizes a Light Gradient Boosted Trees Classifier with Early Stopping for the learning algorithm. This architecture combines the effectiveness of gradient boosting, and features that understand spatial proximity to achieve better accuracy in the classification of multimodal data. The outcome of this study indicates that the proposed model can predict suitable areas for facility construction, thereby facilitating decision-making and future planning in the healthcare sector.

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