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6th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2024

作者： Li, Keqin Chen, Jiajing Yu, Dezhi Dajun, Tao Qiu, Xinyu Lian, Jieting Ji, Ryan Zhang, Shengyuan Wan, Zhenyu Sun, Baiwei Hong, Bo Ni, Fanghao Han, Jiaqi Ama University Department of Computer Science Quezon Philippines Courant Institute New York University 251 Mercer St New YorkNY10012 United States University of California Berkeley University Avenue and Oxford St School of Information BerkeleyCA94720 United States Carnegie Mellon University Master of Science in Mechanical Engineering School of Engineering 5000 Forbes Avenue PittsburghPA United States Northeastern University College of Engineering Seattle United States School of Professional Studies New York University Master of Science in Database Technology 50 West 4th Street New YorkNY United States Cornell University College of Engineering 616 Thurston Ave IthacaNY14853 United States Cornell University Master of Professional Science in Applied Statistics-Data Science College of Computing and Information Science 616 Thurston Ave IthacaNY United States Independent Researcher Beijing China University of California Irvine Master of Computer Science Donald Bren School of Information and Computer Sciences 510 Aldrich Hall IrvineCA United States Northern Arizona University School of Informatics Computing and Cyber Systems FlagstaffAZ United States Shanghai Institute of Technology Shanghai China

ISBN: (纸本)9798350389418

This paper proposes a deep reinforcement learning based on the warehouse environment, the mobile robot obstacle avoidance Algorithm. Firstly, the value function network is improved based on the pedestrian interaction. We can learn to obtain the relative importance of the current state and the historical trajectory state as well as the joint impact on the robot's obstacle avoidance strategy. Secondly, the reward function of reinforcement learning is designed based on the spatial behaviour of pedestrians, and the robot is punished for the state where the angle changes too much, so as to achieve the requirement of comfortable obstacle avoidance. Finally, the feasibility and effectiveness of the deep reinforcement learning-based mobile robot obstacle avoidance algorithm in the warehouse environment in the complex environment of the warehouse are verified through simulation experiments. © 2024 IEEE.

关键词： Deep reinforcement learning

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Design and Fabrication Challenges of Integrated Optical Circuits for Quantum Computing Applications

Design and Fabrication Challenges of Integrated Optical Circ...

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International Conference on Transparent Optical Networks

作者： Simeon I. Tsintzos Konstantinos Tsimvrakidis Alexandra Sinani Adonis Bogris James C. Gates Peter G.R. Smith Ali W. Elshaari Val Zwiller Christos Riziotis National Hellenic Research Foundation Theoretical & Physical Chemistry Institute Athens Greece Department of Informatics and Computer Engineering University of West Attica Egaleo Greece Optoelectronics Research Centre University of Southampton Southampton United Kingdom Department of Applied Physics Royal Institute of Technology (KTH) Stockholm Sweden Institute for Advanced Modelling and Simulation University of Nicosia Nicosia Cyprus

The paper presents current design issues, limitations, and fabrication challenges towards the development of hybrid integrated optical circuits with embedded single photon sources, which are critical components for future quantum computing, sensing, and communication systems. Optical nanowires with embedded quantum dots (NWQD) are very promising single photon sources, with several reported results of integration in high index platforms like silicon or silicon nitride. Silica on silicon is a favorable platform for optical computing, providing the high degree of customization when combined with direct laser writing techniques for definition of optical structures with refractive index modification. However, the low ~10 -3 achievable refractive index contrast imposes strict limitations on the compatibility with NWQD resulting in general in low coupling efficiency as shown in this work. Consideration of several design and fabrication issues demonstrates the potential for NQWD integration in laser written silica based optical circuits with adequate efficiency for practical applications.

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Prediction of Heat Energy Release Rate for Ammonia Combustion in a Constant Volume Combustion Chamber: A Machine Learning Approach

Prediction of Heat Energy Release Rate for Ammonia Combustio...

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International Conference on Electronics, computers and Artificial Intelligence (ECAI)

作者： Lijia Fang Hardeep Singh Mitsuhisa Ichiyanagi Takashi Suzuki Maria Simona Raboaca Constantin Filote Chaman Verma Department of Engineering and Applied Sciences Sophia University Tokyo Japan Turbulence and Energy Laboratory University of Windsor Windsor Canada ICSI Energy Department National Research and Development Institute for Cryogenics and Isotopic Technologies Ramnicu Valcea Romania Faculty of Electrical Engineering and Computer Science Stefan cel Mare University of Suceava Suceava Romania Faculty of Informatics Eötvös Loránd University Budapest Hungary

Addressing global warming requires immediate and concerted action. Transitioning to non-conventional energy sources, such as solar and Aeolian power, reducing emissions from transportation and industry, and implementing sustainable land-use practices are crucial steps. Therefore, Ammonia attracts researchers when used as a fuel, and offers several potential benefits such as higher energy density. However, due to poor combustion speed of Ammonia offers slower energy release. To enhance the average flame velocity of Ammonia, the current investigation employed the exhaust gas expelled from the secondary chamber to compress the mixture within the primary chamber and facilitate its HCCI combustion. The main goal of research is the optimization on air-fuel ER to contribute to the development of more efficient and sustainable constant volume combustion. However, the time required for constructing physical prototypes and conducting experiments can be considerable, thus, to mitigate these challenges, the authors turned to machine learning tools as an alternative approach. In the proposed research, results were evaluated through Support Vector Regression. However, due to poor prediction accuracy, authors tried KNeighborsRegressor model for predicting and validating the results. Finally, it is revealed from the KNN model that data sets are highly accurate.

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Programmable large-scale simulation of lattices with photonic synthetic frequency dimensions

Programmable large-scale simulation of lattices with photoni...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Alen Senanian Logan G. Wright Peter F. Wade Hannah K. Doyle Peter L. McMahon Department of Physics Cornell University Ithaca NY USA School of Applied and Engineering Physics Cornell University Ithaca New York USA NTT Physics and Informatics Laboratories NTT Research Inc Sunnyvale CA USA School of Electrical and Computer Engineering Cornell University Ithaca NY USA Kavli Institute at Cornell for Nanoscale Science Cornell University Ithaca New York USA

We present a programmable analog simulator with up to 10 5 lattice sites capable of simulating 2D and 3D lattices, as well as lattices with non-planar connectivity. We also demonstrate the injection of arbitrary latt... 详细信息

ISBN: (纸本)9781957171258

关键词： Gravity Modulation Modulators Multiplexing Optical measurement Ring resonators

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The Development of the Optical-Electronic Images Segmentation Method Based on the Canny Edge Detector

The Development of the Optical-Electronic Images Segmentatio...

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International computer Sciences and Information Technologies (CSIT)

作者： Hennadii Khudov Oleksandr Makoveichuk Vladyslav Khudov Irina Khizhnyak Temir Kalimulin Rostyslav Khudov Department of Radar Troops Tactic Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine Department of Computer Science and Software Engineering Academician Y. Bugay International Scientific and Technical University Kyiv Ukraine Department of Electronic Computers Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of Theoretical and Applied Informatics V.N.Karazin Kharkiv National University Kharkiv Ukraine

The article deals with the problem associated with the segmentation of color images. The main groups of color image segmentation methods operation, are considered. The main advantages and disadvantages of each group of methods are shown. The paper suggests the use of the Canny edge detector for optical-electronic images obtained from space observation systems. It is proposed to regulate the parameters of the Canny edge detector in order to improve the segmentation result. It’s determined that the value of the lower threshold should be no more than 10-20 unit, and the value of the upper threshold should be within 60-100 unit.

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Exploring the Roles of Agents and Multi-Agent in Improving Mobile Ad Hoc Networks 4

Exploring the Roles of Agents and Multi-Agent in Improving M...

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4th International Symposium on Agents, Multi-Agents Systems and Robotics, ISAMSR 2021

作者： Jubair, Mohammed Ahmed Alabdullah, Abdullah I. M. Mostafa, Salama A. Mustapha, Aida Hassan, Mustafa Hamid Gunasekaran, Saraswathy Shamini College of Information Technology Imam ja'Afar Al-Sadiq University Department of Computer Technical Engineering Al-Muthanna Iraq University of Mosul College of Science Department of Physics Mosul Iraq Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Johor Malaysia Faculty of Applied Sciences and Technology Universiti Tun Hussein Onn Malaysia Johor Malaysia College of Computer Science and Informatics Universiti Tenaga Nasional Kajang43000 Malaysia

ISBN: (纸本)9781728166544

We are experiencing a rapid evolution and advancement of technologies that are capable of supporting the formulation and implementation of robust and adaptive network architectures designed for mobile and dynamic environments. An example of such technologies is the Mobile Ad-Hoc Network (MANET), which supports self-organizing multi-hop heterogeneous network routing services and organization. The importance of such technologies for the future of DoD networking is evident, particularly in the front edge of the battlespace where there is a need for robust and self-organizing network. Another area of such technological advancement is the Multi-Agent Systems (MAS), which are capable of supporting both team-based and independent problem solving in many different environments. These two technologies have been extensively explored, but their combination is largely unexplored. Consequently, this paper aims to investigate the joint operation of agents and multi-agent in the MANET environment. The paper also discusses the research efforts that have been made to optimally improve the technologies. © 2021 IEEE.

关键词： Multi agent systems

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GMRES Methods for Tomographic Reconstruction with an Unmatched Back Projector

arXiv

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arXiv 2021年

作者： Hansen, Per Christian Hayami, Ken Morikuni, Keiichi Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark National Institute of Informatics Faculty of Engineering Information and Systems University of Tsukuba Japan

Unmatched pairs of forward and back projectors are common in X-ray CT computations for large-scale problems;they are caused by the need for fast algorithms that best utilize the computer hardware, and it is an interesting and challenging task to develop fast and easy-to-use algorithms for these cases. Our approach is to use preconditioned GMRES, in the form of the AB- and BA-GMRES algorithms, to handle the unmatched normal equations associated with an unmatched pair. These algorithms are simple to implement, they rely only on computations with the available forward and back projectors, and they do not require the tuning of any algorithm parameters. We show that these algorithms are equivalent to well-known LSQR and LSMR algorithms in the case of a matched projector. Our numerical experiments demonstrate that AB- and BA-GMRES exhibit a desired semi-convergence behavior that is comparable with LSQR/LSMR and that standard stopping rules work well. Hence, AB- and BA-GMRES are suited for large-scale CT reconstruction problems with noisy data and unmatched projector *** Codes 65F10, 65F22 Copyright © 2021, The Authors. All rights reserved.

关键词： computer hardware

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Differential Privacy Protection with Group Onion Routing based on AI-based URL Classification 20

Differential Privacy Protection with Group Onion Routing bas...

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Proceedings of the 2020 ACM International Conference on Intelligent Computing and its Emerging Applications

作者： I-Hsien Liu Yung-Lin Chang Jung-Shian Li Chuan-Gang Liu Department of Electrical Engineering Institute of Computer and Communication Engineering National Cheng Kung University Tainan Taiwan Department of applied informatics and multimedia Chia-Nan University of Pharmacy and Science Tainan Taiwan

ISBN: (纸本)9781450383042

Due to the rapid spread of tablet computers, smartphones, and other mobile information devices, wireless communication technology is fully developed and deployed widely. Mobile Internet access has been a main and important way to communicate the world in daily and it privacy protection also catches much attentions. The Onion Router, better known as Tor, is a technique for anonymous communication over internet without regional restrictions for privacy protection. Apart from this, Tor can reach sites that normal search engine cannot search. As the opinion of Tor, the transmitted data has been encrypted layer by layer, just like onion, before it reaching server. Our research proposed a system predicting URL's category with the use of machine learning technique before visiting. According to the category prediction, we represent different privacy level with three kinds of RSA key lengths on onion routing. Depending on various situations, our system can obtain the balance between security and time cost. Hence, our proposed scheme can make onion routing more flexible and efficiently.

关键词： URL classification Machine learning Privacy Anonymous transmission Tor

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Are you (Google) home? Detecting users’ presence through traffic analysis of smart speakers 4

Are you (Google) home? Detecting users’ presence through tr...

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4th Italian Conference on Cyber Security, ITASEC 2020

作者： Caputo, D. Verderame, L. Merlo, A. Ranieri, A. Caviglione, L. Computer Security Lab Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Italy Institute for Applied Mathematics and Information Technologies National Research Council of Italy Italy

Smart speakers and voice-based virtual assistants are core building blocks of modern smart homes. For instance, they are used to retrieve information, interact with other devices, and command a variety of Internet of Things (IoT) nodes. To this aim, smart speakers and voice-based assistants typically take advantage of cloud architectures: vocal commands of the user are sampled, sent through the Internet to be processed and transmitted back for local execution, e.g., to perform an automation task or activate an IoT device. Even if privacy and security is enforced by means of encryption, features of the traffic, such as the throughput, the size of protocol data units or the IP addresses, can leak important information about the habits of the users as well as the number and the type of IoT nodes deployed. In this perspective, the paper showcases risks of machine learning techniques to develop black-box models to automatically classify traffic and implement privacy leaking attacks. We prove that such traffic analysis allows to detect the presence of a person in a house equipped with a Google Home device, even if the same person does not interact with the smart device. Experimental results collected in a realistic scenario are presented and possible countermeasures are discussed. Copyright © 2020 for this paper by its authors.

关键词： Internet of things

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Quantum meets the minimum circuit size problem

arXiv

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arXiv 2021年

作者： Chia, Nai-Hui Chou, Chi-Ning Zhang, Jiayu Zhang, Ruizhe Luddy School of Informatics Computing and Engineering Indiana University Bloomington United States School of Engineering and Applied Sciences Harvard University Department of Computer Science Boston University Department of Computer Science University of Texas Austin United States

In this work, we initiate the study of the Minimum Circuit Size Problem (MCSP) in the quantum setting. MCSP is a problem to compute the circuit complexity of Boolean functions. It is a fascinating problem in complexity theory — its hardness is mysterious, and a better understanding of its hardness can have surprising implications to many fields in computer science. We first define and investigate the basic complexity-theoretic properties of minimum quantum circuit size problems for three natural objects: Boolean functions, unitaries, and quantum states. We show that these problems are not trivially in NP but in QCMA (or have QCMA protocols). Next, we explore the relations between the three quantum MCSPs and their variants. We discover that some reductions that are not known for classical MCSP exist for quantum MCSPs for unitaries and states, e.g., search-to-decision reductions and self-reductions. Finally, we systematically generalize results known for classical MCSP to the quantum setting (including quantum cryptography, quantum learning theory, quantum circuit lower bounds, and quantum fine-grained complexity) and also find new connections to tomography and quantum gravity. Due to the fundamental differences between classical and quantum circuits, most of our results require extra care and reveal properties and phenomena unique to the quantum setting. Our findings could be of interest for future studies, and we post several open problems for further exploration along this direction. © 2021, CC BY.

关键词： Boolean functions

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