检索结果-内蒙古大学图书馆

IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Per Antoine Carlsen Angelique M. Taylor Darren M Chan Md Zia Uddin Laurel Riek Jim Torresen Logistics Oda Oslo Norway College of Computing and Information Science Cornell Tech Cornell University New York USA HRL Laboratories LLC Malibu CA USA Sustainable Communication Technologies SINTEF Digital Oslo Norway Dept. of Computer Science and Engineering University of California San Diego USA Dept. of Informatics and RITMO University of Oslo Oslo Norway

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

Mobile robots deployed in the homes of disabled people and older adults can play a vital role as companions and aid in activities of daily living, enhancing people’s quality of life. For these robots to effectively assist, it can be helpful if they possess social and interactive skills to facilitate natural and personalized interactions. Personalization, including using proper names and remembering preferences, is crucial for building strong social connections and fostering trust in human-robot interaction. However, achieving personalized interactions necessitates the robot’s ability to autonomously recognize and re-identify individuals without relying on specific constraints or prior knowledge. This work introduces two lightweight Dual convolutional neural networks, LuNet Light and LuNet Lightest, designed for person re-identification in a robotic context without the limitations of existing systems. We introduce a lightweight architecture, LuNet Lightest which achieves near state-of-the-art performance on the MARS dataset. It is well-suited for real-time applications on low-cost, hardware-constrained robots. This person-identification system enables assistive mobile robots to accurately identify users, fostering trust and facilitating natural, personalized interactions.

关键词： Measurement Human-robot interaction Network architecture People with disabilities Real-time systems Mobile robots Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Security assessment in IoT ecosystems 11

Security assessment in IoT ecosystems

引用

Workshops of the 11th EETN Conference on Artificial Intelligence, SETN 2020 Workshops

作者： Evangelou, Sotirios Akasiadis, Charilaos Dept. of Electrical and Computer Engineering University of Thessaly Greece Institute of Informatics and Telecommunications N.C.S.R. 'Demokritos' Greece

The Internet of Things (IoT) and "Smart Everything" trend is a reality that is becoming part of our daily lives. Consequently, there is a gradual increase in the deployment of real world IoT systems that attempt to make use of the various possibilities and benefits the IoT offers. However, the connection of billions of-usually inherently insecure-devices in a network, paired with the lack of a clear security framework for the development of IoT systems and platforms has widened the attack surface of these systems leading to them being targeted by malicious actors. In this paper, we explore the problem and related research, devise an assets taxonomy and focus on the security requirements for each asset category. Then, we discuss countermeasures and good practices as well as new approaches based on AI that improve security and intrusion detection capabilities. We also introduce a metric that can be incorporated by automated security auditing methods. The relevance of this metric is evaluated with respect to correlation across findings from a real-world study. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Trusted Access to 6G Testbeds Through a Security Intent-Driven Software-Defined Perimeter Framework

Trusted Access to 6G Testbeds Through a Security Intent-Driv...

引用

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

作者： Carolina Fernández-Martínez Anastasios Bikos Christos Verikoukis Shuaib Siddiqui i2CAT Foundation Barcelona Spain Dept. of Information and Communication Technologies Universitat Pompeu Fabra Barcelona Spain Iquadrat Informatica SL Barcelona Spain Dept. of Signal Theory and Communications Universitat Politècnica de Catalunya Barcelona Spain Industrial Systems Institute / Athena Research Center Patras Greece Dept. of Computer Engineering and Informatics University of Patras Patras Greece

ISBN: (数字)9798350377644

ISBN: (纸本)9798350377651

Parallel to the evolution of recent trends in the cybersecurity industry and the increase of cyberattacks in the last few years, there is renovated interest on the application of software-defined techniques to enforce best security practices, such as in the Software-Defined Perimeter specification and the Zero Trust architectures. This work proposes a software-defined network segmentation and access control framework aligned with these principles. This solution captures minimal security requirements from testbed operators to establish ad-hoc, isolated connectivity and access control for end-users (experimenters) interacting with exposed endpoints from the exposed services in the cloud testbeds. The elicited architecture, design decision and initial implementation are introduced.

关键词： Access control Industries Conferences Computational modeling computer architecture Market research Ad hoc networks Zero Trust Software defined networking computer crime

来源：评论

学校读者我要写书评

暂无评论

Technical Debt Management: The Road Ahead for Successful Software Delivery

arXiv

引用

arXiv 2024年

作者： Avgeriou, Paris Ozkaya, Ipek Chatzigeorgiou, Alexander Ciolkowski, Marcus Ernst, Neil A. Koontz, Ronald J. Poort, Eltjo Shull, Forrest Dept. of Computing Science University of Groningen Groningen Netherlands Software Engineering Institute Carnegie Mellon University PittsburghPA United States Dept. of Applied Informatics University of Macedonia Thessaloniki Greece QAware GmbH München Germany Department of Computer Science University of Victoria Victoria Canada The Boeing Company MesaAZ United States CGI Rotterdam Netherlands

Technical Debt, considered by many to be the 'silent killer' of software projects, has undeniably become part of the everyday vocabulary of software engineers. We know it compromises the internal quality of a system, either deliberately or inadvertently. We understand Technical Debt is not all derogatory, often serving the purpose of expediency. But, it is associated with a clear risk, especially for large and complex systems with extended service life: if we do not properly manage Technical Debt, it threatens to "bankrupt" those systems. Software engineers and organizations that develop softwareintensive systems are facing an increasingly more dire future state of those systems if they do not start incorporating Technical Debt management into their day to day practice. But how? What have the wins and losses of the past decade of research and practice in managing Technical Debt taught us and where should we focus next? In this paper, we examine the state of the art in both industry and research communities in managing Technical Debt;we subsequently distill the gaps in industrial practice and the research shortcomings, and synthesize them to define and articulate a vision for what Technical Debt management looks like five years hence. © 2024, CC BY-NC-ND.

关键词： Industrial research

来源：评论

学校读者我要写书评

暂无评论

Outage Performance of Cross-Packet HARQ

arXiv

引用

arXiv 2022年

作者： Feng, Jiahui Shi, Zheng Yang, Guanghua Miridakis, Nikolaos I. Ma, Shaodan Tsiftsis, Theodoros A. The School of Intelligent Systems Science and Engineering Jinan University Zhuhai519070 China The Dept. of Informatics and Computer Engineering University of West Attica Aegaleo 12243 Greece The State Key Laboratory of Internet of Things for Smart City University of Macau China

As opposed to hybrid automatic repeat request with incremental redundancy (HARQ-IR) that all the resources are occupied to resend the redundant information, cross-packet HARQ (XP-HARQ) allows the introduction of new information into retransmissions to substantially exploit the remaining resources. This letter provides a profound investigation into the outage performance of XP-HARQ. In particular, the exact outage expression of XP-HARQ is derived if the maximum number of transmissions is two, and tight outage bounds are obtained for more than two transmissions. Moreover, the asymptotic outage analysis of XP-HARQ in the high signal-to-noise ratio (SNR) regime is carried out not only to simplify the outage expression, but also to show that full time diversity is achievable by XP-HARQ. The simulation results are eventually presented for verifications. © 2022, CC BY.

关键词： Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

OpenDR: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics

arXiv

引用

arXiv 2022年

作者： Passalis, Nikolaos Pedrazzi, S. Babuska, R. Burgard, W. Dias, D. Ferro, F. Gabbouj, M. Green, O. Iosifidis, A. Kayacan, E. Kober, J. Michel, O. Nikolaidis, N. Nousi, P. Pieters, R. Tzelepi, M. Valada, A. Tefas, A. Dept. of Informatics Aristotle University of Thessaloniki Greece Cyberbotics Switzerland Dept. of Cognitive Robotics Delft University of Technology Netherlands Dept. of Computer Science University of Freiburg Germany PAL Robotics Spain The units of Computing Sciences and Automation Technology and Mechanical Engineering Tampere University Finland Agrointelli Denmark The Department of Electrical and Computer Engineering Aarhus University Denmark

Existing Deep Learning (DL) frameworks typically do not provide ready-to-use solutions for robotics, where very specific learning, reasoning, and embodiment problems exist. Their relatively steep learning curve and the different methodologies employed by DL compared to traditional approaches, along with the high complexity of DL models, which often leads to the need of employing specialized hardware accelerators, further increase the effort and cost needed to employ DL models in robotics. Also, most of the existing DL methods follow a static inference paradigm, as inherited by the traditional computer vision pipelines, ignoring active perception, which can be employed to actively interact with the environment in order to increase perception accuracy. In this paper, we present the Open Deep Learning Toolkit for Robotics (OpenDR). OpenDR aims at developing an open, non-proprietary, efficient, and modular toolkit that can be easily used by robotics companies and research institutions to efficiently develop and deploy AI and cognition technologies to robotics applications, providing a solid step towards addressing the aforementioned challenges. We also detail the design choices, along with an abstract interface that was created to overcome these challenges. This interface can describe various robotic tasks, spanning beyond traditional DL cognition and inference, as known by existing frameworks, incorporating openness, homogeneity and robotics-oriented perception e.g., through active perception, as its core design principles. Copyright © 2022, The Authors. All rights reserved.

关键词： Robotics

来源：评论

学校读者我要写书评

暂无评论

Techno-economic analysis of cognitive radio models in 5G networks 17

Techno-economic analysis of cognitive radio models in 5G net...

引用

17th International Conference on Mobile Systems and Pervasive Computing, MobiSPC 2020

作者： Bouras, Christos Kollia, Anastasia Papazois, Andreas Computer Technology Institute and Press Diophantus PatrasP.C. 26504 Greece Computer Engineering and Informatics Dept. University of Patras PatrasP.C. 26504 Greece

The first commercial products of 5G will be released within 2020 and therefore, it becomes an absolute necessity to research whether the key enabling technologies are advantageous for the operators to invest in. One of the most fundamental technologies Cognitive Radio (CR), since there is not much research in the field. This paper develops a techno-economic framework for the CR technology and is contrasted with an already existing model for Software Defined Networks (SDN). A Sensitivity Analysis (SA) indicates the cost parameters that are the most expensive ones and should be reconsidered for the model's wide adoption and viability. © 2020 The Authors.

关键词： Cognitive radio

来源：评论

学校读者我要写书评

暂无评论

GeoFedBench: A benchmark for federated GeoSPARQL query processors 19

GeoFedBench: A benchmark for federated GeoSPARQL query proce...

引用

19th International Semantic Web Conference on Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters 2020

作者： Troumpoukis, Antonis Konstantopoulos, Stasinos Mouchakis, Giannis Prokopaki-Kostopoulou, Nefeli Paris, Claudia Bruzzone, Lorenzo Pantazi, Despina-Athanasia Koubarakis, Manolis Institute and Informatics and Telecommunications NCSR Demokritos Greece Dept Information Engineering and Computer Science University of Trento Italy National and Kapodistrian University of Athens Greece

Performance benchmarks are invaluable for evaluating and comparing federated query processing systems, but it is hard to design benchmarks that are both realistic and informative about the systems being tested. In this paper we present GeoFedBench, a benchmark that has been obtained from an actual, practical application of geospatial and linked data querying and uses GeoSPARQL constructs that challenge all phases of federated query processing. The benchmark is publicly available as part of the Kobe suite. © 2020 CEUR-WS. All rights reserved.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

A Secure and Trustworthy Biometric Data Ecosystem for Cross-border Suspect Identification

A Secure and Trustworthy Biometric Data Ecosystem for Cross-...

引用

IEEE International Conference on Big Data

作者： Katerina Kyriakou Apostolos Apostolaras Polychronis Velentzas Georgios Benos Konstantinos Koutsoukos Chrysostomos Symvoulidis Kaitai Liang Zeshun Shi Asterios Leonidis Kyriaki Miniadou Eleni Veroni Spyridon Evangelatos Georgios Th. Papadopoulos Thanasis Korakis Department of Electrical and Computer Engineering University of Thessaly Volos Greece CERTH The Centre for Research & Technology Hellas Volos Greece Research & Development Thridium Ltd. London United Kingdom Delft University of Technology Delft The Netherlands Institute of Computer Science (ICS) Foundation for Research and Technology - Hellas (FORTH) Crete Greece Research & Innovation Development Netcompany-Intrasoft S.A. Luxembourg Luxembourg Dept. of Electronic Engineering Hellenic Mediterranean University Crete Greece Department of Informatics and Telematics Harokopio University of Athens Athens Greece

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

This paper introduces the Biometrics Data Space framework, which is a secure ecosystem built on Data Spaces technology and it is designed to address the challenges of suspect identification during cross-border crime investigation. Apart from Data Spaces technology, the proposed framework innovates by leveraging also Privacy Enhancing Technologies (PETs) and blockchain to enable secure, trustworthy, and sovereign data exchange between Law Enforcement Agencies (LEAs) across borders. Specifically, it utilizes advanced PETs, including Large-Scale Biometric Data Indexing based on deep hashing techniques and Homomorphic Encryption to allow for suspect identification without disclosing sensitive information of personal biometric data. Thus, it enables LEAs to securely compare and exchange encrypted sensitive biometric data, including facial images, fingerprints and voiceprints, while maintaining data privacy and data sovereignty. LEAs define the usage rules for the biometic data they own and these rules are enforced to and respected by the other LEAs participating in the Biometrics Data Space. The proposed architecture is designed to be scalable, allowing the incorporation of additional biometric modalitiies and the easy expansion and integration with new participant LEAs.

关键词： Biometrics Law enforcement Space technology Terrorism Ecosystems Regulation Blockchains Resource management Spectrogram Indexing

来源：评论

学校读者我要写书评

暂无评论

Fuzzy Social Force Model for Robot Soccer Navigation: A Preliminary Report 12

Fuzzy Social Force Model for Robot Soccer Navigation: A Prel...

引用

12th International Conference on Information Technology and Electrical engineering, ICITEE 2020

作者： Dewantara, Bima Sena Bayu Ariyadi, Bagus Nugraha Deby Oktavianto, Hary Politeknik Elektronika Negeri Surabaya Dept. of Informatics and Computer Eng. Surabaya Indonesia Politeknik Elektronika Negeri Surabaya Dept. of Electrical Engineering Surabaya Indonesia

ISBN: (纸本)9781728110974

This paper proposes an adaptive control strategy to improve the performance of the Social Force Model (SFM) based mobile soccer robot navigation using the Fuzzy Inference System (FIS). The combination of FIS dan SFM is then called a Fuzzy Social Force Model (FSFM). In the FSFM strategy, FIS is used to adaptively adjust the parameters of SFM based on the stimulus from the external condition, namely the obstacle's relative distance to the robot, d, and its direction, ?, so that the robot's reactivity and responsiveness can be automatically adjusted. Currently, we adjust only one parameter, namely obstacle's gain value, k. Obstacle's gain value will control the amount of forces produced by the closest obstacle. We tested our proposed method using a realistic 3D simulator, called V-Rep, by utilizing an omnidirectional robot model from Festo, namely Robotino. Our experimental results show that our proposed FSFM can work well by always successfully finishing all of the trials with less collision with obstacles. The comparison results with the fixed-parameter method prove that our proposed method is better and very promising to be implemented for real robot applications. © 2020 IEEE.

关键词： Robot applications

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：