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Network-Layer Perspectives on Satellite–Terrestrial Integrated Networks in 6G: A Comprehensive Review

Engineering 2025年

作者： Nuo Chen Yujie Song Yue Cao Zhili Sun Bo Zhao Mi Wang Debiao He Guojun Peng School of Cyber Science and Engineering Wuhan University Wuhan 430000 China Institute for Communication Systems (ICS) School of Computer Science and Electronic Engineering & Faculty of Engineering and Physical Science University of Surrey Guildford GU2 7XH UK State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan 430000 China

Satellite–terrestrial networks have garnered significant attention in recent years and are extensively applied in intelligent transportation and emergency rescue. This paper provides a comprehensive review of the latest research advancements in satellite–terrestrial integrated network (STIN) technologies from a network perspective, dividing STIN technologies into three categories according to network service flows—namely, topology maintenance, network routing, and orchestration transmission technologies. Furthermore, a novel network-layer perspective is considered to examine the applications of STINs across various domains, along with related frameworks, platforms, simulators, and datasets. Finally, this paper explores the mainstream research directions in STIN technologies, with an innovative focus on the network layer. It reviews the existing literature, outlines future trends, and discusses opportunities for collaboration with related fields.

关键词： Satellite–terrestrial integration Network technology Intelligent transportation

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Knowledge distillation: A survey

arXiv

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arXiv 2020年

作者： Gou, Jianping Yu, Baosheng Maybank, Stephen J. Tao, Dacheng UBTECH Sydney AI Centre School of Computer Science Faculty of Engineering The University of Sydney DarlingtonNSW2008 Australia Department of Computer Science and Information Systems Birkbeck College University of London United Kingdom

In recent years, deep neural networks have been successful in both industry and academia, especially for computer vision tasks. The great success of deep learning is mainly due to its scalability to encode large-scale data and to maneuver billions of model parameters. However, it is a challenge to deploy these cumbersome deep models on devices with limited resources, e.g., mobile phones and embedded devices, not only because of the high computational complexity but also the large storage requirements. To this end, a variety of model compression and acceleration techniques have been developed. As a representative type of model compression and acceleration, knowledge distillation effectively learns a small student model from a large teacher model. It has received rapid increasing attention from the community. This paper provides a comprehensive survey of knowledge distillation from the perspectives of knowledge categories, training schemes, teacher-student architecture, distillation algorithms, performance comparison and applications. Furthermore, challenges in knowledge distillation are briefly reviewed and comments on future research are discussed and forwarded. Copyright © 2020, The Authors. All rights reserved.

关键词： Knowledge management

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Secure and Privacy-Preserving Automated Machine Learning Operations into End-to-End Integrated IoT-Edge-Artificial Intelligence-Blockchain Monitoring System for Diabetes Mellitus Prediction

arXiv

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arXiv 2022年

作者： Hennebelle, Alain Ismail, Leila Materwala, Huned Kaabi, Juma Al Ranjan, Priya Janardhanan, Rajiv School of Computing and Information Systems The University of Melbourne Australia Research Laboratory Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University United Arab Emirates National Water and Energy Center United Arab Emirates University United Arab Emirates College of Health Sciences Department of Internal Medicine United Arab Emirates University United Arab Emirates Mediclinic Al Ain Abu Dhabi United Arab Emirates Bhubaneswar Institute of Technology India Faculty of Medical & Health Sciences SRM Institute of Science & Technology India

Diabetes Mellitus, one of the leading causes of death worldwide, has no cure to date and can lead to severe health complications, such as retinopathy, limb amputation, cardiovascular diseases, and neuronal disease, if left untreated. Consequently, it becomes crucial to take precautionary measures to avoid/predict the occurrence of diabetes. Machine learning approaches have been proposed and evaluated in the literature for diabetes prediction. This paper proposes an IoT-edge-Artificial Intelligence (AI)-blockchain system for diabetes prediction based on risk factors. The proposed system is underpinned by the blockchain to obtain a cohesive view of the risk factors data from patients across different hospitals and to ensure security and privacy of the user’s data. Furthermore, we provide a comparative analysis of different medical sensors, devices, and methods to measure and collect the risk factors values in the system. Numerical experiments and comparative analysis were carried out between our proposed system, using the most accurate random forest (RF) model, and the two most used state-of-the-art machine learning approaches, Logistic Regression (LR) and Support Vector Machine (SVM), using three real-life diabetes datasets. The results show that the proposed system using RF predicts diabetes with 4.57% more accuracy on average compared to LR and SVM, with 2.87 times more execution time. Data balancing without feature selection does not show significant improvement. The performance is improved by 1.14% and 0.02% after feature selection for PIMA Indian and Sylhet datasets respectively, while it reduces by 0.89% for MIMIC III. © 2022, CC BY.

关键词： Logistic regression

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A dragonfly algorithm for solving traveling salesman problem 8

A dragonfly algorithm for solving traveling salesman problem

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8th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2018

作者： Hammouri, Abdelaziz I. Samra, Enas Tawfiq Abu Al-Betar, Mohammed Azmi Khalil, Raid M. Alasmer, Ziad Kanan, Monther Department of Computer Information Systems Al-Balqa Applied University Al-Salt Jordan Department of Computer Science Al-Balqa Applied University Al-Salt Jordan Department of Information Technology Al-Balqa Applied University Al-hoson Irbid Jordan Department of Computer Engineering Al-Balqa Applied University Amman Jordan Department of Mechatronics Engineering Al-Balqa Applied University Amman Jordan

ISBN: (纸本)9781538663240

Traveling Salesman Problem (TSP) is considered as nondeterministic polynomial time hard problem. In the TSP, a salesman should visit a set of cities, and the distances between all pairs of cities are known in advance. The salesman has to find the shortest tour for visiting all cities exactly once and returns back to the starting city. Various methods have been used to tackle TSP, the most commonly employed methods are meta-heuristic algorithms. In this paper, TSP has been tackled by employing a newly created meta-heuristic algorithm, named Dragonfly Algorithm (DA), on well-known datasets (TSPLIB). The idea of DA has been inspired from swarm intelligence. To assess the quality of the proposed approach, it will be compared with other meta-heuristic methods that are available in the literature using the same datasets. The final results showed that the proposed DA-based TSP problem method is able to efficiently address the TSP and it produces competitively comparable results against others produces by well-regards comparative methods. © 2018 IEEE.

关键词： Traveling salesman problem

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Natural language processing: Speaker, language, and gender identification with LSTM 5th

Natural language processing: Speaker, language, and gender i...

引用

5th International Doctoral Symposium on applied Computation and Security systems, ACSS 2018

作者： Nammous, Mohammad K. Saeed, Khalid Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS Sankt Augustin Germany Faculty of Mathematics and Information Sciences Warsaw University of Technology Warsaw Poland Faculty of Computer Science Bialystok University of Technology Bialystok Poland

ISBN: (纸本)9789811337017

Long short-term memory (LSTM) is a state-of-the-art network used for different tasks related to natural language processing (NLP), pattern recognition, and classification. It has been successfully used for speech recognition and speaker identification as well. The amount of training data and the ratio of training to test data are still the key factors for achieving good results, but have their implications on the real usage. The main contribution of this paper is to achieve a high rate of speaker recognition for text-independent continuous speech using small ratio of training to test data, by applying long short-term memory recursive neural network. A comparison with the probabilistic feed-forward neural network has been made for speaker recognition as well as gender and language identification. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Long short-term memory

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SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation

引用

IEEE Transactions on Evolutionary Computation 2024年 1-1页

作者： de Franca, F.O. Virgolin, M. Kommenda, M. Majumder, M.S. Cranmer, M. Espada, G. Ingelse, L. Fonseca, A. Landajuela, M. Petersen, B. Glatt, R. Mundhenk, N. Lee, C.S. Hochhalter, J.D. Randall, D.L. Kamienny, P. Zhang, H. Dick, G. Simon, A. Burlacu, B. Kasak, Jaan Machado, Meera Wilstrup, Casper Cavaz, W.G.L. Federal University of ABC Santo Andre Brazil Evolutionary Intelligence group Centrum Wiskunde and Informatica Science Park Amsterdam Netherlands University of Applied Sciences Upper Austria Hagenberg Austria Computational Health Informatics Program Boston Children’s Hospital Harvard Medical School Boston USA Center for Computational Astrophysics Flatiron Institute and Department of Astrophysical Sciences of Princeton University USA LASIGE Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Computational Engineering Division Lawrence Livermore National Laboratory Livermore USA Department of Mechanical Engineering University of Utah Utah USA Meta FAIR France Victoria University of Wellington School of Engineering and Computer Science New Zealand University of otago Department of Information Science New Zealand Institut für Angewandte Physik Universität TübingenMax Planck Institute for Intelligent Systems Tübingen Germany Abzu AI Orient Plads 1 Nordhavn Denmark

Symbolic regression searches for analytic expressions that accurately describe studied phenomena. The main promise of this approach is that it may return an interpretable model that can be insightful to users, while maintaining high accuracy. The current standard for benchmarking these algorithms is SRBench, which evaluates methods on hundreds of datasets that are a mix of real-world and simulated processes spanning multiple domains. At present, the ability of SRBench to evaluate interpretability is limited to measuring the size of expressions on real-world data, and the exactness of model forms on synthetic data. In practice, model size is only one of many factors used by subject experts to determine how interpretable a model truly is. Furthermore, SRBench does not characterize algorithm performance on specific, challenging sub-tasks of regression such as feature selection and evasion of local minima. In this work, we propose and evaluate an approach to benchmarking SR algorithms that addresses these limitations of SRBench by 1) incorporating expert evaluations of interpretability on a domain-specific task, and 2) evaluating algorithms over distinct properties of data science tasks. We evaluate 12 modern symbolic regression algorithms on these benchmarks and present an in-depth analysis of the results, discuss current challenges of symbolic regression algorithms and highlight possible improvements for the benchmark itself. Authors

关键词： Benchmarking

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Towards Flexible Process Automation: An Approach for Flexible Service Robot Adaptation and Allocation 2019

Towards Flexible Process Automation: An Approach for Flexibl...

引用

Proceedings of the 2019 3rd International Symposium on computer science and Intelligent Control

作者： Matthias Rollenhagen Matthias Lutz Nayabrasul Shaik Kevin Andrews Sebastian Steinau Manfred Reichert Christian Schlegel Institute of Computer Science University of Applied Sciences Ulm Prittwitzstrasse Ulm Germany Institute of Databases and Information Systems Ulm University James-Franck-Ring Ulm Germany

ISBN: (纸本)9781450376617

The dynamic of today's markets demand automation systems that are flexible enough for being adapted to rapid requirement changes. The presented work describes how to make robotic systems more flexible in order to cope with changing processes, products, and environments. We propose flexibilizing service robot task modeling and assignment by coupling them with process management systems and utilize them similarly to human workers. Additionally, a variability management workflow is presented, for not fixing systems at design-time. Instead, variability is left open intentionally and reduced gradually. The combination of these two approaches enables users (e.g. workers) to adapt their robot systems to requirement changes by user-friendly tools and provides flexible service robot allocation.

关键词： Service Robot Software systems Variability Management

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Minimizing interpretations in fuzzy description logics under the Gödel semantics by using fuzzy bisimulations

Minimizing interpretations in fuzzy description logics under...

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作者： Nguyen, Linh Anh Nguyen, Ngoc-Thanh Institute of Informatics University of Warsaw Warsaw Poland Faculty of Information Technology Nguyen Tat Thanh University Ho Chi Minh city Viet Nam Department of Information Systems Faculty of Computer Science and Management Wroclaw University of Science and Technology Poland

We study the problem of minimizing interpretations in fuzzy description logics (DLs) under the Gödel semantics by using fuzzy bisimulations. The considered logics are fuzzy extensions of the DL (a variant of propositional dynamic logic) with additional features among inverse roles, nominals and the universal role. Given a fuzzy interpretation and for E being the greatest fuzzy auto-bisimulation of w.r.t. The considered DL, we define the quotient E of w.r.t. E and prove that it is minimum w.r.t. certain criteria. Namely, E is a minimum fuzzy interpretation that validates the same set of fuzzy terminological axioms in the considered DL as Furthermore, if the considered DL allows the universal role, then E is a minimum fuzzy interpretation bisimilar to as well as a minimum fuzzy interpretation that validates the same set of fuzzy concept assertions in the considered DL as. © 2019 - IOS Press and the authors. All rights reserved.

关键词： Semantics

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Data exchange platform for digital economy applications 6

Data exchange platform for digital economy applications

引用

6th International Conference information Technology and Nanotechnology. Session Data science, ITNT-DS 2020

作者： Surnin, Oleg Ivaschenko, Anton Sitnikov, Pavel Stolbova, Anastasia Khorina, Anastasia Ilyasova, Nataly Ipsi Sec Open Code Data Analysis Department Samara Russia Samara State Technical University Computer Science Department Samara Russia Faculty of Infocommunication Itmo University Saint-Petersburg Russia Samara National Research University Information Systems and Technologies Department Samara Russia Faculty of Infocommunication Itmo University Saint-Petersburg Russia Branch of Fsrc Crystallography Image Processing Systems Institute of Ras and Photonics" RAS Samara Russia

This paper describes an experience of the Data exchange software platform practical use supporting the modern trends of Digital Economy. The platform was initially designed for the suppliers and customers of data sources providing the up-to-date technologies of big data processing as an online service. The platform is also open for software developers to upload new algorithms and technologies in order to help them to find new areas of application. There is presented architecture and its software implementation for an intermediary online platform capable of collecting, processing and analysis of various datasets. Modern companies being the members of digital economy can use this platform to process their data and produce business analytics. They can become both suppliers and providers of data, as well as develop and upload new customized algorithms. First results were achieved in the area of retail and social media analysis. Copyright © 2020 for this paper by its authors.

关键词： Electronic data interchange

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A Comparative Review of ISMS Implementation Based on ISO 27000 Series in Organizations of Different Business Sectors 1

A Comparative Review of ISMS Implementation Based on ISO 270...

引用

1st International Conference computer science and Engineering, IC2SE 2019

作者： Hamdi, Zaidatulnajla Anir Norman, Azah Nuha Abdul Molok, Nurul Hassandoust, Farkhondeh Dept. of Information Systems Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Kuala Lumpur Malaysia Auckland University of Technology Auckland New Zealand

Organizations have different takes on information Security Management systems (ISMS) since security measurements vary according to their business relevance. One way to assure ISMS is being well-implemented is by having a standard compliance such as the ISO 27000 series. The ISO 27000 series is a family of standards that provides a framework for best practice ISMS that helps organizations keep their information assets secure. This paper intends to seek how organizations in different business sectors implement ISMS in their practices. By identifying which organization attains a higher number of ISO requirements, it is anticipated that the characteristics that increase the chances of an organization being certified can be distinguished. This paper reviews case studies regarding the ISMS implementation based on ISO 27000 series between organizations in different business sectors. The result of this paper presents the state of ISO compliance of the organizations. The findings also discussed the characteristics of organizations that are applicable for certification. Through the findings, it is found that the organization, which fulfilled the highest number of ISO requirement, has a stronger possibility of being certified. However, ISO standards should be more dynamic to support diverse business environment thus avoiding generalization to get compliance. © Published under licence by IOP Publishing Ltd.

关键词： ISO Standards

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