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Journal of Network Intelligence 2023年第4期8卷 1406-1425页

作者： Chen, Juan Zeng, Ren-Xian Qiu, Shen-Yu Kang, Ping Zhao, Jia School of Information Engineering Nanchang Institute of Technology Nanchang Key Laboratory of IoT Perception and Collaborative Computing for Smart City China School of Information Engineering Nanchang Institute of Technology China College of Science Nanchang Institute of Technology China

For the firefly algorithm in the solution of complex functions are prone to low accuracy and "premature" phenomenon. In this paper, we propose a tolerance-based elite mutation firefly algorithm (MOFA-TEM). The algorithm employs non-dominated sorting and congestion distance to select the elite leader, which is fused with the individual historical optimal solution to form a more comprehensive integrated information of the population, and jointly guide the movement of the fireflies, which not only en-hances the interactivity of the information between fireflies in the population, but also improves the algorithm’s ability of global exploration. Secondly, a tolerance-based firefly state judgment mechanism is designed, which will exponentially increase the probability of updating the elite leader as the number of individual firefly stagnation increases, which both fully exploits the potential of ’s search for excellence and prevents ineffective search-ing of the population. Finally, if the firefly triggers the tolerance mechanism, the elite mutation strategy will be used to update the and select a new elite learning object to avoid the algorithm from stagnating. Experiments on 19 test functions and validation using Friedman’s test show that MOFA-TEM gives better results compared to other optimization algorithms. © 2023.

关键词： Bioluminescence

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The Functionalities and Features of Personal Health Record Systems 34

The Functionalities and Features of Personal Health Record S...

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34th Australasian Conference on information Systems, ACIS 2023

作者： Alshammari, Modi Vlahu-Gjorgievska, Elena Win, Khin Than School of Computing and Information Technology University of Wollongong NSW Australia

This paper aims to investigate the up-to-date functions and features offered in PHR systems, that might affect PHRs adoption, engagement, and usability. Article search was conducted in the Scopus, Medline, and Web of Science databases and 19 articles were selected in the review based on the inclusion criteria. These studies examined PHRs (Personal Health Record system) functionality, features, and adoption by using different research methods. As a result of the review, PHRs functions were classified into 8 themes (personal information management, communication, medication, laboratory, appointment management, self-monitoring, education & advanced functions) which may impact patients' acceptance and usability of PHRs. It was found that system functionalities affect the utilisation of the patient portal, and PHRs adoption and usability significantly improves when users seek and use features. Copyright © 2023 Modi Alshammari, Khin Than Win, Elena Vlahu-Gjorgievska.

关键词： information management

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Using Machine Learning for Detecting Timing Side-Channel Attacks in SDN 6th

Using Machine Learning for Detecting Timing Side-Channel At...

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Proceedings of the 6th International Symposium on Mobile Internet Security, MobiSec 2022

作者： Shoaib, Faizan Chow, Yang-Wai Vlahu-Gjorgievska, Elena Nguyen, Chau School of Computing and Information Technology University of Wollongong Wollongong Australia

ISBN: (纸本)9789819944293

Software-Defined Networking (SDN) is a networking technology that allows for the programming and efficient management of networks. Due to the separation of the data plane and the control plane, SDN is prone to timing side-channel attacks. The adversary can use timing information to obtain data about the network such as flow tables, routes, controller types, ports, and so on. The focus of current mitigation strategies for timing side-channel attacks is largely on minimizing them through network architectural changes. This adds considerable overhead to the SDNs and makes establishing the origin of the attack a challenge. In this paper, we propose a machine learning-based approach for detecting timing side-channel attacks and identifying their source in SDNs. We adopt the machine learning methodology for this solution since it delivers faster and more accurate output. As opposed to conventional methods, it can precisely detect timing side-channel activity in SDN and determine the attacker’s origin. Because this security solution is intended to be used in association with SDN, its architecture ensures that it has a low impact on network traffic and resource consumption. The overall design findings indicate that our method is effective in detecting timing side-channel attacks in SDN and accurately identifying the attacker’s machine. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Software defined networking

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Sustaining Volunteering in Turbulent Times: A Study of the Use of Social Media for the 2022 UCI Road World Championships 44

Sustaining Volunteering in Turbulent Times: A Study of the U...

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44th International Conference on information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023

作者： Gillen, Joshua J. Freeman, Mark School of Computing and Information Technology University of Wollongong Wollongong Australia

ISBN: (纸本)9781713893622

During the COVID-19 pandemic in Australia, significant changes were introduced with lockdowns and social distancing measures;these changes were heavily felt in the not-for-profit sector. The pandemic prevented the use of traditional methods of volunteering, where work is traditionally carried out in person or on location. Social networking sites and virtual volunteering were used in the not-for-profit sector to maintain social ties with local communities. Despite this effort, not-for-profit organisations post-COVID-19 have found that volunteer numbers have not returned to their pre-pandemic numbers. Using a case study covering the Union Cycliste Internationale (UCI) Road World Championships in Wollongong 2022, this paper provides an example of the current state of the social ties between not-for-profits and the local community showing that a lack of communication leads to weaker social ties with members of the local community using online social networks and traditional news media to help promote the event and to attract a volunteer base while the event occurred. Copyright © 2023 Joshua J. Gillen and Mark Freeman.

关键词： Profitability

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AFuNet: an attention-based fusion network to classify texts in a resource-constrained language

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Neural computing and Applications 2025年第9期37卷 6725-6748页

作者： Hossain, Md. Rajib Hoque, Mohammed Moshiul Dewan, M. Ali Akber Hoque, Enamul Siddique, Nazmul Department of Computer Science & Engineering Chittagong University of Engineering & Technology Chittagong4349 Bangladesh School of Computing and Information Systems Faculty of Science and Technology Athabasca University AthabascaABT9S 3A3 Canada School of Information Technology York University TorontoONM3J 1P3 Canada School of Computing Engineering and Intelligent Systems Ulster University Coleraine United Kingdom

In the era of widespread Internet use and extensive social media interaction, the digital realm is accumulating vast amounts of unstructured text data. This unstructured data often contain undesirable information, necessitating time-consuming manual classification efforts. An intelligent text classification system capable of automatically categorizing digitized texts based on semantic meaning is crucial. However, this task is particularly challenging for low-resource languages like Bengali due to a shortage of annotated corpora, issues with out-of-vocabulary words, lack of domain-specific hyperparameter tuning, limited ability to extract generalized text features, and class imbalances within the corpus. AFuNet: an attention-based fusion network to classify texts in a resource-constrained language. AFuNet undergoes a comprehensive four-phase experimental process, including baseline model evaluation and hyperparameter tuning, late fusion and model selection, attention-based early fusion and model identification, and an ablation study with impact analysis. Fine-tuned based on five Bengali text classification corpora, AFuNet achieves impressive accuracies: 96.60 ± 0.2 (BTCC11), 85.37 ± 0.2 (OSBC), 97.35 ± 0.2 (BARD), 93.74 ± 0.2 (IndicNLP), and 96.51 ± 0.2 (ProthomAlo). In comparison with previous state-of-the-art models on these corpora, AFuNet demonstrates significant accuracy improvements ranging from 0.54% to 4.49%, showcasing its effectiveness in advancing text classification capabilities for the Bengali language. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Semantics

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Sustaining Volunteering in Turbulent Times: A Study of the Use of Social Media for the 2022 UCI Road World Championships 34

Sustaining Volunteering in Turbulent Times: A Study of the U...

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34th Australasian Conference on information Systems, ACIS 2023

作者： Gillen, Joshua J. Freeman, Mark School of Computing and Information Technology University of Wollongong Wollongong Australia

关键词： Profitability

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Hyron: A New Approach for Automating the Network ACL Delivery Pipeline 32

Hyron: A New Approach for Automating the Network ACL Deliver...

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32nd International Conference on Computer Communications and Networks, ICCCN 2023

作者： Taylor, Jacob Neil Le, Ngoc Thuy Baek, Joonsang Susilo, Willy School of Computing and Information Technology University of Wollongong Wollongong Australia

ISBN: (纸本)9798350336184

Automated Access Control List (ACL) configuration has remained an area of research interest for a significant period. However, previous research has not addressed the challenges associated with ACL automation in the context of a complex and evolving industry landscape. We examine the existing research literature on this topic and identify a series of key requirements ('success criteria') that any new system must achieve to be considered an improvement over the status quo. We then design, develop, and demonstrate an approach to ACL automation that embodies these characteristics by combining model-driven ACL synthesis with a modern DevOps-style deployment system. We explain the rationale that drove the design decisions behind the Hyron ACL generation toolkit and how it can enable a fully automated ACL delivery pipeline when integrated with standard developer tools. In contrast to previous research, our design approach reflects automation trends in the industry to ensure mainstream engineers readily adopt our solution. We provide an analysis comparing our approach's benefits to those of previous research. © 2023 IEEE.

关键词： Python

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Securing IoT Devices Against Emerging Security Threats: Challenges and Mitigation Techniques

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Journal of Cyber Security technology 2023年第4期7卷 199-223页

作者： Aziz Al Kabir, Mohammed Elmedany, Wael Sharif, Mhd Saeed College of Information Technology University of Bahrain Sakhir Bahrain School of Architecture Computing and Engineering UEL London United Kingdom

The increasing prevalence of IoT devices has brought about numerous security challenges due to their relatively simple internal architecture and low-powered hardware warranted by their small footprint requirement. As there are billions of IoT devices in use today, the sheer number of such devices pose a great security challenge as they are often constrained by a number of hardware and software limitations in addition to being designed with a focus on convenience, ease of use, mass production, and low cost, rather than security. The seemingly exponentially increasing number of such devices make it harder to keep track of–and patch–insecure IoT devices. This paper explores the common security threats, attacks, and vulnerabilities relating to IoT devices and highlights the challenges associated with securing them against emerging security threats and cyberattacks. Due to their role as gateways to connected devices and susceptibility to forming botnets or facilitating man-in-the-middle attacks, IoT devices are a lucrative target for cybercriminals. The paper discusses various remediation and mitigation techniques that can be implemented to better secure IoT devices, including access control mechanisms, secure communication protocols, and regular updates and patches. By better understanding the security challenges associated with IoT devices and implementing effective mitigation techniques, individuals and businesses can ensure the safety, security, and privacy of their connected devices and networks. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Cybersecurity

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Novel E-Learning Experience and Perceptions with Impacts from Educational Key Opinion Leaders 53

Novel E-Learning Experience and Perceptions with Impacts fro...

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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： Zhang, Susan Shen, Jun Yan, Jun School of Computing & Information Technology University of Wollongong Wollongong Australia

ISBN: (纸本)9798350336429

In recent years, an increasing number of school-age children and adult learners are flocking to e-learning platforms or mobile Apps for personal or professional development. This research compared two studies that were built upon the constructivism model to investigate the parents, whose children are studying or have recently studied online, and also the adult learners' satisfaction, perceived learning outcomes, and recommendations towards Educational Key Opinion Leaders (Edu-KOLs). A two-phase study was designed specifically for both studies. We adopted the quantitative research approach using partial least squares structural equation modelling (PLS-SEM) to interpret the collected data. The findings revealed that for both learning cohorts, Edu-KOLs' knowledge level and course content has a significant influence on learners' perceived learning outcomes and customer advocacy and that higher engagement and interaction levels are favourably associated with their perception of Edu-KOLs. However, the e-learning platform played a positive role in selecting Edu-KOLs for parents but was not significant for adult learners. Perceived outcomes are critical for adult learners, whereas parents are satisfied as long as children are engaged, regardless of what they have learned. © 2023 IEEE.

关键词： E-learning Edu-KOL MOOC partial least squares structural equation model (PLS-SEM)

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Waveform based speech coding using nonlinear predictive techniques: a systematic review

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International Journal of Speech technology 2023年第4期26卷 1031-1059页

作者： Sheferaw, Gebremichael Kibret Mwangi, Waweru Kimwele, Michael Mamuye, Adane School of Computing and Information Technology Jomo Kenyatta University of Agriculture and Technology Juja Nairobi Nairobi62000 Kenya School of Information Technology and Engineering Addis Ababa University Institute of Technology 5Kilo Addis-Ababa Addis-Ababa Ethiopia

Speech coding is a technique that compresses speech signals into a smaller digital form, making it easier to transmit or store, while still maintaining the quality and intelligibility of the speech. The review aimed to identify and analyses the most effective waveform-based nonlinear speech coding prediction techniques, including the use of neural networks and polynomial filters. The study analyzed 29 publications from 2000 to 2023 and found that neural network-based models are widely used for speech compression, with RNN topologies being favored due to their ability to introduce nonlinearity and nonstationary. While nonlinear adaptive speech prediction techniques have been explored for speech coding, further research is needed to optimize the adaptive algorithms used in these models. The review also identified a need for future research to address quality performance and computational cost, and suggested further exploration of RNN predictor models. The methodology used in this study involved a computer science approach that follows three main phases: planning, conducting, and reporting. Six different stages were followed, including determining research questions, defining research approach, study selection criteria, quality measurement criteria, data extraction strategy, and synthesizing extracted data. Overall, this study highlights the need for continued research in the development and improvement of neural network-based speech compression models. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Forecasting

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