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arXiv 2024年

作者： Faklaris, Cori Department of Software and Information Systems College of Computing and Informatics University of North Carolina at Charlotte CharlotteNC United States

U.S. Federal Trade Commission data for 2020-2022 shows that 23% of all fraud reports include Text as the contact method, with reported losses in the same period rising 279%, to $326 million. These numbers, and estimates of other unreported losses, have spurred our lab and others in industry and academia to direct resources to understanding and mitigating smishing. In this workshop paper, we describe three principal challenges in smishing mitigation that are distinct from traditional phishing: (1) limitations of mobile device affordances, (2) the complexity of cellular network infrastructure, and (3) cognitive and contextual factors in mobile device usage. We describe ideas for mitigating smishing, including a high-level overview of our lab's work to create and test interface designs for text-message recipients. © 2024, CC BY-SA.

关键词： Mobile security

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The Usability Testing of Website with Automated Tools (A Case Study at School of Information systems, BINUS University) 7

The Usability Testing of Website with Automated Tools (A Cas...

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7th International Conference on E-Society, E-Education and E-Technology, ESET 2023

作者： Kurniawan, Yohannes Pratama, Bayu Candra, Sevenpri Luhukay, Devyano Johan Anwar, Norizan School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Binus Business School Bina Nusantara University Management Department Jakarta11480 Indonesia School of Information Science College of Computing Informatics and Media Universiti Teknologi MARA Shah Alam40450 Malaysia

ISBN: (纸本)9798350344608

The Information and Communication Technologies (ICT) field has grown significantly over the past few decades. Websites are now crucial tools for the distribution of digital material. In order to compete worldwide and give everyone the information they need. Therefore, websites need to be usable and accessible. The usability of a website is related to how simple it is to use, while accessibility is required for successful and efficient web use. The author uses the School of Information systems website as an object for this research. This research will concentrate on using an automated tool to assess websites. The research objectives are to examine the usability and performance of the website, including information delivery methods and the utilization of every aspect the website offers visitors. The research uses automated tools to evaluate websites such as WAVE, Tenon, Google Lighthouse, and Pingdom. The results of this research could assist stakeholders in improving the quality of the website in order to boost user satisfaction and experience. © 2023 IEEE.

关键词： Information use

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User Experience on a Culture-Based Learning Management System: Students' Perspective

User Experience on a Culture-Based Learning Management Syste...

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Information and Education Technology (ICIET), International Conference on

作者： Regina Garcia Almonte Alvin Monteron Montiano Paul Brian Cerequillo Salili Leonard Marudo Garcia Ramil Roxas Hipolito Arlou Hemedez Fernando Department of Computing and Informatics City College of Calamba Laguna Philippines Management Information Systems Department City College of Calamba Laguna Philippines

ISBN: (数字)9798350371772

ISBN: (纸本)9798350371789

User Experience (UX) refers to the individual experience of users when using software. An institution must analyze the user experience, especially for custom-built software. The goal of this study is to assess the UX to verify that e-Guro, the City College of Calamba's culture-based Learning Management System, satisfies student expectations. To achieve this purpose, an adapted culture-based questionnaire was used to assess UX. With an aggregate mean of 3.62, which was evaluated as acceptable, e-Guro satisfied the users' expectations in terms of goal content, usability objectives, accessibility goals, and engagement goals. The findings provide important insight into how to develop a culture-based learning management system to help achieve teaching and learning objectives more effectively.

关键词： Learning management systems Reviews Aggregates Education Urban areas Software User experience

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Optimising Random Forest Machine Learning Algorithms for User VR Experience Prediction Based on Iterative Local Search-Sparrow Search Algorithm 6

Optimising Random Forest Machine Learning Algorithms for Use...

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6th International Conference on Communications, Information System and Computer Engineering, CISCE 2024

作者： Tang, Xirui Li, Feiyang Cao, Zinan Yu, Qixuan Gong, Yulu College of Computer Sciences Northeastern University BostonMA02115 United States University of Illinois Urbana-Champaign Department of Computer Science ChampaignIL61820 United States The University of Tokyo Department of General Systems Studies Tokyo113-8654 Japan College of Computing Georgia Institute of Technology AtlantaGA30332-0280 United States School of Informatics Computing and Cyber Systems Northern Arizona University FlagstaffAZ86011-4092 United States

ISBN: (纸本)9798350353174

In this paper, an improved method for VR user experience prediction is investigated by introducing a sparrow search algorithm and a random forest algorithm improved by an iterative local search-optimised sparrow search algorithm. The study firstly conducted a statistical analysis of the data, and then trained and tested using the traditional random forest model, the random forest model improved by the sparrow search algorithm, and the random forest algorithm improved based on the iterative local search-sparrow search algorithm, respectively. The results show that the traditional random forest model has a prediction accuracy of 93% on the training set but only 73.3% on the test set, which is poor in generalisation;whereas the model improved by the sparrow search algorithm has a prediction accuracy of 94% on the test set, which is improved compared with the traditional model. What is more noteworthy is that the improved model based on the iterative local search-sparrow search algorithm achieves 100% accuracy on both the training and test sets, which is significantly better than the other two methods. These research results provide new ideas and methods for VR user experience prediction, especially the improved model based on the iterative local search-sparrow search algorithm performs well and is able to more accurately predict and classify the user's VR experience. In the future, the application of this method in other fields can be further explored, and its effectiveness can be verified through real cases to promote the development of AI technology in the field of user experience. © 2024 IEEE.

关键词： Prediction models

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Can Large Language Models Effectively Mitigate Polarization in Social Media Text? 25

Can Large Language Models Effectively Mitigate Polarization ...

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Proceedings of the 17th ACM Web Science Conference 2025

作者： Lucas Raniére Juvino Santos Leandro Balby Marinho Claudio Elizio Calazans Campelo Filippo Menczer Alessandro Flammini Systems and Computing Department Federal University of Campina Grande Campina Grande Paraíba Brazil Luddy School of Informatics Computing and Engineering Indiana University Bloomington Indiana USA

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Syllabus Design and Planning with Artificial Intelligence and the Potential of Generative AI 24

Syllabus Design and Planning with Artificial Intelligence an...

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24th IEEE International Symposium on Computational Intelligence and informatics, CINTI 2024

作者： Kozhanov, Murat Mosavi, Amir Amirov, Azamat Kaibassova, Dinara Poser, Valeria Shakhatova, Aliya Lira, La Eigner, Gyorgy Department of Information and Computing Systems Abylkas Sagninov Karaganda Technical University Karaganda Kazakhstan Obuda University Budapest Hungary Ludovika University of Public Service Budapest Hungary Department of Computer Engineering Astana IT University Astana Kazakhstan John von Neumann Faculty of Informatics Obuda University Budapest Hungary Department of Information Systems L.N.Gumilyov Eurasian National University Astana Kazakhstan

ISBN: (纸本)9798350353433

This article introduces a methodology to identify the fundamental studies carried out using artificial intelligence for syllabus design and planning. A taxonomy of the most relevant studies is presented based on the method and applications. The main studies in the field are reviewed and their contributions are emphasized. The meta-analysis of the results presents the extent and applicability of artificial intelligence in syllabus design and planning. The result shows the essential role of machine learning in the development and improving the process of syllabus design and planning. © 2024 IEEE.

关键词： Adversarial machine learning

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Automatic Speaker Recognition Using Mel-Frequency Cepstral Coefficients Through Machine Learning

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Computers, Materials & Continua 2022年第6期71卷 5511-5521页

作者： U˘gur Ayvaz Hüseyin Gürüler Faheem Khan Naveed Ahmed Taegkeun Whangbo Abdusalomov Akmalbek Bobomirzaevich Department of Computer Engineering Istanbul Technical UniversityIstanbul34485Turkey Department of Information Systems Engineering Mugla Sitki Kocman UniversityMugla48000Turkey Artificial Intelligence Lab Department of Computer EngineeringGachon UniversitySeongnam13557Korea Department of Computer Science College of Computing and InformaticsUniversity of SharjahSharjah27272UAE

Automatic speaker recognition(ASR)systems are the field of Human-machine interaction and scientists have been using feature extraction and feature matching methods to analyze and synthesize these *** of the most commonly used methods for feature extraction is Mel Frequency Cepstral Coefficients(MFCCs).Recent researches show that MFCCs are successful in processing the voice signal with high *** represents a sequence of voice signal-specific *** experimental analysis is proposed to distinguish Turkish speakers by extracting the MFCCs from the speech *** the human perception of sound is not linear,after the filterbank step in theMFCC method,we converted the obtained log filterbanks into decibel(dB)features-based spectrograms without applying the Discrete Cosine Transform(DCT).A new dataset was created with converted spectrogram into a 2-D *** learning algorithms were implementedwith a 10-fold cross-validationmethod to detect the *** highest accuracy of 90.2%was achieved using Multi-layer Perceptron(MLP)with tanh activation *** most important output of this study is the inclusion of human voice as a new feature set.

关键词： Automatic speaker recognition human voice recognition spatial pattern recognition MFCCs spectrogram machine learning artificial intelligence

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Efficient Resource Allocation Algorithm in Uplink OFDM-Based Cognitive Radio Networks

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Computers, Materials & Continua 2023年第5期75卷 3045-3064页

作者： Omar Abdulghafoor Musbah Shaat Ibraheem Shayea Ahmad Hamood Abdelzahir Abdelmaboud Ashraf Osman Ibrahim Fadhil Mukhlif Herish Badal Norafida Ithnin Ali Khadim Lwas Electronic&Telecommunications Engineering Department The American University of KurdistanDuhokKurdistan RegionIraq CTTC BarcelonaSpain Faculty of Electrical and Electronics Engineering Istanbul Technical UniversityIstanbulTurkey Department of Information Systems King Khalid UniversityMuhayel AseerSaudi Arabia Faculty of Computing and Informatics University Malaysia SabahKota KinabaluMalaysia Information Assurance and Security Research Group(IASRG) School of ComputingFaculty of EngineeringUniversiti Teknologi MalaysiaJohorMalaysia R&D Ministry of Industry and MineralsBaghdadIraq

The computational complexity of resource allocation processes,in cognitive radio networks(CRNs),is a major issue to be ***,the complicated solution of the optimal algorithm for handling resource allocation in CRNs makes it unsuitable to adopt in real-world applications where both cognitive users,CRs,and primary users,PUs,exist in the identical geographical ***,this work offers a primarily price-based power algorithm to reduce computational complexity in uplink scenarioswhile limiting interference to PUs to allowable ***,this paper,compared to other frameworks proposed in the literature,proposes a two-step approach to reduce the complexity of the proposed mathematical *** the first step,the subcarriers are assigned to the users of the CRN,while the cost function includes a pricing scheme to provide better power control algorithm with improved reliability proposed in the second *** main contribution of this paper is to lessen the complexity of the proposed algorithm and to offer flexibility in controlling the interference produced to the users of the primary networks,which has been achieved by including a pricing function in the proposed cost ***,the performance of the proposed power and subcarrier algorithm is confirmed for orthogonal frequency-division multiplexing(OFDM).Simulation results prove that the performance of the proposed algorithm is better than other algorithms,albeit with a lesser complexity of O(NM)+O(Nlog(N)).

关键词： Cognitive radio resource allocation OFDM pricing

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Distributed Gibbs Sampling and LDA Modelling for Large Scale Big Data Management on PySpark 7

Distributed Gibbs Sampling and LDA Modelling for Large Scale...

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7th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference, SEEDA-CECNSM 2022

作者： Karras, Christos Karras, Aristeidis Tsolis, Dimitrios Giotopoulos, Konstantinos C. Sioutas, Spyros University of Patras Decentralized Systems Computing Group Computer Engineering and Informatics Department Greece University of Patras Department of History and Archaeology Greece University of Patras Department of Management Science and Technology Greece

ISBN: (数字)9798350398588

ISBN: (纸本)9798350398588

Big data management methods are paramount in the modern era as applications tend to create massive amounts of data that comes from various sources. Therefore, there is an urge to create adaptive, speedy and robust frameworks that can effectively handle massive datasets. Distributed environments such as Apache Spark are of note, as they can handle such data by creating clusters where a portion of the data is stored locally and then the results are returned with the use of Resilient Distributed Datasets (RDDs). In this paper a method for distributed marginal Gibbs sampling for widely used latent Dirichlet allocation (LDA) model is implemented on PySpark along with a Metropolis Hastings Random Walker. The Distributed LDA (DLDA) algorithm distributes a given dataset into P partitions and performs local LDA on each partition, for each document independently. Every nth iteration, local LDA models, that were trained on distinct partitions, are combined to assure the model ability to converge. Experimental results are promising as the proposed system demonstrates comparable performance in the final model quality to the sequential LDA, and achieves significant speedup time-optimizations when utilized with massive datasets. © 2022 IEEE.

关键词： Information management

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Unprecedented Smart Algorithm for Uninterrupted SDN Services During DDoS Attack

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Computers, Materials & Continua 2022年第1期70卷 875-894页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Rizaludin Kaspin Iram Haider Sana Nisar J.P.C.Rodrigues Bhawani Shankar Chowdhry Muhammad AslamUqaili Satya Prasad Majumder Danda B.Rawat Richard Etengu Rajkumar Buyya Faculty of Computing&Informatics Multimedia UniversityPersiaranMultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation Centre63000CyberjayaSelangorMalaysia Federal University of Piauí(UFPI) TeresinaPIBrazil Instituto de Telecomunica珲es 6201-001Covilh?Portugal National Center of Robotics and Automation-Condition Monitoring Systems Lab MUETJamshoroPakistan Department of Electrical and Electronic Engineering BUETDhaka1205Bangladesh Department of Electrical Engineering and Computer Science Data Science and Cybersecurity CenterHoward UniversityWashingtonDCUSA Cloud Computing and Distributed Systems(CLOUDS)Laboratory School of Computing and Information SystemsThe University of MelbourneMelbourneVIC 3053Australia

In the design and planning of next-generation Internet of Things(IoT),telecommunication,and satellite communication systems,controller placement is crucial in software-defined networking(SDN).The programmability of the SDN controller is sophisticated for the centralized control system of the entire ***,it creates a significant loophole for the manifestation of a distributed denial of service(DDoS)attack ***,recently a Distributed Reflected Denial of Service(DRDoS)attack,an unusual DDoS attack,has been ***,minimal deliberation has given to this forthcoming single point of SDN infrastructure failure ***,recently the high frequencies of DDoS attacks have increased *** this paper,a smart algorithm for planning SDN smart backup controllers under DDoS attack scenarios has *** proposed smart algorithm can recommend single or multiple smart backup controllers in the event of DDoS *** obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99%accuracy in placing the smart backup controller under DDoS attacks within 0.125 to 46508.7 s in SDN.

关键词： SDN smart algorithm RTZLK-DAASCP DDoS attack DRDoS

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