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Big social data analysis for quality of MOOC courses: the moderating role of practical examples

Quality and Quantity 2025年 1-33页

作者： Nilashi, Mehrbakhsh Abumalloh, Rabab Ali Zibarzani, Masoumeh Centre for Business Informatics and Industrial Management (CBIIM) UCSI University No. 1 Jalan Menara Gading UCSI Heights Cheras Kuala Lumpur 56000 Malaysia Department of Computer Science and Engineering Qatar University Doha 2713 Qatar Department of Management Faculty of Social Sciences and Economics Alzahra University Tehran Iran

Big social data analysis has played an important role in understanding learners’ preferences in Massive Open Online Courses (MOOCs). This study investigates learners’ satisfaction with MOOCs using big social data analysis and a large-scale survey. The learners’ online reviews are analyzed using a hybrid method based on machine learning techniques and Partial Least Squares Structural Equation Modeling. We adopted a text mining approach, Latent Dirichlet Allocation (LDA), which is widely used in topic modeling. We utilized a large dataset of 6004 online reviews obtained from the learners of Udemy’s online courses. The results from the analysis identified nine topics as aspects of the quality of online courses, namely Course Accessibility, Course Cost, Course Material Quality, Course Organization, Course Resource Availability, Course Usefulness, Instructor Explanation, Instructor Knowledge, and Practical Examples in the Course. The results of the analysis were used to construct a research model, which was evaluated using a large-scale survey (N = 464). The results of the PLS-SEM confirmed the significant impacts of the proposed research factors, except for course organization, on learners’ satisfaction. The results also revealed that the practical examples in the course moderate the relationships between course usefulness, instructor explanation, instructor knowledge, and learners’ satisfaction. The findings of this research contribute to both the theoretical and methodological aspects of discovering and analyzing the influential factors for learners' satisfaction with MOOCs, thereby offering valuable insights for enhancing the overall quality of education in digital learning environments. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.

关键词： Big social data Education quality Learners' satisfaction Learners’ online reviews Online courses Soft computing

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A Web and Mobile Application to Identify the Availability of Drinking Water Information During a Water Crisis

A Web and Mobile Application to Identify the Availability of...

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2023 Intelligent Computing and Control for engineering and Business Systems, ICCEBS 2023

作者： Razeeth, Suhail Shihara, Fathima Pavithra, Kasuni Kaliyamoorthy, Maran Nawaz, Samsudeen Sabraz Kariyapper, R.K.A.R. South Eastern University of Sri Lanka Dept. of Information and Communication Technology Sri Lanka Uva Wellassa University of Sri Lanka Dept. of Computer Science and Informatics Sri Lanka Sri Sai Ram Institute of Management Studies Sri Sai Ram Engineering College India South Eastern University of Sri Lanka Department of Management and Information Technology Sri Lanka

ISBN: (纸本)9798350394580

Sri Lanka faces drinking water related issues often due to many reasons like weather changes, floods, droughts, and tsunamis, affecting the drinking water availability. In such instances, people find difficult to gather information regarding consumable drinking water availability. In order to facilitate the meeting of commercial water sellers and customers and to engage the general public and social services in addressing the drinking water problem, this study is focused on building both web and mobile applications. The web application was implemented with a selected set of functionalities such as social login, social sharing, geocoding, reverse geocoding, viewing, and filtering posts using Angular 6, *** web framework, and Leaflet. The mobile application was developed to direct the customers to the water availability location with a shortest path using the Dijkstra's algorithm. Case evaluation was conducted with the Rotaract Club members in Badulla and thinking aloud method was used to pick up the user's ideas while interacting with the system. It can be concluded that the created web and mobile applications would offer the public a clever way to draw attention to an issue with water availability, and the commercial water service providers are given a venue to market their services and locate potential customers. © 2023 IEEE.

关键词： crowdsourcing GIS mobile application water availability web application

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VeriActor: Dynamic Generation of Challenge-Response Questions for Enhanced Email Sender Verification

VeriActor: Dynamic Generation of Challenge-Response Question...

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IEEE Conference on Communications and Network Security (CNS)

作者： Basel Abdeen Ehab Al-Shaer Waseem Shadid Department of Computer Science School of Engineering & Computer Science University of Texas at Dallas Richardson TX USA S3 Department School of Computer Science Carnegie Mellon University Pittsburgh PA USA SIS Department College of Computing & Informatics University of North Carolina at Charlotte Charlotte NC USA

Challenge-response mechanisms have become widely adopted as a means of user verification. In this process, users are required to provide a set of challenge questions, with their actual answers serving as a means to authenticate the user’s identity. Despite the widespread usability of challenge-response as an authentication mechanism, it remains vulnerable to evasion by attackers who can employ social engineering tactics or gather information to guess or steal the necessary credentials. To address this inherent challenge, this paper presents a novel technique for dynamically generating challenge-response questions based on authentic historical interactions, such as daily communication via email or messaging platforms. We developed deep learning models, utilizing language models such as BERT, and employed semantic analysis to extract and validate highly usable challenge-response questions. These questions are designed to be easily answerable by legitimate users while presenting an unpredictable challenge to potential attackers. As an effective use case demonstration for our proposed system, we developed an email sender verification system capable of real-time identification of suspicious email senders. This system prompts the senders with carefully crafted challenge questions based on previous email exchanges with authentic users, enabling the identification of advanced spear-phishing emails that would otherwise remain undetected. We evaluated the effectiveness of our system, named VeriActor, through the use of annotated datasets and a user study. The experimental results exhibited promising outcomes, with a verification accuracy of 87.8% and a protection accuracy of 83.33%.

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Prioritizing TWAS Genetic Biomarkers for Melanoma Metastasis via Gene Expression Profiling*

Prioritizing TWAS Genetic Biomarkers for Melanoma Metastasis...

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Data Science and engineering in Healthcare, Medicine and Biology, IEEE EMBS Special Topic Conference on

作者： Mohamed N. Saad Belal Medhat Mohamed Hamed Biomedical Engineering Department Faculty of Engineering Minia University Egypt Institute for Biostatistics and Informatics in Medicine and Ageing Research (IBIMA) Rostock University Medical Center Rostock Germany Computer Science and Engineering Department Faculty of Media Engineering and Technology German University in Cairo Egypt Faculty of Media Engineering and Technology German University in Cairo Egypt

The development of novel therapeutic approaches that target gene alterations in melanoma cells remains an area of active research. This study prioritized ten genes out of 76 genes - associated with melanoma through a transcriptome-wide association study (TWAS). We investigated the potential of the identified ten genes in prognosis of metastasis in melanoma *** Relevance: Our findings have clinical implications for melanoma treatment strategies. Targeted therapies that specifically address the dysregulation of our 10 genes may hold promise in preventing or slowing melanoma metastasis.

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Teachers' perceptions of learning design recommendations 19

Teachers' perceptions of learning design recommendations

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19th International Conference on Information Technology Based Higher Education and Training, ITHET 2021

作者： Zalavra, Eleni Papanikolaou, Kyparisia Dimitriadis, Yannis Sgouropoulou, Cleo University Of West Attica Department Of Informatics And Computer Engineering Athens Greece School Of Technological And Pedagogical Education Department Of Education Athens Greece Universidad De Valladolid Department Of Signal Theory Communications And Telematics Engineering Valladolid Spain

ISBN: (纸本)9781728188836

The uptake of personalised approaches in education apart from students' learning needs should also involve teachers' needs. This paper addresses the understudied topic of integrating a Recommender System (RS) in a Learning Design (LD) environment as a means to personalise the support offered to teachers for designing learning. We present a study in a teacher education context, collecting teachers' perceptions of learning design recommendations to explore the recommendation form and method that teachers value while designing. Our findings point out teachers' appreciation of an LD environment integrating a macro form of recommending entire learning designs alike learning objects in online educational repositories. They also favour complementing the macro with a micro form that supports the LD process by recommending specific elements within a learning design. Our study indicates the need for a hybrid recommendation method appropriately filtering a learning design's context and evaluation. Also, this research justifies the need to integrate an RS in an LD environment, reporting as teachers' anticipated benefits (i) stimulating the initiation of designing for learning, (ii) advancing their LD practice by conceiving new design ideas, and (iii) providing a means of developing their LD experience effectively. The anticipated challenges point out the requirement of an RS that provides appropriate recommendations and the high need to cultivate teachers' LD knowledge and mindset towards employing LD environments and RSs effectively. © 2021 IEEE.

关键词： Recommender systems

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Integrated Sensing, Communication, and Computing for Cost-effective Multimodal Federated Perception

arXiv

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arXiv 2023年

作者： Chen, Ning Fan, Xuwei Huang, Bangzhen Zhao, Yifeng Huang, Lianfen Cheng, Zhipeng Du, Xiaojiang Guizani, Mohsen Department of Information and Communication Engineering School of Informatics Xiamen University China School of Future Science and Engineering Soochow University China Department of Electrical and Computer Engineering Stevens Institute of Technology United States Mohamed Bin Zayed University of Artificial Intelligence United Arab Emirates

Federated learning (FL) is a classic paradigm of 6G edge intelligence (EI), which alleviates privacy leaks and high communication pressure caused by traditional centralized data processing in the artificial intelligence of things (AIoT). The implementation of multimodal federated perception (MFP) services involves three subprocesses, including sensing-based multimodal data generation, communication-based model transmission, and computing-based model training, ultimately relying on available underlying multi-domain physical resources such as time, frequency, and computing power. How to reasonably coordinate the multi-domain resources scheduling among sensing, communication, and computing, therefore, is crucial to the MFP networks. To address the above issues, this paper investigates service-oriented resource management with integrated sensing, communication, and computing (ISCC). With the incentive mechanism of the MFP service market, the resources management problem is redefined as a social welfare maximization problem, where the idea of "expanding resources" and "reducing costs" is used to improve learning performance gain and reduce resource costs. Experimental results demonstrate the effectiveness and robustness of the proposed resource scheduling mechanisms. Copyright © 2023, The Authors. All rights reserved.

关键词： Artificial intelligence

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Layer Decomposition Learning Based on Discriminative Feature Group Split with Bottom-Up Intergroup Feature Fusion for Single Image Deraining

SSRN

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SSRN 2023年

作者： Jang, Yunseon Le, Duc-Tai Son, Chang-Hwan Choo, Hyunseung Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of College of Computing and Informatics Sungkyunkwan University Suwon16419 Korea Republic of Department of Software Science Engineering Kunsan National University Gunsan54150 Korea Republic of

As rain streaks hinder feature extraction based on image gradients, the performance of computer vision algorithms such as pedestrian detection and lane detection can be negatively affected. Image deraining is an essential pre-processing step for the algorithms to work reliably in adverse weather conditions. However, detail and texture information in the object and background areas can be lost during deraining due to the structural similarity between rain streaks and object details. To address this, we present a novel layer decomposition learning network (LDLNet) to separate rain streak and object detail layers of the image and remove rain streaks effectively. The proposed LDLNet consists of two parts: discriminative group feature split and group feature merging. The former arranges sparse residual attention modules in series to extract spatial contextual features of rain images following a novel bottom-up inter-group feature fusion approach. The group feature merging part aggregates all the group features with different image appearances into a residual image. Experimental results reveal that the proposed approach makes group features more discriminative, represented by different image appearances including rain streaks and object details. LDLNet achieves superior rain removal and detail preservation in both synthetic datasets and real-world rainy images compared to the state-of-the-art rain removal models. © 2023, The Authors. All rights reserved.

关键词： Rain

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Channel Estimation for UAV-based mmWave Massive MIMO Communications with Beam Squint

Channel Estimation for UAV-based mmWave Massive MIMO Communi...

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European Signal Processing Conference (EUSIPCO)

作者： Evangelos Vlachos Christos Mavrokefalidis Kostas Berberidis Industrial Systems Institute ATHENA Research Center Patras Greece Dept. of Computer Engineering and Informatics University of Patras Patras Greece

ISBN: (数字)9789082797091

ISBN: (纸本)9781665467995

The incorporation of UAVs in 5G and envisioned 6G wireless communication systems is considered for many applications and use-cases, either as part of the infrastructure, providing coverage and connectivity (e.g., during unforeseen and rare events) or as an end-user, e.g., in remote sensing, real-time monitoring and surveillance, to name a few. From the perspective of the physical layer and the involved signal processing algorithms, the transmission environment between the UAVs and the ground communication devices, along with the utilisation of massive MIMO in the mmWave spectrum, require new channel estimation algorithms to support the required physical layer functionality. In this paper, the problem of channel estimation in a multi-user, UAV-based mmWave massive MIMO system is considered in view of the so-called beam squint effect as well as the time-varying nature of the involved channels due to mobility. The proposed approach takes advantage of the low-rank channel matrix and solves a minimisation problem via ADMM, leading to a low complexity, iterative algorithm. The performance of the proposed algorithm is evaluated via simulations and its efficacy is demonstrated over other algorithms from the relevant literature.

关键词： Wireless communication Upper bound Surveillance Channel estimation Signal processing algorithms Massive MIMO Physical layer

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Simultaneous Multi-User MIMO Communications and Multi-Target Tracking with Full Duplex Radios

arXiv

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arXiv 2022年

作者： Islam, Md Atiqul Alexandropoulos, George C. Smida, Besma Department of Electrical and Computer Engineering University of Illinois Chicago United States Department of Informatics and Telecommunications National and Kapodistrian University of Athens Greece

In this paper, we present an Integrated Sensing and Communications (ISAC) system enabled by in-band Full Duplex (FD) radios, where a massive Multiple-Input Multiple-Output (MIMO) base station equipped with hybrid Analog and Digital (A/D) beamformers is communicating with multiple DownLink (DL) users, and simultaneously estimates via the same signaling waveforms the Direction of Arrival (DoA) as well as the range of radar targets randomly distributed within its coverage area. Capitalizing on a recent reduced-complexity FD hybrid A/D beamforming architecture, we devise a joint radar target tracking and DL data transmission protocol. An optimization framework for the joint design of the massive A/D beamformers and the Self-Interference (SI) cancellation unit, with the dual objective of maximizing the radar tracking accuracy and DL communication performance, is presented. Our simulation results at millimeter wave frequencies using 5G NR wideband waveforms, showcase the accuracy of the radar target tracking performance of the proposed system, which simultaneously offers increased sum rate compared with benchmark schemes. © 2022, CC BY.

关键词： Millimeter waves

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MGC: Multiple-Gray-Code for 3D NAND Flash based High-Density SSDs

MGC: Multiple-Gray-Code for 3D NAND Flash based High-Density...

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IEEE Symposium on High-Performance computer Architecture

作者： Yina Lv Liang Shi Qiao Li Congming Gao Yunpeng Song Longfei Luo Youtao Zhang School of Computer Science and Technology East China Normal University Shanghai China Ministry of Education Software/Hardware Co-Design Engineering Research Center School of Informatics Xiamen University Xiamen China Computer Science Department University of Pittsburgh Pittsburgh USA

QLC (4-bit-per-cell) and more-bit-per-cell 3D NAND flash memories are increasingly adopted in large storage systems. While achieving significant cost reduction, these memories face degraded performance and reliability issues. The industry has adopted two-step programming (TSP), rather than one-step programming, to perform fine-granularity program control and choose gray-code encoding, as well as LDPC (Low-Density Parity-Check Code) for error correction. Different flash manufacturers often integrate different gray-codes in their products, which exhibit different performance and reliability characteristics. Unfortunately, a fixed gray-code encoding design lacks the ability to meet the dynamic read and program performance requirements at both application and device *** this paper, we propose MGC, a multiple-gray-code encoding strategy, that adaptively chooses the best gray-code to meet the optimization goals at runtime. In particular, MGC first extracts the performance and reliability requirements based on application-level access patterns and detects the reliability degree of SSD. It then determines the appropriate gray-code to encode the data, either from host/user application or due to garbage collection, before writing the pages to the flash memory. MGC is integrated in FTL (flash translation layer) and enhances the flash controller to enable runtime gray-code arbitration. We evaluate the proposed MGC scheme. The results show that MGC achieves better performance and lifetime guarantee compared with state-of-the-arts and introduces little overhead.

关键词： Performance evaluation Three-dimensional displays Runtime Programming Writing Encoding Parity check codes

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