Salient object recognition is crucial in computer vision;it looks for prominent or salient items in movies or images. Convolutive neural networks, particularly generative adversarial networks, have overgrown and are n...
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Observational studies are widely used in Human-computer Interaction (HCI) research to evaluate usability and user experience with technologies. However, the act of observation may influence participant behaviour and p...
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ISBN:
(纸本)9798350376975;9798350376968
Observational studies are widely used in Human-computer Interaction (HCI) research to evaluate usability and user experience with technologies. However, the act of observation may influence participant behaviour and performance, threatening the validity of study findings. This paper investigates the impact of three observation types on participant outcomes in a simulated HCI study context. Participants completed Sudoku puzzles under baseline (no observation), human observation, sensor-based observation, and combined human/sensor conditions. Performance was assessed by puzzle completion rates. The mental workload was measured via NASA-TLX surveys, heart rate, galvanic skin response, and infrared thermal imaging. Results showed observations negatively impacted performance versus baseline, with human observers inducing the greatest distraction. Experienced participants were more influenced than novices. Task medium also affected engagement and observation reactivity. Findings demonstrate observations introduce bias in HCI research, emphasising careful consideration of observation methods to improve result validity.
This study investigates the efficacy of Latent Dirichlet Allocation (LDA) and PyLDAvis in analyzing feedback from final-year engineering students. By dissecting responses to strategically selected questions, we identi...
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ISBN:
(纸本)9783031734762;9783031734779
This study investigates the efficacy of Latent Dirichlet Allocation (LDA) and PyLDAvis in analyzing feedback from final-year engineering students. By dissecting responses to strategically selected questions, we identify key themes that include collaboration, innovation, and technical skills development. This research provides actionable insights for educators to refine teaching strategies and curriculum design to align with industry trends and student experiences. Our findings underscore the unique capabilities of LDA and PyLDAvis in capturing and visualizing students' nuanced perspectives, thereby offering a valuable tool for enhancing responsive engineering education.
In the contemporary business landscape, software has evolved into a strategic asset crucial for organizations seeking sustainable competitive advantage. The imperative of ensuring software quality becomes evident as l...
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In the contemporary business landscape, software has evolved into a strategic asset crucial for organizations seeking sustainable competitive advantage. The imperative of ensuring software quality becomes evident as low-quality software systems pose formidable challenges to organizational performance. This study delves into the profound impact of three key dimensions of information system quality on organizational performance—information quality (IQ), quality of service (QoS), and software quality (SQ). Anchored in the DeLone and McLean information system (IS) success model, a quantitative questionnaire was administered to 360 industry experts and academics. Rigorous data analysis, employing exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modeling (SEM), revealed significant positive effects of all three quality dimensions on organizational performance. Among these dimensions, software quality emerged as the most influential, showcasing substantial total effects, closely followed by information and service qualities. The study underscores the tangible value derived from strategic investments in enhancing software, information, and service quality. Elevating these facets manifests as a catalyst for improved organizational performance, empowering decision-makers with accurate and timely information while enhancing user satisfaction with the system. This research contributes significantly to the IS success literature by empirically validating the synergistic relationship between information quality, service quality, software quality, and organizational outcomes. The systematic analysis offered in this study goes beyond theoretical validation, providing actionable insights for managers. The findings guide the prioritization of quality initiatives and resource allocation, enabling organizations to maximize competitive advantage. As a future research direction, investigating moderator influences and exploring alternate qualit
The primary objective of a software project is to get a high-quality software product while reducing the cost and the time required to complete the project. To do that, the software needs to be tested before being rel...
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Recognizing multiple faces within a single frame or image presents a significant challenge in facial recognition tasks. This challenge demands robust algorithms capable of handling variations in facial position, unsta...
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In order to address the obstacles posed by the growing security issues of the Internet of Things to the development of big data, this paper conducts in-depth research on the defense of the most harmful DDoS attack. Th...
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The purpose of this article is to develop methods for representing scientific documentation in the form of graphs and their subsequent use. It analyzes the current state of quantitative and bibliometric methods for do...
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The identification of struggling students in a scalable manner in large computerscience courses continues to attract researchers' attention because of the high failure and dropout rates in such courses. In the la...
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ISBN:
(纸本)9798350376975;9798350376968
The identification of struggling students in a scalable manner in large computerscience courses continues to attract researchers' attention because of the high failure and dropout rates in such courses. In the last two decades, studies on this topic made significant progress in taking advantage of dynamic data sources and employing machine learning techniques to identify struggling students. However, the success of these studies was still limited due to reasons such as oversimplification and utilizing exclusive tools. These limitations make it difficult to replicate the findings of prior research on this topic. To address these issues and explore the extent to which we can replicate studies on this topic, this study replicated a recent study that explored identifying struggling students at the topic level using contextagnostic features. Our results demonstrate the potential of context-agnostic features in identifying struggling students with varied success rates. Our findings shed light on the robustness and feasibility of using machine learning techniques to identify struggling students in large computerscience courses. Finally, our discussion provides useful guidance on future studies and replications on this topic.
This paper introduces a lightweight, configurable interface, bus can be cascaded expansion of the airborne electromechanical interface unit. The device is applied to the electrical control system of small and medium-s...
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