In today's world almost all organizations heavily depend on Web-based systems or web applications for their day-to-day operations. In this paper, we will present zoned role-based (ZRB) approach to the design and i...
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ISBN:
(纸本)9783031752001;9783031752018
In today's world almost all organizations heavily depend on Web-based systems or web applications for their day-to-day operations. In this paper, we will present zoned role-based (ZRB) approach to the design and implementation of integrated web-based systems for organizations and enterprises. In contrast to Role-Based Access Control (RBAC), well-known in computer security, this approach can be used throughout the entire life cycle of a web-based system, and can make the design, implementation, deployment and maintenance of integrated web system more efficient and effective for all organizations and enterprises. In this approach, areas of business, or divisions, departments or designated groups of employees for specific missions are called zones, and for each zone a set of roles are defined;for each role, some web apps, each of which consists of a set of operations, are designed and implemented for users in their respective roles to conduct their business in each associated zone;and control of user access to each operation can then be done explicitly by associating each operation with roles by inference based on the relationships between roles. Within such a zoned role-based integrated system, once a user has roles assigned in each zone he or she is affiliated, he will be able to access, precisely, all the apps and operations needed to fulfill his or her role or roles in respective zone, with only one authentication. Such integration is rather important and convenient especially when users may be affiliated with multiple zones or play multiple roles.
Proving properties about robotic systems with humans-in-the-loop relies on assumptions about human behaviour. Existing technologies require expertise not reasonably expected from psychologists and human-factors engine...
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Throughout the years, automobile companies achieved outstanding progress in manufacturing safe, reliable, and affordable vehicles. Many companies and manufacturers are developing autonomous cars for the future years. ...
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This study presents a novel translational method for suicide prevention research, employing customizable virtual reality (VR) simulations that mimic real-life situations. We aim to validate the usability of these VR s...
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The escalating complexity of modern software systems has rendered the management of requirements increasingly arduous, often plagued by redundancy, inconsistency, and inefficiency. Traditional manual methods prove ina...
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The escalating complexity of modern software systems has rendered the management of requirements increasingly arduous, often plagued by redundancy, inconsistency, and inefficiency. Traditional manual methods prove inadequate for addressing the intricacies of dynamic, large-scale datasets. In response, this research introduces SQUIRE (Semantic Quick Requirements engineering), a cutting-edge automated framework leveraging advanced Natural Language Processing (NLP) techniques, specifically Sentence-BERT (SBERT) embeddings and hierarchical clustering, to semantically organize requirements into coherent functional clusters. SQUIRE is meticulously designed to enhance modularity, mitigate redundancy, and strengthen traceability within requirements engineering processes. Its efficacy is rigorously validated using real-world datasets from diverse domains, including attendance management, e-commerce systems, and school operations. Empirical evaluations reveal that SQUIRE outperforms conventional clustering methods, demonstrating superior intracluster cohesion and inter-cluster separation, while significantly reducing manual intervention. This research establishes SQUIRE as a scalable and domain-agnostic solution, effectively addressing the evolving complexities of contemporary software development. By streamlining requirements management and enabling software teams to focus on strategic initiatives, SQUIRE advances the state of NLP-driven methodologies in Requirements engineering, offering a robust foundation for future innovations.
The detection of road defects is crucial for ensuring vehicular safety and facilitating the prompt repair of roadway imperfections. Existing YOLOv8-based models face the following issues: extraction capabilities and i...
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In the transition to the"digital" era, many large enterprises have adopted enterprise architecture methodologies for top-level design, business architecture as the core content of enterprise architecture, it...
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To address the problem of inaccurate prediction of slab quality in continuous casting, an algorithm based on particle swarm optimisation and differential evolution is proposed. The algorithm combines BP neural network...
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Universities are increasingly integrating real-world projects into softwareengineering curricula to prepare students for careers involving complex concepts like Microservices Architecture (MSA). Students frequently s...
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Anxiety disorders significantly impact individuals' quality of life and are traditionally assessed using subjective methods, which often lack accuracy. Recent advancements have enabled the use of physiological sig...
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