Electronic information services are robust platforms that impact daily life and facilitate new research. Increasing software modularity and reusability saves time and money. Numerous designs and programming are challenging when developing a complex educational information system. This article proposes a new paradigm of multi-dimensional information layers, aspects, functional data, and composition rules in software development to create practical educational information platforms. The proposed approach uses aspect orientation throughout educational information's software development life cycle, from planning to implementation and evaluation. Finally, the authors demonstrate and evaluate the design model's modularity and adaptation through fine-granularity design and class reuse. The result reduces invasive changes, promotes modularity and reuse, and eliminates duplication in component-based software design.
End user involvement is crucial in improving software development processes. Hence, nowadays user interface (UI) and user experience (UX) are particularly concerned with end user interactions in many software designs as most methodologies have inconsistencies between design and implementation. Besides, it is relatively difficult to make changes in complex software and personal finance application is one of the more complex software to design, develop, and adapt. This paper proposes the development of a mobile personal finance application using informative multidimensional layering. We have separated functional data cutting across the relationships of three categories and datasets showing operational semantics of dimensions, and combined layers of three-dimensional information including aspect elements through components. This study is concerned with the corresponsive composition of end user features using visual interfaces. It is illustrated in a Three-layer User Interface Composition Model to transfer and compose layers, functional data, aspect elements, and components to Graphical User Interfaces (GUIs). Therefore, an integrated view of the software system would make the design and implementation consistent to support our framework in a more straightforward manner.
IoT technology is widely applied to many areas, including agriculture. The smart farming design and implementation deal with farm operations and management effectively. The aim of this research enables supporting a vermiculture smart farming kit based on IoT technology. The layered architecture design is represented to support the deployment of sensors, networks, monitoring systems, data collections, and watering decision system. Information flow diagram is proposed to improve how the web application of our smart kit system can implement based on the system requirements. The evaluations of the smart kit are investigated to deal with consistency and effectiveness comparing between a traditional and the smart kit of earthworm vermicomposting. The gaps of farmers' needs can be satisfied to advance the better solutions of the smart farming kit.
Biometric recognition may be used in conjunction with human authentication on a smartphone to improve accuracy, reliability, and simplicity, and to aid in fraud prevention and user authentication. While single biometric authentication addresses environmental degradation and sensor noise limitations, and the single point of failure scenario in biometric systems can result in more robust biometric systems, multimodal biometric authentication can improve the accuracy of identification and recognition. The purpose of this research is to propose a facial and speech authentication system that is cloud-based and supports a web-based examination approach. The system enables students' biometrics to be registered, students to be recognized, and student recognition results to be reported. The confusion matrix is used to compare the results of positive and negative detection in various ways, including accuracy score, precision value, and recall value. Adaptive multimodal biometric authentication should be designed and evaluated for further research using the optimal weights for each biometric.
Traditional identity verification of students based on the human proctoring approach can cause a scam identity verification and ineffective processing time, particularly among vast groups of students. Most student identification cards are outdated personal information. Several biometric recognition approaches have been proposed and can be adopted to strengthen students' identity verification. Most educational adoption technology struggles with evaluation and validation techniques to ensure that biometric recognition systems are unquestionably suitable for utilization and implementation to fulfill student identity verification. This study presents the internet of things to develop flexible biometric recognition systems and an approach to assess the quality of biometric systems for educational use by investigating the effectiveness of identity verification of various biometric recognition technologies compared to the traditional verification method. The unimodal, multimodal, and semi-multimodal biometric technologies were tested using the developed internet of things-base biometric recognition systems examined by applying the proposed quality metrics of scoring factors based on accuracy, error rate, processing time, and cost. Hundreds of undergraduate exam takers were a sample group. Key findings indicate that the designed and presented systems suitably attain identity verification of exam students using a unimodal biometric. A unimodal face biometric system promises excellent support. A unimodal fingerprint biometric system assures the second excellent aid for student identity verification. However, multimodal and semi-multimodal biometric systems provide better accuracy with few handling times and higher costs. This study contributes significantly to the knowledge of utilizing biometric recognition for identity verification in smart educational use.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.