Obtaining high-quality remote sensing images is crucial in generating a three-dimensional terrain for flight simulators. However, due to the presence of haze and other impact factors, collected remote sensing images u...
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With the emergence of AI for good, there has been an increasing interest in building computer vision data-driven deep learning inclusive AI solutions. Sign language Recognition (SLR) has gained attention recently. It ...
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As computer programs run in the highly complex systems of hierarchical software and hardware, it is difficult to be visually observed, the problem of function parameter passing has become a pain point for teachers and...
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ISBN:
(数字)9798331540883
ISBN:
(纸本)9798331540890
As computer programs run in the highly complex systems of hierarchical software and hardware, it is difficult to be visually observed, the problem of function parameter passing has become a pain point for teachers and students. There are four ways to pass parameters, and no programming language can support all the four ways. To meet the needs of different learners, an online virtual experiment platform of parameter passing is developed, where the experiments of four methods parameter passing can be carried out. In addition, the experiments could be done by a mobile phone, which the space-time limit of learning is broken. In virtual simulation module, the dynamic changes of computer memory could be simulated and displayed when the function pseudo-code is running, so that the parameter passing process becomes intuitive, and it is easy for students to understand the working mechanism of function parameter passing. Finally, the teaching goal is achieved by the joint action of the other modules, such as basic training, extended improvement and test enhancement, etc. The results of practice show that the enthusiasm and initiative of students are improved, and it has obvious results in assisting students to master the knowledge of function parameter passing.
software architectures are fundamental to the development, evolution, and quality of software-intensive systems. Architectures rarely exist in isolation, but instead adhere to overarching structures such as architectu...
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ISBN:
(数字)9798331533366
ISBN:
(纸本)9798331533373
software architectures are fundamental to the development, evolution, and quality of software-intensive systems. Architectures rarely exist in isolation, but instead adhere to overarching structures such as architectural patterns and styles, frameworks, software product line architectures, and reference architectures. To fully leverage the benefits of these structures, conformance between them is essential, enhancing interoperability, reducing costs through reusability, mitigating project risks, and facilitating the adoption of best practices. In our previous work, we introduced the concept of continuous conformance and focused on detecting architectural violations using a model-driven engineering approach. In this paper, we extend our previous work by proposing a large language model-based recommender system into the model-driven tool to suggest resolutions for architectural violations. Leveraging large language models, we reduce the accidental complexity of model-driven techniques by combining the reasoning capabilities of large language models with the formalization of architectures as (meta)models. We evaluate the success rate using two large language models and architectures from the IoT domain, including one reference architecture and four software architectures that we manually mutate in 16 faulty architectures. The results demonstrate the system's effectiveness in providing intelligent, context-aware recommendations for restoring architectural conformance.
In this paper, the analysis and modeling of an integrated system of a small wind power plant without a transformer based on Permanent magnet synchronous (PMSG) with switched boost inverter (SBI) is proposed. Then theo...
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ISBN:
(数字)9798331533946
ISBN:
(纸本)9798331533953
In this paper, the analysis and modeling of an integrated system of a small wind power plant without a transformer based on Permanent magnet synchronous (PMSG) with switched boost inverter (SBI) is proposed. Then theoretical calculations related to SBI performance in different operating modes are presented. Finally, a small wind turbine system based on PMSG is modeled for off-grid load, and in order to show the performance of the system and confirm the correctness of the theoretical calculations, the presented configuration is simulated in PSCAD/EMTDC software and the results are presented in detail.
The safety of ship structures has always been a focal point in the field of marine engineering, and the monitoring and assessment of crack propagation are crucial for preventing structural failure. With the rapid deve...
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ISBN:
(数字)9798350389579
ISBN:
(纸本)9798350389586
The safety of ship structures has always been a focal point in the field of marine engineering, and the monitoring and assessment of crack propagation are crucial for preventing structural failure. With the rapid development of materials science and computer technology, simulation analysis has become an effective means of studying crack behavior. By applying advanced finite element software such as ABAQUS and combining it with the principles of fracture mechanics, accurate simulations of crack propagation can be achieved, revealing its development patterns. In recent years, the emergence of new methods such as Virtual Crack Closure Technique (VCCT), singularity element method, and cohesive zone models has provided new solutions for crack analysis in complex structures. These methods not only enhance the understanding of material behavior but also provide a theoretical basis for ship design, elevating safety to a new level. Overall, the simulation and analysis of crack propagation based on ABAQUS offer strong data support for the safety assessment of ship structures.
The dynamic nature of web and softwaresystems requires modularization methods that can adapt to frequent updates and diverse structures while maintaining scalability and efficiency. In this research, we propose a RoB...
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ISBN:
(数字)9798331508913
ISBN:
(纸本)9798331508920
The dynamic nature of web and softwaresystems requires modularization methods that can adapt to frequent updates and diverse structures while maintaining scalability and efficiency. In this research, we propose a RoBERTa-based Module Detection framework that leverages transformer models to classify and manage software modules using the semantic content of source code, comments, and related textual data. Unlike traditional dependency graph-based methods, which face computational bottlenecks, our content-driven approach offers a streamlined, scalable solution for softwaresystems. This framework represents a significant step in automating modularization, eliminating the need for extensive documentation, and leveraging semantic content to manage complexity in modern software development. Experimental results demonstrate the method's efficiency: for Mozilla Version 3.7, the model achieved 92.55 % accuracy and 92.47 % F1-score after four epochs, while for Version 134.0, it reached 98.13% accuracy and 98.02 % F1-score with rapid convergence and minimal training loss. Additionally, the model achieved an outstanding accuracy and F1-score of 99.70 % for Chromium.
This research paper describes the design and analysis of a microstrip patch antenna (MPA) and 1 ×2 array configuration operating at 2.4 GHz using computer simulation technology (CST). These antennas are widely us...
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Water leakage in distribution networks is a significant challenge, especially in regions with limited infrastructure like Huancayo, Peru, where losses account for 32.82% of the distributed volume. This study introduce...
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ISBN:
(数字)9798331522216
ISBN:
(纸本)9798331522223
Water leakage in distribution networks is a significant challenge, especially in regions with limited infrastructure like Huancayo, Peru, where losses account for 32.82% of the distributed volume. This study introduces a machine learning-based approach to detect leaks using four algorithms: Autoencoder LSTM, Isolation Forest, One-Class SVM, and K-Nearest Neighbors (KNN). The methodology involved preprocessing historical consumption data (2018–2024) into 12-month temporal sequences per client and evaluating the models based on F1 Score, Precision, and Mean Absolute Error (MAE). Among the algorithms, the Autoencoder LSTM demonstrated superior performance with the highest precision (0.89) and the lowest MAE (0.00402). Its robustness in high-variability contexts enables early and reliable leak detection, providing a cost-effective solution for optimizing water management in resource-constrained environments.
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