Cryptographic protocols are used to relax the ever-developing quantity of linked gadgets that make up the net of things (IoT). Those cryptographic protocols have been designed to make certain that IoT tool traffic sta...
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The creation of software documentation is widely recognized as a critical and demanding undertaking within the rapidly changing realm of software development. This study introduces a novel method for generating softwa...
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The availability of large-scale datasets, advanced architectures, and powerful computational resources have led to effective code models that automate diverse softwareengineering activities. The datasets usually cons...
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Refactoring is an important activity in softwareengineering. Whether it takes place during the initial design of a system, or during maintenance, it is a powerful tool that can be used in order to keep code working a...
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ISBN:
(纸本)9798350351194;9798350351187
Refactoring is an important activity in softwareengineering. Whether it takes place during the initial design of a system, or during maintenance, it is a powerful tool that can be used in order to keep code working and maintainable. Refactoring is used to eliminate Code Smells, in other words poorly designed code, while maintaining the functionality of the code. Keeping code understandable and well designed is critical to the success of any software project. In this paper, we present a literature review of recent advances and trends in refactoring and examine the practice of refactoring by looking at its key tenets.
This paper presents the evolving role of artificial intelligence (AI) in improving internal control and management processes. AI-driven technologies, including Generative Adversarial Networks (GANs) and ontologies, in...
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AI-Powered Edge Computing is accelerating the integration of the cyber world with the ever-growing list of new physical IoT devices and will fundamentally change and empower the way humans interact with the world. In ...
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ISBN:
(纸本)9798350376975;9798350376968
AI-Powered Edge Computing is accelerating the integration of the cyber world with the ever-growing list of new physical IoT devices and will fundamentally change and empower the way humans interact with the world. In this paper, we prototyped and analyzed three edge computing architectures for running SmartFall, a real-time fall detection application that uses accelerometer data from the watch, to compare the trade-off in relationship to battery consumption, potential data loss, machine learning model's prediction accuracy, and latency in model inferencing. Our experiments show that running the machine learning prediction on the server using the TensorFlow native model format has achieved the best model accuracy without draining the battery power of the smartwatches. However, the optimal selection of the software architecture depends on the intended deployment environment, projected user numbers, users' privacy concerns, and network stability.
The rapid growth of Information Technology (IT) as well as computerscience becomes an important evolution in marketable painting applications. The systematic authentication of paintings embraces the implication into ...
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With an association of principles created to improve collaboration amidst the operations and development teams, DevOps offers few agile practices. The paper's main goal is to conduct research about how the practic...
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As one of the research hotspots in natural language processing, text sentiment analysis has received extensive attention in recent years. Aiming at the problem that the unidirectional TCN in BERT-TCN cannot fully extr...
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ISBN:
(纸本)9798331539894;9798331539887
As one of the research hotspots in natural language processing, text sentiment analysis has received extensive attention in recent years. Aiming at the problem that the unidirectional TCN in BERT-TCN cannot fully extract the contextual semantic features of the word vectors of text, a text sentiment analysis model based on BERT and Bidirectional Temporal Convolutional Network (BiTCN) is proposed. The model first uses the BERT model to obtain the word vector representations of text, and then the word vectors are input into BiTCN to extract contextual semantic features from the forward and backward directions of the word vectors. Finally, the contextual semantic features are input into a softmax classifier for sentiment classification. Experiments show that compared with the BERT-TCN model, the BERT-BiTCN model has improved accuracy, precision, recall, and F1 value.
In the era of rapid Internet expansion, the data generated has witnessed exponential growth, concealing valuable information within. Consequently, the field of data mining has flourished, finding extensive application...
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ISBN:
(纸本)9798350381641
In the era of rapid Internet expansion, the data generated has witnessed exponential growth, concealing valuable information within. Consequently, the field of data mining has flourished, finding extensive applications across diverse industries. However, its full potential remains untapped in the realm of higher education. In light of the "Big Data Analysis and Mining" course, this paper makes a detailed investigation on the problems existing in practical teaching. To address these problems, we propose an intelligent practical teaching platform based on data mining technology. This platform harnesses data mining and cloud storage techniques, adopting a blended approach that seamlessly integrates online and offline teaching methods. It offers a comprehensive solution for practical teaching, with the primary objective of enhancing the effectiveness of practical teaching and augmenting students' hands-on capabilities. Finally, we present the outcomes and applications of this platform since its inception over one year ago, showcasing its tangible impact on higher education.
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