Class libraries play a key role in object-oriented paradigm. They provide, by and large, the most commonly reused components in object-oriented environments. In this paper, we use a number of metrics to study reusabil...
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In order to select a small subset of informative genes from gene expression data for cancer classification, recently, many researchers are analyzing gene expression data using various computational intelligence method...
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The research has shown that process-oriented programming languages provide a suitable means for developing concurrent systems. However, in the development of a concurrent system, there is a challenge to manage consist...
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The research has shown that process-oriented programming languages provide a suitable means for developing concurrent systems. However, in the development of a concurrent system, there is a challenge to manage consistency between design and implementation. To deal with such a challenge, we propose a new formal verification methodology and illustrate it by a running example. In this methodology, a concurrent system is designed using a process algebra, namely communicating sequential processes, and implemented in a process-oriented programming language, namely Erasmus. The consistency between the design and the implementation of such a concurrent system is verified formally using category theory.
In spite of its importance to software quality, software testing is often considered the "poor man" of softwareengineering processes, left to the end of many projects, and frequently omitted altogether. Com...
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Wireless Sensor Networks (WSNs) are exposed to many security attacks, and it can be easily compromised. One of the main reasons for these vulnerabilities is the deployment nature, where sensor nodes are deployed witho...
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This paper presents a framework for parallel intelligent education that involves physical and virtual learning for a personalized learning *** especially focus on Chat Generative Pre-trained Transformer(ChatGPT)owing ...
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This paper presents a framework for parallel intelligent education that involves physical and virtual learning for a personalized learning *** especially focus on Chat Generative Pre-trained Transformer(ChatGPT)owing to its considerable potential to supplement regular class *** address the strengths and weaknesses of learning with ***,we discuss the challenges and solutions of the proposed parallel intelligent education with ChatGPT.
Different types of heterogeneous multiple service robots are working in the same environment to help humans in many ways in a smart house. These service robots have different capabilities based on the different contro...
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Worldwide cotton is the most profitable cash *** year the production of this crop suffers because of several *** an early stage,computerized methods are used for disease detection that may reduce the loss in the produ...
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Worldwide cotton is the most profitable cash *** year the production of this crop suffers because of several *** an early stage,computerized methods are used for disease detection that may reduce the loss in the production of *** several methods are proposed for the detection of cotton diseases,however,still there are limitations because of low-quality images,size,shape,variations in orientation,and complex *** to these factors,there is a need for novel methods for features extraction/selection for the accurate cotton disease *** in this research,an optimized features fusion-based model is proposed,in which two pre-trained architectures called EfficientNet-b0 and Inception-v3 are utilized to extract features,each model extracts the feature vector of length N×*** that,the extracted features are serially concatenated having a feature vector lengthN×*** prominent features are selected usingEmperor PenguinOptimizer(EPO)*** method is evaluated on two publically available datasets,such as Kaggle cotton disease dataset-I,and Kaggle *** EPO method returns the feature vector of length 1×755,and 1×824 using dataset-I,and dataset-II,*** classification is performed using 5,7,and 10 folds *** Quadratic Discriminant Analysis(QDA)classifier provides an accuracy of 98.9%on 5 fold,98.96%on 7 fold,and 99.07%on 10 fold using Kaggle cotton disease dataset-I while the Ensemble Subspace K Nearest Neighbor(KNN)provides 99.16%on 5 fold,98.99%on 7 fold,and 99.27%on 10 fold using Kaggle cotton-leaf-infection dataset-II.
Automatic leaf recognition algorithm is widely used in plant taxonomy, horticulture teaching, traditional Chinese medicine research and plant protection, which is one of the research hotspots in information science. D...
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Optimization problems widely arise in various science and engineering fields and can be computationally expensive in many real-world applications. Evaluation of the fitness function to assess a candidate solution is t...
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