Remote sensing images are the product of information obtained by various sensors, and the higher the resolution of the image, the more information it contains. Therefore, improving the resolution of the remote sensing...
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software testing is a critical phase in software development to ensure the reliability and quality of software systems. With the increasing complexity of software applications, the number of test cases can grow signif...
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Addressing the need for improved GPS accuracy, especially for low-dynamic users, this study introduces a GPS augmentation system employing Low Earth Orbit (LEO) satellites. We detail the principles of satellite naviga...
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Visualisations drive all aspects of the Machine Learning (ML) Development Cycle but remain a vastly untapped resource by the research community. ML testing is a highly interactive and cognitive process which demands a...
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Visualisations drive all aspects of the Machine Learning (ML) Development Cycle but remain a vastly untapped resource by the research community. ML testing is a highly interactive and cognitive process which demands a...
Visualisations drive all aspects of the Machine Learning (ML) Development Cycle but remain a vastly untapped resource by the research community. ML testing is a highly interactive and cognitive process which demands a human-in-the-loop approach. Besides writing tests for the code base, bulk of the evaluation requires application of domain expertise to generate and interpret visualisations. To gain a deeper insight into the process of testing ML systems, we propose to study visualisations of ML pipelines by mining Jupyter notebooks. We propose a two prong approach in conducting the analysis. First, gather general insights and trends using a qualitative study of a smaller sample of notebooks. And then use the knowledge gained from the qualitative study to design an empirical study using a larger sample of notebooks. Computational notebooks provide a rich source of information in three formats—text, code and images. We hope to utilise existing work in image analysis and Natural Language Processing for text and code, to analyse the information present in notebooks. We hope to gain a new perspective into program comprehension and debugging in the context of ML testing.
In the era of digital transformation, the sheer volume of network security data poses significant challenges in terms of organization and retrieval. Traditional search engines fail to provide contextual answers, neces...
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software plays an increasingly important role in assuring effective and efficient operation of industrial automation engineering systems. We plan an interactive full-day workshop to discuss softwareengineering method...
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Water and fertilizer coupling is a high-efficiency technology for the development of facility ***,the interaction effect of nitrogen(N)and air carbon dioxide(CO_(2))on hydroponic purple cabbage,especially on its leaf ...
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Water and fertilizer coupling is a high-efficiency technology for the development of facility ***,the interaction effect of nitrogen(N)and air carbon dioxide(CO_(2))on hydroponic purple cabbage,especially on its leaf anthocyanins under hydroponic solution systems,remains *** this study,six treatments were set as C0N0,C0N2,C0N4,C1N0,C1N2 and C1N4,with N0,N2 and N4 being 0.0 g/L,0.2 g/L and 0.4 g/L exogenous urea-N to hydroponic solution dilution,respectively.C0 and C1 were set as with and without CO_(2)fertilizer(i.e.,800 g CO_(2)agent added one week after transplanting and 600 g CO_(2)agent added when the plant reached 15 cm in height),*** experiments were conducted to investigate the interaction effect of N and air CO_(2)(N×CO_(2))on the growth,photosynthesis,yield and anthocyanin content of hydroponic purple cabbage Brassica campestris *** results showed N×CO_(2)extremely significantly influenced plant height(H),net photosynthetic rate(Pn),stomatal conductance(Gs),intercellular oxidation concentration(Ci),transpiration rate(Tr),leaf water use efficiency(LWUE)and *** C1N0 treatment had the largest yield at 262.5 g/plant,with higher values for root length,root weight,plant height and leaf number than the other *** Pn,Ci and Tr of C1N4 were the highest at 3.05μmol CO_(2)/m2·s,352.8μmol CO_(2)/m2·s and 2.31 mmol H2O/m2·s,*** C1N2 treatment received the largest Gs value of 0.70 mol H2O/m2·s and the largest Tr of 2.31 mmol H2O/m2·*** was the highest LWUE for C0N2(1.41)and the highest anthocyanin content for C1N2(1.35 mg/kg).There was a significant negative correlation between leaf number and anthocyanin(r=-0.414,p<0.05).The findings demonstrated that adding CO_(2)fertilizer and 0.2 g/L exogenous urea-N to hydroponic solution dilution is a potential N×CO_(2)coupling strategy to increase anthocyanin and the yield of purple cabbage.
With the development of science and technology, modern war has changed from traditional mechanized war to electronic war. Electronic warfare has become the mainstream combat mode in modern war. At present, the electro...
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We present HasBugs, an extensible and manually-curated dataset of real-world 25 Haskell Bugs from 6 open source repositories. We provide a faulty, tested, and fixed version of each bug in our dataset with reproduction...
We present HasBugs, an extensible and manually-curated dataset of real-world 25 Haskell Bugs from 6 open source repositories. We provide a faulty, tested, and fixed version of each bug in our dataset with reproduction packages, description, and bug context. For technical users, the dataset is meant to either help researchers adapt techniques from other programming languages to Haskell or to provide a human-verified gold standard for tools evaluation and enable future reproducibility. We also see applicability for qualitative research, e.g., by analysis of bug lifecycles and comparison to other languages. We provide a companion website for easy access and overview under https://***/HasBugs/.
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