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Context Even with the increasing use of Systematic Literature Reviews (SLR) in software engineering (SE), there are still a number of barriers faced by SLR authors. These barriers increase the cost of conducting SLRs. Objective For many of these barriers, appropriate tool support could reduce their impact. In this paper, we use interactions with the SLR community in SE to identify and prioritize a set of requirements for SLR tooling infrastructure. Method This paper analyzes and combines the...
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The large and growing number of published studies, and their increasing rate of publication, makes the task of identifying relevant studies in an unbiased way for inclusion in systematic reviews both complex and time consuming. Text mining has been offered as a potential solution: through automating some of the screening process, reviewer time can be saved. The evidence base around the use of text mining for screening has not yet been pulled together systematically; this systematic review...
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Abstract The parameterization of moist convection contributes to uncertainty in climate modeling and numerical weather prediction. Machine learning (ML) can be used to learn new parameterizations directly from high‐resolution model output, but it remains poorly understood how such parameterizations behave when fully coupled in a general circulation model (GCM) and whether they are useful for simulations of climate change or extreme events. Here we focus on these issues using...
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Abstract While global warming has generally increased the occurrence of extreme precipitation, the physical mechanisms by which climate change alters regional and local precipitation extremes remain uncertain, with debate about the role of changes in the atmospheric circulation. We use a convolutional neural network (CNN) to analyze large‐scale circulation patterns associated with U.S. Midwest extreme precipitation. The CNN correctly identifies 91% of observed precipitation...
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Article impact statement: Machine learning optimizes processes of systematic evidence synthesis and improves its utility for evidence-based conservation.
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Utilising satellite images for planning and development is becoming a common practice as computational power and machine learning capabilities expand. In this paper, we explore the use of satellite image derived building footprint data to classify the residential status of urban buildings in low and middle income countries. A recently developed ensemble machine learning building classification model is applied for the first time to the Democratic Republic of the Congo, and to Nigeria. The...
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Pretrained general-purpose language models can achieve state-of-the-art accuracies in various natural language processing domains by adapting to downstream tasks via zero-shot, few-shot and fine-tuning techniques. Because of their success, the size of these models has increased rapidly, requiring high-performance hardware, software, and algorithmic techniques to enable training such large models. As the result of a joint effort between Microsoft and NVIDIA, we present details on the training...
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Abstract Although Climate Change is a global phenomenon, the impact in Africa is anticipated to be greater than in many other parts of the world. This expectation is supported by many factors, including the relatively low shock tolerance of many African countries and the relatively high percentage of African workers engaged in the agricultural sector. High-income countries are increasingly turning their focus to climate change adaptation, and Artificial Intelligence (AI) is a...
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Greetings, if our institution opts for the Tier 3 plan for the ChatGPT API, allowing students to utilize our API, and the usage either surpasses or falls below the predefined limits of Tier 3, how does it influence the monthly pricing? To clarify, if usage exceeds the Tier 3 limits, will our monthly payment remain fixed at $1000, or will the pricing be adapted according to our actual usage? You can refer to the link provided for details on the tier plans: https://platform.openai.com/docs/guides/...
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