Contrails (condensation trails) are line-shaped ice clouds caused by aircraft and are a substantial contributor to aviation-induced climate change. Contrail avoidance is potentially an inexpensive way to significantly reduce the climate impact of aviation. An automated contrail detection system is an essential tool to develop and evaluate contrail avoidance systems. In this article, we present a human-labeled dataset named OpenContrails to train and evaluate contrail detection models based on GOES-16 Advanced Baseline Imager (ABI) data. We propose and evaluate a contrail detection model that incorporates temporal context for improved detection accuracy. The human labeled dataset and the contrail detection outputs are publicly available on Google Cloud Storage atgs://goes_contrails_dataset.

Predicting wildfire spread is critical for land management and disaster preparedness. To this end, we present ’Next Day Wildfire Spread,’ a curated, large-scale, multivariate data set of historical wildfires aggregating nearly a decade of remote-sensing data across the United States. In contrast to existing fire data sets based on Earth observation satellites, our data set combines 2D fire data with multiple explanatory variables (e.g., topography, vegetation, weather, drought index, population density) aligned over 2D regions, providing a feature-rich data set for machine learning. To demonstrate the usefulness of this data set, we implement a neural network that takes advantage of the spatial information of this data to predict wildfire spread. We compare the performance of the neural network with other machine learning models: logistic regression and random forest. This data set can be used as a benchmark for developing wildfire propagation models based on remote sensing data for a lead time of one day.

Considers the problem of querying the data in applications such as spreadsheets and word processors. This problem has several motivations from the perspective of data integration, interoperability and OLAP. We provide an architecture for realizing interoperability among such diverse applications and address the challenges that arise specifically in the context of querying data stored in spreadsheet applications. A fundamental challenge is the lack of a well-defined schema. We propose a framework in which the user can specify the layout of data in a spreadsheet, based on his perception of the important concepts underlying that data. Layout specifications can be viewed as the "physical schema" of a spreadsheet. We motivate the concept of an abstract database machine (ADM) that uses the layout specifications to provide a relational view of the data in spreadsheet applications and, similar to a DBMS, supports efficient querying of the spreadsheet data. We develop a methodology for building ADMs for spreadsheets and describe our implementation of an ADM for Microsoft Excel applications, based on the above methodology. Our implementation platform is IBM PCs running Windows NT, Microsoft Office and OLE 2.0. We demonstrate the generality and practicality of our approach by developing a formal characterization of the class of spreadsheets that can be handled in our framework. Our results show that the approach is capable of handling a broad class of naturally occurring spreadsheet applications. This work is part of an office tool integration project.

article Free Access Share on Picture programming project Authors: Nita Goyal Hewlett-Packard Laboratories, Palo Alto, CA Hewlett-Packard Laboratories, Palo Alto, CAView Profile , Charles Hoch Hewlett-Packard Laboratories, Palo Alto, CA Hewlett-Packard Laboratories, Palo Alto, CAView Profile , Ravi Krishnamurthy Hewlett-Packard Laboratories, Palo Alto, CA Hewlett-Packard Laboratories, Palo Alto, CAView Profile , Brian Meckler Hewlett-Packard Laboratories, Palo Alto, CA Hewlett-Packard Laboratories, Palo Alto, CAView Profile , Michael Suchow Hewlett-Packard Laboratories, Palo Alto, CA Hewlett-Packard Laboratories, Palo Alto, CAView Profile , Moshe Zloof Hewlett-Packard Laboratories, Palo Alto, CA Hewlett-Packard Laboratories, Palo Alto, CAView Profile Authors Info & Claims ACM SIGMOD RecordVolume 26Issue 2June 1997 pp 514–516https://doi.org/10.1145/253262.253377Online:01 June 1997Publication History 1citation267DownloadsMetricsTotal Citations1Total Downloads267Last 12 Months3Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Programming nontrivial GUI applications is currently an arduous task. Just as the use of a declarative language simplified the programming of database applications, we ask whether we can do the same for GUI programming? Can we then import a large body of knowledge from database research? We answer these questions by describing our experience in building nontrivial GUI applications initially using C++ programming and subsequently using Logic++, a higher order Horn clause logic language on complex objects with object-oriented features. We abstract a GUI application as a set of event handlers. Each event handler can be conceptualized as a transition from the old screen/program state to a new screen/program state. We use a data centric view of the screen/program state (i.e., every entity on the screen corresponds to proxy datum in the program) and express each event handler as a query dependent update, albeit a complicated one. To express such complicated updates we use Logic++. The proxy data are expressed as derived views that are materialized on the screen. Therefore, the system must be active in maintaining these materialized views. Consequently, each event handler is conceptually an update followed by a fixpoint computation of the proxy data. Based on our experience in building the GUI system, we observe that many database techniques such as view maintenance, active DB, concurrency control, recovery, optimization as well as language concepts such as higher order logic are useful in the context of GUI programming.