In this paper, we report on an operational procedure for use by the Corps of Engineers to acquire land use information for hydrologic planning purposes. The operational constraints preclude the use of dedicated, interactive image processing facilities. The procedure, which is summarized in detail, combines manual interpretation techniques and the batch-mode computer analysis of Landsat digital ...

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The classical multi-level capacitated lot-sizing problem is often not suitable to correctly capture resource requirements and precedence relations. We tackle this issue by explicitly modeling these two aspects. Two models are presented; one considering batch production and the other one allowing lot-streaming. Comparisons with traditional models demonstrate the capability of the new approach to...

Apache Flink1 is an open-source system for processing streaming and batch data. Flink is built on the philosophy that many classes of data processing applications, including real-time analytics, continuous data pipelines, historic data processing (batch), and iterative algorithms (machine learning, graph analysis) can be expressed and executed as pipelined fault-tolerant dataflows. In this pape...

Abstract Implementing complex algorithms for big data, artificial intelligence, and graph processing requires enormous effort. Succinct, declarative programs to solve problems that can be efficiently executed batching streaming data are in demand. This paper presents Nexus, a distributed Datalog evaluation system. It evaluates using the semi-naive algorithm batch incremental asynchronous iterat...

We address the problem of scheduling jobs with non-identical sizes and distinct processing times on a single batch-processing machine, aiming at minimizing makespan. The extensive literature this NP-hard mostly focuses heuristics. Using an arc-flow based optimization approach, we construct novel formulation that represents it as determining flows in graphs. size increases machine capacity numbe...