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Modern scientific research centers require the fast, fault-tolerant storing systems for the collecting and processing of large amounts of scientific data originating from different sources and serving a great variety of client applications all over the world. This problem has great importance in many fields of science, such as geoinformatics, climate modeling, high-energy physics, astrophysics, and others. It is reasonable to use the concept of distributed computing to preprocess, normalize and aggregate scientifi...

Reverse vending machines (RVM) are a key part of used plastic containers utilization system in Europe and the United States. Waste recognition and sorting in RVM machines can be performed by any of the following procedures: by determining the container material (e.g. using the IR-spectrometer), by recognition of the container type by its shape, or by the barcode identification.[1] These three basic control-procedures make any attempt of the fraud completely impossible. But at the same time, it makes the RVM too ex...

Authors describe the novel approach to boost the scientific data analysis performance with the data-storing schema for distributed scientific research systems. This approach optimizes the workload on storage nodes and enhances the computation performance. Managing the enormous output of scientific research systems is expected to be the most technically difficult part of all recent projects producing Petabytes of imagery data. In this paper we describe the distributed storage structure with indexing techniques whic...