Abstract: A manipulator for components, in particular sheet metal parts, includes a base body mountable stationarily or movable along a guide arrangement, a first pivot arm pivotally coupled to the base body via a horizontal first pivot axis, a second pivot arm pivotally coupled to the first pivot arm via a horizontal second pivot axis and a third pivot arm pivotally coupled to the second pivot arm via a horizontal third pivot axis. A first axis of rotation extending radially to the third pivot axis is formed on the third pivot arm. A gripper support arm is rotatably coupled to the third pivot arm via the first axis of rotation and extends radially to the first axis of rotation. A gripping arrangement is rotatably coupled to the gripper support arm via a second axis of rotation spaced from the first axis of rotation. A bending installation includes the manipulator.

Abstract: A network attached storage management appliance that can be inserted into a pre-existing network. The appliance sits between an end user and the available storage and optimizes performance and storage through acceleration of data, migration of data, compression of data, deduplication of data, and expansion of storage. The device moves data between lower- and higher-performance storage, with frequently accessed data sitting in higher-performance storage and infrequently accessed data sitting in lower-performance storage.

Abstract: A network attached storage management appliance that can be inserted into a pre-existing network. The appliance sits between an end user and the available storage and optimizes performance and storage through acceleration of data, migration of data, compression of data, deduplication of data, and expansion of storage. The device moves data between lower- and higher-performance storage, with frequently accessed data sitting in higher-performance storage and infrequently accessed data sitting in lower-performance storage.

Abstract: A network attached storage management appliance that can be inserted into a pre-existing network. The appliance sits between an end user and the available storage and optimizes performance and storage through acceleration of data, migration of data, compression of data, deduplication of data, and expansion of storage. The device moves data between lower- and higher-performance storage, with frequently accessed data sitting in higher-performance storage and infrequently accessed data sitting in lower-performance storage.

Abstract: Techniques for data deduplication are disclosed. In one particular exemplary embodiment, the techniques may be realized as a method for data deduplication comprising receiving a write request for a unit of data, generating a fingerprint for the unit of data, transmitting at least a portion of the fingerprint to a plurality of deduplication monitors, performing the write request using an indicator indicating a location of a previously stored unit of data having a fingerprint matching the transmitted at least a portion of the fingerprint if a response indicating the previously stored unit of data having the fingerprint matching the transmitted at least a portion of the fingerprint is received from at least one of the plurality of deduplication monitors, and performing the write request using the unit of data if no response is received.

Abstract: A computer-implemented method for deduplicating data is disclosed. The method may include identifying a request to transfer data from a client in a deduplication system to a server in the deduplication system. The method may also include determining, based at least in part on performance of the deduplication system, whether to deduplicate the data before transferring the data from the client to the server. The method may further include performing the following, the order of which is based on the determination: deduplicating the data and transferring the data from the client to the server. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Analog data is compressed by processing certain data from data storage and interpolating data between data points which fall within an acceptable error range. Data points are compressed by modifying or eliminating data depending upon the slope relationship of a stored data point to artificial data points, which are representative of the range of accepted deviations from the original data point.

Abstract: Certain exemplary embodiments comprise a method for transforming a raw set of electrical power generation process data associated with a first physical storage space into a representation of the raw set. The representation of the raw set can be associated with a second physical storage space that is smaller than the first physical storage space. The method can comprise receiving a non-zero user-specified deviation metric relating to the raw set of electrical power generation process data. The method can comprise automatically calculating a deviation measure of at least three data points from the raw set, the at least three data points comprising an opposing pair of end points. The method can comprise automatically comparing the deviation measure to the deviation metric. The method can comprise automatically deleting all data points intermediate to the opposing pair of end points if the deviation measure does not exceed the deviation metric.

Abstract: Certain exemplary embodiments comprise a method for transforming a raw set of electrical power generation process data associated with a first physical storage space into a representation of the raw set. The representation of the raw set can be associated with a second physical storage space that is smaller than the first physical storage space. The method can comprise receiving a non-zero user-specified deviation metric relating to the raw set of electrical power generation process data. The method can comprise automatically calculating a deviation measure of at least three data points from the raw set, the at least three data points comprising an opposing pair of end points. The method can comprise automatically comparing the deviation measure to the deviation metric. The method can comprise automatically deleting all data points intermediate to the opposing pair of end points if the deviation measure does not exceed the deviation metric.

Abstract: Analog data is compressed by processing certain data from data storage and interpolating data between data points which fall within an acceptable error range. Data points are compressed by modifying or eliminating data depending upon the slope relationship of a stored data point to artificial data points, which are representative of the range of accepted deviations from the original data point.