Abstract: A system (CDD) and related method for facilitating an iterative reconstruction operation. In iterative reconstruction, imagery in image domain is reconstructed in plural steps from measured projection data in projection domain. The system and methods use a trained machine learning module (MLM). The system receives input correction data generated in the iterative reconstruction operation. The system predicts, based on the input correction data, output correction data. The output correction data is provided for facilitating correcting a current image, as reconstructed in a given step, into a new image.

Abstract: A nonwoven web is made by displacing an air-permeable mesh-belt conveyor in a horizontal travel direction and spinning and then depositing crimped continuous filaments as a web at a deposit region on the air-permeable mesh-belt conveyor. A first preconsolidation stage is provided downstream of the deposit region and a second preconsolidation separated by a suction gap from the first stage. Air is drawn air through the web and the conveyor at the deposit region at a first predetermined speed, the first and second consolidation stages at a second and third predetermined speeds, and at the suction gap either not at all or at a fourth predetermined equal to at most substantially less than the second predetermined speed.

Abstract: A three dimensional neural network accelerator that includes a first neural network accelerator tile that includes a first transmission coil, and a second neural network accelerator tile that includes a second transmission coil, wherein the first neural network accelerator tile is adjacent to and aligned vertically with the second neural network accelerator tile, and wherein the first transmission coil is configured to wirelessly communicate with the second transmission coil via inductive coupling.

Abstract: A method for heating a catalytic converter includes a) switching on a compressor; b) at least partially opening an injection valve; c) setting a combustion-air/fuel ratio of ?<1 in combustion chambers; d) detecting an actual value of the oxygen content in the exhaust gas; and e) comparing the actual value with a target value, where the target value corresponds to an exhaust-gas oxygen content that would be set in a region of the catalytic converter if the combustion-air/fuel ratio in the combustion chambers is approximately ?=1, where a manipulated variable output by a controller on a basis of a deviation of the actual value from the target value is kept constant when the actual value reaches one of two limit values of a value range within which the target value is ranged, and where the two limit values deviate from the target value by approximately 3%.

Abstract: In one set of embodiments, a hardware module of a computer system can receive a stream of addresses corresponding to memory units being accessed by a central processing unit (CPU) of the computer system. The hardware module can further generate a frequency estimate for each address in the stream of addresses, the frequency estimate being indicative of a number of times a memory unit identified by the address has been accessed by the CPU, and can determine, based on the generated frequency estimates, a set of n most frequently accessed memory units.

Abstract: An optically structured element (1) for minimizing or preventing bird collisions, includes a carrier element (2), a high-reflectivity region (3), and a low-reflectivity region (4); which is distinguished in that a double cone reflectance difference of a first double cone reflectance of the high-reflectivity region (3) and a second double cone reflectance of the low-reflectivity region (4) is greater than or equal to 5% and a VIS transmission ratio of the first VIS transmittance and the second VIS transmittance is greater than or equal to 70% and less than or equal to 200%.

Abstract: In one set of embodiments, a hardware module of a computer system can receive a stream of addresses corresponding to memory units being accessed by a central processing unit (CPU) of the computer system. The hardware module can further generate a frequency estimate for each address in the stream of addresses, the frequency estimate being indicative of a number of times a memory unit identified by the address has been accessed by the CPU, and can determine, based on the generated frequency estimates, a set of n most frequently accessed memory units.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for three-dimensionally stacked neural network accelerators. In one aspect, a method includes obtaining data specifying that a tile from a plurality of tiles in a three-dimensionally stacked neural network accelerator is a faulty tile. The three-dimensionally stacked neural network accelerator includes a plurality of neural network dies, each neural network die including a respective plurality of tiles, each tile has input and output connections. The three-dimensionally stacked neural network accelerator is configured to process inputs by routing the input through each of the plurality of tiles according to a dataflow configuration and modifying the dataflow configuration to route an output of a tile before the faulty tile in the dataflow configuration to an input connection of a tile that is positioned above or below the faulty tile on a different neural network die than the faulty tile.

Abstract: Data processing systems (DPS) and related methods for nuclear medicine imaging. At an input interface (IN), first projection data (?), or a first image (V) reconstructable from the first projection data, is received. The first projection data is associated with a first waiting period (?T*). The first waiting period indicates the time period from administration of a tracer agent to a start of acquisition by a nuclear medicine imaging apparatus (IA) of the projection date. A trained machine learning module (MLM) estimates, based on the first projection data (?) or on the first image (V), a second projection data (??) or a second image (V?) associable with a second waiting period (?T), longer than the first waiting period (?T*). Nuclear imaging can thus be conducted quicker. Similar machine learning based data processing systems and related methods are also envisaged to reduce acquisition time periods or the time it takes to reconstruct imagery.

Abstract: Described herein are systems, methods, and software to manage time calibration associated with an oscillator of a computing system. In one example, a computing system monitors clock cycles for an oscillator on the computing system, receives timing messages from a server, and calculates the frequency of the oscillator at intervals based on the monitored clock cycles and timing messages. The computing system further identifies a temperature from a temperature sensor at each of the intervals and generates a function to demonstrate frequency of the oscillator versus temperatures from the temperature sensor based on the identified temperatures and frequencies at the intervals.

Abstract: The invention refers to an apparatus that allows to improve the image quality of nuclear images, e.g. PET images. The apparatus (110) comprises a providing unit (111) for providing nuclear image data of a region of interest, a providing unit (112) for providing a motion signal indicative of a motion of the region of interest, a determination unit (113) for determining different motion states of the region of interest based on the motion signal, a determination unit (114) for determining for each motion state nuclear image data corresponding to the motion state, a reconstruction unit (115) for reconstructing an absorption map for each motion state based on the corresponding nuclear image data of the respective motion state, and a reconstruction unit (116) for reconstructing one or more nuclear images of the region of interest based on the nuclear image data and the absorption maps reconstructed for each motion state.

Abstract: A three dimensional neural network accelerator that includes a first neural network accelerator tile that includes a first transmission coil, and a second neural network accelerator tile that includes a second transmission coil, wherein the first neural network accelerator tile is adjacent to and aligned vertically with the second neural network accelerator tile, and wherein the first transmission coil is configured to wirelessly communicate with the second transmission coil via inductive coupling.

Abstract: A non-transitory computer-readable medium stores instructions readable and executable by at least one electronic processor (181, 182, 20) to perform an imaging method (100). The method includes: reconstructing emission imaging data to generate an emission image of a lesion; converting intensity values of the emission image to at least one standardized uptake value (SUV value) for the lesion; processing input data using a regression neural network (NN) (28) to output an SUV correction factor for the lesion, wherein the input data includes at least two of (i) image data comprising the emission image or a feature vector representing the emission image, (ii) the at least one SUV value, (iii) a size of the lesion, and (iv) reconstruction parameters used in the reconstructing; and controlling a display device (24) to display at least one of (I) the SUV correction factor and (II) a corrected SUV value generated by applying the SUV correction factor to the at least one SUV value.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for three-dimensionally stacked neural network accelerators. In one aspect, a method includes obtaining data specifying that a tile from a plurality of tiles in a three-dimensionally stacked neural network accelerator is a faulty tile. The three-dimensionally stacked neural network accelerator includes a plurality of neural network dies, each neural network die including a respective plurality of tiles, each tile has input and output connections. The three-dimensionally stacked neural network accelerator is configured to process inputs by routing the input through each of the plurality of tiles according to a dataflow configuration and modifying the dataflow configuration to route an output of a tile before the faulty tile in the dataflow configuration to an input connection of a tile that is positioned above or below the faulty tile on a different neural network die than the faulty tile.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for three-dimensionally stacked neural network accelerators. In one aspect, a method includes obtaining data specifying that a tile from a plurality of tiles in a three-dimensionally stacked neural network accelerator is a faulty tile. The three-dimensionally stacked neural network accelerator includes a plurality of neural network dies, each neural network die including a respective plurality of tiles, each tile has input and output connections. The three-dimensionally stacked neural network accelerator is configured to process inputs by routing the input through each of the plurality of tiles according to a dataflow configuration and modifying the dataflow configuration to route an output of a tile before the faulty tile in the dataflow configuration to an input connection of a tile that is positioned above or below the faulty tile on a different neural network die than the faulty tile.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for three-dimensionally stacked neural network accelerators. In one aspect, a method includes obtaining data specifying that a tile from a plurality of tiles in a three-dimensionally stacked neural network accelerator is a faulty tile. The three-dimensionally stacked neural network accelerator includes a plurality of neural network dies, each neural network die including a respective plurality of tiles, each tile has input and output connections. The three-dimensionally stacked neural network accelerator is configured to process inputs by routing the input through each of the plurality of tiles according to a dataflow configuration and modifying the dataflow configuration to route an output of a tile before the faulty tile in the dataflow configuration to an input connection of a tile that is positioned above or below the faulty tile on a different neural network die than the faulty tile.

Abstract: A three dimensional neural network accelerator that includes a first neural network accelerator tile that includes a first transmission coil, and a second neural network accelerator tile that includes a second transmission coil, wherein the first neural network accelerator tile is adjacent to and aligned vertically with the second neural network accelerator tile, and wherein the first transmission coil is configured to wirelessly communicate with the second transmission coil via inductive coupling.

Abstract: A three dimensional neural network accelerator that includes a first neural network accelerator tile that includes a first transmission coil, and a second neural network accelerator tile that includes a second transmission coil, wherein the first neural network accelerator tile is adjacent to and aligned vertically with the second neural network accelerator tile, and wherein the first transmission coil is configured to wirelessly communicate with the second transmission coil via inductive coupling.

Abstract: An optical security device can be used to view sensitive information provided in an obscured format via a potentially untrusted and/or compromised computer. The techniques described herein enable use of untrusted computers for access to sensitive information. The optical security device employs one or more forms of visual cryptography such as spatial cryptography and/or temporal cryptography in some instances via a programmable mask and/or a programmable color filter to reveal sensitive information that is provided in an obscured form by a potentially untrusted computer.

Abstract: An optical security device can be used to view sensitive information provided in an obscured format via a potentially untrusted and/or compromised computer. The techniques described herein enable use of untrusted computers for access to sensitive information. The optical security device employs one or more forms of visual cryptography such as spatial cryptography and/or temporal cryptography in some instances via a programmable mask and/or a programmable color filter to reveal sensitive information that is provided in an obscured form by a potentially untrusted computer.