Abstract: A method for fine-tuning a convolutional neural network (CNN) and a sensor system based on a CNN are disclosed. The sensor system may be deployed at a deployment location. The CNN may be fine-tuned for the deployment location using sensor data, e.g., images, captured by a sensor device of the sensor system at the deployment location. The sensor data may include objects that are not present in an initial data set used for training the CNN. The sensor data and the initial data set may be input to the CNN to train the CNN and obtain fine-tuned parameters of the CNN. The CNN can thus be fine-tuned to the deployment location of the sensor system, with an increased chance of recognizing objects when using the sensor system and the CNN to recognize objects in captured sensor data.

Abstract: In accordance with at least one aspect of this disclosure, a board capacitor can include a first plate formed from a first conductive plane of a circuit board, a dielectric formed by a non-conductive core of the circuit board, and a second plate formed from a second conductive plane of the circuit board. The first plate and the second plate can be separated by the dielectric.

Abstract: Disclosed herein is a method and system for identifying abnormal images in a set of medical images for optimal assessment of the medical images. A plurality of global features from each medical image is extracted based on pretrained weights associated with each global feature. Similarly, plurality of local features from each medical image is extracted analyzing a predefined number of image patches generated from a higher resolution image corresponding to each medical image. Further, an abnormality score for each medical image is determined based on weights associated with a combined feature set obtained by concatenating the plurality of global features and the plurality of local features. Thereafter, the medical image is identified as an abnormal image when the abnormality score of the medical image is higher than a predefined first threshold score.

Abstract: Embodiments of the present disclosure include techniques for programming hierarchical schedulers for ports of network devices. A configuration for configuring a hierarchy of a plurality of scheduling nodes of a packet scheduler is received. The packet scheduler is configured to schedule packets for egress out of a port of the network device. The configuration is specified in a human-readable format. Based on the configuration, the packet scheduler of the port is programmed. A plurality of packets are received at a plurality of physical queues communicatively coupled to the packet scheduler. The packet scheduler is used to select a packet in the plurality of packets from a physical queue in the plurality of physical queues. The selected packet is forwarded out the port of the network device.

Abstract: According to one implementation of the present disclosure, a method includes providing one or more tuning parameters of a transistor device at a first temperature of a range of temperatures below a temperature threshold; and adjusting the one or more tuning parameters until one or more second parameters of the transistor device corresponds to substantially the same value at the first temperature as a second temperature above the temperature threshold.

Abstract: Systems and methods are disclosed for generating device test cases for medical imaging devices, which are not only reflective of current actual field usage of the device but also provide outlook on future usage. A probabilistic model of usage patterns is generated from historic data present in the device field logs by mining the current usage patterns. A Deep Long Short Term Memory Neural Network model of the usage patterns is constructed to predict the future usage patterns. Additionally, to capture the changing trends of device usage patterns in the field, predictive models are continuously updated in real time, and the test cases generated log files by the models are integrated into an automated testing system.

Abstract: A method for fine-tuning a convolutional neural network (CNN) and a sensor system based on a CNN are disclosed. The sensor system may be deployed at a deployment location. The CNN may be fine-tuned for the deployment location using sensor data, e.g., images, captured by a sensor device of the sensor system at the deployment location. The sensor data may include objects that are not present in an initial data set used for training the CNN. The sensor data and the initial data set may be input to the CNN to train the CNN and obtain fine-tuned parameters of the CNN. The CNN can thus be fine-tuned to the deployment location of the sensor system, with an increased chance of recognizing objects when using the sensor system and the CNN to recognize objects in captured sensor data.

Abstract: This invention relates generally to articles, devices, and methods for inhibiting or preventing the formation of scale during various industrial processes. In certain embodiments, a vessel is provided for use in an industrial process, the vessel having a textured, liquid-impregnated surface in contact with a mineral solution, wherein the liquid-impregnated surface comprises a matrix of features spaced sufficiently close to stably contain an impregnating liquid lubricant therebetween or therewithin, wherein the impregnating lubricant has a low surface energy density, and wherein the spreading coefficient Sos(w) of the impregnating lubricant (subscript ‘o’) on the substrate (subscript ‘s’) in the presence of the salt solution (subscript ‘w’) is greater than zero, such that the impregnating lubricant fully submerges the textured substrate.

Abstract: An access system for spinal surgery through a lateral approach comprises a tissue retractor including a center body supporting a centering guide having an elongate opening defining an alignment axis. A pair of retractor blades are movably supported by the center body one blade each on either side of said the centering guide, each retractor blade having a proximal end and a distal end, the distal ends of each retractor blade being configured for placement adjacent a spinal column of a patient. A plurality of elongate disc anchors is provided, each disc anchor being sized for individual removable receipt through the centering guide opening. Each disc anchor has a length such that the distal end of each disc anchor extends distally beyond the distal ends of the retractor blades when each disc anchor is respectively disposed in the centering guide opening.

Abstract: A process for preparing a Mn+4 doped phosphor of formula I Ax[MFy]:Mn+4?? I includes combining a first solution comprising a source of A and a second solution comprising H2MF6 in the presence of a source of Mn, to form the Mn+4 doped phosphor; wherein A is Li, Na, K, Rb, Cs, or a combination thereof; M is Si, Ge, Sn, Ti, Zr, Al, Ga, In, Sc, Y, La, Nb, Ta, Bi, Gd, or a combination thereof; x is the absolute value of the charge of the [MFy] ion; y is 5, 6 or 7; and wherein a value of a Hammett acidity function of the first solution is at least ?0.9. Particles produced by the process may have a particle size distribution with a D50 particle size of less than 10 ?m.

Abstract: A process for preparing a Mn+4 doped phosphor of formula I Ax[MFy]:Mn+4?? I includes combining a first solution comprising a source of A and a second solution comprising H2MF6 in the presence of a source of Mn, to form the Mn+4 doped phosphor; wherein A is Li, Na, K, Rb, Cs, or a combination thereof; M is Si, Ge, Sn, Ti, Zr, Al, Ga, In, Sc, Y, La, Nb, Ta, Bi, Gd, or a combination thereof; x is the absolute value of the charge of the [MFy] ion; y is 5, 6 or 7; and wherein a value of a Hammett acidity function of the first solution is at least ?0.9. Particles produced by the process may have a particle size distribution with a D50 particle size of less than 10 ?m.

Abstract: In certain embodiments, the invention is directed to apparatus comprising a liquid-impregnated surface, said surface comprising an impregnating liquid and a matrix of solid features spaced sufficiently close to stably contain the impregnating liquid therebetween or therewithin, and methods thereof. In some embodiments, one or both of the following holds: (i) 0<??0.25, where ? is a representative fraction of the projected surface area of the liquid-impregnated surface corresponding to non-submerged solid at equilibrium; and (ii) Sow(a)<0, where Sow(a) is spreading coefficient, defined as ?wa??wo??oa, where ? is the interfacial tension between the two phases designated by subscripts w, a, and o, where w is water, a is air, and o is the impregnating liquid.

Abstract: Implementations described herein are directed to a device with a processor and memory having stored thereon instructions that, when executed by the processor, cause the processor to acquire an integrated circuit layout of physical cells from a database and define wirelength relationships between input/output connections and a cell count for the physical cells in multiple domains. The instructions may cause the processor to define wirelength parameters of the integrated circuit layout in each domain of the multiple domains and generate a data file for the integrated circuit layout of the physical cells based on the wirelength relationships and the wirelength parameters to guide power and performance of the integrated circuit layout of the physical cells. The instructions may cause the processor to fabricate, or contribute to the fabrication of, an integrated circuit based on the data file for the integrated circuit layout of the physical cells.

Abstract: State of the art automated bin packing systems fail to handle dynamic scenarios in which information on dimensions of objects to be loaded is not available in advance. These systems also fail to consider capabilities of robots used for the automated packing of objects/bins. The disclosure herein generally relates to automated bin packing, and, more particularly, to a system and method for autonomous multi-bin parcel loading system. The system handles an online object packing in which information on dimensions of objects to be loaded is not available in advance. The system is also configured to consider capabilities of one or more robots used for loading objects to containers, while generating recommendations for object packing.

Abstract: A process for preparing a Mn+4 doped phosphor of formula I Ax[MFy]:Mn+4?? I includes gradually adding a first solution to a second solution gradually discharging the product liquor from the reactor while volume of the product liquor in the reactor remains constant; wherein A is Li, Na, K, Rb, Cs, or a combination thereof; M is Si, Ge, Sn, Ti, Zr, Al, Ga, In, Sc, Y, La, Nb, Ta, Bi, Gd, or a combination thereof; x is the absolute value of the charge of the [MFy] ion; y is 5, 6 or 7. The first solution includes a source of M and HF and the second solution includes a source of Mn to a reactor in the presence of a source of A.

Abstract: Synthesizing a color stable Mn4+ doped phosphor by contacting a gaseous fluorine-containing oxidizing agent with a precursor of: AaBbCcDdXx:Mn4+; AaiBbiCciDdXxYd:Mn4+; A13G2?m?nMnmMgnLi3F12Op; or AZF4:Mn4+. Where A is Li, Na, K, Rb, Cs, or a combination; B is Be, Mg, Ca, Sr, Ba, or a combination; C is Sc, Y, B, Al, Ga, In, Tl, or a combination; D is Ti, Zr, Hf, Rf, Si, Ge, Sn, Pb, or a combination; X is F or a combination of F and one of Br, Cl, and I; Y is O, or a combination of O and one of S and Se; A1 is Na or K, or a combination; G is Al, B, Sc, Fe, Cr, Ti, In, or a combination; Z is La, Ce, Pr, Nd, Pm, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Sc, Y, In, or a combination.

Abstract: In certain embodiments, the invention is directed to apparatus comprising a liquid-impregnated surface, said surface comprising an impregnating liquid and a matrix of solid features spaced sufficiently close to stably contain the impregnating liquid therebetween or therewithin, and methods thereof. In some embodiments, one or both of the following holds: (i) 0<??0.25, where ? is a representative fraction of the projected surface area of the liquid-impregnated surface corresponding to non-submerged solid at equilibrium; and (ii) Sow(a)<0, where Sow(a) is spreading coefficient, defined as ?wa??wo??oa, where ? is the interfacial tension between the two phases designated by subscripts w, a, and o, where w is water, a is air, and o is the impregnating liquid.

Abstract: A process for preparing a Mn+4 doped phosphor of formula I includes gradually adding a first solution comprising a source of M and HF and a second solution comprising a source of Mn to a reactor, in the presence of a source of A and an anion selected from phosphate, sulfate, acetate, and combinations thereof, to form a product liquor comprising the Mn+4 doped phosphor. The process also includes gradually discharging the product liquor from the reactor while volume of the product liquor in the reactor remains constant. A is Li, Na, K, Rb, Cs, or a combination thereof; M is Si, Ge, Sn, Ti, Zr, Al, Ga, In, Sc, Y, La, Nb, Ta, Bi, Gd, or a combination thereof; x is the absolute value of the charge of the [MFy] ion; and y is 5, 6 or 7.

Abstract: Implementations described herein are directed to a device with a processor and memory having stored thereon instructions that, when executed by the processor, cause the processor to acquire an integrated circuit layout of physical cells from a database and define wirelength relationships between input/output connections and a cell count for the physical cells in multiple domains. The instructions may cause the processor to define wirelength parameters of the integrated circuit layout in each domain of the multiple domains and generate a data file for the integrated circuit layout of the physical cells based on the wirelength relationships and the wirelength parameters to guide power and performance of the integrated circuit layout of the physical cells. The instructions may cause the processor to fabricate, or contribute to the fabrication of, an integrated circuit based on the data file for the integrated circuit layout of the physical cells.

Abstract: Systems and methods are disclosed for generating device test cases for medical imaging devices, which are not only reflective of current actual field usage of the device but also provide outlook on future usage. A probabilistic model of usage patterns is generated from historic data present in the device field logs by mining the current usage patterns. A Deep Long Short Term Memory Neural Network model of the usage patterns is constructed to predict the future usage patterns. Additionally, to capture the changing trends of device usage patterns in the field, predictive models are continuously updated in real time, and the test cases generated log files by the models are integrated into an automated testing system.