Abstract: The present disclosure relates to a spheroidizing-annealed steel for the ball screw having high strength and resistance to low temperatures, wherein the chemical composition of the steel in mass percentage is: C: 0.40-0.70%, Si: 1.20-1.80%, Mn: 1.00-1.60%, Cr: 0.80-1.20%, S: ?0.025%, P?0.025%, Ni: 0.10-0.60%, Cu: 0.30-0.80%, Mo: 0.10-0.40%, Al?0.05%, Ca?0.0010%, Ti?0.003%, O?0.0010%, As?0.04%, Sn?0.03%, Sb?0.005%, Pb?0.002%, the balance is Fe and unavoidable impurities. In microstructure of the steel, cementite exists in a spheroidized state with a diameter of 0.1-0.5 ?m, preferably 0.3-0.5 ?m, a spheroidizing rate is 95% or more, and the rest is ferrite.

Abstract: A method for increasing the yield of Amadori rearrangement products (ARP) based on a mechanism in which addition of tea polyphenols to deoxyosones inhibits degradation of the ARP. The method includes the following steps: dissolving and mixing amino acid, sugar and tea polyphenol in water, and adjusting a pH value; placing the obtained mixed solution in a reaction flask, and heating the mixed solution at a constant temperature in a water bath to obtain a reaction solution; and performing vacuum decompression dehydration reaction at a constant temperature; after the reaction is completed, using an ice bath to terminate the reaction to obtain a solid reactant, and redissolving the solid reactant in water to obtain an ARP solution. This method promotes the formation of ARP and inhibits degradation of ARP, so that ARP is accumulated and enriched in a large amount (80% and above yield).

Abstract: Methods, systems, and techniques for performing automatic source code generation for use in a data transformation process. A computer obtains a data file comprising data transformation rules. Using those rules, the computer automatically generates computer source code for use in a data transformation process to transform source data into target data. The source data may, for example, be raw data from a data lake, and the computer source code may be Scala computer code for execution within an Apache Spark™ framework. The data lake may execute the computer source code to transform the raw data stored in the data lake into the target data, and the target data may then be stored in the data warehouse.

Abstract: A method for preparing an intermediate by a reduced glutathione-indicated amino acid Maillard reaction is provided. The method includes a two-stage reaction at an increased temperature. A reduced glutathione is added after different times of a low-temperature reaction, and a subsequent Maillard reaction is effectively inhibited on a basis wherein a substance is interacted with an intermediate degradation product to reduce a formation of colored substances. Comparing with a browning of Maillard products after a high-temperature stage, a reaction time with a best color inhibition effect is found to be the optimal preparation condition of the intermediate, and the intermediate is prepared in an aqueous medium at a low temperature under this optimal preparation condition. The method uses the water soluble reduced glutathione as a tracer to improve a tracing accuracy comparing to cysteine.

Abstract: A method includes activating a first object detector and a second object detector. The first object detector is operable to detect a first type of object in a set of image frames, and the second object detector is operable to detect a second type of object in the set of image frames. The method also includes activating a first set of attribute classifiers and a second set of attribute classifiers. The method also includes generating first statistics for the first object detector and second statistics for the second object detector. The method also includes modifying activation of at least the second set of attribute classifiers based on a comparison of the first statistics and the second statistics.

Abstract: A method for increasing the yield of Amadori rearrangement products (ARP) based on a mechanism in which addition of tea polyphenols to deoxyosones inhibits degradation of the ARP. The method includes the following steps: dissolving and mixing amino acid, sugar and tea polyphenol in water, and adjusting a pH value; placing the obtained mixed solution in a reaction flask, and heating the mixed solution at a constant temperature in a water bath to obtain a reaction solution; and performing vacuum decompression dehydration reaction at a constant temperature; after the reaction is completed, using an ice bath to terminate the reaction to obtain a solid reactant, and redissolving the solid reactant in water to obtain an ARP solution. This method promotes the formation of ARP and inhibits degradation of ARP, so that ARP is accumulated and enriched in a large amount (80% and above yield).

Abstract: Using a distance sensor, a set of distances to a target object is measured, a distance in the set being measured at a time. From the set of distances and corresponding times, a trajectory of the target object is predicted. Based on receiving a signal identifying a friendly device, a correlation of the trajectory with a trajectory of the friendly device is determined. Responsive to the trajectory being predicted to intercept a defined volume around the distance sensor and responsive to the correlation being above a threshold degree of correlation, the target object is classified as a threat. Responsive to the trajectory being predicted to intercept a defined volume around the distance sensor and responsive to the correlation being below a threshold degree of correlation, a threat level corresponding to the target object is identified based on the trajectory of the target object and trajectory of the friendly device.

Abstract: A method includes activating a first object detector and a second object detector. The first object detector is operable to detect a first type of object in a set of image frames, and the second object detector is operable to detect a second type of object in the set of image frames. The method also includes activating a first set of attribute classifiers and a second set of attribute classifiers. The method also includes generating first statistics for the first object detector and second statistics for the second object detector. The method also includes modifying activation of at least the second set of attribute classifiers based on a comparison of the first statistics and the second statistics.

Abstract: A method for preparing an intermediate by a reduced glutathione-indicated amino acid Maillard reaction is provided. The method includes a two-stage reaction at an increased temperature. A reduced glutathione is added after different times of a low-temperature reaction, and a subsequent Maillard reaction is effectively inhibited on a basis wherein a substance is interacted with an intermediate degradation product to reduce a formation of colored substances. Comparing with a browning of Maillard products after a high-temperature stage, a reaction time with a best color inhibition effect is found to be the optimal preparation condition of the intermediate, and the intermediate is prepared in an aqueous medium at a low temperature under this optimal preparation condition. The method uses the water soluble reduced glutathione as a tracer to improve a tracing accuracy comparing to cysteine.

Abstract: A method, a computer program product, and a computer system for determining a location using street view images. A mobile device obtains an image captured by the mobile device, obtains a set of street view images, and obtains a first graph of the image captured by the mobile device and a plurality of second graphs of the set of the street view images. The first graph includes nodes representing interest points in the image captured by the mobile device, and the plurality of the second graphs includes nodes representing interest points in the set of the street view images. The mobile device determines a location of the mobile device, based on relevance between the first graph and the plurality of the second graphs.

Abstract: A method includes activating a first object detector and a second object detector. The first object detector is operable to detect a first type of object in a set of image frames, and the second object detector is operable to detect a second type of object in the set of image frames. The method also includes activating a first set of attribute classifiers and a second set of attribute classifiers. The method also includes generating first statistics for the first object detector and second statistics for the second object detector. The method also includes modifying activation of at least the second set of attribute classifiers based on a comparison of the first statistics and the second statistics.

Abstract: Techniques for dataset processing are provided. A plurality of feature vectors is generated for a plurality of pixel regions from a plurality of images, and a plurality of clusters is generated based on the plurality of feature vectors. A score is assigned to each respective pixel region in the plurality of pixel regions based at least in part on a cluster the respective pixel region is associated with. A unified dataset is created by, for each respective cluster in the plurality of clusters, computing a representative index for each pixel region in the respective cluster by comparing the pixel regions in the cluster, and modifying the score of the pixel regions in the cluster based on the computed representative indices. A confidence index is generated for the unified dataset based at least in part on a level of fragmentation in the unified dataset.

Abstract: Using a distance sensor, a set of distances to a target object is measured, a distance in the set being measured at a time. From the set of distances and corresponding times, a trajectory of the target object is predicted. Based on receiving a signal identifying a friendly device, a correlation of the trajectory with a trajectory of the friendly device is determined. Responsive to the trajectory being predicted to intercept a defined volume around the distance sensor and responsive to the correlation being above a threshold degree of correlation, the target object is classified as a threat. Responsive to the trajectory being predicted to intercept a defined volume around the distance sensor and responsive to the correlation being below a threshold degree of correlation, a threat level corresponding to the target object is identified based on the trajectory of the target object and trajectory of the friendly device.

Abstract: A method includes activating a first object detector and a second object detector. The first object detector is operable to detect a first type of object in a set of image frames, and the second object detector is operable to detect a second type of object in the set of image frames. The method also includes activating a first set of attribute classifiers and a second set of attribute classifiers. The method also includes generating first statistics for the first object detector and second statistics for the second object detector. The method also includes modifying activation of at least the second set of attribute classifiers based on a comparison of the first statistics and the second statistics.

Abstract: Techniques for dataset processing are provided. A plurality of feature vectors is generated for a plurality of pixel regions from a plurality of images, and a plurality of clusters is generated based on the plurality of feature vectors. A score is assigned to each respective pixel region in the plurality of pixel regions based at least in part on a cluster the respective pixel region is associated with. A unified dataset is created by, for each respective cluster in the plurality of clusters, computing a representative index for each pixel region in the respective cluster by comparing the pixel regions in the cluster, and modifying the score of the pixel regions in the cluster based on the computed representative indices. A confidence index is generated for the unified dataset based at least in part on a level of fragmentation in the unified dataset.

Abstract: Datasets containing a plurality of images are processed. A plurality of regions within the images are determined, where each of the plurality of regions corresponds to a facial region. A feature vector is generated for each of the plurality of pixel regions, and the plurality of pixel regions are clustered into a plurality of clusters based on the generated feature vectors. An initial score is assigned to each respective pixel region in the plurality of pixel regions, and the plurality of pixel regions are sorted based on the assigned scores. A representative index is computed for each respective pixel region by comparing each respective pixel regions with each other pixel region in the respective cluster. The score of each pixel region is modified based on the computed representative indices, and the pixel regions are sorted based on the modified scores. A confidence index is generated for the unified dataset.

Abstract: A method, a computer program product, and a computer system for determining a location using street view images. A mobile device obtains an image captured by the mobile device, obtains a set of street view images, and obtains a first graph of the image captured by the mobile device and a plurality of second graphs of the set of the street view images. The first graph includes nodes representing interest points in the image captured by the mobile device, and the plurality of the second graphs includes nodes representing interest points in the set of the street view images. The mobile device determines a location of the mobile device, based on relevance between the first graph and the plurality of the second graphs.

Abstract: Aspects determining anomalous events, wherein processors determine a trajectory of tracked movement of an object through an image field of a camera partitioned into a matrix grid of different local units. The aspects generate anomaly confidence decision values for image features extracted from video data of the tracked movement of the object as a function of fitting extracted image features to normal patterns of local motion pattern models defined by dominant distributions of extracted image features. The aspects further extract trajectory features from the video data relative to the trajectory of the tracked movement of the object, and generate global anomaly confidence decision values for the object trajectory as a function of fitting the extracted trajectory features to a normal learned motion trajectory model. The aspects determine anomalous events as a function of the generated global anomaly confidence decision value and the anomaly confidence decision values.

Abstract: Methods and system are provided for monitoring a queue. A method includes receiving by sensors a non-visual identifier at predefined locations of a queue. Further, the method includes capturing by image capture devices images of an object possessing the non-visual identifier at the predefined locations of the queue. Further, the method includes visually tracking another object in the queue based on transformations of a predefined feature extracted from the images of the object possessing the non-visual identifier at the predefined locations.

Abstract: A method, a computer program product, and a computer system for determining a location using street view images. A mobile device obtains an image captured by the mobile device, obtains a set of street view images, and obtains a first graph of the image captured by the mobile device and a plurality of second graphs of the set of the street view images. The first graph includes nodes representing interest points in the image captured by the mobile device, and the plurality of the second graphs includes nodes representing interest points in the set of the street view images. The mobile device determines a location of the mobile device, based on relevance between the first graph and the plurality of the second graphs.