Abstract: Provided are a pose prediction method and apparatus, and a model training method and apparatus. The pose prediction method includes: performing target identification on a first image to be predicted to determine an area where a target object is located; determining a transformed target image based on the area where the target object is located; inputting the transformed target image into a pose decoupling prediction model for pose prediction; and determining a rotation amount of the target object based on an outputted result of a rotation amount branch network of the pose decoupling prediction model and determining a translation amount of the target object based on an outputted result of rotation amount branch network of the pose decoupling prediction model. By means of decoupling rotation and translation in object pose, the accuracy of pose prediction can be improved.

Abstract: The present disclosure provides a method for assessing hot coal fallout propensity of burning cigarettes based on human behavior features of ash-flicking action. The method is characterized in that the method is accomplished through an apparatus for detecting hot coal fallout propensity based on human behavior features of ash-flicking action, which include behavior features of human action of flicking cigarette ash, features of holding a cigarette, and features of force applying process and other aspects. This method can provide objective and accurate test basis for evaluation of cigarette fallout performance.

Abstract: The present disclosure discloses a drilling machine. The drilling machine may include a base, a mast arranged on the base, an iron roughneck, a drill floor mechanical arm, a top drive arranged on the mast, a pipe racker on a finger board, a power finger board, a power catwalk arranged on the ground, and an elevator arranged on the top drive. The drill machine and a corresponding tripping out and tripping in method may be used to vertically transport a stand between a well center and a region of at least one pipe setback efficiently, which may improve the efficiency of tripping out and tripping in, and reduce the risk of accidents in the well. In addition, the present disclosure provides a corresponding method for offline connecting and disconnecting stands during a drilling operation, which may reduce a preparation time during the drilling, improve the drilling efficiency, and reduce the cost of oilfield development.

Abstract: The present disclosure discloses a drilling machine. The drilling machine may include a base, a mast arranged on the base, an iron roughneck, a drill floor mechanical arm, a top drive arranged on the mast, a pipe racker on a finger board, a power finger board, a power catwalk arranged on the ground, and an elevator arranged on the top drive. The drill machine and a corresponding tripping out and tripping in method may be used to vertically transport a stand between a well center and a region of at least one pipe setback efficiently, which may improve the efficiency of tripping out and tripping in, and reduce the risk of accidents in the well. In addition, the present disclosure provides a corresponding method for offline connecting and disconnecting stands during a drilling operation, which may reduce a preparation time during the drilling, improve the drilling efficiency, and reduce the cost of oilfield development.

Abstract: A vector-valued regularized kernel function approximation (VVRKFA) based fault diagnosis method for an analog circuit comprises the following steps: (1) obtaining fault response voltage signals of an analog circuit; (2) performing wavelet packet transform on the collected signals, and calculating wavelet packet coefficient energy values as feature parameters; (3) optimizing regularization parameters and kernel parameters of VVRKFA by using a quantum particle swarm optimization algorithm and training a fault diagnosis model; and (4) identifying a circuit fault by using the trained diagnosis model. In the invention, the classification performance of the VVRKFA method is superior to other classification algorithms, and optimization of parameters by the quantum particle swarm optimization (QPSO) algorithm is also superior to the traditional method of obtaining parameters.

Abstract: An analog-circuit fault diagnosis method based on continuous wavelet analysis and an ELM network comprises: data acquisition: performing data sampling on output responses of an analog circuit respectively through Multisim simulation to obtain an output response data set; feature extraction: performing continuous wavelet analysis by taking the output response data set of the circuit as training and testing data sets respectively to obtain a wavelet time-frequency coefficient matrix, dividing the coefficient matrix into eight sub-matrixes of the same size, and performing singular value decomposition on the sub-matrixes to calculate a Tsallis entropy for each sub-matrix to form feature vectors of corresponding faults; and fault classification: submitting the feature vector of each sample to the ELM network to implement accurate and quick fault classification.

Abstract: In one embodiment, a target tracking method includes: receiving a current frame of picture including a target object; determining, based on a drift determining model, whether a tracker drifts for tracking of the target object in the current frame of picture, where the drift determining model is obtained through modeling based on largest values of responses values of a training sample used to train the drift determining model, where the training sample is collected from a training picture that includes the target object, where the response value of the sample is a value indicating a probability that the training sample is the target object in the training picture; and outputting a tracking drift result, where the tracking drift result includes: drift is generated for the tracking of the target object, or no drift is generated for the tracking of the target object.

Abstract: The invention belongs to the field of bioengineering and food technology, and discloses a method for enzymatic resolution of chiral substances, including the following steps: (1) preparing an enzyme solution with a lipase concentration of 1-3000 U/mL, and adding a soluble salt, a hydrophilic solvent and a hydrophobic solvent to the enzyme solution to form a three-liquid phase system; the hydrophobic solvent contains esters or amide compounds composed of racemic chiral compounds; (2) subjecting the three-liquid phase system to enzyme-catalyzed reaction under stirring condition; after the reaction is completed, standing or centrifuging the three-liquid phase system to divide it into three layers, which are a upper liquid layer, a middle liquid layer and a lower liquid layer from top to bottom.

Abstract: A vector-valued regularized kernel function approximation (VVRKFA) based fault diagnosis method for an analog circuit comprises the following steps: (1) obtaining fault response voltage signals of an analog circuit; (2) performing wavelet packet transform on the collected signals, and calculating wavelet packet coefficient energy values as feature parameters; (3) optimizing regularization parameters and kernel parameters of VVRKFA by using a quantum particle swarm optimization algorithm and training a fault diagnosis model; and (4) identifying a circuit fault by using the trained diagnosis model. In the invention, the classification performance of the VVRKFA method is superior to other classification algorithms, and optimization of parameters by the quantum particle swarm optimization (QPSO) algorithm is also superior to the traditional method of obtaining parameters.

Abstract: Disclosed is a Chinese medicinal composition prepared from the following medical raw materials in parts by weight: 1 part of ginseng, 0.8-1.5 parts of ginkgo leaf and 0.018-0.030 part of stigma croci.

Abstract: An enzymatic method for preparing glyceryl butyrate, comprising: (1) carrying out an esterification reaction between n-butyric acid and glycerol using lipase as a catalyst, ethyl acetate and/or ethyl formate as an additive; (2) separating the reaction product, recovering the additive by distillation under reduced pressure to obtain glyceryl butyrate. The invention uses lipase as a catalyst to catalyze the esterification reaction of n-butyric acid and glycerin at normal temperature and normal pressure, reduces the energy consumption of the reaction. Also, the reaction condition is mild, no side reaction happens, and no water-carrying agent is used. In addition, the additive increases the catalytic efficiency of the lipase and the conversion rate of butyric acid.

Abstract: A method for diagnosing analog circuit fault based on cross wavelet features includes steps of: inputting an excitation signal to an analog circuit under test, and collecting time domain response output signals to form an original data sample set; dividing the original data sample set into a training sample set and a test sample set; performing cross wavelet decomposition on both sets; applying bidirectional two-dimensional linear discriminant analysis to process the wavelet cross spectra of the training sample set and the test sample set, and extracting fault feature vectors of the training sample set and the test sample set; submitting the fault feature vectors of the training sample set to a support vector machine for training an SVM classifier, constructing a support vector machine fault diagnosis model; and inputting the fault feature vectors of the test sample set into the model to perform fault classification.

Abstract: A method and an apparatus for accessing a file, and a storage system. The method includes: determining L first-file invoking request messages; separately adding, according to physical sector information in the L first-file invoking request messages, the L first-file invoking request messages to M first-file dispatch queues; and processing a first-file invoking request message included in each first-file dispatch queue, to obtain an invoking request message of each first-file dispatch queue, where the invoking request message is used to access a first file. By means of the method and apparatus for accessing a file and the storage system in the embodiments of the present disclosure, a corresponding dispatch queue is allocated to an invoking request message of a micro file, so that combination processing can be performed on invoking request messages of multiple micro files, and a quantity of times of invoking a micro file is reduced.

Abstract: The present disclosure has provided an automatic multichannel apparatus for assessing hot coal fallout propensity of burning cigarettes and an assessing method thereof. The apparatus comprises a multichannel rotary plate unit, an automatic supplying unit for cigarette samples, an automatic ignition and burning line detection unit for cigarette samples, a cigarette holding and force applying unit, an automatic hot coal fallout detection and removal unit, a smoke collecting unit during suction, a suction unit, a gas exhaust unit arranged in a main frame, and an electric circuit and air path control unit for controlling actions and processes of the above units. The apparatus operates based on certain steps and performs automatic ignition and burning line detection on cigarette samples inserted into a rotary plate in sequence.

Abstract: A method includes obtaining, by a first program of an electronic device, a notification associated with a dynamic message of a second program of the electronic device, and, in response to detecting that a message display interface of the first program is switched from an inactive status to an active status, displaying the dynamic message on the message display interface.

Abstract: In one embodiment, a target tracking method includes: receiving a current frame of picture including a target object; determining, based on a drift determining model, whether a tracker drifts for tracking of the target object in the current frame of picture, where the drift determining model is obtained through modeling based on largest values of responses values of a training sample used to train the drift determining model, where the training sample is collected from a training picture that includes the target object, where the response value of the sample is a value indicating a probability that the training sample is the target object in the training picture; and outputting a tracking drift result, where the tracking drift result includes: drift is generated for the tracking of the target object, or no drift is generated for the tracking of the target object.

Abstract: An analog-circuit fault diagnosis method based on continuous wavelet analysis and an ELM network comprises: data acquisition: performing data sampling on output responses of an analog circuit respectively through Multisim simulation to obtain an output response data set; feature extraction: performing continuous wavelet analysis by taking the output response data set of the circuit as training and testing data sets respectively to obtain a wavelet time-frequency coefficient matrix, dividing the coefficient matrix into eight sub-matrixes of the same size, and performing singular value decomposition on the sub-matrixes to calculate a Tsallis entropy for each sub-matrix to form feature vectors of corresponding faults; and fault classification: submitting the feature vector of each sample to the ELM network to implement accurate and quick fault classification.

Abstract: A method for diagnosing analog circuit fault based on vector-valued regularized kernel function approximation, includes steps of: step (1) acquiring a fault response voltage signal of an analog circuit; step (2) carrying out wavelet packet transform on the collected signal, and calculating a wavelet packet coefficient energy value as a characteristic parameter; step (3) utilizing a quantum particle swarm optimization algorithm to optimize a regularization parameter and kernel parameter of vector-valued regularized kernel function approximation, and training a fault diagnosis model; and step (4) utilizing the trained diagnosis model to recognize circuit faults.

Abstract: The present disclosure provides a method for assessing hot coal fallout propensity of burning cigarettes based on human behavior features of ash-flicking action. The method is characterized in that the method is accomplished through an apparatus for detecting hot coal fallout propensity based on human behavior features of ash-flicking action, which include behavior features of human action of flicking cigarette ash, features of holding a cigarette, and features of force applying process and other aspects. This method can provide objective and accurate test basis for evaluation of cigarette fallout performance.

Abstract: The present disclosure provides a method for assessing hot coal fallout propensity of burning cigarettes based on human behavior features of ash-tapping action. The method is characterized in that the method is accomplished through an apparatus for detecting hot coal fallout propensity based on human behavior features of ash-tapping action, which include behavior features of human action of tapping cigarette ash, features of holding a cigarette, and features of force applying process and other aspects. This method can provide objective and accurate test basis for evaluation of cigarette fallout performance.