Abstract: A heterogeneous computing terminal for task scheduling is provided, including a processing unit and multiple computing units. The heterogeneous computing terminal generates a task scheduling strategy. The target computing unit acquires a target upgrade program, is upgrade based on the target upgrade program, processes a target task and sends a processing result to the processing unit. The processing unit combines processing results sent by multiple target computing units to obtain a processing result of an initial task set. The heterogeneous computing terminal can upgrade the computing unit online, that is, dynamically update the computing unit, thereby greatly expanding the versatility of the computing unit of hardware. Scheduling strategy adapted to the task can be generated, and the computing unit can dynamically provide better task processing capabilities. The computing efficiency of the heterogeneous computing terminal is improved.

Abstract: A method for calculating a state of charge of a battery is provided. The method includes: estimating a first state of charge of the battery by using a first state of charge estimation algorithm; estimating a second state of charge of the battery by using a second state of charge estimation algorithm; determining a first weight corresponding to the first state of charge and a second weight corresponding to the second state of charge based on state data of the battery; and calculating the state of charge of the battery based on the first state of charge and the first weight, and the second state of charge and the second weight. With method for calculating a state of charge of a battery in the present disclosure, the accuracy of calculating the state of charge of the battery can be improve d with a lower computation cost.

Abstract: A method and a device for forecasting an electric load, an electronic device, and a computer-readable storage medium are provided. The method includes: acquiring historical load data prior to a forecast date; generating a load sequence based on the historical load data; performing variational mode decomposition on the load sequence, to obtain multiple intrinsic mode components and a residual that are corresponding to the load sequence; and inputting the multiple intrinsic mode components and the residual into respective forecasting models, and determining a load value on the forecast date based on forecasting results of all the forecasting models. With the method and the device, the electronic device, and the computer-readable storage medium, the load sequence is decomposed based on the variational mode decomposition, so that more dimensional feature information in the load sequence can be mined. Moreover, the residual is also used as valid data.

Abstract: A thermal-runaway warning method, system, and terminal for a power station are provided. The method comprises: obtaining collected data of a battery module comprised in the power station, wherein the collected data comprises collected temperature values of the battery module collected by temperature measuring devices; normalizing the collected data to obtain a standard dataset; training a CNNLSTM-based temperature predicting model based on the standard dataset to obtain a trained CNNLSTM-based temperature predicting model; and obtaining a predicted temperature value of the battery module within an output time window based on the trained CNNLSTM-based temperature predicting model, and determining whether there is a risk of thermal runaway in the power station based on the predicted temperature value.

Abstract: Embodiments are directed to managing data for a predictive learner recommendation platform. A platform that includes applications hosted in an application layer may be provided. The applications may be employed to provide a request to determine a pathway prediction for a learner such that the pathway prediction may be associated with a role offered by employers. Prediction engines associated with the request may be determined based on the service layer interface and the request such that the request may be provided to the determined prediction engines via the service layer interface. The prediction engines may be employed to generate the pathway prediction based on a learner profile that corresponds with the learner, a role success profile that corresponds to the employers, and models that are trained to predict matches between the learner profile and the role success profile.

Abstract: Embodiments are directed to managing data correlation over a network. Role success models that correspond to roles and to success criteria may be provided. A student profile that includes skill vectors may be provided based on student information. Role success models may be employed to determine intermediate scores based on the skill vectors and the success criteria. A predictive score for the student that corresponds with a predicted performance of the student in the roles may be generated based on the one or more intermediate scores. Actions for the student may be determined based on a mismatch of the skill vectors and role skill vectors that correspond to the roles. In response to the student performing the actions: updating the one or more skill vectors based on a completion of the actions; and updating the predictive score based on the role success models and the updated skill vectors.

Abstract: The invention discloses a method, a system, a device, and a medium for detecting a battery state of health. The method includes extracting a target curve segment from a first charging characteristic curve of a battery under test; and determining, according to a corresponding relation between characteristic parameters of the target curve segment and the battery state of health, the battery state of health matching the characteristic parameters of the target curve segment, and determining the battery state of health as the battery state of health of the battery under test. By utilizing said corresponding relation as the calculation basis, the invention improves the reliability and accuracy of the detection of battery state of health detection. The invention also tracks instances of abusive conditions that accelerate battery aging, assessing whether such conditions accelerate battery degradation and issuing warnings accordingly.

Abstract: The invention discloses a method, a system, an electronic device, and a storage medium for determining performance of a power battery. The method includes the following steps: acquiring historical data of the power battery in at least two charging processes; determining, according to historical data in one charging process, a dQ/dV curve and a direct current internal resistance corresponding to said charging process; calculating a relative change rate of internal resistance capacity in any two charging processes; and determining the performance of the power battery according to the relative change rate of internal resistance capacity and a relative change rate of internal resistance capacity range corresponding to fault type. The invention can effectively determine whether the performance of the power battery is abnormal by combining, in the two charging processes, the target peak value of a dQ/dV curve of the power battery and the change in direct current internal resistance.

Abstract: A method includes: when it is determined that a user's gesture of moving an electronic device is a preset gesture, obtaining a capacitance measurement value sensed at a contact in a preset area of the touchscreen, where the preset area is located in a peripheral edge area of the touchscreen; and when the obtained capacitance measurement value meets a first preset condition, controlling display status switching of the touchscreen.

Abstract: The present invention relates to the technical field of optical communications, and relates to an optical amplification method and an amplifier, and in particular, to a self-adaptive wave band amplification method and an amplifier. The present invention consists of a master amplifying unit and a slave amplifying unit, and can autonomously detect the service signal wave band range of an optical transmission line, and according to the detection result, the two amplifying units do not need to perform scheduling or configuration from the level of network management, and perform direct interaction and action from the bottom layer to implement self-adaptive on, off and adjustment in real time. On one hand, power consumption is reduced, and energy is saved; and on the other hand, the performance is optimized, and an optimal optical amplification index is obtained.

Abstract: Embodiments are directed to managing data for unified graph representation of skills and acumen. Information associated with one or more subjects may be classified to provide profile information that conforms to a unified schema. Fields of the profile information may be classified as facts, fact-relationships, actions, skills, or skill-relationships based on the unified schema. A plurality of profile graphs may be generated based on map models and the facts, the fact-relationships, the actions, the skills, or the skill-relationships such that the map models include one or more directives for associating the facts, the fact-relationships, the actions, the skills, or the skill-relationships with one or more nodes or one or more edges in the plurality of profile graphs. In response to query information provided by one or more analysis applications, classifying a portion of the plurality of profile graphs based on the query information.

Abstract: A computing system can receive location data from a computing device of a driver. Based at least in part on the location data, execute a location-based feasibility model to determine that one or more anomalous locational attributes are present, where the location-based feasibility model outputs a probability that the computing device of the respective driver is performing location-spoofing. Based on the probability indicating that the computing device of the driver is performing location-spoofing, the system associates a data set with a driver profile of the respective driver.

Abstract: Embodiments are directed to managing data for unified graph representation of skills and acumen. Information associated with one or more subjects may be classified to provide profile information that conforms to a unified schema. Fields of the profile information may be classified as facts, fact-relationships, actions, skills, or skill-relationships based on the unified schema. A plurality of profile graphs may be generated based on map models and the facts, the fact-relationships, the actions, the skills, or the skill-relationships such that the map models include one or more directives for associating the facts, the fact-relationships, the actions, the skills, or the skill-relationships with one or more nodes or one or more edges in the plurality of profile graphs. In response to query information provided by one or more analysis applications, classifying a portion of the plurality of profile graphs based on the query information.

Abstract: A computing system can receive location data from computing devices of drivers, each of the computing devices operating a designated application associated with an application service. The system can determine a set of locational attributes of a respective driver and determine whether one or more anomalous locational attributes are present in the set of locational attributes of the respective driver. In response to determining that one or more anomalous locational attributes are present, the system can associate a data set with a driver profile of the respective driver.

Abstract: Embodiments are directed to managing courses. Course information for a course may be provided. Skill terms may be determined for the course based on the course information and skill models. Candidate skills may be determined based on the skill terms and a unified skill dictionary such that the skill terms may be mapped to the candidate skills based on the unified skill dictionary. A summary of the course information and the candidate skills may be displayed to a subject matter expert. if the subject matter expert confirms that a candidate skill may be taught by the course, the candidate skill may be associated with a course profile for the course that includes the confirmed candidate skills and proficiency scores for the confirmed skills.

Abstract: Embodiments are directed to data ingestion over a network. Raw data and integrated data associated with a plurality of separate data sources may be provided such that the raw data includes content associated with a plurality of subjects. Categorization models may be employed to categorize the raw data based on various features, such as, format, structure, data source, variability, volume, or associated entities. Matching models may be determined based on the categorization of the of the raw data, the integrated data and the content associated with the plurality of subjects. Matching models may generate a plurality of unified facts based on the raw data and the integrated data such that each unified fact is associated with a score associated with a quality of its match with a unified schema.

Abstract: Provided are methods of forming a carbon-carbon bond between a first compound and a second compound through a hydroarylation chemical reaction. The methods include contacting the first compound and the second compound in the presence of an acid catalyst. The methods include forming a carbon-carbon bond wherein the first compound includes a first aryl group that is electron-deficient. Provided is a method of generating a quaternary carbon through a hydroarylation chemical reaction.

Abstract: Disclosed are an organic compound based on triazine and benzoxazole and an application thereof in an OLED device. The compound of the present application has a relatively high glass transition temperature and molecular thermal stability, is low in absorption and high in refractive index in the field of visible light, and is capable of effectively improving the light extraction efficiency of an OLED device when applied to a capping layer of the OLED device; with a deep HOMO energy level and high electronic mobility, the compound of the present application can be used as the hole blocking layer or the electron transport layer material, so that the recombination degree of the hole and the electron in the light-emitting layer can be improved, and thus the light-emitting efficiency of the OLED device can be enhanced and the service life of the OLED device can be prolonged.

Abstract: Embodiments are directed to managing data for a predictive learner recommendation platform. A platform that includes applications hosted in an application layer may be provided. The applications may be employed to provide a request to determine a pathway prediction for a learner such that the pathway prediction may be associated with a role offered by employers. Prediction engines associated with the request may be determined based on the service layer interface and the request such that the request may be provided to the determined prediction engines via the service layer interface. The prediction engines may be employed to generate the pathway prediction based on a learner profile that corresponds with the learner, a role success profile that corresponds to the employers, and models that are trained to predict matches between the learner profile and the role success profile.

Abstract: Embodiments are directed to managing data correlation over a network. Student information may be provided. Position information based on potential employers may be provided. Student profiles may be generated based on translation models and the student information. The student information may be translated into unified facts included in the student profiles. Position profiles may be generated based on the translation models and the position information. The position information may be translated into other unified facts in the position profiles. The student profiles may be correlated with the position profiles based on recommendation models, the unified facts, and the other unified facts. Each student profile and position profile pair may be associated with a score based on a strength of the correlation. Reports may be provided that include each pair of the student profile. A plurality of pairs may be ordered based on the score associated with each pair.