Abstract: A system is provided for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The memory may include program code which when executed by the at least one processor provides operations including: processing a container file with a trained machine learning model, wherein the trained machine learning is trained to determine a classification for the container file indicative of whether the container file includes at least one file rendering the container file malicious; and providing, as an output by the trained machine learning model, an indication of whether the container file includes the at least one file rendering the container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.

Abstract: Methods, non-transitory computer readable media, and computing devices are disclosed that provision an analytics application in an instance of a software development platform. The analytics application comprises a schema, one or more functions, and one or more dashboard templates. Raw analytics data is extracted according to the schema. The raw analytics data is logged by the software development platform in one or more databases and is based on monitored activity associated with a software development process performed on the software development platform. The one or more functions are then applied to the extracted raw analytics data to generate performance metrics for the software development process. The one or more dashboard templates are populated based on the performance metrics and the populated one or more dashboard templates are embedded into a user interface of the software development platform to facilitate visualization of the raw analytics data.

Abstract: Methods, non-transitory computer readable media, and computing devices are disclosed that obtains and stores a mapping of status values to process-blocks within stages associated with a linear process performed on an enterprise application network. A work item status in change records of the database is correlated with the status values based on the mapping to identify one of the stages for work items. Event records are then generated based on the correlation, activity records of the database, and another correlation of a unique identifier of one of the work items in each of the change and activity records. A generated value stream map (VSM) is then output for display that comprises a graphical timeline of activity associated with the linear process and metrics generated based on the event records and comprising real-time metrics for the process-blocks or stages and aggregate metrics for the linear process.

Abstract: Data is analyzed using feature hashing to detect malware. A plurality of features in a feature set is hashed. The feature set is generated from a sample. The sample includes at least a portion of a file. Based on the hashing, one or more hashed features are indexed to generate an index vector. Each hashed feature corresponds to an index in the index vector. Using the index vector, a training dataset is generated. Using the training dataset, a machine learning model for identifying at least one file having a malicious code is trained.

Abstract: In one respect, there is provided a system for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The at least one memory may include program code that provides operations when executed by the at least one processor. The operations may include: training, based on a training data, a machine learning model to enable the machine learning model to determine whether at least one container file includes at least one file rendering the at least one container file malicious; and providing the trained machine learning model to enable the determination of whether the at least one container file includes at least one file rendering the at least one container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.

Abstract: A media terminal includes two integrated currency devices, each device providing at least one feature/operation that is similar to or is the same as the other device. Two independent sessions to each device are made and presented to a transaction application of the terminal as a single aggregated session. When the transaction application issues a command through the single aggregated session, a decision is made that is transparent to the application as to which device should process the command on behalf of the application and the command is issued to the selected device over the corresponding independent session. Results or notifications provided by the selected device are aggregated and provided to the application over the single aggregated session. In an embodiment, the two integrated currency devices are different types of devices from one another.

Abstract: Disclosed is a consumable for use with apparatus for heating aerosolisable material to volatilise at least one component of the aerosolisable material. The consumable comprises an outer tube, an inner member inside the outer tube, and at least one support that supports the inner member relative to the outer tube so that at least one air gap exists between the inner member and the outer tube. At least one of the inner member, the outer tube and the support comprises aerosolisable material that is heatable to generate aerosol in the air gap. The consumable has at least one outlet for permitting the aerosol to pass out of consumable from the air gap.

Abstract: In one respect, there is provided a system for classifying malware. The system may include a data processor and a memory. The memory may include program code that provides operations when executed by the processor. The operations may include: providing, to a display, contextual information associated with a file to at least enable a classification of the file, when a malware classifier is unable to classify the file; receiving, in response to the providing of the contextual information, the classification of the file; and updating, based at least on the received classification of the file, the malware classifier to enable the malware classifier to classify the file. Methods and articles of manufacture, including computer program products, are also provided.

Abstract: In one aspect, a computer-implemented method is disclosed. The computer-implemented method may include determining a sketch matrix that approximates a matrix representative of a reference dataset. The reference dataset may include at least one computer program having a predetermined classification. A reduced dimension representation of the reference dataset may be generated based at least on the sketch matrix. The reduced dimension representation may have a fewer quantity of features than the reference dataset. A target computer program may be classified based on the reduced dimension representation. The target computer program may be classified to determine whether the target computer program is malicious. Related systems and articles of manufacture, including computer program products, are also disclosed.

Abstract: A system is provided for classifying an instruction sequence with a machine learning model. The system may include at least one processor and at least one memory. The memory may include program code that provides operations when executed by the at least one processor. The operations may include: processing an instruction sequence with a trained machine learning model configured to detect one or more interdependencies amongst a plurality of tokens in the instruction sequence and determine a classification for the instruction sequence based on the one or more interdependencies amongst the plurality of tokens; and providing, as an output, the classification of the instruction sequence. Related methods and articles of manufacture, including computer program products, are also provided.

Abstract: A modular light for removably attaching to a bio-printer robot end effector, where the light includes: an annular modular light ring housing with an annular opening for receiving the end effector of the bioprinting robot; the housing substantially surrounding a dispensing tip of the end effector; a power supply interface to receive electrical power from the end effector; a plurality of LEDs positioned annularly around the end effector within the annular modular light ring housing, where the plurality of LEDs are spaced in at least two annular rows, where each of the at least two annular rows are at a unique elevational position within the annular modular light ring housing with respect to a light output plane of the annular modular light ring housing; the LEDs are in electrical communication with the power supply interface; and a controller communicatively coupled with the LEDs and the power supply interface.

Abstract: In one respect, there is provided a system for classifying an instruction sequence with a machine learning model. The system may include at least one processor and at least one memory. The memory may include program code that provides operations when executed by the at least one processor. The operations may include: processing an instruction sequence with a trained machine learning model configured to detect one or more interdependencies amongst a plurality of tokens in the instruction sequence and determine a classification for the instruction sequence based on the one or more interdependencies amongst the plurality of tokens; and providing, as an output, the classification of the instruction sequence. Related methods and articles of manufacture, including computer program products, are also provided.

Abstract: A power supply for a smooth power output level transitioning includes an energy storage circuit for temporarily storing electric energy for driving a load, a semiconductor switch for pulse-width modulation (PWM) switching, and a digital PWM controller. The digital PWM controller generates a driving waveform to regulate on and off status of the semiconductor switch. The driving waveform toggles between PWM periods of a first type and PWM periods of a second type, and gradually adjusts a ratio of numbers of the PWM periods of the two types over time. The toggling driving waveform achieves one or more intermediate finer power output level that cannot be realized by a single type of PWM period with an intermediate duty cycle, due to the minimum item unit of the driving waveform limited by a clock rate of the digital PWM controller.

Abstract: The present invention provides processes for the preparation of 3, 5-Dihydroxy-4-isopropyl-trans-stilbene or a salt or solvate thereof and novel intermediates used therein. In some embodiments the 3, 5-Dihydroxy-4-isopropyl-trans-stilbene is prepared from (E)-2-chloro-2-isopropyl-5-styrylcyclohexane-1,3-dione. Also disclosed are crystal forms of 3, 5-Dihydroxy-4-isopropyl-trans-stilbene or a salt or solvate thereof and pharmaceutical compositions comprising same.

Abstract: The disclosure includes methods, systems and apparatus for predictive management of efficient selecting and receiving of retail electric utility service to a facility for a period, by automated selecting of a retail utility service provider corresponding to a selected least cost path of predicted rate plan choices across the period, wherein costs of all possible, viable time-bounded predicted rate plan choices are determined for predicted consumer usage where a predicted market of retail rate formulas for the period are predicted in relation to at least one variable, such as weather.

Abstract: The present invention provides processes for the preparation of 3, 5-Dihydroxy-4-isopropyl-trans-stilbene or a salt or solvate thereof and novel intermediates used therein. In some embodiments the 3, 5-Dihydroxy-4-isopropyl-trans-stilbene is prepared from (E)-2-chloro-2-isopropyl-5-styrylcyclohexane-1,3-dione. Also disclosed are crystal forms of 3, 5-Dihydroxy-4-isopropyl-trans-stilbene or a salt or solvate thereof and pharmaceutical compositions comprising same.

Abstract: In one respect, there is provided a system for training a neural network adapted for classifying one or more instruction sequences. The system may include at least one processor and at least one memory. The memory may include program code which when executed by the at least one processor provides operations including: training, based at least on training data, a machine learning model to detect one or more predetermined interdependencies amongst a plurality of tokens in the training data; and providing the trained machine learning model to enable classification of one or more instruction sequences. Related methods and articles of manufacture, including computer program products, are also provided.

Abstract: The present invention provides processes for the preparation of 3,5-Dihydroxy-4-isopropyl-trans-stilbene or a salt or solvate thereof and novel intermediates used therein. In some embodiments the 3,5-Dihydroxy-4-isopropyl-trans-stilbene is prepared from (E)-2-chloro-2-isopropyl-5-styrylcyclohexane-1,3-dione. Also disclosed are crystal forms of 3,5-Dihydroxy-4-isopropyl-trans-stilbene or a salt or solvate thereof and pharmaceutical compositions comprising same.

Abstract: The present disclosure relates to pyrophoric pellets that break apart into individual particulates or agglomerates when exposed to air and emit infrared radiation. The pyrophoric pellets include: (a) about 35 to about 95 wt. % of pyrophoric particles; (b) about 0.05 to about 30 wt. % of one or more thermally expandable particles; (c) about 1 to about 40 wt. % of one or more additives that modify IR signature; and (d) optionally, one or more additives that produce smoke at a temperature of 150° C. or greater. The pyrophoric pellets are particularly useful as countermeasures to protect against incoming missiles.

Abstract: A method and system for detecting and grouping users in electronic communications includes detecting electronic communications by a user using a device having a computer to communicate with other users. A number of message recipients are identified in the electronic communications. The message recipients are placed in a social graph based on a criteria such as the frequency of the electronic communications between the user and the message recipients. A group is created of the message recipients based on the social graph, and the group is presented to the user. The group can be accessed by the user for routing future electronic communications.