Abstract: An aerosol delivery device is provided that includes a user interface including a pushbutton and a display. A control component contained coupled to the user interface controls operation of at least one functional element of the aerosol delivery device. The control component controls the display to present a menu including a plurality of menu items selectable using only the pushbutton. Each menu item of the plurality of menu items is associated with a respective functional element of the aerosol delivery device, and the control component is configured to navigate the plurality of menu items, and select a currently-presented menu item of the plurality of menu items for control of the respective functional element, in response to respective first and second types of presses of the pushbutton, the first and second types of presses being of different durations.

Abstract: The disclosed technology teaches facilitate User and Entity Behavior Analytics (UEBA) by classifying a file being transferred as encrypted or not. The technology involves monitoring movement of a files by a user over a wide area network, detecting file encryption for the files using a trained classifier, wherein the detecting includes processing by the classifier some or all of the following features extracted from each of the files: a chi-square randomness test; an arithmetic mean test; a serial correlation coefficient test; a Monte Carlo-Pi test; and a Shannon entropy test, counting a number of the encrypted files moved by the user in a predetermined period, comparing a predetermined maximum number of encrypted files allowed in the predetermined period to the count of the encrypted files moved by the user and detecting that the user has moved more encrypted files than the predetermined maximum number, and generating an alert.

Abstract: An approach to arrange sensors needed for automated driving, especially where semitrailer trucks are operating in an autonomous convoy with one automated or semi-automated truck following another. The sensors are fitted to a location adjacent to or within the exterior rearview mirrors, on each of the left- and right-hand side of the tractor. The sensors provide overlapping fields of view looking forward of the vehicle and to both the left and right hand sides at the same time.

Abstract: Robotic systems for orthopedic surgery are provided. The robotic systems may include at least first and second motors coupled to each other. An output shaft of one of the motors may be connectable to a surgical tool guide. An output shaft of another of the motors may be coupled to a portion of a ball and socket joint. A corresponding portion of the ball and socket joint may be coupled to a bone mount which may be attached to a bone to mount the first and second motors to bone for performing orthopedic surgical procedures.

Abstract: An autonomous vehicle's control systems include an A-kit module that operates autonomy logic to generate a desired trajectory from sensor data. A B-kit module receives the desired trajectory and generates inputs for actuators such as steering, brake and throttle actuators based on the desired trajectory. Safing logic (which may be located in the A-kit, B-kit, both the A-kit and the B-kit or elsewhere within or outside of the vehicle) receives a sensor fault indication and executes a contingency trajectory such as a safing maneuver to bring the vehicle to a safe state.

Abstract: A delivery system includes a shaft including first and second main lumens spaced from each other and forming a common U-shaped lumen at distal portions of the lumens, a delivery device including a first and second members disposed within the first and second main lumens and a manifold coupling the first and second members disposed in the common U-turn lumen, wherein proximal movement of the first member of the delivery device along a first longitudinal axis causes corresponding proximal movement of the manifold within the common U-turn lumen and corresponding proximal movement of the second member along a second longitudinal axis different than the first longitudinal axis.

Abstract: The technology disclosed relates to a method, system, and non-transitory computer-readable media that trains a cloud traffic classifier to classify cross-application communications as malicious command and control (C2) traffic or benign cloud traffic. The training uses blocks of malicious Hypertext Transfer Protocol (HTTP) transactions targeted at a plurality of cloud applications by a plurality of clients prequalified as malicious command and control (C2) cloud traffic, and also blocks of benign HTTP transactions targeted at the plurality of cloud applications by the plurality of clients prequalified as benign cloud traffic. A cloud traffic classifier is trained on the cross-application malicious training example set and on the cross-application benign training example set by processing the blocks of the malicious and benign HTTP transactions as inputs, and generating outputs that classify the training examples as respectively malicious C2 cloud traffic or benign cloud traffic.

Abstract: The disclosed technology teaches training a classifier that classifies a file being transferred as encrypted or not. The technology involves accessing a plurality of training sample files, each of which is accompanied by a label of encrypted or not encrypted, sampling a configurable number of bytes of each respective file, generating features from the sampled bytes, including generating at least three of the following features: a chi-square randomness test; an arithmetic mean test; a serial correlation coefficient test; a Monte Carlo-Pi test; a Shannon entropy test; applying the generated features to train coefficients of a classifier algorithm to classify the sample files as encrypted or not encrypted; and saving the trained coefficients and classifier, whereby the classifier is trained to classify the sample files as encrypted or not encrypted.

Abstract: The disclosed technology teaches facilitate User and Entity Behavior Analytics (UEBA) by classifying a file being transferred as encrypted or not. The technology involves monitoring movement of a files by a user over a wide area network, detecting file encryption for the files using a trained classifier, wherein the detecting includes processing by the classifier some or all of the following features extracted from each of the files: a chi-square randomness test; an arithmetic mean test; a serial correlation coefficient test; a Monte Carlo-Pi test; and a Shannon entropy test, counting a number of the encrypted files moved by the user in a predetermined period, comparing a predetermined maximum number of encrypted files allowed in the predetermined period to the count of the encrypted files moved by the user and detecting that the user has moved more encrypted files than the predetermined maximum number, and generating an alert.

Abstract: A priming device for a fluid cartridge, a fluid dispense device configured for priming the fluid cartridge, and a method for priming a fluid cartridge. The priming device includes an impact mechanism for a fluid cartridge, wherein the fluid cartridge is devoid of a backpressure device and has a fluid reservoir and an ejection head chip in fluid flow communication with the fluid reservoir.

Abstract: A priming device for a fluid cartridge, a fluid dispense device configured for priming the fluid cartridge, and a method for priming a fluid cartridge. The priming device includes an impact mechanism for a fluid cartridge, wherein the fluid cartridge is devoid of a backpressure device and has a fluid reservoir and an ejection head chip in fluid flow communication with the fluid reservoir.

Abstract: The technology disclosed relates to a method, system, and non-transitory computer-readable media that classifies cloud traffic between a client and cloud application as malicious command and control (C2) cloud traffic or benign cloud traffic. A cloud traffic classifier, in communication with a network security system, is provided intercepted cloud traffic as an input, and generate an output that classifies the cloud traffic as malicious command and control (C2) cloud traffic or benign cloud traffic. The classifier may use signals such as beaconing behavior, anomalous entity, anomalous agent, anomalous username, anomalous username, anomalous agent, cat's paw behavior of the client, anomalous hostname access patterns, and/or malicious task sequence execution.

Abstract: An insect breeding device comprising at least one insect cage; a bin for holding drinking water or a tap for providing drinking water; a first pipe connected to the tap for receiving the drinking water, wherein the pipe is entering the at least one insect cage through a first opening; a nozzle, coupled to the first pipe, positioned inside the at least one insect cage configured to deliver the drinking water to the interior of the at least one insect cage; and a second pipe, coupled to a second opening, different from the first opening and located in the top wall of the cage or in a side wall of the cage, in the at least one insect cage, configured to deliver conditioned air into the at least one insect cage; and a third pipe, coupled to a third opening, different from the first and second opening and located in the top wall of the cage or in a side wall of the cage opposite to the second opening, in the at least one insect cage, configured to receive the conditioned air from the at least one insect cage.

Abstract: The technology disclosed relates to a method, system, and non-transitory computer-readable media that detects malicious communication between a command and control (C2) cloud resource on a cloud application and malware on an infected host, using a network security system. The network security system reroutes the cloud traffic to the network security system. The incoming requests of the cloud traffic are directed to a cloud application in the plurality of cloud applications, and wherein the cloud application has a plurality of resources. The network security system analyzes the incoming requests, determines that the incoming requests are targeted at one or more malicious resources in the plurality of resources.

Abstract: The technology disclosed includes a system to group security alerts generated in a computer network and prioritize grouped security alerts for analysis, through graph-based clustering. The graph used to form clusters includes entities in the computer network represented as scored nodes, and relationships of entities as weighted edges. The technology disclosed includes traversing the graph starting at starting nodes and propagating native scores through and to neighboring nodes connected by the weighted edges. The propagated scores at visited nodes are normalized by attenuation based on contributing neighboring nodes of a respective visited node. An aggregate score for a visited node is calculated by accumulating propagated scores at visited nodes with their respective native scores. The technology disclosed forms clusters of connected nodes in the graph that have a respective aggregate score above a selected threshold. The clusters are ranked and prioritized for analysis, pursuant to the aggregate scores.

Abstract: The technology disclosed relates to a method, system, and non-transitory computer-readable media that trains a cloud traffic classifier to classify cross-application communications as malicious command and control (C2) traffic or benign cloud traffic. The training uses blocks of malicious Hypertext Transfer Protocol (HTTP) transactions targeted at a plurality of cloud applications by a plurality of clients prequalified as malicious command and control (C2) cloud traffic, and also blocks of benign HTTP transactions targeted at the plurality of cloud applications by the plurality of clients prequalified as benign cloud traffic. A cloud traffic classifier is trained on the cross-application malicious training example set and on the cross-application benign training example set by processing the blocks of the malicious and benign HTTP transactions as inputs, and generating outputs that classify the training examples as respectively malicious C2 cloud traffic or benign cloud traffic.

Abstract: An approach to arrange sensors needed for automated driving, especially where semitrailer trucks are operating in an autonomous convoy with one automated or semi-automated truck following another. The sensors are fitted to a location adjacent to or within the exterior rearview mirrors, on each of the left- and right-hand side of the tractor. The sensors provide overlapping fields of view looking forward of the vehicle and to both the left and right hand sides at the same time.

Abstract: An approach to arrange sensors needed for automated driving, especially where semitrailer trucks are operating in an autonomous convoy with one automated or semi-automated truck following another. The sensors are fitted to a location adjacent to or within the exterior rearview mirrors, on each of the left- and right-hand side of the tractor. The sensors provide overlapping fields of view looking forward of the vehicle and to both the left and right hand sides at the same time.

Abstract: The technology disclosed includes a system to group security alerts generated in a computer network and prioritize grouped security alerts for analysis. The system includes graphing entities in the computer network as entities connected by one or more edges. Native scores for pending alerts are assigned to nodes or to edges between the nodes. A connection type is assigned to each edge and weights are assigned to edges representing relationship strength between the nodes. The technology disclosed includes traversing the graph starting at starting nodes and propagating native scores through and to neighboring nodes connected by the edges. Aggregate score for a visited node is calculated by accumulating propagated scores at visited nodes with their respective native scores. The technology disclosed forms clusters of connected nodes in the graph that have a respective aggregate score above a selected threshold. The clusters are ranking and prioritized for analysis.

Abstract: The invention relates to a climate control device for controlling the temperature and humidity of air supplied to colonies of insects cultured in an industrial scale insect farm. In particular, the invention relates to a controllable air conditioning system comprising a network of pipes connecting at least one cluster comprising at least one insect farming cage, such that air is conditionable in the cages at the cluster level. More specifically, the invention relates to a system comprising a central main air conditioning facility providing temperature conditioned air and absolute air humidity conditioned air to each of a number of local air conditioning devices, each separate local air conditioning device providing temperature conditioned air and absolute air humidity conditioned air to each of a plethora of clusters of insect breeding cages separately, said cages housed in an temperature conditioned farming room.