Abstract: Disclosed are various embodiments for automated testing of systems and applications. A first computing device may be in data communication with a second computing device. The first computing device can receive a fault instruction specifying receive a fault instruction specifying a fault to inject into a virtual compute instance, parameters for the fault, a duration of the fault, and an identifier of the virtual compute instance. The first computing device can then send a command to a second computing device that hosts the virtual compute instance, wherein the command specifies at least the fault, the parameters for the fault, and the virtual compute instance. In turn, the second computing device can receive the command from the first computing device, save a pre-fault state of the virtual compute instance, and then introduce the fault into the virtual compute instance.

Abstract: Techniques for presence-detection devices to vary presence-detection sensitivity to detect different types of movements by objects, such as major movements and minor movements, using ultrasonic signals. The devices detect movement of a person in an environment by emitting ultrasonic signals into the environment, and characterizing the change in the frequency, or the Doppler shift, of the reflections of the ultrasonic signals off the person caused by the movement of the person relative to the presence-detection devices. The presence-detection devices may control the presence-detection sensitivity in order to detect major movements, such as a user walking in a room, as well as objects minor movements, such as a user typing at a computer. By adjusting the presence-detection sensitivity, the devices are able to improve the overall accuracy of detecting the presence of users in an environment.

Abstract: Systems, methods, and computer-readable media are disclosed for validating a machine learning model. In one aspect, a machine learning model validation system can receive a test machine learning model, analyze an output of the test machine learning model, determine a degree of similarity between the test machine learning model and one or more machine learning models stored in a database based on the output of the test machine learning model, and determining whether the test machine learning model complies with a set of validation rules based on the degree of the similarity with respect to one or more thresholds.

Abstract: A LIDAR system has one or more light splitters and multiple light combiners. The LIDAR system also has multiple optical pathways through which light signals travel. The optical pathways include delay pathways that each extends from one of the one or more splitters to one of the light combiners. The optical pathways include expedited pathways that each extends from one of the splitters to one of the light combiners. Each of the light combiners has one of the delay pathways and one of the expedited pathways extending to the light combiner. The delay pathways and the expedited pathways are configured such that the delay pathway to each light combiner is longer than the expedited pathway to the same light combiner. Each of the delay pathways has a common portion and a separated portion. The common portion of each delay pathway is shared by the other delay pathways. In contrast, the separated portion of a delay pathways is not shared with the other delay pathways.

Abstract: The present disclosure relates to the technical field of semiconductors, and provides a method and an apparatus for determining an address mapping relationship, and a storage medium. The method for determining an address mapping relationship includes: obtaining a mapping relationship table between preset addresses and DRAM physical addresses under a preset condition; and analyzing values of bit addresses in the DRAM physical address according to a first preset rule, to determine an attribute of each bit address in the DRAM physical address, where the attribute is used for representing an address field of the DRAM physical address.

Abstract: The imaging system has a photonic circuit chip that includes multiple cores that each includes a port through which an outgoing optical signal exits the photonic circuit chip. Each of the cores is configured such that the outgoing signal exits the photonic circuit chip traveling toward a location that is above or below the photonic circuit chip. Additionally, each of the cores is configured to combine light from one of the outgoing signals with a reference signal so as to generate a signal beating at a beat frequency. The imaging system also includes electronics that use the beat frequencies from the cores to calculate data that indicates a radial velocity and/or distance between the system and one or more objects located outside of the system.

Abstract: A computer storage device having a host interface, a controller, non-volatile storage media, and firmware. The firmware instructs the controller to: allocate a named portion of the non-volatile storage device; generate, according to a first block size, first block-wise mapping data; translate, using the first block-wise mapping data, logical addresses defined in the named portion to logical addresses defined for the entire non-volatile storage media, which can then be further translated to physical addresses in a same way for all named portions; determine a second block size; generate, according to the second block size, second block-wise mapping data; translate, using the second block-wise mapping data, the logical addresses defined in the named portion to the logical addresses defined for the entire non-volatile storage media.

Abstract: Methods, systems, and devices for an interactive environmental control system are described. In some examples, operating temperatures for individual zones of an environment may be determined based on inputs received from occupants of the respective zones. For example, a building may be separated into zones, and environmental conditions at each zone may be monitored and adjusted independently. Each occupant of a zone may update their environmental preference and the system may utilize the user inputs to set and adjust an operating temperature for the respective zone based on the occupants' preferences. In some examples, the system may implement machine learning techniques to predict and set operating conditions for the zones based on inputs, such as a history of inputs, from building occupants (e.g., from occupants of a respective zone).

Abstract: Techniques to reduce overhead in a direct memory access (DMA) engine can include processing descriptors from a descriptor queue to obtain a striding configuration to generate tensorized memory descriptors. The striding configuration can include, for each striding dimension, a stride and a repetition number indicating a number of times to repeat striding in the corresponding striding dimension. One or more sets of tensorized memory descriptors can be generated based on the striding configuration. Data transfers are then performed based on the generated tensorized memory descriptors.

Abstract: A magazine ammunition unloader may include a body comprising: a magazine loading conduit adapted to receive a magazine containing ammunitions and the ammunitions contained in the magazine; and an ammunition ejecting conduit connected to the magazine loading conduit; and a wheel housed in the body, the wheel comprising a tooth adapted to push one at the time the ammunitions from the magazine into the ammunition ejecting conduit; and driving means adapted to drive the wheel, thereby ejecting one at the time the ammunitions from the magazine.

Abstract: An edge computing device may control load devices and DER (distributed energy resource) devices. The edge computing device may be associated with an electric meter located at a premises or with a distribution transformer located at a secondary substation. The control of the load devices and DER devices may be based in part on forecasted pricing information that considers factors such as equipment ratings for distribution equipment, environmental conditions, historical patterns of generation and load, and user input.

Abstract: An autoclaving microplate washing system for cells and non-adhering three-dimensional (3D) cell cultures is provided. The autoclaving microplate washing system may include a dispensing pump; an aspirating peristaltic pump; and a processor configured to execute a cleaning control program, which when executed causes the autoclaving microplate washing system to independently control: the dispensing pump to control a first flow rate of a solution from a fluid reservoir through a plurality of dispense lines for output via the dispense pipes in microplate wells corresponding to positions of the dispense pipes; and the aspirating peristaltic pump to control a second flow rate of a waste solution through a plurality of aspiration lines for aspiration via aspiration pipes in microplate wells corresponding to positions of the aspiration pipes.

Abstract: The present disclosure relates to systems and techniques for developing APIs that utilize multiple pre-existing APIs. The present disclosure also relates to a user interface that allows for chaining APIs together as a function of multiple pre-existing APIs. The present disclosure also relates to security and authorization of a user to execute one or more APIs as part of an API chain.

Abstract: A candidate attribute combination of a first data set is identified, such that the candidate attribute combination meets a data type similarity criterion with respect to a collection of data types of sensitive information for which the first data set is to be analyzed. A collection of input features is generated for a machine learning model from the candidate attribute combination, including at least one feature indicative of a statistical relationship between the values of the candidate attribute combination and a second data set. An indication of a predicted probability of a presence of sensitive information in the first data set is obtained using the machine learning model.

Abstract: A system having a processing device and a controller, operatively connected to a memory sub-system via a communication channel, to: store information identifying an amount of available capacity of a buffer of the memory sub-system; transmit, through the communication channel to the memory sub-system, one or more write commands to store data in memory components of the memory sub-system, where the memory sub-system queues the one or more write commands in the buffer; update the information by deducting, from the amount of available capacity, an amount of buffer capacity used by the one or more write commands to generate a current amount of available capacity of the buffer; and determine whether to generate an information request to the memory sub-system based at least in part on the current amount of available capacity.

Abstract: Execution status of managed time series processing tasks may be tracked. Status of a time series processing task that operations on different portions of a time series may be respectively captured. A request for the status of one of the portions of the time series with respect to the time series processing task may be received. The status may be identified and returned. For failed tasks, a failure reason may be generated by the time series processing system and included in a response with a failure status.

Abstract: The present disclosure includes apparatuses, methods, and systems for data relocation in memory. An embodiment includes a controller, and a memory having a plurality of physical units of memory cells. Each of the physical units has a different sequential physical address associated therewith, a first number of the physical units have data stored therein, a second number of the physical units do not have data stored therein, and the physical address associated with each respective one of the second number of physical units is a different consecutive physical address in the sequence. The controller can relocate the data stored in the physical unit of the first number of physical units, whose physical address in the sequence is immediately before the first of the consecutive physical addresses associated with the second number of physical units, to the last of the consecutive physical addresses associated with the second number of physical units.

Abstract: Described herein are systems and methods for improving defect detection in an automated production process. The system comprises a memory that stores executable components and a processor, operatively coupled to the memory, that executes the executable components. The executable components comprise an automation defect component and a machine learning component. The automation defect component retrieves parametric data associated with the production process. The automation defect component provides the parametric data to a machine learning algorithm. The machine learning component generates common attributes between the defective items. The machine learning component identifies a set of common attributes shared between the defective items and a non-defective item. The machine learning component modifies the set of the common attributes shared between the defective items and the non-defective item. The machine learning component generates defect indicators based on the common attributes.

Abstract: Apparatuses and methods can be related to implementing a transformer neural network in a memory. A transformer neural network can be implemented utilizing a resistive memory array. The memory array can comprise programmable memory cells that can be programed and used to store weights of the transformer neural network and perform operations consistent with the transformer neural network.

Abstract: The present disclosure is directed to logic based read sample offset operations in a memory sub-system. A processing device performs a first read, a second read, and a third read of data from a memory devices using a first center value corresponding to a first read level threshold, a negative offset value, and a positive offset value, respectively. The processing device performs a XOR operation on results from the first and second reads to obtain a first value and a XOR operation on results from the second and third reads to obtain a second value. The processing device performs a first count operation on the first value to determine a first difference bit count and a second count operation on the second value to determine a second difference bit count. The processing device can store or output the first difference bit count and the second difference bit count.