Abstract: The present disclosure provides a semiconductor wafer. The semiconductor wafer includes: a scribe line between a first row of dies and a second row of dies, and a benchmark circuit disposed on the scribe line. The benchmark circuit includes a first switching circuit, a first process control monitoring (PCM) device and a second PCM device coupled to the first switching circuit, and a second switching circuit. The first switching circuit is configured to selectively couple the first PCM device and the second PCM device to receive a test signal, wherein the first PCM device and the second PCM device are configured to output a first output signal and a second output signal in response to the test signal, respectively. The second switching circuit is configured to selectively couple the first PCM device and the second PCM device to output the first output signal or the second output signal.

Abstract: A matching design method of static stiffness for a combined box body structure of a large reducer is provided, including the following steps, building a transmission system model and an initial structure model and obtaining load data; performing a statics analysis; obtaining primary design variables and design responses; constructing design variables; constructing a static stiffness matching target of a combined box body; constructing an objective function; setting constraint conditions; constructing a response surface proxy model; constructing a static stiffness matching optimization model of combined box body; obtaining optimal design variables and obtaining an optimal structure model of the box body; performing the statics analysis on the optimal structure model of the box body, and performing a contrastive analysis with statics analysis results of the corrected box body two-dimensional unit finite element model to confirm optimization effects.

Abstract: The present invention provides a GPS interference source positioning method, apparatus, electronic device, and readable storage medium, which relates to the technical field of wireless communications.

Abstract: The present disclosure provides a semiconductor wafer. The semiconductor wafer includes: a scribe line between a first row of dies and a second row of dies; and a benchmark circuit disposed adjacent to the scribe line and electrically coupled to a first conductive contact and a second conductive contact. The benchmark circuit includes a first device-under-test (DUT); a second DUT; a first switching circuit configured to selectively couple the first DUT and the second DUT to the first conductive contact; and a second switching circuit configured to selectively couple the first DUT and the second DUT to the second conductive contact.

Abstract: In response to receiving a request for an identity key from a first entity, an identity key for the first entity is generated. A first request from the first entity to replicate a set of data is received. The generated identity key for the first entity is added to the metadata of the set of data requested to be replicated. A determination is made whether a replication rule exists for the first entity. In response to determining that a replication rule exists for the first entity, the set of data is replicated according to the replication rule for the first entity.

Abstract: Various implementations disclosed herein include devices, systems, and methods that generates a three-dimensional (3D) model of an object based on images and tracked positions of a device during acquisition of the images. For example, an example process may include acquiring sensor data during movement of the device in a physical environment including an object, the sensor data including images of a physical environment acquired via a camera on the device, identifying the object in at least some of the images, tracking positions of the device during acquisition of the images based on identifying the object in the at least some of the images, the positions identifying positioning of the device with respect to a coordinate system defined based on a position and orientation of the object, and generating a 3D model of the object based on the images and positions of the device during acquisition of the images.

Abstract: A system and method for safety testing a host autonomous vehicle (AV). This method includes: generating a trained machine learning (ML) agent and testing the host AV in an environment that includes one or more background vehicles configured to operate according to the trained ML agent. The ML agent is generated by: (i) obtaining a testing state model having non-safety-critical states and safety-critical states, (ii) editing the testing state model to obtain an edited testing state model that omits data concerning the non-safety-critical states, and (iii) training a ML agent using the edited state testing model so as to generate the trained ML agent.

Abstract: A computer-implemented method comprises initializing a plurality of segment lists. Each segment list of the plurality of segment lists corresponds to a respective one of a plurality of disk drives. Each segment list divides storage space of the respective disk drive into a plurality of segments. The method further comprises, for each of the plurality of disk drives, identifying one or more candidate segments from the plurality of segments; calculating a respective segment distance variance for one or more combinations of identified candidate segments. Each combination of identified candidate segments includes one candidate segment for each of the plurality of disk drives. The method further comprises selecting a combination of the one or more combinations of identified candidate segments having the smallest respective segment distance variance; and storing data on the plurality of disk drives according to the selected combination of identified candidate segments.

Abstract: Various implementations disclosed herein include devices, systems, and methods that generates a three-dimensional (3D) model of an object based on images and tracked positions of a device during acquisition of the images. For example, an example process may include acquiring sensor data during movement of the device in a physical environment including an object, the sensor data including images of a physical environment acquired via a camera on the device, identifying the object in at least some of the images, tracking positions of the device during acquisition of the images based on identifying the object in the at least some of the images, the positions identifying positioning of the device with respect to a coordinate system defined based on a position and orientation of the object, and generating a 3D model of the object based on the images and positions of the device during acquisition of the images.

Abstract: A computer-implemented method comprises initializing a plurality of segment lists. Each segment list of the plurality of segment lists corresponds to a respective one of a plurality of disk drives. Each segment list divides storage space of the respective disk drive into a plurality of segments. The method further comprises, for each of the plurality of disk drives, identifying one or more candidate segments from the plurality of segments; calculating a respective segment distance variance for one or more combinations of identified candidate segments. Each combination of identified candidate segments includes one candidate segment for each of the plurality of disk drives. The method further comprises selecting a combination of the one or more combinations of identified candidate segments having the smallest respective segment distance variance; and storing data on the plurality of disk drives according to the selected combination of identified candidate segments.

Abstract: A bicycle folding mechanism includes a frame, a stem, and a front fork. The frame includes a front tube at an end thereof. The stem is inserted into the front tube. The stem is connected and pivotal relative to the frame. The stem has an end, which is adjacent to the frame, connected with a connecting seat. The front fork includes at least one connecting end and at least one front end on opposite ends. The at least one connecting end is connected and pivotal relative to the connecting seat such that the front fork is pivotal relative to the connecting seat. The front fork is pivotal between a deployed position in which the at least one front end is positioned away from the frame and a folded position in which the at least one front end is positioned adjacent to the frame.

Abstract: In response to receiving a request for an identity key from a first entity, an identity key for the first entity is generated. A first request from the first entity to replicate a set of data is received. The generated identity key for the first entity is added to the metadata of the set of data requested to be replicated. A determination is made whether a replication rule exists for the first entity. In response to determining that a replication rule exists for the first entity, the set of data is replicated according to the replication rule for the first entity.

Abstract: Embodiments of the present disclosure relate to methods, systems, and computer program products for storage management. In one embodiment, a computer-implemented method is disclosed. According to the method, in response to receiving a request related to managing the at least one directory entry in the file system, at least one directory entry in a file system may be determined by a file system in a storage system, where each of the at least one directory entry is represented by digital numbers. An index for each of the at least one directory entry may be managed in the file system by the file system, where an index key for the index comprises the digital numbers themselves. In other embodiments, a computer-implemented system and a computer program product for managing the index are disclosed.

Abstract: Data-locality-aware task scheduling on hyper-converged computing infrastructures is provided. A plurality of data blocks referenced in an input/output (I/O) request are identified. The I/O request is based on scheduling logic that executes within a container that is deployed on a hyper-converged infrastructure. A block-location mapping table is scanned using a data block identifier that is associated with a present data block of the plurality of data blocks. Physical node(s) of the hyper-converged infrastructure that store the present data block are identified. A container-instance mapping table is scanned using one or more physical node identifiers that are associated with the physical node(s) that store the present data block. Container(s) deployed on physical node(s) that store the present data block are identified. The scheduling logic is provided with a list of identifier(s) that are respectively associated with the containers that are deployed on the physical node(s) that store the present data block.

Abstract: Detecting deadlock in a distributed computing environment. Potential deadlocks between resources of nodes in a computing cluster by determining resource reverse pairs of the resources for each transaction from trace or log files using data analytics. The potential deadlocks are identified offline by matching a global or local resource between the nodes in sub-transactions of each transaction as recursively identified from a transaction resource chain.

Abstract: An approach, for fileset based data locality management in Distributed File Systems. A data locality manager receives fileset identifiers and associated block allocation information, for storing in data block locality tables. The data locality manager determines data block locality factors based on the fileset identifiers and the block allocation information, creating a collection of the data block locality factors. The data locality manager stores the collection of the data block locality factors in the data block locality tables. The data locality manager receives the fileset identifiers for determining the collection of the data block locality factors associated to the fileset identifiers and outputs the collection of the data block locality factors.

Abstract: A bicycle folding mechanism includes a frame, a stem, and a front fork. The frame includes a front tube at an end thereof. The stem is inserted into the front tube. The stem is connected and pivotal relative to the frame. The stem has an end, which is adjacent to the frame, connected with a connecting seat. The front fork includes at least one connecting end and at least one front end on opposite ends. The at least one connecting end is connected and pivotal relative to the connecting seat such that the front fork is pivotal relative to the connecting seat. The front fork is pivotal between a deployed position in which the at least one front end is positioned away from the frame and a folded position in which the at least one front end is positioned adjacent to the frame.

Abstract: Embodiments of the present disclosure relate to methods, systems, and computer program products for storage management. In one embodiment, a computer-implemented method is disclosed. According to the method, in response to receiving a request related to managing the at least one directory entry in the file system, at least one directory entry in a file system may be determined by a file system in a storage system, where each of the at least one directory entry is represented by digital numbers. An index for each of the at least one directory entry may be managed in the file system by the file system, where an index key for the index comprises the digital numbers themselves. In other embodiments, a computer-implemented system and a computer program product for managing the index are disclosed.

Abstract: Embodiments for detecting deadlock in a distributed computing environment. Potential deadlocks between resources of nodes in a computing cluster by determining resource reverse pairs of the resources for each transaction from trace or log files using data analytics. The potential deadlocks are identified offline by matching a global or local resource between the nodes in sub-transactions of each transaction as recursively identified from a transaction resource chain.

Abstract: Data-locality-aware task scheduling on hyper-converged computing infrastructures is provided. A plurality of data blocks referenced in an input/output (I/O) request are identified. The I/O request is based on scheduling logic that executes within a container that is deployed on a hyper-converged infrastructure. A block-location mapping table is scanned using a data block identifier that is associated with a present data block of the plurality of data blocks. Physical node(s) of the hyper-converged infrastructure that store the present data block are identified. A container-instance mapping table is scanned using one or more physical node identifiers that are associated with the physical node(s) that store the present data block. Container(s) deployed on physical node(s) that store the present data block are identified. The scheduling logic is provided with a list of identifier(s) that are respectively associated with the containers that are deployed on the physical node(s) that store the present data block.