Abstract: Methods and systems are presented for classifying a particular user account as a fraudulent user account by analyzing links between the user account and two or more known fraudulent user accounts collectively. Attributes of the particular user account are compared against attributes of a plurality of known fraudulent accounts to determine that the particular user account has shared attributes with a first known fraudulent account and a second known fraudulent account. The shared attributes with the first known fraudulent account and the second known fraudulent account are analyzed collectively to determine a risk level for the particular user account. The risk level may indicate a likelihood that the particular user account corresponds to a fraudulent account.

Abstract: A 3D printing system for continuous fiber reinforced composite materials is provided. The 3D printing system does not require the fiber and resin to be premixed before they are used in 3D printing. Instead, the 3D printing system includes a guiding device that deposits fiber preform onto a build plate to form a predetermined shape, a preparation module that processes the fiber preform, a dispenser that dispenses a resin material on the fiber preform, a heater that applies heat to the mixture of the fiber preform and the resin materials to form a composite material, and a curing module that applies pressure and heat to cure the composite material.

Abstract: Methods and systems are presented for classifying a particular user account as a fraudulent user account by analyzing links between the user account and two or more known fraudulent user accounts collectively. Attributes of the particular user account are compared against attributes of a plurality of known fraudulent accounts to determine that the particular user account has shared attributes with a first known fraudulent account and a second known fraudulent account. The shared attributes with the first known fraudulent account and the second known fraudulent account are analyzed collectively to determine a risk level for the particular user account. The risk level may indicate a likelihood that the particular user account corresponds to a fraudulent account.

Abstract: A process for additive manufacturing of a nanocomposite is disclosed. The process includes providing a uniform filament comprising a carbon fiber material and a polymer binder; dispensing the uniform filament to form a preform architecture that defines a first 3-dimensional bulk structure having a first set of volume-defining dimensions; heating the preform architecture to remove the polymer binder, thereby forming a porous carbon scaffold; and incorporating a matrix material into the porous carbon scaffold to form a third 3-dimensional bulk structure. The carbon scaffold defines a second 3-dimensional bulk structure having a second bulk volume, wherein the second bulk volume is equal to the first bulk volume within a tolerance of 10%. A system for additive manufacturing of a fiber reinforced composite is also disclosed. The system has a filament dispenser; means for moving the filament dispenser; a heater; and a matrix material applicator.

Abstract: Provided are solid-state hybrid electrolytes. The hybrid electrolytes have a polymeric material layer, which may be a polymer copolymer layer or a gel polymer copolymer layer, disposed on at least a portion of an exterior surface or all of the exterior surfaces of a solid-state electrolyte. A hybrid electrolyte can form an interface with an electrode of an ion-conducting battery that exhibits desirable properties. The solid-state electrolyte can comprise a monolithic SSE body, a mesoporous SSE body, or an inorganic SSE having fibers et strands, which may be aligned. In the case of solid-state electrolytes that have strands, the strands can be formed using a sacrificial template. The hybrid solid-state electrolytes can be used in ion-conducting batteries, which may be flexible, ion-conducting batteries.

Abstract: Well data (e.g., well log) may be divided into multiple segments, and different samplings of data in the individual segments may be performed to increase the amount of data that is used to train a seismic inversion model. Synthetic well data may be generated from real well data to increase the amount of well data from which sampling is performed.

Abstract: Well data (e.g., well log) may be divided into multiple segments, and different samplings of data in the individual segments may be performed to increase the amount of data that is used to train a seismic inversion model. Synthetic well data may be generated from real well data to increase the amount of well data from which sampling is performed.

Abstract: The present invention discloses a prestressed-bolted dry-assembled segmental precast hybrid tower with grouting-free, comprising a top steel tower tube, a reverse self-balancing steal-concrete transition section, and a prestressed-bolted dry-assembled segmental precast concrete tower with grouting-free dry fast splicing and a gear reinforced wind turbine foundation; the steel tower tube, the steel-concrete transition section, the concrete tower tube and the hollow wind turbine foundation are integrally connected from top to bottom through a prestressed steel strand system to improve the overall bending resistance of the tower; the upper end of the prestressed steel strands is anchored to the steel-concrete transition section, and the lower end is anchored to the bottom face of the wind turbine foundation corbel; the concrete tower tube is composed of a number of segmental tapered precast concrete tower segments, which are grouting free spliced vertically, and the vertical splicing utilizes positioning pins to

Abstract: Machine learning techniques are used in combination with graph data structures to perform automated classification of accounts. Graphs may be constructed using a seed node and then expanded outward to second-degree nodes and third-degree nodes that are connected to a seed user account node via direct interaction between the accounts. Characterization information regarding the interaction between accounts can be stored in the graph (e.g., quantity of interactions, types of interactions) as well as other metrics and metadata. A classifier, using random forest or another technique, may be trained using a number of different graphs that can then be used to reach a determination as to whether a user account falls into one particular category or another. These techniques can identify accounts that may be violating terms of service, committing a security violation, and/or performing illegal actions in a way that is not ascertainable from human analysis.

Abstract: A 3D printing systems for continuous fiber reinforced composite materials is disclosed. The 3D printing system does not require the fiber and resin to be premixed before they are used in 3D printing. Instead, the 3D printing system includes a guiding device that deposits fiber preform onto a building plate to form a predetermined shape, a preparation module that processes the fiber preform, a dispenser that dispenses a resin material on the fiber preform, a heater that applies heat to the mixture of the fiber preform and the resin materials to form a composite material, and a curing module that applies pressure and heat to cure the composite material.

Abstract: Methods and systems are presented for classifying a particular user account as a fraudulent user account by analyzing links between the user account and two or more known fraudulent user accounts collectively. Attributes of the particular user account are compared against attributes of a plurality of known fraudulent accounts to determine that the particular user account has shared attributes with a first known fraudulent account and a second known fraudulent account. The shared attributes with the first known fraudulent account and the second known fraudulent account are analyzed collectively to determine a risk level for the particular user account. The risk level may indicate a likelihood that the particular user account corresponds to a fraudulent account.

Abstract: The present invention discloses a prestressed-bolted dry-assembled segmental precast hybrid tower with grouting-free, comprising a top steel tower tube, a reverse self-balancing steal-concrete transition section, and a prestressed-bolted dry-assembled segmental precast concrete tower with grouting-free dry fast splicing and a gear reinforced wind turbine foundation; the steel tower tube, the steel-concrete transition section, the concrete tower tube and the hollow wind turbine foundation are integrally connected from top to bottom through a prestressed steel strand system to improve the overall bending resistance of the tower; the upper end of the prestressed steel strands is anchored to the steel-concrete transition section, and the lower end is anchored to the bottom face of the wind turbine foundation corbel; the concrete tower tube is composed of a number of segmental tapered precast concrete tower segments, which are grouting free spliced vertically, and the vertical splicing utilizes positioning pins to

Abstract: Machine learning techniques are used in combination with graph data structures to perform automated classification of accounts. Graphs may be constructed using a seed node and then expanded outward to second-degree nodes and third-degree nodes that are connected to a seed user account node via direct interaction between the accounts. Characterization information regarding the interaction between accounts can be stored in the graph (e.g., quantity of interactions, types of interactions) as well as other metrics and metadata. A classifier, using random forest or another technique, may be trained using a number of different graphs that can then be used to reach a determination as to whether a user account falls into one particular category or another. These techniques can identify accounts that may be violating terms of service, committing a security violation, and/or performing illegal actions in a way that is not ascertainable from human analysis.

Abstract: Machine learning techniques are used in combination with graph data structures to perform automated classification of accounts. Graphs may be constructed using a seed node and then expanded outward to second-degree nodes and third-degree nodes that are connected to a seed user account node via direct interaction between the accounts. Characterization information regarding the interaction between accounts can be stored in the graph (e.g., quantity of interactions, types of interactions) as well as other metrics and metadata. A classifier, using random forest or another technique, may be trained using a number of different graphs that can then be used to reach a determination as to whether a user account falls into one particular category or another. These techniques can identify accounts that may be violating terms of service, committing a security violation, and/or performing illegal actions in a way that is not ascertainable from human analysis.

Abstract: Methods and systems are presented for classifying a particular user account as a fraudulent user account by analyzing links between the user account and two or more known fraudulent user accounts collectively. Attributes of the particular user account are compared against attributes of a plurality of known fraudulent accounts to determine that the particular user account has shared attributes with a first known fraudulent account and a second known fraudulent account. The shared attributes with the first known fraudulent account and the second known fraudulent account are analyzed collectively to determine a risk level for the particular user account. The risk level may indicate a likelihood that the particular user account corresponds to a fraudulent account.

Abstract: Disclosed is a method of fabricating a battery or battery component having a solid state electrolyte. A scaffold is provided, the scaffold comprising: a dense central layer comprising a dense electrolyte material, the dense central layer having a first surface, and a second surface opposite the first surface; a first porous layer comprising a first porous electrolyte material, the first porous layer disposed on the first surface of the dense central layer, the porous electrolyte material having a first network of pores therein; wherein each of the dense electrolyte material and the first porous electrolyte material are independently selected from garnet materials. Carbon is infiltrated into the first porous layer. Sulfur is also infiltrated into the first porous layer. The battery component may be used in a variety of battery configurations.

Abstract: Metal alloy layers on substrates. The metal-alloy layers (e.g., lithium-metal layers, sodium-metal layers, and magnesium-metal layers) can be disposed on, for example, a solid-state electrolyte material. The metal-alloy layers can be used in, for example, solid-state batteries. A metal alloy layer can be an anode or part of an anode of a solid state battery.

Abstract: The present disclosure relates to a method and system for determining an estimated time of arrival relating to a target trip. The method includes extracting, by a processor, sample characteristic data relating to a target trip, wherein the sample characteristic data comprises first feature data corresponding to a route relating to the target trip and second feature data corresponding to a link of the route; obtaining a prediction model for estimating time of arrival; and determining, by the processor, an estimated time of arrival (ETA) relating to the target trip based on the prediction model and the sample characteristic data.

Abstract: Provided are solid-state hybrid electrolytes. The hybrid electrolytes have a polymeric material layer, which may be a polymer/copolymer layer or a gel polymer/copolymer layer, disposed on at least a portion of an exterior surface or all of the exterior surfaces of a solid-state electrolyte. A hybrid electrolyte can form an interface with an electrode of an ion-conducting battery that exhibits desirable properties. The solid-state electrolyte can comprise a monolithic SSE body, a mesoporous SSE body, or an inorganic SSE having fibers or strands, which may be aligned. In the case of solid-state electrolytes that have strands, the strands can be formed using a sacrificial template. The hybrid solid-state electrolytes can be used in ion-conducting batteries, which may be flexible, ion-conducting batteries.

Abstract: Disclosed is a method of fabricating a battery or battery component having a solid state electrolyte. A scaffold is provided, the scaffold comprising: a dense central layer comprising a dense electrolyte material, the dense central layer having a first surface, and a second surface opposite the first surface; a first porous layer comprising a first porous electrolyte material, the first porous layer disposed on the first surface of the dense central layer, the porous electrolyte material having a first network of pores therein; wherein each of the dense electrolyte material and the first porous electrolyte material are independently selected from garnet materials. Carbon is infiltrated into the first porous layer. Sulfur is also infiltrated into the first porous layer. The battery component may be used in a variety of battery configurations.