Abstract: Disclosed systems, apparatuses, and methods enable remotely controlling robotic-assisted medical systems, such as robotic-assisted surgery systems, for performing remote robotic-assisted medical procedures. Disclosed approaches provide a secure, efficient, and dynamically-created virtual network for connecting physician consoles and robotic-assisted medical systems. Disclosed approaches improve efficiency, security, scalability, and reliability of remote robotic-assisted medical procedures.

Abstract: Disclosed systems, apparatuses, and methods enable remotely controlling robotic-assisted medical systems, such as robotic-assisted surgery systems. Disclosed approaches provide a scalable, flexible, and efficient network for connecting physician consoles and robotic-assisted medical procedure systems. Disclosed approaches improve deployment and safety of robotic-assisted medical procedures.

Abstract: Disclosed systems, apparatuses, and methods enable remotely controlling robotic-assisted medical systems, such as robotic-assisted surgery systems, for performing remote robotic-assisted medical procedures. Disclosed approaches provide a secure, efficient, and dynamically-created virtual network for connecting physician consoles and robotic-assisted medical systems. Disclosed approaches improve efficiency, security, scalability, and reliability of remote robotic-assisted medical procedures.

Abstract: There is disclosed in one example a computing apparatus, including: a hardware platform including a processor circuit and a memory circuit; first means for accessing a machine learning engine; second means for accessing a user interface; and instructions encoded within the memory to instruct the processor to: load into the machine learning engine via the first means an object prevalence model, including an enterprise-specific prevalence model; provide to the machine learning engine an object set from the enterprise; identify an enterprise-novel object from the object set; solicit and receive via the second means user-sourced feedback for the enterprise-novel object; and act according to the user-sourced feedback.

Abstract: Systems and methods are provided for feeding an electrode into a container using an electrode feeder system. A fixed gripper is coupled to a support frame at or near a fixed base plate. A moveable gripper is positioned at or near a lower limit switch located at or near a base plate. The moveable gripper is coupled to one or more sliders that are coupled to the support frame. An electrode is positioned through the fixed gripper and the moveable gripper, and the fixed gripper is closed around the electrode. The moveable gripper is closed around the electrode and the fixed gripper is opened. The moveable gripper is lowered along a length of the electrode feeder system causing the electrode to be lowered into the container. The steps are repeated until a process occurring in the container is complete or the electrode is consumed.

Abstract: Systems and methods are disclosed herein for ion exchange wherein process fluid is injected at multiple points within the ion exchange vessel simultaneously, allowing the contaminants and/or the contaminated process fluid to be distributed homogenously throughout the ion exchange media. These systems and methods may be implemented in one or more of fixed, mobile, and modular embodiments.

Abstract: Systems and methods are provided for feeding an electrode into a container using an electrode feeder system. A fixed gripper is coupled to a support frame at or near a fixed base plate. A moveable gripper is positioned at or near a lower limit switch located at or near a base plate. The moveable gripper is coupled to one or more sliders that are coupled to the support frame. An electrode is positioned through the fixed gripper and the moveable gripper, and the fixed gripper is closed around the electrode. The moveable gripper is closed around the electrode and the fixed gripper is opened. The moveable gripper is lowered along a length of the electrode feeder system causing the electrode to be lowered into the container. The steps are repeated until a process occurring in the container is complete or the electrode is consumed.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to determine mutex entropy for malware classification. An example apparatus includes interface circuitry to access a mutex associated with a software application, the mutex to include a mutex identifier string, normalizer circuitry to normalize the mutex identifier string, character probability circuitry to determine character probabilities of characters within the normalized mutex identifier string, the character probabilities based on a historical mutex character distribution, entropy calculator circuitry to calculate an entropy value for the mutex based on the character probabilities, classifier circuitry to classify the mutex as clean or malicious based on the entropy value, and protector circuitry to mitigate malicious attacks based on the classification.

Abstract: Systems and methods are disclosed herein for ion exchange wherein process fluid is injected at multiple points within the ion exchange vessel simultaneously, allowing the contaminants and/or the contaminated process fluid to be distributed homogeneously throughout the ion exchange media. These systems and methods may be implemented in one or more of fixed, mobile, and modular embodiments.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to determine mutex entropy for malware classification. An example apparatus includes interface circuitry to access a mutex associated with a software application, the mutex to include a mutex identifier string, normalizer circuitry to normalize the mutex identifier string, character probability circuitry to determine character probabilities of characters within the normalized mutex identifier string, the character probabilities based on a historical mutex character distribution, entropy calculator circuitry to calculate an entropy value for the mutex based on the character probabilities, classifier circuitry to classify the mutex as clean or malicious based on the entropy value, and protector circuitry to mitigate malicious attacks based on the classification.

Abstract: There is disclosed in one example a computing apparatus, including: a hardware platform including a processor circuit and a memory circuit; first means for accessing a machine learning engine; second means for accessing a user interface; and instructions encoded within the memory to instruct the processor to: load into the machine learning engine via the first means an object prevalence model, including an enterprise-specific prevalence model; provide to the machine learning engine an object set from the enterprise; identify an enterprise-novel object from the object set; solicit and receive via the second means user-sourced feedback for the enterprise-novel object; and act according to the user-sourced feedback.