Abstract: A modular, radio frequency (“RF”) system includes one or more directional antennas and is configured with both hardware and software components to enable the RF system to monitor (e.g., detect or track signals or objects) and/or interact with (e.g., track signals or objects, or transmit signals) objects in particular directions. The RF system includes one or more machine learning models to determine, based on received signals, one or more signals to transmit.

Abstract: A modular, radio frequency (“RF”) system includes one or more directional antennas and is configured with both hardware and software components to enable the RF system to monitor (e.g., detect or track signals or objects) and/or interact with (e.g., track signals or objects, or transmit signals) objects in particular directions. The RF system includes one or more machine learning models to determine, based on received signals, one or more signals to transmit.

Abstract: A modular, radio frequency (“RF”) system includes one or more directional antennas and is configured with both hardware and software components to enable the RF system to monitor (e.g., detect or track signals or objects) and/or interact with (e.g., track signals or objects, or transmit signals) objects in particular directions. The RF system includes one or more machine learning models to determine, based on received signals, one or more signals to transmit.

Abstract: A modular, radio frequency (“RF”) system includes one or more directional antennas and is configured with both hardware and software components to enable the RF system to monitor (e.g., detect or track signals or objects) and/or interact with (e.g., track signals or objects, or transmit signals) objects in particular directions. The RF system includes one or more machine learning models to determine, based on received signals, one or more signals to transmit.

Abstract: A modular, radio frequency (“RF”) system includes one or more directional antennas and is configured with both hardware and software components to enable the RF system to monitor (e.g., detect or track signals or objects) and/or interact with (e.g., track signals or objects, or transmit signals) objects in particular directions. The RF system includes one or more machine learning models to determine, based on received signals, one or more signals to transmit.

Abstract: A modular, radio frequency (“RF”) system includes one or more directional antennas and is configured with both hardware and software components to enable the RF system to monitor (e.g., detect or track signals or objects) and/or interact with (e.g., track signals or objects, or transmit signals) objects in particular directions. The RF system includes one or more machine learning models to determine, based on received signals, one or more signals to transmit.

Abstract: A modular, radio frequency (“RF”) system includes one or more directional antennas and is configured with both hardware and software components to enable the RF system to monitor (e.g., detect or track signals or objects) and/or interact with (e.g., track signals or objects, or transmit signals) objects in particular directions. The RF system includes one or more machine learning models to determine, based on received signals, one or more signals to transmit.

Abstract: A modular, radio frequency (“RF”) system includes one or more directional antennas and is configured with both hardware and software components to enable the RF system to monitor (e.g., detect or track signals or objects) and/or interact with (e.g., track signals or objects, or transmit signals) objects in particular directions. The RF system includes one or more machine learning models to determine, based on received signals, one or more signals to transmit.

Abstract: A modular, radio frequency (“RF”) system includes one or more directional antennas and is configured with both hardware and software components to enable the RF system to monitor (e.g., detect or track signals or objects) and/or interact with (e.g., track signals or objects, or transmit signals) objects in particular directions. The RF system includes one or more machine learning models to determine, based on received signals, one or more signals to transmit.

Abstract: Some embodiments include a plan analysis server system with a computing device that couples to a back-end database server including current plan data, and calculates an eligible employee total by counting the number of employees records in the current plan data. The operations also include totaling a plan asset size by summing account balances for all eligible employees, determining employees with non-zero deferral from the current plan data, and calculating a current participation rate by calculating the percentage of eligible employees with non-zero deferral. The current plan is displayed in a primary window as selected by the user from user input. The processor optionally processes a scenario display utilizing the eligible employee data and administrator input. The at least one scenario display is displayed as one or more layers on the current plan data and displayed in the primary window as selected by the user from the user input.

Abstract: A scissor type magnetic sensor having an improved back edge bias structure. The back edge bias structure extends beyond the sides of the sensor stack for improved bias moment and is formed on a flat topography that provide for improved magnetic biasing. The sensor is formed by a method that includes first defining a sensor width and then depositing a multi-layer insulation layer that includes a dielectric layer that is resistant to ion milling and the depositing a fill layer over the dielectric layer that is removable by ion milling. After the multi-layer insulation layer has been deposited the back edge (i.e. stripe height) of the sensor is formed by masking and ion milling. This ion milling removes portions of the non-magnetic, electrically insulating fill layer that extend beyond the stripe height and beyond the sides of the sensor, leaving the dielectric layer there-beneath.

Abstract: A scissor type magnetic sensor having an improved back edge bias structure. The back edge bias structure extends beyond the sides of the sensor stack for improved bias moment and is formed on a flat topography that provide for improved magnetic biasing. The sensor is formed by a method that includes first defining a sensor width and then depositing a multi-layer insulation layer that includes a dielectric layer that is resistant to ion milling and the depositing a fill layer over the dielectric layer that is removable by ion milling. After the multi-layer insulation layer has been deposited the back edge (i.e. stripe height) of the sensor is formed by masking and ion milling. This ion milling removes portions of the non-magnetic, electrically insulating fill layer that extend beyond the stripe height and beyond the sides of the sensor, leaving the dielectric layer there-beneath.

Abstract: A method for manufacturing a magnetic sensor that allows the sensor to be constructed with a very narrow track width and with smooth, well defined side walls. A tri-layer mask structure is deposited over a series of sensor layers. The tri-layer mask structure includes an under-layer, a Si containing hard mask deposited over the under-layer and a photoresist layer deposited over the Si containing hard mask. The photoresist layer is photolithographically patterned to define a photoresist mask. A first reactive ion etching is performed to transfer the image of the photoresist mask onto the Si containing hard mask. The first reactive ion etching is performed in a chemistry that includes CF4, CHF3, O2, and He. A second reactive ion etching is then performed in an oxygen chemistry to transfer the image of the Si containing hard mask onto the under-layer, and an ion milling is performed to define the sensor.

Abstract: A method for manufacturing a magnetic sensor that allows the sensor to be constructed with a very narrow track width and with smooth, well defined side walls. A tri-layer mask structure is deposited over a series of sensor layers. The tri-layer mask structure includes an under-layer, a Si containing hard mask deposited over the under-layer and a photoresist layer deposited over the Si containing hard mask. The photoresist layer is photolithographically patterned to define a photoresist mask. A first reactive ion etching is performed to transfer the image of the photoresist mask onto the Si containing hard mask. The first reactive ion etching is performed in a chemistry that includes CF4, CHF3, O2, and He. A second reactive ion etching is then performed in an oxygen chemistry to transfer the image of the Si containing hard mask onto the under-layer, and an ion milling is performed to define the sensor.

Abstract: A method for measuring recession in a wafer undergoing an asymmetrical ion mill process. The method includes the formation of first and second reference features and possibly a dummy feature. The reference features are constructed such that the location of the midpoint between them is unaffected by the asymmetrical ion mill. By measuring the distance between a portion of the dummy feature and the midpoint between the reference features, the amount of recession of the dummy feature can be measured. The measurement can be used to calculate the relative location of the flare to the read sensor rear edge through overlay information. The reference features can be constructed as a pair of isosceles triangles with apexes that face one another. By keeping the angles of the sides of the features steep (ie.

Abstract: A corrosive composition, such as an alkaline aqueous carbon dispersion, a cleaner, a cleaner conditioner, or a conditioner, comprises a corrosion inhibitor, e.g., benzotriazole. The corrosion inhibitor is present in an amount effective to reduce or stop the dissolution of metal from a metallic surface, such as a printed circuit board, in contact with the composition. A method to reduce or stop the dissolution of metal from a metallic surface in contact with a corrosive composition, and a method to stabilize or recover a corrosive composition containing metal contaminants by adding an effective amount of a corrosion inhibitor to the corrosive composition.

Abstract: A corrosive composition, such as an alkaline aqueous carbon dispersion, a cleaner, a cleaner conditioner, or a conditioner, comprises a corrosion inhibitor, e.g., benzotriazole. The corrosion inhibitor is present in an amount effective to reduce or stop the dissolution of metal from a metallic surface, such as a printed circuit board, in contact with the composition. A method to reduce or stop the dissolution of metal from a metallic surface in contact with a corrosive composition, and a method to stabilize or recover a corrosive composition containing metal contaminants by adding an effective amount of a corrosion inhibitor to the corrosive composition.

Abstract: A method of making and using thin film calibration features is described. To fabricate a calibration standard according to the invention raised features are first formed from an electrically conductive material with a selected atomic number. A conformal thin film layer is deposited over the exposed sidewalls of the raised features. The sidewall material is selected to have a different atomic number and is preferably an nonconductive such as silicon dioxide or alumina. After the nonconductive material deposition, a controlled directional RIE process is used to remove the insulator layer deposited on the top and bottom surface of the lines and trenches. The remaining voids between the sidewalls of the raised features are filled with a conductive material. The wafer is then planarized with chemical mechanical planarization (CMP) to expose the nonconductive sidewall material on the surface. The nonconductive sidewall material will be fine lines embedded in conductive material.

Abstract: A corrosive composition, such as an alkaline aqueous carbon dispersion, a cleaner, a cleaner conditioner, or a conditioner, comprises a corrosion inhibitor, e.g., benzotriazole. The corrosion inhibitor is present in an amount effective to reduce or stop the dissolution of metal from a metallic surface, such as a printed circuit board, in contact with the composition. A method to reduce or stop the dissolution of metal from a metallic surface in contact with a corrosive composition, and a method to stabilize or recover a corrosive composition containing metal contaminants by adding an effective amount of a corrosion inhibitor to the corrosive composition.

Abstract: The method for controlling the depth of polishing during a CMP process involves the deposition of a polishing stop layer at an appropriate point in the device fabrication process. The stop layer is comprised of a substance that is substantially more resistant to polishing with a particular polishing slurry that is utilized in the CMP process than a polishable material layer. Preferred stop layer materials of the present invention are tantalum and diamond-like carbon (DLC), and the polishable layer may consist of alumina. In one embodiment of the present invention the stop layer is deposited directly onto the top surface of components to be protected during the CMP process. A polishable layer is thereafter deposited upon the stop layer, and the CMP polishing step removes the polishable material layer down to the portions of the stop layer that are deposited upon the top surfaces of the components. The stop layer is thereafter removed from the top surface of the components.