Agilent Technologies

About: Agilent Technologies is a company organization based out in Santa Clara, California, United States. It is known for research contribution in the topics: Signal & Mass spectrometry. The organization has 7398 authors who have published 11518 publications receiving 262410 citations. The organization is also known as: Agilent Technologies, Inc..

Systems and methods of monitoring thin film deposition

Abstract: Systems and methods of monitoring thin film deposition are described. In one aspect, a thin film deposition sensor includes an acoustical resonator (e.g., a thin film bulk acoustical resonator) that has an exposed surface and is responsive to thin film material deposits on the exposed surface. A substrate clip may be configured to attach the thin film deposition sensor to a substrate. A transceiver circuit may be configured to enable the thin film deposition sensor to be interrogated wirelessly. A method of monitoring a thin film deposition on a substrate also is described.

Using eye detection for providing control and power management of electronic devices

Abstract: Eye detection is used as the basis for providing power management or other variations of operational parameters of a controlled device. The system includes an imager and eye detection processing which cooperate to detect light received from a person's eye. The eye detection processing generates an output that can be used for determinations regarding presence of one or more persons or presence of a specific person. This output is used as the basis for switching the controlled device between at least two power consumption states. Eye detection may also be used to allow a person to actively adjust operational conditions of the controlled device, since unnatural eye blinking patterns may be associated with particular commands.

A microscopic look at WiFi fingerprinting for indoor mobile phone localization in diverse environments

Abstract: WiFi fingerprinting has received much attention for indoor mobile phone localization. In this study, we examine the impact of various aspects underlying a WiFi fingerprinting system. Specifically, we investigate different definitions for fingerprinting and location estimation algorithms across different indoor environments ranging from a multi-storey office building to shopping centers of different sizes. Our results show that the fingerprint definition is as important as the choice of location estimation algorithm and there is no single combination of these two that works across all environments or even all floors of a given environment. We then consider the effect of WiFi frequency bands (e.g., 2.4GHz and 5GHz) and the presence of virtual access points (VAPs) on location accuracy with WiFi fingerprinting. Our results demonstrate that 5GHz signals are less prone to variation and thus yield more accurate location estimation. We also find that the presence of VAPs improves location estimation accuracy.

Thin film bulk acoustic resonator (FBAR) and inductor on a monolithic substrate and method of fabricating the same

Abstract: An apparatus having both a resonator and an inductor fabricated on a single substrate and a method of fabricating the apparatus are disclosed. The apparatus includes a resonator and an inductor that is connected to the resonator. Both the resonator and the inductor are fabricated over their respective cavities to produce a high Q-factor filter circuit.

Optical screen pointing device with inertial properties

Abstract: An apparatus for controlling the position of a screen pointer for an electronic device having a display screen includes an imaging surface against which a portion of the tip of a human digit may be placed. A light source illuminates that portion of the tip of the digit that is placed against the imaging surface, thereby generating reflected images. The apparatus includes a motion transducer. A lens receives the reflected images and directs the reflected images onto the motion transducer. The motion transducer generates digital representations of the reflected images. The motion transducer generates a first set of movement data based on the digital representations of the reflected images. The first set of movement data is indicative of motion of the tip of the digit across the imaging surface. A controller generates a second set of movement data when the tip of the human digit is removed from the imaging surface. The second set of movement data is indicative of motion of the tip of the digit across the imaging surface prior to removal of the tip.