Techniques for managing files in a computer system are provided. According to one technique, an association is established between a type of file system operation, a file, and an interested entity. It is detected when that type of file system operation is performed on the file. In response to detecting that that type of file system operation is performed on the file, a message is sent to the interested entity.

Event notification system tied to a file system

An apparatus and method for converting a capacitance measured on a sensor element to a digital code. The apparatus may include a switching capacitor as a sensor element of a sensing device, and a sigma-delta modulator coupled to the sensor element to convert a capacitance measured on the sensor element to a digital code. The switching capacitor is in a feedback loop of the sigma-delta modulator. The method may include measuring a capacitance on a sensor element of a sensing device using a sigma-delta modulator, and converting the capacitance measured on the sensor element to a digital code.

Capacitance to code converter with sigma-delta modulator

A method for locating a conductive object at a touch-sensing surface may include detecting a first resolved location for the conductive object at the touch-sensing surface based on a first scan of the touch-sensing surface, predicting a location for the conductive object, and determining a second resolved location for the conductive object by performing a second scan of a subset of sensor elements of the touch-sensing surface, wherein the subset of sensor elements is selected based on the predicted location of the conductive object.

Predictive touch surface scanning

A switch circuit and method is described. In one embodiment, the switch circuit is configured to couple each of a plurality of plurality of capacitive sense elements and a plurality of capacitance sensors in different modes. In a first mode, the switch circuit is configured to couple each of the plurality of capacitance sensors to a group of two or more of the plurality of capacitive sense elements. In a second mode, the switch circuit is configured to couple the plurality of capacitance sensors to individual ones of the two or more of the plurality of capacitive sense elements in one of the groups.

Apparatus and method for reducing average scan rate to detect a conductive object on a sensing device

While machine learning and artificial intelligence have long been applied in networking research, the bulk of such works has focused on supervised learning. Recently, there has been a rising trend of employing unsupervised machine learning using unstructured raw network data to improve network performance and provide services, such as traffic engineering, anomaly detection, Internet traffic classification, and quality of service optimization. The growing interest in applying unsupervised learning techniques in networking stems from their great success in other fields, such as computer vision, natural language processing, speech recognition, and optimal control (e.g., for developing autonomous self-driving cars). In addition, unsupervised learning can unconstrain us from the need for labeled data and manual handcrafted feature engineering, thereby facilitating flexible, general, and automated methods of machine learning. The focus of this survey paper is to provide an overview of applications of unsupervised learning in the domain of networking. We provide a comprehensive survey highlighting recent advancements in unsupervised learning techniques, and describe their applications in various learning tasks, in the context of networking. We also provide a discussion on future directions and open research issues, while identifying potential pitfalls. While a few survey papers focusing on applications of machine learning in networking have previously been published, a survey of similar scope and breadth is missing in the literature. Through this timely review, we aim to advance the current state of knowledge, by carefully synthesizing insights from previous survey papers, while providing contemporary coverage of the recent advances and innovations.

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Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges

A pulse width modulator ( 100 ) and method that facilitates high resolution pulse width modulation is provided. The pulse width modulator ( 100 ) creates a pulse width modulated signal having a duty cycle that is proportional to a controllable delay in the modulator. The pulse width modulator combines a first digitally controllable delay ( 102 ) with a delay adjustment ( 104 ) to provide the controllable delay. In one embodiment, a digital counter ( 202 ) is used to provide coarse delay, with the delay adjustment device ( 210 ) coupled to the digital counter ( 202 ) to provide the fine, high resolution, delay control. Together the digital counter ( 202 ) and delay adjustment device ( 210 ) provide high resolution pulse width modulation. In one particular implementation, the analog delay adjustment device ( 100 ) comprises a delay block ( 500 ) designed to provide delay adjustment that is selectively controllable by changing a capacitance in the device.

High resolution pulse width modulator

Interpreting sensor data in Internet-of-Things applications is a challenging problem particularly in embedded systems. We consider sensor data analytics where machine learning algorithms can be fully implemented on an embedded processor/sensor board. We develop an efficient real-time realization of a Gaussian mixture model (GMM) for execution on the NXP FRDM-K64F embedded sensor board. We demonstrate the design of a customized program and data structure that generates real-time sensor features, and we show details and training/classification results for select IoT applications. The integrated hardware/software system enables real-time data analytics and continuous training and re-training of the machine learning (ML) algorithm. The real-time ML platform can accommodate several applications with lower sensor data traffic.

Integrating machine learning in embedded sensor systems for Internet-of-Things applications

A method for reducing programming or data errors generated by a new computer program or data set when the computer program updates or replaces an existing computer program. A set of baseline output records is generated by running the existing computer program on an input file (step 701). A set of revised output records is generated by running the new computer program with the input file (step 702). The baseline and revised output records are mapped to form an association between corresponding records (step 707). The associated records are compared using tolerance data stored in a control file to produce a plurality of difference records, a portion of which represents the programming or data errors (step 711). The difference records are examined to identify the portion of the difference records corresponding to the programming or data errors for editing the new computer program.

Smart compare tool and method

A mechanism by which a MEMS gyroscope sensor can be calibrated using data gathered from other sensors in a system incorporating the MEMS gyroscope sensor is provided. Data gathered from an accelerometer and a magnetometer in fixed orientation relative to the gyroscope is used to calculate changes in orientation of a system. A constant acceleration vector measured by the accelerometer and a constant magnetic vector measured by the magnetometer are used as reference vectors in a solution to Wahba's problem to calculate a rotation matrix providing the system's orientation with respect to those two constant vectors. By comparing changes in orientation from one time to a next time, measured rates of angular change can be calculated. The measured rates of angular change can be used along with observed gyroscope rates of angular change as input to a linear regression algorithm, which can be used to compute gyroscope trim parameters.

Systems and method for gyroscope calibration

Embodiments include systems that include at least one integrated circuit (IC) and methods for their testing. Each IC includes an input interconnect to receive an input signal, a test enable interconnect to receive a test enable signal, and a controller (e.g., a TAP controller) for performing testing of the integrated circuit based on values in at least one register (values corresponding to the input signal). Each IC also includes an input port and a multiplexer coupled to the first input interconnect, the at least one register, and the input port. The multiplexer is controllable to pass the input signal to the input port in response to non-assertion of the test enable signal, and to pass the input signal to the at least one register in response to assertion of the test enable signal. When the system includes multiple controllers, each controller may implement a different opcode-to-instruction mapping.

Michael E. Stanley

Papers

High resolution pulse width modulator

Integrating machine learning in embedded sensor systems for Internet-of-Things applications

Smart compare tool and method

Systems and method for gyroscope calibration

Methods and apparatus for testing multiple-IC devices