Fujitsu Corporation

Facebook, Inc.

B Thomas Adler

David Loren Marvit

Jawahar Jain

Albert H M Reinhardt

Stergios Stergiou

Hitoshi Matsumoto

Rajalakshmi Balakrishnan

Alexander Gilman

Alex Gilman

Yannis Labrou

John J Sidorowich

Albert C Braun

Bruce A Wilcox

Albert Reinhardt

Sahil Rihan

Madan Bahadur

Srishti Srivastava

Albert HM Reinhardt

It is determined whether an installed firmware of a device matches a reference firmware for the device. In response to a determination that the installed firmware of the device does not match the reference firmware for the device, different types of content sections of the installed firmware of the device are extracted. At least one of the content sections is identified as a dynamic section. A portion of the installed firmware selected to exclude at least the dynamic section is compared with a corresponding portion of the reference firmware to determine a comparison result. A security action is performed based at least in part on the comparison result.

Detecting malicious firmware modification

According to one embodiment of the present invention, a method for selecting metadata for sensor data streams may be provided. The method may include receiving a first sensor data stream associated with a user. The first data stream may be generated by one or more sensors co-located with the user. A plurality of tags that are each associated with one or more sensor value ranges may be accessed. A first tag may be selected from the plurality of tags according to a relationship between the first sensor data stream and the one or more sensor value ranges associated with the first tag. The method may further include facilitating reporting of the first tag.

Selecting metadata for sensor data streams

In one embodiment, modeling topics includes accessing a corpus comprising documents that include words. Words of a document are selected as keywords of the document. The documents are clustered according to the keywords to yield clusters, where each cluster corresponds to a topic. A statistical distribution is generated for a cluster from words of the documents of the cluster. A topic is modeled using the statistical distribution generated for the cluster corresponding to the topic.

Modeling topics using statistical distributions

In particular embodiments, a method includes accessing data streams from a first group of physiological sensors monitoring a person, a second group of deconfounding sensors monitoring the person, and a third group of sensors monitoring a stressor, analyzing data sets collected from the person when the person is exposed and not exposed to the stressor, and determining a current stress factor for the stressor with respect to the person based on the analysis.

Calculating and monitoring a composite stress index

In one embodiment, a set of target search terms for a search is received. Candidate terms are selected, where a candidate term is selected to reduce an ontology space of the search. The candidate terms are sent to a computer to recommend the candidate terms as search terms. In another embodiment, a document stored in one or more tangible media is accessed. A set of target tags for the document is received. Terms are selected, where a term is selected to reduce an ontology space of the document. The terms are sent to a computer to recommend the terms as tags.

Recommending terms to specify ontology space

In particular embodiments, a method includes generating a 3D display of an avatar of a person, where the avatar can receive inputs identifying a type of a physiological event, a location of the physiological event in or on a person's body in three spatial dimensions, a time range of the physiological event, a quality of the physiological event, and rendering the physiological event on the avatar based on the inputs.

Recording and analyzing data on a 3D avatar

In particular embodiments, a method includes accessing an original data stream from a sensor, associating a timestamp with each of the samples in the data stream based on a system clock, and recording the original data stream with the associated timestamps.

Data aggregation platform

In particular embodiments, a method includes accessing data streams from at least two of an accelerometer, a heart-rate monitor, a blood-pressure monitor, a pulse oximeter, or a mood sensor monitoring a person, analyzing data sets collected from the person when the person is engage and not engaged in a therapy, and determining a current stress factor for the therapy on the person based on the analysis.

Calculating and monitoring the efficacy of stress-related therapies

In particular embodiments, a method includes accessing data streams from an accelerometer and one or more of a heart-rate monitor, a blood-pressure monitor, a pulse oximeter, or a mood sensor monitoring a person, analyzing data sets collected from the person when the person is engaged in various activities, and determining a current stress index of the person based on the analysis.

Continuous monitoring of stress using accelerometer data

In particular embodiments, a method includes accessing data streams from a mood sensor and one or more of a heart-rate monitor, a blood-pressure monitor, a pulse oximeter, or an accelerometer monitoring a person, analyzing data sets collected from the person when the person is stressed and unstressed, analyzing the data sets, and determining a current stress index of the person based on the analysis.

Continuous monitoring of stress using self-reported psychological or behavioral data

In particular embodiments, a method includes accessing data streams from an environmental sensor, and one or more of a mood sensor, a heart-rate monitor, a blood-pressure monitor, a pulse oximeter, or an accelerometer monitoring a person, analyzing data sets collected from the person when the person is exposed to various environmental states, and determining a current stress index of the person based on the analysis.

Continuous monitoring of stress using environmental data

In certain embodiments, generating a hierarchy of terms includes accessing a corpus comprising terms. The following is performed for one or more terms to yield parent-child relationships: one or more parent terms of a term are identified according to directional affinity; and one or more parent-child relationships are established from the parent terms and each term. A hierarchical graph is automatically generated from the parent-child relationships.

Automatically generating a hierarchy of terms

A predetermined number of temporary terms are obtained that have the highest differential affinity to each of a number of candidate terms. Each temporary term and the associated differential affinity is placed into a set of temporary terms. An average differential affinity is calculated for each temporary term of the set of temporary terms, the average differential affinity representing an average of differential affinities from the each temporary term to every term of the initial set of terms. One or more terms with an average differential affinity that fails to satisfy a predetermined threshold are removed from the temporary set. One or more terms of the temporary set with differential affinities above the threshold are placed into the set of candidate terms. One or more terms of the set of candidate terms are selected and output to a user.

Determining candidate terms related to terms of a query

In one embodiment, assigning tags to a document includes accessing the document, where the document comprises text units that include words. The following is performed for each text unit: a subset of words of a text unit is selected as candidate tags, relatedness is established among the candidate tags, and certain candidate tags are selected according to the established relatedness to yield a candidate tag set for the text unit. Relatedness between the candidate tags of each candidate tag set and the candidate tags of other candidate tag sets is determined. At least one candidate tag is assigned to the document according to the determined relatedness.

Selecting tags for a document by analyzing paragraphs of the document

In one embodiment, identifying clusters of words includes accessing a record that records affinities. An affinity between a first and second word describes a quantitative relationship between the first and second word. Clusters of words are identified according to the affinities. A cluster comprises words that are sufficiently affine with each other. A first word is sufficiently affine with a second word if the affinity between the first and second word satisfies one or more affinity criteria. A clustering analysis is performed using the clusters.

Growing community of inventors

Sunnyvale, CA, United States of America

B Thomas Adler