Abstract: In general terms this invention provides embodiment of systems that permit better usage of consumer generated data that permit the consumer methods to monetize the information and maintain control over the data at the time of its creation and at later times. Certain embodiments comprise a user whose interaction can cause a provider to create data regarding the interaction. The user can authenticate the data using encryption aspects and permit the user to self-publish data. The self-publishing can occur in a manner that only requires direct trust of the technology provider regarding the data validity. The invention may incorporate an Ethereum network. Embodiments of the system may verify, exchange, encrypt and decrypt data allowing purchasers to purchase the data or certain portions of it.

Abstract: In general terms this invention provides embodiment of systems that permit better usage of consumer generated data that permit the consumer methods to monetize the information and maintain control over the data at the time of its creation and at later times. Certain embodiments comprise a user whose interaction can cause a provider to create data regarding the interaction. The user can authenticate the data using encryption aspects and permit the user to self-publish data. The self-publishing can occur in a manner that only requires direct trust of the technology provider regarding the data validity. The invention may incorporate an Ethereum network. Embodiments of the system may verify, exchange, encrypt and decrypt data allowing purchasers to purchase the data or certain portions of it.

Abstract: Systems and methods for assaying a test entity for a property, without measuring the property, are provided. Exemplary test entities include proteins, protein mixtures, and protein fragments. Measurements of first features in a respective subset of an N-dimensional space and of second features in a respective subset of an M-dimensional space, is obtained as training data for each reference in a plurality of reference entities. One or more of the second features is a metric for the target property. A subset of first features, or combinations thereof, is identified using feature selection. A model is trained on the subset of first features using the training data. Measurement values for the subset of first features for the test entity are applied to thereby obtaining a model value that is compared to model values obtained using measured values of the subset of first features from reference entities exhibiting the property.

Abstract: In general terms this invention provides embodiment of systems that permit better usage of consumer generated data that permit the consumer methods to monetize the information and maintain control over the data at the time of its creation and at later times. Certain embodiments comprise a user whose interaction can cause a provider to create data regarding the interaction. The user can authenticate the data using encryption aspects and permit the user to self-publish data. The self-publishing can occur in a manner that only requires direct trust of the technology provider regarding the data validity. The invention may incorporate an Ethereum network. Embodiments of the system may verify, exchange, encrypt and decrypt data allowing purchasers to purchase the data or certain portions of it.

Abstract: Systems and methods for assaying a test entity for a property, without measuring the property, are provided. Exemplary test entities include proteins, protein mixtures, and protein fragments. Measurements of first features in a respective subset of an N-dimensional space and of second features in a respective subset of an M-dimensional space, is obtained as training data for each reference in a plurality of reference entities. One or more of the second features is a metric for the target property. A subset of first features, or combinations thereof, is identified using feature selection. A model is trained on the subset of first features using the training data. Measurement values for the subset of first features for the test entity are applied to thereby obtaining a model value that is compared to model values obtained using measured values of the subset of first features from reference entities exhibiting the property.

Abstract: Systems and methods for assaying a test entity for a property, without measuring the property, are provided. Exemplary test entities include proteins, protein mixtures, and protein fragments. Measurements of first features in a respective subset of an N-dimensional space and of second features in a respective subset of an M-dimensional space, is obtained as training data for each reference in a plurality of reference entities. One or more of the second features is a metric for the target property. A subset of first features, or combinations thereof, is identified using feature selection. A model is trained on the subset of first features using the training data. Measurement values for the subset of first features for the test entity are applied to thereby obtaining a model value that is compared to model values obtained using measured values of the subset of first features from reference entities exhibiting the property.

Abstract: Systems and methods for assaying a test entity for a property, without measuring the property, are provided. Exemplary test entities include proteins, protein mixtures, and protein fragments. Measurements of first features in a respective subset of an N-dimensional space and of second features in a respective subset of an M-dimensional space, is obtained as training data for each reference in a plurality of reference entities. One or more of the second features is a metric for the target property. A subset of first features, or combinations thereof, is identified using feature selection. A model is trained on the subset of first features using the training data. Measurement values for the subset of first features for the test entity are applied to thereby obtaining a model value that is compared to model values obtained using measured values of the subset of first features from reference entities exhibiting the property.

Abstract: A method for organizing network flow information within a relational database relates to minimizing contention for the network flow information. In particular, data is generally aggregated at certain time intervals and separately organized. In this way, contention is decreased as analysis can occur on the separated existing flow records, which are optionally aggregated, while new raw flow records are stored. In another embodiment, the aggregated data can be re-aggregated at second, larger time intervals.

Abstract: The present invention provides a system and method for using network flows records exported from network routers to provide information about the traffic entering/exiting the device. Network flow information exported from network devices identify the network devices involved in the flow using their network address. An application displays a user friendly host name of the network device. This method describes the steps necessary to efficiently resolve the network device address to their domain names.

Abstract: A method for organizing network flow information within a relational database relates to minimizing contention for the network flow information. In particular, data is generally aggregated at certain time intervals and separately organized. In this way, contention is decreased as analysis can occur on the separated existing flow records, which are optionally aggregated, while new raw flow records are stored. In another embodiment, the aggregated data can be re-aggregated at second, larger time intervals.