Abstract: Techniques are provided detecting diluted drugs using machine learning. Measurements and images corresponding to a product are obtained, wherein the product is formulated as a liquid, and wherein the measurements and images capture physical, spectral, optical, and/or chemical properties of the product. The measurements and images are provided to a machine learning model, wherein the machine learning model is trained using data generated from interactive learning modules (e.g., a generative adversarial network). The machine learning model detects whether the product or chemical is a real or counterfeit product. In addition, these techniques may be used by practitioners (e.g., medical personnel dispensing a prescribed dosage of a drug with a specific dilution level) to detect prescription errors at the point of administration.

Abstract: Techniques are provided for detecting counterfeit products. Measurements and images corresponding to a product are obtained, wherein at least a portion of the measurements or images are obtained from a mobile/IoT/IoB device. The measurements and images are provided to a trained machine learning model to progressively analyze the measurements and images. Based on the progressive analysis, a determination/prediction is made with an associated confidence score as to whether the product is real or counterfeit.

Abstract: An approach for providing a cap with an embedded high-resolution lens and a sampling insert that is used during an authentication of a composition of a liquid in a container sealed by the cap. The cap has a top portion of a cap with an opening, a sampling insert inside the opening in the top portion of the cap, and a high-resolution lens inside an opening in the sampling insert.

Abstract: Techniques are provided detecting diluted drugs using machine learning. Measurements and images corresponding to a product are obtained, wherein the product is formulated as a liquid, and wherein the measurements and images capture physical, spectral, optical, and/or chemical properties of the product. The measurements and images are provided to a machine learning model, wherein the machine learning model is trained using data generated from interactive learning modules (e.g., a generative adversarial network). The machine learning model detects whether the product or chemical is a real or counterfeit product. In addition, these techniques may be used by practitioners (e.g., medical personnel dispensing a prescribed dosage of a drug with a specific dilution level) to detect prescription errors at the point of administration.

Abstract: Techniques are provided for detecting counterfeit products. Measurements and images corresponding to a product are obtained, wherein at least a portion of the measurements or images are obtained from a mobile/IoT/IoB device. The measurements and images are provided to a trained machine learning model to progressively analyze the measurements and images. Based on the progressive analysis, a determination/prediction is made with an associated confidence score as to whether the product is real or counterfeit.

Abstract: Transitioning a data file in an archive system from read-write to write-once-read-many (“WORM”) is triggered by a control file rather than using a timeout approach or a overload approach. A storage manager may receive a series of archive instructions to write a data file to an archive. During this time, the archive file may be in a read-write state. The storage manager may receive a control file, which may be structured, such as an XML file. Receipt of the control file signals to an storage manager archive system that the data file has been written to the archive and triggers the storage manager to make the data file immutable by switching it from read-write state to WORM state.

Abstract: An apparatus, system, and method are provided for gathering trace data indicative of resource activity on a computer system. The present invention includes a monitoring module that initiates one or more activity monitors on a target computer system to detect different types of resource activity. A determination module determines activity indicators involving resources of the target computer system using the one or more activity monitors. The activity indicators may comprise a variety of information useful in identifying one or more separate resource activities. A collection module organizes the activity indicators into trace data representative of the resource activity. Preferably, the monitoring module, determination module, and collection module operate continuously on the target computer system. In this manner, the trace data includes an accurate set of both current activity indicators as well as historical activity indicators.

Abstract: An apparatus, system, and method are provided for analyzing the association of a resource to a business process. The invention includes an origination module, an evaluation module, and an identification module. The origination module receives an identifier and derives a seed resource associated with the identifier. The evaluation module applies heuristic routines to trace data and derives a set of candidate resources, and each heuristic routine assigns each candidate resource a probability value. The evaluation module further combines the probabilities for each candidate resource into a combined probability. The identification module identifies a resource associated to a business process by examining the combined probability of a candidate resource with a threshold value. The heuristic routines, thresholds, techniques for combining probabilities and the like are modifiable to accommodate user needs and system changes over time.

Abstract: Transitioning a data file in an archive system from read-write to write-once-read-many (“WORM”) is triggered by a control file rather than using a timeout approach or a overload approach. A storage manager may receive a series of archive instructions to write a data file to an archive. During this time, the archive file may be in a read-write state. The storage manager may receive a control file, which may be structured, such as an XML file. Receipt of the control file signals to an storage manager archive system that the data file has been written to the archive and triggers the storage manager to make the data file immutable by switching it from read-write state to WORM state.

Abstract: Provided is a method for managing a network providing Input/Output (I/O) paths between a plurality of host systems and storage volumes in storage systems. An application service connection definition is provided for each connection from a host to a storage volume. At least one service level guarantee definition is provided indicating performance criteria to satisfy service requirements included in at least one service level agreement with at least one customer for network resources. Each service level guarantee definition is associated with at least one application service connection definition. Monitoring is performed as to whether Input/Output (I/O) requests transmitted through the multiple I/O paths satisfy performance criteria indicated in the service level guarantee definition associated with the I/O paths.

Abstract: An apparatus, system, and method are provided for automatically discovering and grouping files and other resources used by a business process. The present invention includes a monitoring module that collects trace data representative of operational behavior of software applications. An analysis module analyzes the trace data to discover resources affiliated with the business process. A determination module defines a logical application corresponding to the business process and includes the resources discovered by the analysis module. The logical application is automatically defined such that business policies may be readily implemented on the logical application as a whole. Manual identification of resources for a business process is eliminated or substantially reduced.

Abstract: An apparatus, system, and method are provided for gathering trace data indicative of resource activity on a computer system. The present invention includes a monitoring module that initiates one or more activity monitors on a target computer system to detect different types of resource activity. A determination module determines activity indicators involving resources of the target computer system using the one or more activity monitors. The activity indicators may comprise a variety of information useful in identifying one or more separate resource activities. A collection module organizes the activity indicators into trace data representative of the resource activity. Preferably, the monitoring module, determination module, and collection module operate continuously on the target computer system. In this manner, the trace data includes an accurate set of both current activity indicators as well as historical activity indicators.

Abstract: An apparatus, system, and method are provided for associating resources using a time based algorithm. The apparatus comprises an initialization module, a query module, and a resource time module. The initialization module receives a seed identifier that identifies a seed resource. The seed resource may be a data file, an executable file, a directory, or another data structure associated with a logical application or business process. The query module accesses trace data and searches the trace data for a candidate resource that might be linked to the seed resource. The trace data describes a plurality of resource events that occur on a computer or network system. The resource time module selects a candidate resource based on a similar time attribute recorded in the trace data. The similar time attribute may refer to an access time of the candidate resource that is similar to, such as within a time range, an access time of a seed resource or otherwise linked resource.