Abstract: A system to facilitate configuration of infrastructure resources is described. The system includes a plurality of on-premises infrastructure appliances, each appliance including a plurality of infrastructure devices and an on-premises infrastructure controller to control the plurality of infrastructure devices. The system further includes a cloud services resource configuration manager, communicatively coupled to each of the on-premises infrastructure controllers, to configure each of the on-premises infrastructure appliances via a respective on-premises infrastructure controller.

Abstract: Examples described herein relate to providing a simplified interface by a cloud platform to an IaC service. According to an example, operational details associated with multiple infrastructure as code (IaC) tools are abstracted by providing an application programming interface (API) of an IaC service through which multiple IaC templates are available for use to deploy workloads against multiple services within a cloud platform. Each IaC template describes a workload according to an IaC tool and specifies input parameters for the workload. A request to create a deployment based on a particular IaC template is received via the API. The request is satisfied by internally executing the IaC tool associated with the particular template based on parameter values supplied for the specified input parameters for the particular workload.

Abstract: Examples described herein relate to a configuration manager for configuring a cloud application at a SaaS platform. The configuration manager is hosted on a cloud platform separate from a tenant site. The configuration manager receives a request for enabling remote management of the cloud application hosted on the tenant site. The configuration manager determines configuration content applicable for the cloud application from a configuration repository and configures the SaaS platform for remotely managing the cloud application based on the configuration content. The SaaS platform is a service associated with a management tooling used at the tenant site. The management tooling may be a monitoring tooling or a logging tooling. Once configured, the SaaS platform receives monitoring data or logging data from the infrastructure at the tenant site.

Abstract: Examples described herein relate to a configuration manager for configuring a cloud application at a SaaS platform. The configuration manager is hosted on a cloud platform separate from a tenant site. The configuration manager receives a request for enabling remote management of the cloud application hosted on the tenant site. The configuration manager determines configuration content applicable for the cloud application from a configuration repository and configures the SaaS platform for remotely managing the cloud application based on the configuration content. The SaaS platform is a service associated with a management tooling used at the tenant site. The management tooling may be a monitoring tooling or a logging tooling. Once configured, the SaaS platform receives monitoring data or logging data from the infrastructure at the tenant site.

Abstract: A system to facilitate configuration of infrastructure resources is described. The system includes a plurality of on-premises infrastructure appliances, each appliance including a plurality of infrastructure devices and an on-premises infrastructure controller to control the plurality of infrastructure devices. The system further includes a cloud services resource configuration manager, communicatively coupled to each of the on-premises infrastructure controllers, to configure each of the on-premises infrastructure appliances via a respective on-premises infrastructure controller.

Abstract: A kernel-based method determines the similarity of a first spectrum and a second spectrum. Each spectrum represents a result of spectral analysis of a material or chemical and comprises a set of spectral attributes distributed across a spectral range. The method calculates a kernel function which makes use of the shape of the spectral response surrounding a spectral point. This is achieved by comparing the value of an spectral attribute in a spectrum and each of a set of neighboring spectral attributes within a window around the spectral attribute. Weighting values can be applied to calculations when deriving the kernel function. The weighting values can assign different degrees of importance to different regions of the spectrum. The method can be used to: classify unknown spectra; predict the concentration of an analyte within a mixture; database searching for the closest match using a kernel-derived distance metric; visualization of high-dimensional spectral data in two or three dimensions.

Abstract: The provision of call handling treatments to callers interacting with an automated call-handling system is managed by, for each of a plurality of callers, providing a sequence of call handling treatments to the caller in accordance with workflows; monitoring a measurable performance indicator associated with that caller's behavior; determining an association between the performance indicator and the call handling treatments provided to the caller; and recording the association. Then, based on the recorded associations, the system determines a pattern of deviation in the performance indicator attributable to the call handling treatments; and alters the workflow in response to the deviation by making a change in the workflow selected from promoting a call handling treatment to an earlier point in the workflow; demoting a call handling treatment to a later point in the workflow; adding a call handling treatment to the workflow; and removing a call handling treatment from the workflow.

Abstract: A kernel-based method determines the similarity of a first spectrum and a second spectrum. Each spectrum represents a result of spectral analysis of a material or chemical and comprises a set of spectral attributes distributed across a spectral range. The method calculates a kernel function which makes use of the shape of the spectral response surrounding a spectral point. This is achieved by comparing the value of an spectral attribute in a spectrum and each of a set of neighbouring spectral attributes within a window around the spectral attribute. Weighting values can be applied to calculations when deriving the kernel function. The weighting values can assign different degrees of importance to different regions of the spectrum. The method can be used to: classify unknown spectra; predict the concentration of an analyte within a mixture; database searching for the closest match using a kernel-derived distance metric; visualisation of high-dimensional spectral data in two or three dimensions.

Abstract: A method of and system for generating models with which to classify or quantify spectra of unknown mixtures of compounds to permit the specific identification or quantification of a target analyte in complex mixtures based on spectral data, the method comprising the steps of: providing a training set of training spectra, each spectrum representing a mixture of known compounds and each having a plurality of spectral attributes, each at a different wavelength, choosing a plurality of wavelengths, determining at least the value of the spectral attribute at each chosen wavelength in each training spectrum in the training set, and building a model for each chosen wavelength by correlating the determined attribute values at said chosen wavelength, a method and system for classifying the spectrum of a mixture of unknown compounds, and a method and system for quantifying the spectrum of a mixture of unknown compounds to determine concentrations therein, using said models.