Abstract: A system and method are disclosed for displaying a visualization of tasks to be performed across one or more time intervals. Embodiments include receiving two or more tasks from a task database comprising one or more attributes in a table format, the table having two or more rows and two or more columns, adding a column to each of the two or more tasks comprising the volume of tasks to be cumulatively performed during a time interval and adding a column to each of the two or more tasks comprising the cumulative volume due during the time interval. Embodiments also include displaying, on a graphical user interface, a visualization of the cumulative volume due and the cumulative planned curve representing the volume of tasks to be performed across one or more time intervals.

Abstract: A system and method are disclosed for a low-touch centralized system to predict service level failure in a supply chain using machine learning. Embodiments include receiving only historical supply chain data from an archiving system for one or more supply chain entities storing items at stocking locations, predicting one or more supply chain events during a prediction period by applying a predictive model to a sample of historical supply chain data, calculating an occurrence risk score for at least one of the one or more supply chain events and indicating a possibility that the at least one of the one or more supply chain events will occur, generating one or more alerts identifying at least one item and at least one alert stocking location, rendering an alert heatmap visualization comprising one or more selectable user interface elements, and provide one or more tools for initiating corrective actions to be undertaken.

Abstract: A system and method are disclosed for a low-touch centralized system to predict service level failure in a supply chain using machine learning. Embodiments include receiving only historical supply chain data from an archiving system for one or more supply chain entities storing items at stocking locations, predicting one or more supply chain events during a prediction period by applying a predictive model to a sample of historical supply chain data, calculating an occurrence risk score for at least one of the one or more supply chain events and indicating a possibility that the at least one of the one or more supply chain events will occur, generating one or more alerts identifying at least one item and at least one alert stocking location, rendering an alert heatmap visualization comprising one or more selectable user interface elements, and provide one or more tools for initiating corrective actions to be undertaken.

Abstract: A system and method are disclosed for a low-touch centralized system to predict service level failure in a supply chain using machine learning. Embodiments include receiving only historical supply chain data from an archiving system for one or more supply chain entities storing items at stocking locations, predicting one or more supply chain events during a prediction period by applying a predictive model to a sample of historical supply chain data, calculating an occurrence risk score for at least one of the one or more supply chain events and indicating a possibility that the at least one of the one or more supply chain events will occur, generating one or more alerts identifying at least one item and at least one alert stocking location, rendering an alert heatmap visualization comprising one or more selectable user interface elements, and provide one or more tools for initiating corrective actions to be undertaken.

Abstract: A system and method are disclosed for receiving only historical supply chain data from an archiving system for one or more supply chain entities storing items at stocking locations, predicting one or more supply chain events during a prediction period by applying a prediction model to a sample of historical supply chain data, calculating an occurrence risk score for at least one of the one or more supply chain events and indicating a possibility that the at least one of the one or more supply chain events will occur, generating one or more alerts identifying at least one item and at least one alert stocking location, rendering an alert heatmap visualization comprising one or more selectable user interface elements, and provide one or more tools for initiating corrective actions to be undertaken in order to resolve one or more underlying causes of the at least one alert supply chain event.

Abstract: A system and method are disclosed for receiving only historical supply chain data from an archiving system for one or more supply chain entities storing items at stocking locations, predicting one or more supply chain events during a prediction period by applying a prediction model to a sample of historical supply chain data, calculating an occurrence risk score for at least one of the one or more supply chain events and indicating a possibility that the at least one of the one or more supply chain events will occur, generating one or more alerts identifying at least one item and at least one alert stocking location, rendering an alert heatmap visualization comprising one or more selectable user interface elements, and provide one or more tools for initiating corrective actions to be undertaken in order to resolve one or more underlying causes of the at least one alert supply chain event.

Abstract: A system and method are disclosed for receiving only historical supply chain data from an archiving system for one or more supply chain entities storing items at stocking locations, predicting one or more supply chain events during a prediction period by applying a prediction model to a sample of historical supply chain data, calculating an occurrence risk score for at least one of the one or more supply chain events and indicating a possibility that the at least one of the one or more supply chain events will occur, generating one or more alerts identifying at least one item and at least one alert stocking location, rendering an alert heatmap visualization comprising one or more selectable user interface elements, and provide one or more tools for initiating corrective actions to be undertaken in order to resolve one or more underlying causes of the at least one alert supply chain event.

Abstract: A system and method are disclosed for receiving only historical supply chain data from an archiving system for one or more supply chain entities storing items at stocking locations, predicting one or more supply chain events during a prediction period by applying a prediction model to a sample of historical supply chain data, calculating an occurrence risk score for at least one of the one or more supply chain events and indicating a possibility that the at least one of the one or more supply chain events will occur, generating one or more alerts identifying at least one item and at least one alert stocking location, rendering an alert heatmap visualization comprising one or more selectable user interface elements, and provide one or more tools for initiating corrective actions to be undertaken in order to resolve one or more underlying causes of the at least one alert supply chain event.

Abstract: A continuous variable quantum encryption key distribution system comprises a sender (Alice) able to randomly choose the phase and the amplitude of each coherent light pulse of a signal, to provide a coherent state defined by a first quadrature and a second quadrature that are random, and to transmit to a receiver (Bob) the signal pulses (S) and a local oscillator (LO), the receiver comprising a homodyne detector (36) for measuring a randomly chosen quadrature of a signal pulse. The sender comprises a device for time-division multiplexing the pulses of the signal (S) and of the local oscillator (LO) to handle the transmission over an optical fiber (10) of the signal and local oscillator pulses to the receiver. The receiver comprises a demultiplexer (31), able to send the received pulses over a first channel (32), or over a second channel (33). The channels are applied as inputs to the homodyne detector (36).

Abstract: A continuous variable quantum encryption key distribution system comprises a sender (Alice) able to randomly choose the phase and the amplitude of each coherent light pulse of a signal, to provide a coherent state defined by a first quadrature and a second quadrature that are random, and to transmit to a receiver (Bob) the signal pulses (S) and a local oscillator (LO), the receiver comprising a homodyne detector (36) for measuring a randomly chosen quadrature of a signal pulse. The sender comprises a device for time-division multiplexing the pulses of the signal (S) and of the local oscillator (LO) to handle the transmission over an optical fiber (10) of the signal and local oscillator pulses to the receiver. The receiver comprises a demultiplexer (31), able to send the received pulses over a first channel (32), or over a second channel (33). The channels are applied as inputs to the homodyne detector (36).

Abstract: One aspect of the present invention is related to a quantum cryptographic scheme comprising at least one sending unit including a physical means of encoding and distributing a raw key in the quadrature components of quantum coherent states that are continuously modulated in phase and amplitude, at least one receiving unit containing a physical means of performing homodyne detection of the quantum coherent states in order to measure the quadrature components of the states, a quantum channel for connecting the sending unit to the receiving unit, a two-way authenticated public channel for transmitting non-secret messages between the sending unit and the receiving unit, a quantum key distribution protocol ensuring that the information tapped by a potential eavesdropper can be estimated from the quantum channel parameters, and a direct or reverse reconciliation protocol that converts the raw continuous data into a common binary key.