215 results about "Algorithmics" patented technology

An automated system for matching orders to buy and sell securities at the midpoint of a best bid and offer (“BBO”), wherein the automated system is adapted to (i) operate on a fully-anonymous and continuous basis, (ii) process multiple, computer-generated orders, of any size, transmitted by algorithmic, program, and other automated trading systems, (iii) automatically match multiple, executable orders according to a priority scheme, and (iv) execute a matching algorithm that maximizes tradable volume when an executable order can not be matched according to the priority scheme. The system may be executed at a server or participant system, or combination of the two.

An enhanced memory algorithmic processor ("MAP") architecture for multiprocessor computer systems comprises an assembly that may comprise, for example, field programmable gate arrays ("FPGAs") functioning as the memory algorithmic processors. The MAP elements may further include an operand storage, intelligent address generation, on board function libraries, result storage and multiple input / output ("I / O") ports. The MAP elements are intended to augment, not necessarily replace, the high performance microprocessors in the system and, in a particular embodiment of the present invention, they may be connected through the memory subsystem of the computer system resulting in it being very tightly coupled to the system as well as being globally accessible from any processor in a multiprocessor computer system.

Provided a system and method for detecting an event while discriminating against false alarms in a monitored space using at least one sensor suite to acquire signals, transmitting the signals to a sensor system device where the signal is processed into data packets, transmitting the data packets to a data fusion device, where the data packets are aggregated and algorithmic data fusion analysis is performed to generate threat level information. The threat level information is distributed to a supervisory control system where an alarm level can be generated when predetermined criteria are met to indicate the occurrence of an event in the monitored space.

A decision support system and method, which receives user inputs comprising: at least one user criterion, and at least one user input tuning parameter representing user tradeoff preferences for producing an output; and selectively produces an output of tagged data from a clustered database in dependence on the at least one user criterion, the at least one user input tuning parameter, and a distance function; receives at least one reference-user input parameter representing the at least one reference-user's analysis of the tagged data and the corresponding user inputs, to adapt the distance function in accordance with the reference-user inputs as a feedback signal; and clusters the database in dependence on at least the distance function, wherein the reference-user acts to optimize the distance function based on the user inputs and the output, and on at least one reference-user inference.

Systems and methods for applying time-dependent algorithmic compensation functions to data output from a continuous analyte sensor. Some embodiments determine a time since sensor implantation and / or whether a newly initialized sensor has been used previously.

A hardware and operating system independent platform and / or run time architecture that implements a configuration and algorithmic based application and process for enabling multiple virtual machines or internal networked physical servers (hosts) to be organized into groups or “realms” in real time and against specific configurable metrics. The configurable metrics include one or more of the following; load or processing capacity availability, cost of CPU processing, location based on risk, importance to business continuity priority requirements, disaster recovery strength and priority, geographic location of host aligned to IP, and any other client specific or custom requirements. A realm manager balances all of these configurable metrics and creates an algorithm to address allocation. The algorithm is fully elastic, allowing for automatic opening and closing of virtual machines to accommodate any internal or external changes.

An efficient simulation system of quantum algorithm gates for classical computers with a Von Neumann architecture is described. In one embodiment, a Quantum Algorithm is solved using an algorithmic-based approach, wherein matrix elements of the quantum gate are calculated on demand. In one embodiment, a problem-oriented approach to implementing Grover's algorithm is provided with a termination condition determined by observation of Shannon minimum entropy. In one embodiment, a Quantum Control Algorithm is solved by using a reduced number of quantum operations.

A system and method for monitoring a user's mental health tor and collect data concerning. The user's use of electronic devices is tracked, such as usage of his mobile phone, tablet and his web activity. The invention “learns” each patient's unique behavioral patterns to be used as a “base line” representing the steady state (chronic phase) of the patient. The algorithmic processing unit detects any irregularities in a patient's behavioral patterns and produces a deterioration prediction. If it is determined that a threshold is exceeded, an alert is sent to a health professional.

Each of plural sigma-delta modulators having a sampling capacitor, an integrator, and a quantizer are connected to each other in parallel. Each of the sigma-delta modulators conducts parallel oversampling in which an analog input signal is sampled by a sampling capacitor, and the sampling result is quantized by the integrator and the quantizer. Then, the quantized values of the sigma-delta modulators are added to obtain MSBs, the residue values of the integrators after quantizing in the respective sigma-delta modulators are added, and the addition result of the residue values is converted analog-to-digital to obtain LSBs.

A computing system and method are provided for algorithmic electronic system level design. An exemplary system comprises a plurality of databases for storing a plurality of functional models, a plurality of computational element models, and a plurality of hardware definition representations. An application design processor is adapted to perform a first functional simulation of an algorithm using a plurality of computational element architecture definitions to generate a first selection of a plurality of computational elements and corresponding control code for an implementation of the algorithm. A control and memory modeling processor is adapted to generate a plurality of flow transforms from the algorithm and to convert the plurality of flow transforms into the plurality of plurality of computational element models. A system simulation processor is adapted to convert the plurality of computational element models into the plurality of hardware definition representations and to perform a second functional simulation of the algorithm using the plurality of computational element models corresponding to the first selection and the corresponding control code.

This invention provides a negotiation method and a device for registration method and a safety algorithm of user, in which, the method includes: UPE starts up registration to MME and adds registration information including a safety algorithm onto the MME, which negotiates with the UE to determine a safety algorithm. From this plan we can see that the UPE reports its supported safety algorithm ability by registration to let the safety algorithm negotiation of the user side is finished in the NE of the control side so as to divide the NE function more reasonable, when the UE and UPE have not any common supported safety algorithm, the MME can decide if the UE adhesion process is done before the route collocation process of the user side to reduce signaling interaction number and lighten operation burden of the system and new negotiation of user side safety algorithm between UPE and UE in the re-location of UPE speeds up the connection process of user sides.

The invention discloses a warning and responding system used for intranet network attack detection. The system comprises a management center, a detecting machine and a database. The management center is used for configuring and amending each parameter of the detecting machine, receiving and storing warning message sent by the detecting machine and inquiring the state of the detecting machine. Anomaly information detection is carried out on an intranet network by an anomaly detection algorithmic module of the detecting machine, the anomaly detection algorithmic module obtains anomaly detection information and confirms the reliability of the information. When the reliability of the anomaly detection information reaches a preset value, the warning message is sent. The isolation time and the isolation form of an IP address generating the anomaly detection information are confirmed according to the warning message, and the IP address is isolated. The IP address that the isolation time reaches the preset value is released from isolation. The method can detect and prevent the attack from an intranet mainframe to outer net or other intranet mainframes exactly and effectively in time.

A safety enhancement warning system includes an avoidance system which communicates with a multiple of geographical positional systems. A geographic algorithm of the avoidance system utilizes a recursive algorithmic to determine if the aircraft will enter a sensitive area. If the aircraft distance to a sensitive area decreases below a predefined minimum threshold, then an audible and / or visual warning is issued. For certain sensitive areas, aircraft RF emissions are silenced or reduced in power when the predetermined minimum threshold breaches the sensitive area. The use of the avoidance system enables usage of relatively inexpensive UWB radar for the proximity sensor suite to assure avoidance of interference with particular delicate instruments and thereby meet regulations such as those propagated by the FCC.

The present disclosure relates to a media attribution system that improves multi-channel media attribution by employing discrete-time survival modeling. In particular, the media attribution system uses event data (e.g., interactions and conversions) to generate positive and negative conversion paths, which the media attribution system uses to train an algorithmic attribution model. The media attribution system also uses the trained algorithmic attribution model to determine attribution scores for each interaction used in the conversion paths. Generally, the attribution score for an interaction indicates the effect the interaction has in influencing a user toward conversion.

The invention discloses a heterogeneous multi-core infrared image processing system and method. The method mainly includes: 1, utilizing programmable logic of a Zynq to realize a driving schedule of a detector to complete collection and caching of an infrared image; 2, utilizing a CPU0 (central processing unit 0) of the Zynq to operate a Linux operating system to write a Qt-based display and control interface; 3, utilizing a CPU1 of the Zynq to respond to a serial port command in real time, and setting a system parameter and a video driving chip online; 4, utilizing the programmable logic to realize algorithmic hardware acceleration and a driving schedule of a video chip. The heterogeneous multi-core infrared image processing system and method has the advantages that a structure of ARM+FPGA in an all programmable platform Zynq chip is utilized to develop the heterogeneous multi-core infrared image processing system, design difficulty of hardware is remarkably reduced, a system bandwidth chokepoint brought by interconnection of conventional framework chip levels is removed, simplicity and flexibility in design and integration of a user IP (internet protocol) are realized, and high universality is realized.

NAND architecture non-volatile content addressable (CAM) memory devices and methods are described that allows for high density, low cost CAM devices. In addition, the NAND architecture non-volatile CAM memory operates with reduced power consumption characteristics for low power and portable applications. In one NAND architecture non-volatile CAM memory embodiment a wired NOR match line array is utilized. In another embodiment a NAND match line array is shown. In yet other embodiments, hierarchal addressing, hash addressing, tree search and algorithmic / hardware engine based search is detailed utilizing both conventional NAND architecture non-volatile Flash memory arrays and dedicated NAND architecture CAM arrays utilizing wired NOR and wired NAND match lines.

The invention provides an electronic magnetic compass error compensation method which bases on deformation round distribution and cyclical assumptions. The measurement error caused by around ferromagnetic materials and other factors must be compensated to enhance electronic magnetic compass measurement accuracy. At present, domestic and foreign popular methods of compensation are based on assumptions which relate to the effect of the environmental interference magnetic field causing the magnetic field strength level projection component distribution from round into oval. But because of more and complicated influence factors, in fact the magnetic field strength level projection component distribution can not be guarantee as perfect oval. In view of this situation, the invention provides error compensation algorithmic method which bases on deformation round distribution and cyclical assumptions, the objective is to compensate the measurement error caused by around ferromagnetic materials and other factors, and achieve magnetic azimuth high-precision measurement.

The present invention concerns a new category of integrated circuitry and a new methodology for adaptive or reconfigurable computing. The preferred IC embodiment includes a plurality of heterogeneous computational elements coupled to an interconnection network. The plurality of heterogeneous computational elements include corresponding computational elements having fixed and differing architectures, such as fixed architectures for different functions such as memory, addition, multiplication, complex multiplication, subtraction, configuration, reconfiguration, control, input, output, and field programmability. In response to configuration information, the interconnection network is operative in real-time to configure and reconfigure the plurality of heterogeneous computational elements for a plurality of different functional modes, including linear algorithmic operations, non-linear algorithmic operations, finite state machine operations, memory operations, and bit-level manipulations. The various fixed architectures are selected to comparatively minimize power consumption and increase performance of the adaptive computing integrated circuit, particularly suitable for mobile, hand-held or other battery-powered computing applications.

The invention applies a Voronoi diagram to wireless sensor network node coverage optimization and provides a coverage mechanism based on a Voronoi diagram blind area type new arithmetic. The coverage mechanism is used for providing an optimal solution to a problem of the wireless sensor network node coverage. The problem of the wireless sensor network node coverage is defined as a problem of disk coverage, a wireless sensor is idealized, and the position of a sensor node is regarded as a center of circle, thereby sensing a standard circle with a radius. By means of the Voronoi diagram, an area under monitoring is divided into multiple Voronoi units; a method of removing nodes in the Voronoi units one by one is adopted; and newly-generated geometric centers of the Voronoi units are calculated. A result is assessed by comparing "coverage rate", "node distribution uniformity" and "coverage efficiency" of the area (in order to prevent experimental chance, repeat operation for 30 times and then take the average). Through simulation experiments, validity and high effectiveness of the algorithmic provided by the invention are verified.

The invention discloses a single-point intersection signal control method based on deep cycle Q learning. The method comprises the following steps: learning an optimal signal control strategy at a single intersection by using a deep cyclic Q learning (DRQN) algorithm, wherein according to the DRQN algorithm, an LSTM neural network is introduced on the basis of DQN, the characteristic that the LSTMcan memorize time axis information is utilized, the current intersection input state is comprehensively expressed by combining the states of the intersection at the previous several moments instead of the state of the intersection at the current moment and thus the influence of the POMDP characteristics of the intersection on deep Q learning performance is reduced. The performance of the improvedDRQN algorithm provided by the invention is superior to that of the DQN algorithm and is also superior to that of a traditional intersection timing control method. When the traffic flow is close to saturation and supersaturation, the DRQN algorithm can observe the state of the intersection at each moment and make an optimal opportunity choice, thereby improving the traffic efficiency of the intersection.

An encryption system and method that may encrypt all of the transmitted and received data packets on the data link layer without collisions on the Initialization Vector (IV). In the encryption system and method a new final key value may be generated and applied to every transmitted and received data packet. The encryption system and method provide for a novel three phase algorithmic process for generating a final secret key.

Methods for noninvasively evaluating indicators of cardio-pulmonary performance of a subject, such as cardiac output, pulmonary capillary blood flow, and blood carbon dioxide content, include obtaining data of an expiratory carbon dioxide signal and comparing data generated by an algorithmic lung model to the data of the expiratory carbon dioxide signal of a subject. The variables that are input into the algorithmic lung model are adjusted until the data generated thereby reflects that of the measured expiratory carbon dioxide signal with a desired degree of accuracy. Once the algorithmic lung model replicates the data of the measured expiratory carbon dioxide signal with the desired degree of accuracy, one or more of the input values may be used to determine one or more of the cardiac output, pulmonary capillary blood flow, or a blood gas content of the subject from which the expiratory carbon dioxide signal was obtained.

This invention relates to a method and system of self-auditing for recovering refundable sales taxes, including but not limited to value-added (VAT), by performing specifically established tax compliance algorithmic functions. Business entities are entitled to recover tax paid on purchased goods and services. The method and system allow the business to conduct self-audit on their own accounting system, which contains its business related accounts payable accounting transaction data in order to extract specific data anomalies related to sales tax entitlements. The method and system process and identify specific transaction details and calculate differential monetary currency tax recovery amounts that have been overlooked as tax entitlements or overpaid in error to vendors for their determination of their net tax owing to various government bodies.

The present invention relates to a system and method for electronic and algorithmic data mining of an individual physician's prescribing history to determine the approximate distribution of diseases within their practice population for optimizing pharmaceutical sales and marketing. Rapid and large-scale determination of specific clinical safety and efficacy attributes of a marketed drug which are most pertinent and relevant to a given physician, when compared to a competitor's drug, are defined and tabularized. Major clinical characteristics taken into account include a drug's safety, efficacy, cost, dosing convenience, formulary insurance coverage, side effect profiles, and FDA approval for the intended use. A symbolic representation of knowledge is employed in which the marketed drug and each competitor's drug are compared algorithmically against each other with a scoring system that is based upon machine analysis of each major clinical characteristic. The score is further refined according to the number and severity of safety interactions which are relevant to the comparison, and also based upon predicted prevalence of such interactions within a specific physician's practice.

A flight data recorder system containing an aircraft condition monitoring function which includes a reconfigurable algorithmic network which defines operations on a set of flight data along with interpreters to analyze the flight data. The reconfigurable algorithmic network accepts flight data from a variety of sources. The reconfigurable network defines functional relationships between various flight data and performs operations on the various flight data. The flight data sources and the relationships therebetween can be configured by the user. The reconfigurable algorithmic network allows customization of a flight data analysis function without the need to recertify operational software.

In an exemplary embodiment, some of the main aspects of the present invention are the following: (i) Data model: We introduce tensor streams to deal with large collections of multi-aspect streams; and (ii) Algorithmic framework: We propose window-based tensor analysis (WTA) to effectively extract core patterns from tensor streams. The tensor representation is related to data cube in On-Line Analytical Processing (OLAP). However, our present invention focuses on constructing simple summaries for each window, rather than merely organizing the data to produce simple aggregates along each aspect or combination of aspects.

The invention provides a hexapod robot obstacle avoidance method based on fuzzy Q learning. The method comprises the steps that a hexapod robot measures the obstacle distance around the robot througha front ultrasonic sensor and converts the measured obstacle distance into a finite state set through fuzzy inference; according to the finite state set, obstacle avoidance simulation modeling is carried out in a simulation platform; a Q learning algorithm is used to learn the action taken by the hexapod robot in the corresponding state; the state set of the hexapod robot in the current state is determined; fuzzy inference is used to determine the action set of the hexapod robot; and the actions are fused to determine the next action. The obstacle avoidance method can realize a great obstacleavoidance effect in an environment where the number of obstacles is large, and has a good market prospect.