477 results about "Seasonality" patented technology

A hybrid manual / programmable thermostat for a furnace or air conditioner offers the simplicity of a manual thermostat while providing the convenience and versatility of a programmable one. Initially, the hybrid thermostat appears to function as an ordinary manual thermostat; however, it privately observes and learns a user's manual temperature setting habits and eventually programs itself accordingly. If users begin changing their preferred temperature settings due to seasonal changes or other reasons, the thermostat continues learning and will adapt to those changes as well. For ease of use, the thermostat does not require an onscreen menu as a user interface. In some embodiments, the thermostat can effectively program itself for temperature settings that are set to occur at particular times daily or just on weekends, yet the user is not required to enter the time of day or the day of the week.

A hybrid manual / programmable thermostat for a furnace or air conditioner offers the simplicity of a manual thermostat while providing the convenience and versatility of a programmable one. Initially, the hybrid thermostat appears to function as an ordinary manual thermostat; however, it privately observes and learns a user's manual temperature setting habits and eventually programs itself accordingly. If users begin changing their preferred temperature settings due to seasonal changes or other reasons, the thermostat continues learning and will adapt to those changes as well. For ease of use, the thermostat does not require an onscreen menu as a user interface. In some embodiments, the thermostat can effectively program itself for temperature settings that are set to occur at particular times daily or just on weekends, yet the user is not required to enter the time of day or the day of the week.

The present invention provides a multitude of embodiments for landscape water conservation with automated water budgeting or seasonal adjustment. Water budget automation may be implemented within an irrigation controller, by means of an add-on or a plug-in to the controller, or broadcast from a central location. The environmental data used for automated water budgeting may be historical including ambient temperature, wind, solar radiation, relative humidity, soil moisture, soil temperature, or evapotranspiration, or combinations thereof, or with a combination of current sensor data. The automated water budgeting may be accomplished with a percentage accumulation method which adjusts watering intervals and schedules, or on a daily percentage basis. In addition, government based restricted watering schedules may be combined within all the above embodiments to provide additional flexibility for water conservation.

One embodiment practicing aspects of the present invention provides a computer-implemented method for adjusting a reference selling profile for a reference product, comprising retrieving one or more reference selling profiles corresponding to daily or more frequent historical data for one or more reference products, and adjusting the reference selling profiles to correct for one or more promotions which impacted the historical data. Other embodiments and aspects provide for determining location distribution shares, projecting sales, determining distribution quantities, comparing alternative markdown scenarios, etc.

Multi-step statistical modeling in one embodiment of the present disclosure enables anomaly detection, forecasting and / or root cause analysis of the energy consumption for a portfolio of buildings using multi-step statistical modeling. In one aspect, energy consumption data associated with a building, building characteristic data associated with the building, building operation and activities data associated with the building, and weather data are used to generate a variable based degree model. A base load factor, a heating coefficient and a cooling coefficient associated with the building and an error term are determined from the variable based degree model and used to generate a plurality of multivariate regression models. A time series model is generated for the error term to model seasonal factors which reflect monthly dependence on energy use and an auto-regressive integrated moving average model (ARIMA) which reflects temporal dependent patterns of the energy use.

The invention belongs to the field of orchard mechanical equipment and particularly relates to a hydraulic system of orchard picking equipment. Power is provided for an up-installed conveying system and a chassis steering system simultaneously through a constant displacement pump. Flow input of a stacking conveying belt motor and a main conveying belt motor is controlled through a proportional multi-way valve. Control over the extending-and-contracting movement speed of a hydraulic cylinder is achieved through a speed regulation valve. Functions such as automatic conveying of fruit picking andautomatic cartoning of fruits are achieved. Problems that labor capacity of pure manual picking is large, picking efficiency is low and the picking cost is high are solved. The characteristics that fruit harvesting is strong in seasonality and short in harvesting time are met.

An ET based irrigation system includes a stand alone irrigation controller with a seasonal adjust feature and a stand alone weather station including at least one environmental sensor. The ET based irrigation system further includes a stand alone ET unit operatively connected to the irrigation controller and the weather station. The ET unit includes programming configured to calculate an estimated ET value using a signal from the environmental sensor and to automatically modify a watering schedule of the irrigation controller through the seasonal adjust feature based on the estimated ET value to thereby conserve water while maintaining plant health.

Real-time fraud prevention software-as-a-service (SaaS) products include computer instruction sets to enable a network server to receive medical histories, enrollments, diagnosis, prescription, treatment, follow up, billings, and other data as they occur. The SaaS includes software instruction sets to combine, correlate, categorize, track, normalize, and compare the data sorted by patient, healthcare provider, institution, seasonal, and regional norms. Fraud reveals itself in the ways data points deviate from norms in nonsensical or inexplicable conduct. The individual behaviors of each healthcare provider are independently monitored, characterized, and followed by self-spawning smart agents that can adapt and change their rules as the healthcare providers evolve. Such smart agents will issue flags when their particular surveillance target is acting out of character, outside normal parameters for them. Fraud controls can therefore be much tighter than those that have to accommodate those of a diverse group.

Real-time fraud prevention software-as-a-service (SaaS) products include computer instruction sets to enable a network server to receive medical histories, enrollments, diagnosis, prescription, treatment, follow up, billings, and other data as they occur. The SaaS includes software instruction sets to combine, correlate, categorize, track, normalize, and compare the data sorted by patient, healthcare provider, institution, seasonal, and regional norms. Fraud reveals itself in the ways data points deviate from norms in nonsensical or inexplicable conduct. The individual behaviors of each healthcare provider are independently monitored, characterized, and followed by self-spawning smart agents that can adapt and change their rules as the healthcare providers evolve. Such smart agents will issue flags when their particular surveillance target is acting out of character, outside normal parameters for them. Fraud controls can therefore be much tighter than those that have to accommodate those of a diverse group.

A computer implemented system and methods for forecasting the future values of a time series with multiple seasonal cycles are described. The forecasting method of the present invention include 1) two multi-seasonal exponential smoothing methods, 2) the seasonal sub-series method splitting a time series into multiple sub-series, and 3) the aggregate-to-period forecasting method.

An irrigation controller has a control panel including a display and a plurality of user inputs. A processor is operatively connected to the control panel and to a memory. A plurality of switches are operatively connected to the processor for turning a power signal ON and OFF to a plurality of valves that deliver water to a plurality of sprinklers in different zones. Programming is stored in the memory for implementing a seasonal adjustment feature that is independently operable with a plurality of individual watering programs to selectively energize the valves. The programming calculates a soil moisture requirement value for each program using a signal from at least one soil moisture sensor that is associated with a zone that is assigned to that watering program, and automatically modifies the watering program assigned to that zone through the seasonal adjust feature based on the soil moisture requirement value.

Environmental characteristics of habitable environments (e.g., hotel or motel rooms, spas, resorts, cruise boat cabins, offices, hospitals and / or homes, apartments or residences) are controlled to eliminate, reduce or ameliorate adverse or harmful aspects and introduce, increase or enhance beneficial aspects in order to improve a “wellness” or sense of “wellbeing” provided via the environments. Control of intensity and wavelength distribution of passive and active Illumination addresses various issues, symptoms or syndromes, for instance to maintain a circadian rhythm or cycle, adjust for “jet lag” or season affective disorder, etc. Air quality and attributes are controlled. Scent(s) may be dispersed. Noise is reduced and sounds (e.g., masking, music, natural) may be provided. Environmental and biometric feedback is provided. Experimentation and machine learning are used to improve health outcomes and wellness standards.

A soil moisture based irrigation system includes a stand alone irrigation controller with a seasonal adjust feature and a stand alone weather station including at least one soil moisture sensor. The soil moisture based irrigation system further includes a stand alone soil moisture control unit operatively connected to the irrigation controller and the soil moisture sensor. The soil moisture control unit includes programming configured to calculate an estimated soil moisture requirement value using a signal from the soil moisture sensor and to automatically modify a watering schedule of the irrigation controller through the seasonal adjust feature based on the estimated soil moisture requirement value to thereby conserve water while maintaining plant health.

Robust forecasting techniques are relatively immune from anomalies or outliers in observed data, such as a stream of data values reflective of the operation or use of a computer system. One robust technique provides a relatively accurate forecast of seasonal behavior even in the presence of an anomaly in corresponding historical data. Another robust forecasting technique provides a relatively accurate forecast even in the presence of an anomaly that spans multiple recent observations. In one embodiment, both techniques are used in combination to automatically detect anomalies in the operation and / or use of a multi-user computer system.

A methodology for automatic a priori data pattern analysis is provided. Described methods allow consistent and objective determination of outliers; trend; seasonality; and level shifts; and the production of better models and more accurate forecasts. In addition, a two-step way to automatically determine seasonality and locate possible events in the data set is described. Decomposition of data into seasonal, trend and level components; detection of outliers and level-shift events in the time series based on statistical analysis of the time series; detection of seasonality based on statistical analysis of clusters of data, known as cluster-based seasonality analysis, or CBSA; evaluation of the goodness of fit of a model to data, using the existing goodness of fit indicator, R2; and seasonality analysis, using a sequence of cluster-based seasonality analysis (CBSA) and Fourier analysis are described.

Dynamic policy systems and methods for implementing network management of a network include pre-calculating management policies for the network, in an off-line manner, based on past observed network load taking into consideration seasonality of network load, forecasts of the network load, and planned events on the network load; selecting a policy from the pre-calculated management policies, to manage the network in an on-line manner, wherein the selecting is either time-based or performance-based; and performing network management functions in the network utilizing the selected policy.

An online system presents remote users with static incentives, dynamic incentives and the ability to create and submit customizable incentives related to goods or services of interest to the user. By using the incentive delivery system, the user can research goods or services of interest and in an interactive fashion create an incentive package most desirable to the user and submit same to a central location. The systems performs decisioning routines on submitted incentive requests and makes such requests available for review. Ultimately, the submitted requests may be accepted or rejected or a counter-incentive may be issued to the user for consideration. A manufacturer, such as an automobile manufacturer, can offer incentives direct to its consumers and enter into an electronic dialogue with its customers to help drive profits and sales in the most efficient manner. For instance, where certain models of vehicles are in over-supply in a certain geographic region a manufacturer may in real-time tailor its incentive offerings to help account for seasonal or other demand events. Further, the manufacturer can in real-time see the response to its incentives offerings and make appropriate changes to insure the desired result of its marketing efforts is obtained. A graphical user interface enables the remote user to search products or services of interest and to selectively build desired incentives and submit same for acceptance.

The invention relates to a method for extracting blueberry anthocyanin, which comprises the following steps of: (1) pretreating a raw material; (2) extracting the blueberry anthocyanin, namely adding extracting solution in a volume ratio of the raw material to liquid for leaching to obtain leach liquor, centrifugally collecting and merging clarified supernate which is leached and centrifuged twice, and centrifuging and concentrating under reduced pressure to obtain crude extract of the blueberry anthocyanin; and (3) refining the blueberry anthocyanin, namely adsorbing and eluting the crude extract of the blueberry anthocyanin through macroporous resin, concentrating eluent under reduced pressure, and performing freeze drying or spray drying on concentrated solution of the blueberry anthocyanin to obtain a finished product of the blueberry anthocyanin. The method solves the problems of strong harvesting seasonality and difficult storage of blueberry fruits and huge economic loss due torot caused by the unsalable blueberry fruits, has the advantages of simple process, controlled operation, low cost and no pollution, and is particularly suitable for extracting the blueberry anthocyanin on a large scale.

The present invention provides a method and apparatus for detecting and preventing a plurality of denial of service (DOS) and distributed denial of service (DDOS) attacks. The apparatus includes classifiers for parsing packets; meters storing statistics for the classified packets and detecting flood thresholds; an Ager for maintaining timeouts; a decision multiplexer for multiplexing inputs from various meters and determines whether to allow or deny the packet; and a threshold estimation means for estimating thresholds based on past data from meters, baselines, trends and seasonality. The apparatus includes a PCI interface through which a host can interact, learn continuously and set thresholds in a continuous and adaptive manner so as to prevent rate based DOS and DDOS attacks. The apparatus includes a mechanism to track culprit sources at layer 2 and layer 3 through a multiplicative increment method.

Multi-step statistical modeling in one embodiment of the present disclosure enables anomaly detection, forecasting and / or root cause analysis of the energy consumption for a portfolio of buildings using multi-step statistical modeling. In one aspect, energy consumption data associated with a building, building characteristic data associated with the building, building operation and activities data associated with the building, and weather data are used to generate a variable based degree model. A base load factor, a heating coefficient and a cooling coefficient associated with the building and an error term are determined from the variable based degree model and used to generate a plurality of multivariate regression models. A time series model is generated for the error term to model seasonal factors which reflect monthly dependence on energy use and an auto-regressive integrated moving average model (ARIMA) which reflects temporal dependent patterns of the energy use.

The invention provides a large frozen soil model test system with a moisturizing function and a frost heaving test function. A moisturizing system and a refrigeration system of the model test system are arranged in a model tank box body; a loading system capable of vertically moving is arranged at the top of the model tank box body; a temperature field test device is arranged at the periphery of the refrigeration system; a frost heaving three-dimensional stress-strain test device is arranged on the inner side wall in the model tank box body; and a frost heaving and thaw collapse observation device is fixedly arranged at the top of the model tank box body. The large frozen soil model test system has the beneficial effects that a platform for scientific research is provided for researching the physical and mechanical properties of artificially frozen soil and optimizing an artificial freezing method; the large frozen soil model test system can be widely applied to freezing method construction model tests in the fields of geotechnical engineering, underground construction, traffic engineering and the like, for example, simulation tests are carried out on underground construction such as shield tunnel inlet and outlet freezing reinforcement, contact passage freezing method construction, and deep foundation pit freezing support; in addition, the natural frozen soil can also be simulated by adjusting control parameters of refrigerating machines; and large frozen soil model test system is applied to research on damages and effects on buildings and structures caused by seasonally frozen ground and frozen soil in permafrost regions.

Robust forecasting techniques are relatively immune from anomalies or outliers in observed data, such as a stream of data values reflective of the operation or use of a computer system. One robust technique provides a relatively accurate forecast of seasonal behavior even in the presence of an anomaly in corresponding historical data. Another robust forecasting technique provides a relatively accurate forecast even in the presence of an anomaly that spans multiple recent observations. In one embodiment, both techniques are used in combination to automatically detect anomalies in the operation and / or use of a multi-user computer system.

A method for in-season macro and micronutrient application based on predicted yield potential, coefficient of variation, and a nutrient response index. The inventive method includes the steps of: determining a nutrient response index for a field; determining the normalized difference vegetation index (NDVI) of an area to fertilize; determining the coefficient of variation of NDVI over a plot; determining a predicted crop yield for the area without additional nutrient; determining an attainable crop yield for the area with additional nutrient; determining the nutrient requirement for the area as the difference between the nutrient removal at the attainable yield minus the nutrient removal at the predicted yield, adjusted by the efficiency of nutrient utilization in the particular crop as indicated by the coefficient of variation.

A repeatability score is described for determining the quality and reliability of product sales data for generating seasonal demand forecasts. The repeatability scores are calculated from seasonal sales data stored in a data warehouse. Products are sorted based on their reliability scores such that those products that are highly seasonal and have a reliable year-to-year demand pattern are used to form initial or unique demand models. Products that are determined to be less reliable based on their repeatability score are added to the unique demand models through an iterative matching process or left out of the unique demand models.

A business tuning system collects streams of informational reports from remote renewable energy systems. A database holds the information and associates it with a particular renewable energy business operation. A pre-processor semi-structures the information into failure analyses, sales histories, performance results, regional trends, seasonal trends, and demographics. A data mining processor provides for knowledge discovery and prediction from semi-structured information related to said particular renewable energy business operation.

A method and system are provided for presenting rates for travel services using dynamic pricing bands. The dynamic pricing bands represent approximate rates for travel services relative to available rates during or close to the proposed dates of travel, or at or near the proposed travel destination. Each dynamic pricing band is keyed to a particular color, intensity, pattern, sound, or other graphical and / or audio characteristic, thereby providing the consumer a sense of the seasonal, regional, day of week, or other variability of rates for travel services without having to compare actual numbers. The dynamic pricing bands are applied to an interactive presentation of rates for travel services to allow the consumer to explore possible rate variations for particular travel services in a manner that provides a birds-eye view, is intuitive and user-friendly.

An anomaly detection and resolution system (ADRS) is disclosed for automatically detecting and resolving anomalies in computing environments. The ADRS may be implemented using an anomaly classification system defining different types of anomalies (e.g., a defined anomaly and an undefined anomaly). A defined anomaly may be based on bounds (fixed or seasonal) on any metric to be monitored. An anomaly detection and resolution component (ADRC) may be implemented in each component defining a service in a computing system. An ADRC may be configured to detect and attempt to resolve an anomaly locally. If the anomaly event for an anomaly can be resolved in the component, the ADRC may communicate the anomaly event to an ADRC of a parent component, if one exists. Each ADRC in a component may be configured to locally handle specific types of anomalies to reduce communication time and resource usage for resolving anomalies.

Method, apparatus, and system, including computer program products, implementing and using techniques for time series analysis, wherein the time series exhibit trend and / or seasonality. Model parameters of the time series data are determined by selecting and / or suggesting a most appropriate combination of trend and seasonality of the time series data based on analysis of variances of transformed time series data.