1660 results about "Statistical analyses" patented technology

System(s) and method(s) for compensation of propagation delay offsets of wireless signals. Compensation is accomplished through determination of an effective wireless signal propagation delay that accounts for signal path delay and propagation delay over the air. Such determination is based at least in part on statistical analysis of accurate location estimates of reference positions throughout a coverage sector or cell, and location estimates of the reference positions generated through time-of-flight (TOF) measurements of wireless signals. Determination of propagation or signal path delay offset also is attained iteratively based at least in part on reference location estimates and TOF location estimates. High-accuracy location estimates such as those obtained through global navigation satellite systems are employed as reference location estimates. Position of probes or wireless beacons, deployed throughout a sector or cell, also are employed as reference locations. Compensation of propagation delay offset improves accuracy of conventional TOF location estimates and radio network performance.

An unsupervised statistical analytics approach to detecting fraud utilizes cluster analysis to identify specific clusters of claims or transactions for additional investigation, or utilizes association rules as tripwires to identify outliers. The clusters or sets of rules define a “normal” profile for the claims or transactions used to filter out normal claims, leaving “not normal” claims for potential investigation. To generate clusters or association rules, data relating to a sample set of claims or transactions may be obtained, and a set of variables used to discover patterns in the data that indicate a normal profile. New claims may be filtered, and not normal claims analyzed further. Alternatively, patterns for both a normal profile and an anomalous profile may be discovered, and a new claim filtered by the normal filter. If the claim is “not normal” it may be further filtered to detect potential fraud.

Financial data including general ledger balances and underlying journal entries are examined to determine whether risks of material misstatement due to fraudulent financial reporting can be identified. The financial data is analyzed statistically and modeled over time, comparing actual data values with predicted data values to identify anomalies in the financial data. The anomalous financial data is then analyzed using clustering algorithms to identify common characteristics of the various transactions underlying the anomalies. The common characteristics are then compared with characteristics derived from data known to derive from fraudulent activity, and the common characteristics are reported, along with a weight or probability that the anomaly associated with the common characteristic is an identification of risks of material misstatement due to fraud. Large volumes of financial data are therefore efficiently processed to accurately identify risks of material misstatement due to fraud in connection with financial audits, or for actual detection of fraud in connection with forensic and investigative accounting activities.

For Parkinson's patients to function at their best, their medications need to be optimally adjusted to the diurnal variation of symptoms. For this to occur, it is important for the managing clinician to have an accurate picture of how the patient's bradykinesia/hypokinesia and dyskinesia and the patient's perception of movement state fluctuate throughout the normal daily activities. The present invention uses wearable accelerometers coupled with computer implemented learning and statistical analysis techniques in order to classify the movement states of Parkinson's patients and to provide a timeline of how the patients fluctuate throughout the day.

A device for identifying interference source in wireless communications is provided, including a correlation compound module, a matching and screening module, a statistical analysis module, and a match identification module. The correlation compound module uses the time of arrival (TOA) of the burst as the synchronization basis to compound the correlated frequency word, time difference of arrival (TDOA) word, amplitude word and angle of arrival (AOA) word to form a burst descriptor word (BDW). The matching and screening module uses the BWD to match the burst library to screen out the non-interference sources. The statistic analysis module uses the screened outcome for statistical analysis, and obtains a source discriminator file (SDF). The matching and identification module uses the SDF to search the interference source library for matching and obtains an identification result.

An apparatus, system, method, and computer readable medium containing computer-executable code for implementing image analysis uses multivariate statistical analysis of sample images, and allows segmentation of the image into different groups or classes, depending on a correlation to one or more sample textures, or sample surface features. In one embodiment, the invention performs multivariate statistical analysis of ultrasound images, wherein a tumor may be characterized by segmenting viable tissue from necrotic tissue, allowing for more detailed in vivo analysis of tumor growth beyond simple dimensional measurements or univariate statistical analysis. Application of the apparatus and method may also be used for characterizing other types of samples having textured features including, for example, tumor angiogenesis biomarkers from Power Doppler.

The present invention is a power load forecasting method based on big data technology and a research application system based on the method. With the support of big data technology, a variety of mature open source products are integrated to form a data source, data integration, data storage, Data calculation, data analysis, implementation of electrical load characteristic analysis and electrical load forecast analysis. The invention effectively improves the efficiency of mass data processing, and solves the limitations of traditional statistical analysis assumptions and judgments. It can scientifically and accurately predict the electricity demand of the future power, which is conducive to the peak-shaving and valley-filling and stable operation of the power grid, and provides decision-making support for the company's power grid planning, equipment maintenance, and power deployment.

A system and method using statistical analysis for the process of analyzing and generating organizational policies is presented. This inventive method comprises, for one or more tests, using a test to calculate a test result for the policy based on current violator entities and potential violator entities, and determining a policy ranking for the policy based on the test result of the test, and evaluating the policy based on the policy rankings determined from the tests. The method can also comprise creating a repository comprising the policy rankings for the plurality of policies. The repository can be used to trend, benchmark, alert and improve the policies. The method can also comprise creating a rule profile for the one policy comprising the one policy, the current violator entities of the policy, the potential violator entities of the policy, the test results and the policy rankings from the tests.

A comprehensive scheme to detect phishing emails using features that are invariant and fundamentally characterize phishing. Multiple embodiments are described herein based on combinations of text analysis, header analysis, and link analysis, and these embodiments operate between a user's mail transfer agent (MTA) and mail user agent (MUA). The inventive embodiment, PhishNet-NLP™, utilizes natural language techniques along with all information present in an email, namely the header, links, and text in the body. The inventive embodiment, PhishSnag™, uses information extracted form the embedded links in the email and the email headers to detect phishing. The inventive embodiment, Phish-Sem™ uses natural language processing and statistical analysis on the body of labeled phishing and non-phishing emails to design four variants of an email-body-text only classifier. The inventive scheme is designed to detect phishing at the email level.

Similarity of email message characteristics is used to detect bulk and spam email. A determination of “sameness” for purposes of both bulk and spam classifications can use any number and type of evaluation modules. Each module can include one or more rules, tests, processes, algorithms, or other functionality. For example, one type of module may be a word count of email message text. Another module can use a weighting factor based on groups of multiple words and their perceived meanings. In general, any type of module that performs a similarity analysis can be used. A preferred embodiment of the invention uses statistical analysis, such as Bayesian analysis, to measure the performance of different modules against a known standard, such as human manual matching. Modules that are performing worse than other modules can be valued less than modules having better performance. In this manner, a high degree of reliability can be achieved. To improve performance, if a message is determined to be the same as a previous message, the previous computations and results for that previous message can be re-used. Users can be provided with options to customize or regulate bulk and spam classification and subsequent actions on how to handle the classified email messages.

To provide a wind turbine generator, a wind turbine generator system, and a power-generation control method of a wind turbine generator that are capable of improving the power-generation capability and reducing the fatigue load on the windmill. A data accumulation unit 25 sequentially accumulates data sets of a generated output power P during operation of the wind turbine generator, an incoming wind speed Ws estimated on the basis of a wind speed measured at the anemometer, and a wind direction deviation, which is the difference between a wind direction θw measured at the anemoscope and the orientation of the nacelle; statistical analysis of the data accumulated is carried out by an analyzing unit 26; a distribution curve corresponding to the wind direction deviation of the generated output power at each incoming wind speed is determined; the wind direction deviation corresponding to the peak of the distribution curve is set as a correction value θd of the anemoscope; the correction value of the anemoscope for each incoming wind speed is stored in the wind-direction correction table 27; the wind direction Vw measured at the anemoscope is corrected with the correction value θd of the anemoscope for each incoming wind speed Ws; and power-generation control is carried out using the corrected wind direction as a control parameter.

Load balancing of activities on physical disk storage devices is accomplished by monitoring reading and writing operations to blocks of contiguous storage locations on the physical disk storage devices. A list of exchangeable pairs of blocks is developed based on size and function. Statistics accumulated over an interval are then used to obtain access activity values for each block and each physical disk drive. A statistical analysis leads to a selection of one block pair. After testing to determine any adverse effect of making that change, the exchange is made to more evenly distribute the loading on individual physical disk storage devices.

The present invention uses market research data to access nutrient intakes of a population. Dietary collection using 24-hour recall generally does not reflect a pattern of “usual” intake behavior for a population group. To determine the impact of food consumption patterns on nutrient intake, a unique methodology using 14-day food diary was developed. The food industry has traditionally used detailed food records to track the consumption of specific branded food items and monitor the growth of food categories, but some of the most valuable databases available concerning longer-term (e.g., 14-day) food intake do not record portion size on an individual consumption basis. Other databases based on shorter-term (24-hour recall) survey periods record portion sizes but are not very representative of eating habits. The preferred exemplary embodiment integrates two such databases with a third data set providing detailed nutrient information for each of a wide variety of foods consumed to provide a combined database for processing nutrient intake reports using statistical analysis. This flexible system allows the user to categorize the population based on “usual” consumption of food categories, specific foods and/or specific brands of foods and determine dietary differences versus their “non-using” counterparts.

A business and software method to cost-effectively optimize product and/or service development portfolios, to reduce time to market, and to better integrate and align product or service strategy with brand strategy. The business and software method includes defining in detail the product and service attributes that characterize the ideal customer experience, categorizing the attributes, assigning a numerical value of importance to the attributes, and applying those values to statistical analysis of each assessed product development initiative in terms of alignment with ideal experience and potential competitive impact relative to the resources and risks required to bring each initiative to market. A prioritization for product development resource allocation is developed based upon these analyses. The prioritization is presented in the form of decision intelligence tools for an organization to use and reach informed judgments concerning resource allocation to develop, maintain, or optimize a given product or service portfolio. The decision intelligence tools serve to improve business performance, increase market impact, and build brand equity for products and services of a given organization by improving alignment between what the organization promises customers and what it actually delivers.

The invention discloses an information entropy variance analysis-based abnormal traffic detection method. According to the method, a large quantity of Internet user access logs are obtained, and collected data is processed via a system; attack behaviors or abnormal behaviors can be rapidly identified and recorded via big data mining, association and statistical analysis; invasive attack alarm information data can be formed; a complete attack path can be constructed via relevant invasive attack data analysis, and therefore an object of invasion tracking and positioning can be attained. Via use of the abnormal traffic detection method, behavior after events can be traced and machine learning of user access behaviors can be realized, a false alarm rate of a system can be lowered, a network traffic detectability set is put forward, a baseline for normal network traffic is described, and reference is provided for abnormity detection.

A portable monitoring device for monitoring of the short term, mid term and long term risks of Sudden Infant Death Syndrome (SIDS) and to estimate the risk of onset of positional plagiocephaly. The monitoring device acquires one or more signals associated to the typical breath and positioning patterns of an infant through a tri-axial accelerometer, and registers the data in electronic format, where statistical analysis of the signal and pattern recognition are performed in real time by a processing unit. The device monitors the breath activity of an infant in various conditions, alerting a caregiver when a potentially dangerous situation is detected. The monitoring is attached to the clothes of the infant. Statistical analysis of the registered data is performed for quantifying the long term SIDS risk, the risk of plagiocephaly and for optimizing the functional parameters of the monitoring device.