82 results about "Receiver operating characteristic" patented technology

Adjusting confidence score thresholds is described for a speech recognition engine. The speech recognition engine is implemented in multiple computer processes functioning in a computer processor, and is characterized by an associated receiver operating characteristic (ROC) curve. A results confirmation process interprets user confirmation of speech recognition results within a given confidence score threshold to create a confirmed portion of the ROC curve for the speech recognition engine. A curve extension process extends the confirmed portion of the ROC curve by extrapolation of unconfirmed speech recognition results beyond the confidence score threshold to generate an extended ROC curve. A threshold adjustment process adjusts the confidence score threshold based on the extended ROC curve to meet target operating constraints for operating the speech recognition engine to perform automatic speech recognition of user speech inputs.

The invention discloses a multi-parameter magnetic resonance image based prostate cancer computer auxiliary identification system and method. The multi-parameter magnetic resonance image based prostate cancer computer auxiliary identification system comprises three portions of an image preprocessing module, a parameter processing module and a prediction and evaluation module. According to the multi-parameter magnetic resonance image based prostate cancer computer auxiliary identification system, the characteristics of a T2 weighted image, a diffusion weighted image and a dynamic enhanced image are comprehensively utilized and the purpose of the identification of the prostate cancer focus is achieved through an artificial neural network structure; the ROC (Receiver Operating Characteristic) area under curve of the peripheral zone of prostate of the system is 0.931 and the identification accuracy is 0.887 and the ROC area under curve in the central gland is 0.909 and the identification accuracy is 0.915 through a test; the image information obtained through the conventional magnetic resonance imaging scanning sequence scanning sequence can be well integrated, quantitative parameters in the images are utilized in a maximum mode, and the identification result of the prostate cancer is objectively provided; the operation is simple and convenient, the reference can be intuitively provided for doctors, and the important basis is provided for the subsequent diagnosis scheme.

Polygenic disorders are due to the additive effect of multiple genes interacting with the environment. Because of the small effect size of each gene and considerable genetic heterogeneity, when single genes are examined, the outcome of association and linkage analyses are variable from study to study. Techniques are needed that take these unique characteristics of polygenic disorders into consideration. The present invention discloses that the formation of a polygenic score, consisting of the additive effect of multiple candidate genes, and its assessment using receiver operating characteristic (ROC) plots, provides such a technique. Six genes previously shown to be associated with Alzheimer's disease were examined, APOE, ACE, ACP1, ESR1, PNMT and SLC6A4. The total fraction of the variance, the area under the ROC plots, and the range of risks were similar for both groups indicating that despite genetic heterogeneity and the small effect size of most genes, consistent risk analyses could be obtained by examining the additive effect of these multiple genes. The present invention also discloses diagnostic tests for determining a subject's risk of developing Alzheimer's Disease or specifically Late Onset Alzheimer's Disease.

A method and device (8) for verifying the authenticity of media content is provided. According to an embodiment accurate tampering location for digital image authentication is provided. Typically, a suspect image is divided into blocks. For each block, an authentication bit is generated by computing a property of the image content and then thresholding said property to give a ‘0’ or ‘1’. The authentication bits of the suspect image are compared with those of the original image. If there is a mismatch, and the content has indeed been tampered, tampering is detected. A mismatch due to allowable operations, such as e.g. compression, is called a false alarm, which should be avoided. A so-called ROC curve (Receiver Operating Characteristic) gives the relation between detection probability and false alarm probability. Preferably, the threshold used to determine the authentication bits represents an operation point on the ROC curve. In accordance with an embodiment of the invention, an operation point corresponding to a low false alarm probability is initially chosen. In order to more precisely identify a tampered image area, the authentication decisions are repeated for neighbouring blocks, using a different operation point. This continues until no further tampered blocks are found. Thus improved tampering localisation is provided, being valuable e.g. to authenticate images captured by e.g. a security camera, and localise any tampered areas, whereby the value of these images is increased as e.g. evidence in a court of law.

A machine-learning based artificial intelligence device for finding an estimate of patent quality, such as patent lifetime or term is disclosed. Such a device may receive a first set of patent data and generate a list of binary classifiers. A candidate set of binary classifiers may be selected and using a heuristic search, for example an artificial neural network (ANN), a genetic algorithm, a final set of binary classifiers is found by maximizing iteratively a yield according to a cost function, such an area under a curve (AUC) of a receiver operating characteristic (ROC). The device may then receive patent information for a target patent and report an estimate of patent quality according to the final set of binary classifiers.

Methods and systems for detecting and defeating a low and slow application DDoS attack, comprising: computing the Entropy of a plurality of detectors, at least in part selected from a group Geo detector, a group response size detector, a group preference detector, and an individual client behavior detector, wherein the plurality of detectors each describe a feature of traffic affected by the DDoS attack; composing the plurality of detectors on one or more of a Receiver Operating Characteristic (ROC) curve basis and a correlation basis; and implementing a countermeasure to mitigate the DDoS attack.

Data representing application deployment attributes, network topology, and network performance attributes based on a reduced set of element attributes is utilized to simulate application deployment. The data may be received from a user directly, a program that models a network topology or application behavior, and a wizard that implies the data based on an interview process. The simulation may be based on application deployment attributes including application traffic pattern, application message sizes, network topology, and network performance attributes. The element attributes may be determined from a lookup table of element operating characteristics that may contain element maximum and minimum boundary operating values utilized to interpolate other operating conditions. Application response time may be derived using an iterative analysis based on multiple instances of one or more applications wherein a predetermined number of iterations is used or until a substantially steady state of network performance is achieved.

A method to use a receiver operator characteristics curve for model comparison in machine condition monitoring. The method and systems of using this method may be used to evaluate different monitoring models. These models may be used to monitor a variety of different systems such as power plant systems or magnetic resonance imaging systems. The methods use training data and designate one or more points in the data as a false negative, thereby permitting a receiver operator characteristics analysis to be performed. Multiple receiver operator characteristics analyses may be performed either on different models or on different points within a single model, thereby permitting the receiver operator characteristics analyses to be used to select a beneficial model for monitoring a particular system.

The present invention belongs to the color image processing technical field and relates to a global color contrast detection and saliency map segmentation method. The method of the invention includes saliency detection and saliency map segmentation; according to the saliency detection, a global color contrast method is adopted; according to the saliency map segmentation, a dynamic threshold method is adopted. According to the method of the present invention, a preliminary saliency map is obtained through extracting the features of global color contrast; the saliency of the preliminary saliency map is improved through using color dispersion and spatial information; and with the saliency map generated in the above steps adopted as an initial value, a threshold value which is dynamically updated by iteration is adopted to segment a plurality of salient targets. As indicated by the experiment result of a published Achanta database, the performance of the method of the invention on an ROC (receiver operating characteristic) curve is superior to that of methods in literatures and reports, and the method of the invention is applicable to multi-target detection and segmentation problems.

Methods for constructing multivariate predictive models for diagnosing diseases for which test methods are individually inadequate, including: (a) performing laboratory tests on a statistically significant test population of individuals; (b) generating a score function from a linear combination of test panel results; (c) performing a receiver operating characteristic (ROC) regression or alternative regression technique of the score function using those tests and β coefficients calculated simultaneously to maximize the area under the curve (AUC) of the function and chosen simultaneously to generate the largest area below that portion of the ROC curve for the (1−t0) quantile of individuals without disease, where t0 represents the maximum acceptable false-positive rate; (d) calculating individual pre-test disease odds; generating a diagnostic likelihood ratio of disease by determining the frequency of each individual's test score in the diseased population relative to the control population; and multiplying pre-test odds by the likelihood ratio to determine individual post-test disease odds; (e) converting a set of posttest odds into posttest probabilities for each potential multivariate methodology and creating an ROC curve for each methodology by altering posttest probability cutoff values; (f) comparing partial ROC areas generated by one or more regression techniques to determine the optimal methodology; and (g) dichotomizing the optimal methodology by finding that point on the ROC curve tangent to a line with slope (1−p) C / p·B, where p is population prevalence of disease, B is regret associated with failing to treat patients with disease and C is regret associated with treating a patient without disease.

A system for facilitating the detection and successful decoding of a quick paging channel adapted for use with a wireless communications system supporting a primary paging channel and a quick paging channel. The system includes a first mechanism for detecting a pilot signal associated with the quick paging channel based on a received signal and includes a coherent integrator of a first length and a noncoherent integrator of a second length. The second mechanism determines receiver operating characteristics of the system based on the pilot signal and a quick paging channel signal associated with the quick paging channel. The third mechanism optimizes the first length and the second length based on the receiver operating characteristics. In a specific embodiment, the first mechanism includes a CDMA receive chain for receiving the received signal and providing a digital received signal in response thereto to a sample Random Access Memory (RAM). The sample RAM includes a mechanism for sampling the digital received signal at predetermined time slots and providing a sampled received signal in response thereto. An interpolator adjusts the rate of the sampled received signal and provides a rate-adjusted signal in response thereto. The first mechanism includes a searcher that includes the first coherent integrator, a second coherent integrator, and the noncoherent integrator. A complex despreader correlates the rate-adjusted received signal with a pseudo noise candidate code and providing a correlation result in response thereto.

Described is a system for multi-class classifier threshold-offset estimation for visual object recognition. The system receives an input image with input features for classifying. A pair-wise classifier is trained for each pair of a plurality of object classes. A set of classification responses is generated, and a multi-class receiver-operating-characteristics (ROC) curve is computed for a set of threshold-offsets. An objective function of classification performance is computed from the ROC curve and optimized using particle swarm optimization (PSO) to generate a set of optimized threshold-offsets. The optimized threshold-offsets are then applied to the classification responses. The resulting classification responses are compared to a predetermined value to classify each input feature as belonging to one object class or another. The tuning of the threshold-offsets with (PSO) improves classification performance in a visual object recognition system.

Provided are an apparatus and method for fast and adaptive computer-aided detection of pulmonary nodules and differentiation of malignancy from benignancy in thoracic CT images using a hierarchical vector quantization scheme. Anomalous pulmonary nodules are detected by obtaining a two-dimensional (2D) feature model of a pulmonary nodule, segmenting the pulmonary nodule by performing vector quantification to expand the 2D feature model to a three-dimensional (3D) model, and displaying image information representing whether the pulmonary nodule is benign, based upon the 3D model expanded from the 2D feature model, with duplicate information eliminated by performing feature reduction performed using a principal component analysis and a receiver operating characteristics area under the curve merit analysis. A textural feature analysis detects an anomalous pulmonary nodule, and 2D texture features are calculated from 3D volumetric data to provide improved gain compared to calculation from a single slice of 3D data.

Systems and methods for detection and localization of image and document forgery. The method can include the step of receiving a dataset having a plurality of authentic images and a plurality of manipulated images. The method can also include the step of benchmarking a plurality of image forgery algorithms using the dataset. The method can further include the step of generating a plurality of receiver operating characteristic (ROC) curves for each of the plurality of image forgery algorithms. The method also includes the step of calculating a plurality of area under curve metrics for each of the plurality of ROC curves. The method further includes the step of training a neural network for image forgery based on the plurality of area under curve metrics.

The invention discloses a traditional Chinese painting identification method based on Radon BEMD (bidimensional empirical mode decomposition) transformation. The method comprises the following steps: authentic works and fake works of a certain traditional Chinese painting painter are collected according to a same resolution to form a painting library; a small piece with the same length and width and with abundant brush strokes is collected from each painting so as to form a sample library; characteristics are extracted from each sample so as to form a characteristic vector library; a random extractor is used to divide the characteristic vector library into a training set and a test set; a plurality of comparably good classification models are trained according to a 0.623 self-service method and a support vector machine method, and an ROC (receiver operating characteristic) curve is used as an assessment standard; and an expert ballot method is used to identify the concentrated characteristic vector in a test, and a result is outputted in terms of an identification accuracy. The method of the invention does not require comparing and analyzing a plurality of small contents in the authentic and fake traditional Chinese paintings; and the method can be applied to a wider area and is more operable; in the method, after the noise and the balance are screened out, the characteristics are extracted to prevent interference caused by the noise; and the identification accuracy of authentic and fake traditional Chinese painting digital images is improved.

The invention discloses a land use change modeling method and system implemented in combination with spatial filtering and relates to the field of geographical information sciences. The method focuses on eliminating the spatial autocorrelation influence of data in the process of land use change modeling, and comprises the following steps: collecting original data, and preprocessing the original data so as to generate a data set sequence; determining the optimum distance of spatial filtering by using a variation function, and then splitting variable factors by using a Getis principle based a spatial filtering method; constructing a logistic regression model according to a filtered sample, and assessing the model by using methods such as fitting accuracies and ROC (receiver operating characteristic) curves; and finally, providing a Markov chain and a customized change pattern for forecasting the trend of land use change. According to the invention, based on a statistics mathematical model, a spatial filtering mode is adopted for making up the shortcomings and defects of the mathematical model in geo-spatial calculation, so that through the combination of the two, the fitting accuracy of the model is improved, and the model is more conform to the time and space characteristics of land use change.

Provided is a method for detecting a LFM signal under a low signal-to-noise ratio. The method comprises the following steps of: performing short-time Fourier transform (STFT) in a linear regular regin on a received LFM signal so as to obtain a STFT spectrum of the LFM signal in the linear regular regin; performing Hough transformation on the STFT spectrum in the linear regular regin; performing traversal on a matrix subjected to the Hough transformation by using a two-dimensional sliding window and performing energy accumulation in the sidling window so as to obtain a test statistic; and obtaining an optimal decision threshold according to a receiver operating characteristic curve (ROC) in order to detect the LFM signal. The method has a good detection performance on the LFM signal in a low signal-to-noise ratio environment.

A method and device (8) for verifying the authenticity of media content is provided. According to an embodiment accurate tampering location for digital image authentication is provided. Typically, a suspect image is divided into blocks. For each block, an authentication bit is generated by computing a property of the image content and then thresholding said property to give a '0' or '1'. The authentication bits of the suspect image are compared with those of the original image. If there is a mismatch, and the content has indeed been tampered, tampering is detected. A mismatch due to allowable operations, such as e.g. compression, is called a false alarm, which should be avoided. A so-called ROC curve (Receiver Operating Characteristic) gives the relation between detection probability and false alarm probability. Preferably, the threshold used to determine the authentication bits represents an operation point on the ROC curve. In accordance with an embodiment of the invention, an operation point corresponding to a low false alarm probability is initially chosen. In order to more precisely identify a tampered image area, the authentication decisions are repeated for neighbouring blocks, using a different operation point. This continues until no further tampered blocks are found. Thus improved tampering localisation is provided, being valuable e.g. to authenticate images captured by e.g. a security camera, and localise any tampered areas, whereby the value of these images is increased as e.g. evidence in a court of law.

The invention discloses a method for identifying user interest. The method includes acquiring training samples and test samples; extracting characteristics of the training samples and the test samples by the aid of first preset algorithms and computing the optimal model parameters of logic regression models according to the characteristics of the training samples by the aid of iterative algorithms; evaluating the logic regression models with the optimal model parameters according to the characteristics of the test samples and the areas under ROC (receiver operating characteristic) curves (AUC) and acquiring first theme classifiers by means of training; determining themes of text data by the aid of the first theme classifiers, computing scores of the themes of the text data according to the logic regression models with the optimal model parameters and computing confidence scores of the themes according to second preset algorithms. Training is carried out according to the text data to obtain corresponding topic models, and the topic models are manually annotated to obtain the training samples. Users are interested in the themes with the computed confidence scores. The invention further discloses a device for identifying the user interest and a computer readable storage medium. The method, the device and the computer readable storage medium have the advantages that the user interest can be identified, and accordingly enterprises can be assisted in accurately positioning potential clients.

The invention provides a circuit breaker operating characteristic analytical method based on the virtual prototype technology, which includes steps: firstly, setting up a speed index system, a displacement index system and a force index system for evaluating circuit breaker operating characteristics; secondly, determining eigenvalue of each index in the index systems; thirdly, setting up a circuit breaker model and obtaining simulation value of each eigenvalue by kinematically and dynamically simulating the circuit breaker operation process; and fourthly, calculating a deviation matrix of the circuit breaker operating characteristics according to a simulation value matrix and a reference value matrix. Applying the method to the circuit breaker design stage enables designers to comprehensively consider multiple operating characteristics. Compared with the prior art only considering several operating characteristics including switching-on and switching-off speed and switching-on and switching-off time, the method has the advantages that ten operating characteristics are comprehensively considered to lead the designers to work out more optimized designs, product development risks can be effectively reduced, and foundations can be established for comprehensive product performance improvement.

The present invention provides a method and apparatus for design verification. The method comprises operating a device in the system in a first state, modifying at least one operational characteristic of the device to operate in a second state, and determining if an error condition occurs in the system in response to modifying the operational characteristic of the device. The apparatus comprises an interface and a verification module adapted to receive a control signal from the interface and to adjust an operating characteristic of the apparatus to exercise a system in a manner that is capable of revealing one or more error conditions in the system in response to receiving the control signal.

A new combined index of structure and function (CSFI) for staging and detecting glaucomatous damage is provided. An observational study including 333 glaucomatous eyes (295 with perimetric glaucoma and 38 with preperimetric glaucoma) and 330 eyes of healthy subjects is described. All eyes were tested with standard automated perimetry (SAP) and spectral domain optical coherence tomography (SDOCT) within 6 months. Estimates of the number of retinal ganglion cells (RGC) were obtained from SAP and SDOCT and a weighted averaging scheme was used to obtain a final estimate of the number of RGCs for each eye. The CSFI was calculated as the percent loss of RGCs obtained by subtracting estimated from expected RGC numbers. The performance of the CSFI for discriminating glaucoma from normal eyes and the different stages of disease was evaluated by receiver operating characteristic (ROC) curves. The mean CSFI, representing the mean estimated percent loss of RGCs, was 41% and 17% in the perimetric and pre-perimetric groups, respectively (P<0.001). They were both significantly higher than the mean CSFI in the normal group (P<Q.0( )1). The CSFI had larger ROC curve areas than isolated indexes of structure and function for detecting perimetric and preperimetric glaucoma and differentiating among early, moderate and advanced stages of visual field loss. An index combining structure and function performed better than isolated structural and functional measures for detection of perimetric and preperimetric glaucoma as well as for discriminating different stages of the disease.

The invention discloses a fault diagnosis method for a rotary machine based on angle resampling and an ROC (Receiver Operating Characteristic)-SVM (Support Vector Machine) and belongs to the field offault diagnosis of mechanical equipment. The method comprises the steps of eliminating fluctuation of a rotation speed by use of an angle resampling technology; performing characteristic value extraction from the dimensions of a time domain and a time-frequency domain; and implementing characteristic selection and fault diagnosis of the rotary machine by use of the ROC-SVM. According to the faultdiagnosis method for the rotary machine based on angle resampling and the ROC-SVM, the change of the number of sampling points of a vibration signal in unit time caused by the fluctuation of the rotation speed can be effectively eliminated by use of the angle resampling method, thereby improving the quality of the subsequent extraction characteristic value; the time domain and the time-frequency domain are combined to achieve wider characteristic extraction and obtain sufficient vibration signal information; the characteristic selection and fault diagnosis are performed by use of the ROC-SVM,the best characteristics are selected to prevent poor characteristics from reducing the effect of a fault classifier; the accuracy and effectiveness of the bearing fault diagnosis can be improved, thediagnosis speed can be accelerated, and a new concept is provided for solving the problem of the bearing fault diagnosis.

According to the present invention, it is found that a DNA methylation marker exists in the DNA of host T cells and peripheral blood mononuclear cells (PBMCs) of cancer patients. The invention discloses CG IDs derived from PBMCs DNA, wherein the clinical progression staging of hepatocellular carcinoma (HCC) and chronic hepatitis can be predicted through the methylation level of the CG IDs in the DNA of PBMCs or T cells. The present invention further discloses a kit for predicting HCC by using the identified CG IDs, and applications of a pyrosequencing DNA methylation experiment, a receiver operating characteristic (ROC) experiment, a penalized regression experiment and hierarchical clustering analysis in prediction of HCC. According to the present invention, any one of technicists in the field can obtain the DNA methylation marker for any cancers and the clinical progression staging of any cancers; and the DNA methylation marker (CG IDs) is used for diagnosing cancers, different clinical progression staging of cancers, the response of patients undergoing treatment to treatment, and chronic hepatitis B or chronic hepatitis C.

The invention relates to an extraction method for a bedrock coast line, comprising: based on an object-oriented method, performing multi-scale segmentation on remote sensing image data from which thebedrock coast line is going to be extracted; establishing operating characteristics according to the remote sensing image data after the multi-scale segmentation; establishing a membership functionaccording to the established operating characteristics; setting adiscrimination interval of the membership function for discriminating seawater by using a fuzzy rule, and assigning the membership function by using the discrimination interval; classifying the assigned membership function, and extracting a seawater object to obtain the bedrock coast line. The invention further relates to an extractionsystem for a bedrock coast line. The method and the system have strong global search capability and robustness, can better distinguish, extract and amplify the characteristics useful for classification, and are clear in classification result contour and low in degree of fragmentation of classification results.

The invention discloses a serum marker miR-301a with the sequence of SEQ ID NO. 1 and application of a kit prepared by adopting the miR-301a marker as a molecular marker in early diagnosis for pancreatic cancer induced by pancreatitis and curative effect monitoring. The kit prepared by adopting the miR-301a marker can conveniently and quickly detect the expression level of miRNA, it is not necessary to customize special primer sequences additionally, and by detecting the blood plasma, pancreatic cancer tissue and expression level of the miR-301a in a pancreatic cancer cell line of a patient suffering from pancreatitis and pancreatic cancer, the Pearson correlation test is utilized for analyzing the relationship between the miR-301a and a known traditional marker of pancreatitis and comparing the miR-301a with the known traditional marker of pancreatitis; through a receiver operating characteristic curve (ROC), the identification capacity of the miR-301a and joint detection by the miR-301a and CA199 in pancreatic cancer diagnosis and pancreatic cancer staging is evaluated, and the potential value of the miR-301a marker of the blood plasma in early diagnosis for pancreatic cancer induced by pancreatitis is investigated to provide a new theory and a new test basis for early diagnosis and targeted therapy of pancreatic cancer from the miRNA level.

In a signal processing system, a set of channel signals from an array of sensors of different operating characteristics are processed in calibration circuitry that calculates individual average values of the channel signals and calculates an average of the individual average values of channel signals as a reference value. Reciprocal calculators calculate reciprocal values of the individual average values of the channel signals. Scaling circuitry scales the reciprocal values by the reference value to produce a set of amplitude calibration signals and scales the channel signals by the calibration signals respectively. As a result, the channel signals are normalized by their own average values and scaled by the reference value to produce a set of calibrated channel signals.

A method and system to detect the microcalcifications (MC) in different type of images viz. X-ray images / mammograms / computer tomography with varied densities using nonlinear energy operator (NEO) is disclosed to favor precise detection of early breast cancer. Such Microcalcifications are associated with both high intensity and high frequency content. The same NEO output is useful to detect and remove the irrelevant curvilinear structures (CLS) thereby helps in reducing the false alarms in micro calcification detection technique. This is effective on different dataset (scanned film, mammograms with large spatial resolution such as CR and DR) of varied breast composition (viz. dense, fatty glandular, fatty), demonstrated quantitatively by Free-response receiver operating characteristic (FROC). Importantly, the method and apparatus of the invention can be used in conjunction with machine learning techniques viz. SVM to favor detection of incipient or small microcalcifications, thus benefiting radiologists in confirming detection of micro-calcifications in X-rays images / mammograms and reducing death rates.