300 results about "Sample Type" patented technology

Apparatus for and method of fully automatic rapid scanning and digitizing of an entire microscope sample, or a substantially large portion of a microscope sample, using a linear array detector synchronized with a positioning stage that is part of a computer controlled microscope slide scanner. The invention provides a method for composing the image strips obtained from successive scans of the sample into a single contiguous digital image. The invention also provides a method for statically displaying sub-regions of this large digital image at different magnifications, together with a reduced magnification macro-image of the entire sample. The invention further provides a method for dynamically displaying, with or without operator interaction, portions of the contiguous digital image. In one preferred embodiment of the invention, all elements of the scanner are part of a single-enclosure that has a primary connection to the Internet or to a local intranet. In this embodiment, the preferred sample type is a microscope slide and the illumination and imaging optics are consistent with transmission mode optics optimized for diffraction-limited digital imaging.

Methods and devices are provided for determining a suitable site for sampling physiological fluid. In the subject methods, a potentially suitable physiological sampling site is selected, the fluid flow of the site is characterized and the site is then determined to be suitable based on the whether the site has high or low flow. Suitability may also be determined based on the type of sample obtainable from the site, where the order of the above-described steps may be altered. The subject devices include at least one site flow characterization element for determining the flow characteristics of a potential physiological sampling site and/or at least one sample type characterization element for determining whether the vasculature is arterial, venous or neither, i.e., an interstitial fluid sampling site. The subject methods and devices are particularly suited for use in the detection of physiological sampling sites in the fingers, arms, legs, earlobes, heels, feet, nose and toes. Also provided are kits that include the subject devices for use in practicing the subject methods.

An embodiment of monitoring resource usage in a computing environment begins with a first client registering a session with a monitoring entity. The session comprises an event type, a count, a start condition, an end condition, and a sample type. Next, a second client registers with the session. Upon occurrence of the start condition and until occurrence of the end condition or until interrupted, the monitoring entity iteratively initiates a counting of occurrences of the event type that continues until reaching the count and saves a sample according to the sample type upon reaching the count. The resource monitoring entity provides at least a portion of a plurality of samples to the first client.

The invention provides methods and compositions, e.g., kits, for removing contaminants from nucleic acids in a sample, e.g., environmental or biological samples such as soil, food, plant, animal, microorganism or water samples. The invention provides methods and compositions for isolating nucleic acids from environmental and biological samples in a scaleable process free of contaminating substances that inhibit PCR and other downstream applications. Exemplary sample types include soil, water, plant and food. The methods and compositions of the invention can be used for isolating and/or detecting nucleic acids from prokaryotic and eukaryotic organisms and for detecting multiple types of organisms in a sample. Thus, the methods and compositions of the invention are useful for detecting organisms pertaining to agriculture, forensics biology and/or combating bioterrorism.

The present invention provides a microarray chip for use in the analysis of various sample types. The microarray chips disclosed herein generally comprise a substrate covered with a coating material comprising a photoresist material, wherein the coating material is patterned to comprise a plurality of microstructures such as microwells and/or microcolumns. Methods for preparing and utilizing the microarray chips of the invention are further provided. The microarray chips of the instant invention find particular use in high-throughput assays.

Compositions, methods and kits are described for identifying biomolecules (e.g., proteins and nucleic acids) expressed in a biological sample that are associated with the presence, development, or progression of a disease (such as cancer), or more generally determination of the etiology or risk factors associated with a disease. Sample types analyzed by the disclosed methods include but are not limited to archival tissue blocks that have been preserved in a fixative, tissue biopsy samples, tissue microarrays, and so forth. The methods disclosed herein correlate expression profiles of biomolecules with various disease types, and allow for the determination of relative survival rates; in some embodiments, the methods permit determination of survival rates for a subject with cancer. In other embodiments, the disclosure relates to methods for evaluating therapeutic regimes for the treatment, such as treatment of cancer.

The invention discloses a video smoke detecting method based on multi-feature fusion. The video smoke detecting method includes extracting motion targets from a training video sequence, judging whether or not a suspected smoke area according to color features, extracting shape irregularity features, area growth features and K background fuzzy features from the suspected smoke area to combine into feature vectors to combine into feature vector, subjecting the feature vector into positive and negative sample division to obtain training samples; using the feature vector of the training samples as output and sample types as output and training a classifier; extracting the feature vector from images to be detected by the same method, and inputting the feature vector to judge whether smoke is or not. The features can be extracted from the suspected smoke area, smoke can be comprehensively judged and detection efficiency of smoke is improved.

A simple yet high performance optical system is described which is tailored to enabling efficient detection of the luminescence emissions of near infrared-to-visible upconverting phosphors. The system is comprised of simple and relatively low cost optical components and is designed to telecentrically enable low optical power NIR excitation and high sensitivity VIS and NIR detection of the upconverting phosphor (UCPs), particularly the lanthanide doped UCP nanocrystals which show great promise for utility as molecular taggants in many applications of biomedicine, security and environmental monitoring. The overall system is designed to facilitate compact spectrophotometric instrument manufacture and is adaptable to multiple liquid or solid sample types and formats.

The sample type digestive tract medicine releasing and sampling device includes a shell to form sealed cavity; an inwards non-return valve communicated with the inside of the shell in the front end of the shell; a magnetic switch, a power source, a power source managing and controlling unit, a driving unit, a sealing layer and a rubber piston inside the shell; and an outer trigger. After the triggering signal the outer trigger sends is received and treated by the signal control unit, the driving unit relieves the stored mechanical energy based on the command to drive the piston, the stored medicine is exhausted through an outwards non-return valve to the digestive tract, and liquid enters the liquid storing bin through the opened inwards non-return valve. After the piston reaches to the top of the shell, the stroke ends, two valves are closed automatically to separate the collected liquid inside the liquid storing bin from outside. The medicine releasing and sampling device has high reliability, low power consumption, long stand-by time and simple structure.

The invention discloses a drilling grabbing shovel type combined sampler device for planetoid detection and a use method of the drilling grabbing shovel type combined sampler device. The device comprises a feeding mechanism, a drilling mechanism, a grabbing shovel mechanism and a mounting plate. The use method comprises the following steps of (1) resetting a motor; (2) checking the motor; (3) performing sampling by a grabbing shovel motor; (4) detecting a shovel; (5) rotating a drilling rod to downwards move; (6) checking the drilling rod; (7) lifting the drilling rod; (8) checking the drilling rod; (9) performing sampling; (10) checking a sampling pipe; (11) enabling the drilling mechanism to upwards move; (12) checking a micro switch contact; (13) stopping a feeding motor; (14) checking a sampler; (15) arranging samples; (16) checking the shovel; (17) arranging the samples; (18) checking the sampling pipe; and (19) performing resetting. According to the drilling grabbing shovel type combined sampler device for planetoid detection and the use method of the drilling grabbing shovel type combined sampler device, sample collection can be realized on the surface of a planetoid, and deep sampling can be executed; bedding information of the samples can be kept; the device has the advantages of large sampling amount, various sample types, retention of original appearances of the samples and the like.

The present invention provides an adjuvant disease diagnosis method based on patient test results. The method comprises: cleaning original data, and constructing sample data according to the test category; using the current xgboost framework with high speed and high accuracy to improve the algorithm and reduce the error rate, designing the model loss function and optimizing the number of iterations of the model, and training the multiple diagnostic models according to the type of the sample; and outputting some diseases with relatively large probability that patients could be suffered from. The present invention provides the disease diagnosis method with high reliability for assisting doctors to improve the diagnosis rate of the disease and reduce the misdiagnosis rate.

The embodiment of the invention discloses an obstacle detection method and device, a vehicle and a storage medium. The method comprises the following steps: obtaining a depth map around a vehicle; performing ground fitting based on the depth map to determine a ground equation; determining an obstacle candidate point set according to the ground equation and based on the depth map; clustering each candidate point in the obstacle candidate point set to obtain at least one independent obstacle; and identifying and filterng false detection obstacles in at least one independent obstacle to obtain anobstacle detection result based on the depth map. It can avoid the obstacle missing detection problem caused by the sparse sampling points when using the laser radar for detection; and the missing detection problem caused due to the fact that since not all types of obstacles can be used as samples for model training when a monocular camera is adopted for detection, the types of untrained samplescannot be detected, can also be avoided.

Methods and systems are disclosed for developing profiles of a state of a biological system based on the discernment of similarities, differences, and/or correlations between a plurality of data sets that are derived from one or more biomolecular component types, one or more biological sample types, and/or one or more types of measurements.

A license plate recognition system and method recognizes a license plate attached to a vehicle and bears a license plate number. The system includes a database module, a reducing module, an image capturing unit, a sorting unit, and a recognizing module. The database module stores license plate position sample type-related data and license plate number sample type-related data whose quantity is reducible by the reducing module. The image capturing unit captures license plate images at different imaging resolutions to generate license plate position image eigenvalue and license plate number image eigenvalue. The sorting unit computes the license plate position image eigenvalue to generate license plate position type-related data and computes the license plate number image eigenvalue to generate license plate number type-related data. The recognizing module compares the license plate number type-related data with the license plate number sample type-related data, thereby recognizing the license plate number.

The invention relates to an informationalized bio-sample library management system and a sample management method. The system comprises a project related part, a device related part and an information related part, the project related part records establishment of a project in which samples are management, project progress and tasks and code management; the device related part is used to monitor and manage devices related in the sample collecting, packaging, transporting and storing processes; and the information related part recodes information from project establishment to the whole processes. The system and method have the advantages that characteristics, including multiple projects, diverse samples, different storage specifications and multiple sub libraries, of large comprehensive sample libraries as a national gene pool are combined to monitor and manage the whole process including collection, processing, transportation, library-in, library-out and in-library of the samples.

The present invention relates to a feature clustering comparison-based power prediction method and a device for a photovoltaic power station and belongs to the technical field of photovoltaic power generation. According to the technical scheme of the method, firstly, three most significant feature amounts that influence the prediction precision of the photovoltaic power are acquired and accumulated as historical meteorological data. Secondly, the obtained historical meteorological data are adopted as data samples to be clustered, so that the samples are divided into k types of high similarity. Meanwhile, the cluster center of each type of samples is obtained. Thirdly, a prediction model of a corresponding type is established based on the historical data of each type. Fourthly, a corresponding prediction model nearest to the cluster center of a current object is selected for prediction. In this way, different meteorological data are divided into different types of samples. Meanwhile, photovoltaic output prediction models in different meteorological conditions are established, so that the prediction models are trained in the more targeted manner. Moreover, the power prediction is conducted based on the power prediction models established in different meteorological conditions. Therefore, the prediction accuracy of the photovoltaic power is improved.

The invention belongs to the field of unmanned ship route planning, and particularly relates to a method for planning the route of an unmanned ship based on the SVM algorithm. The method comprises the following steps: constructing a standard unmanned ship, and putting the standard unmanned ship to sail in a typical sea area; searching standard related data when the standard unmanned ship encounters a barrier in the typical sea area, and saving the standard related data into a database; calculating by utilizing a least square SVM algorithm according to the database to obtain a complete sample bank; searching actual related data when the standard unmanned ship encounters a barrier in the typical sea area when the unmanned ship sails in the actual sea area; comparing the actual related data with the data in the complete sample bank to obtain a corresponding actual sample model; and planning the route of the standard unmanned ship according to the actual sample model. The method enables the planning result to be high in precision and small in error under the condition of limited sample data, and has good independence and strong stability.

The invention discloses a personalized medication gene detection kit and application. The personalized medication gene detection kit is suitable for multiple kinds of sample types including dried blood spots, whole blood and buccal swabs, information of all medicine gene polymorphic sites can be acquired at once, the sequencing effective rate is 50% or above, the sequencing cover degree is 100%, the average sequencing depth exceeds 3000 X, the library building success rate is larger than or equal to 98.5%, and the medicine gene polymorphic site detection accuracy is larger than or equal to 99.9%; a primer group is high in specificity and little in nonspecific amplification, interference among primers can be well overcome, under the situation of up to 186 primer sequences, one-tube multiplePCR reaction is achieved, moreover, amplicon is high in uniformity, and under the situation of large amplification area GC content difference, overall effective amplification can be conducted. The detection kit, the primer group and a library building method can be applied to personalized medication gene detection, and guidance is provided for personalized medication.

The invention provides a die casting surface defect detection method and a die casting surface defect detection system based on machine vision. The die casting surface defect detection system comprises an image acquisition unit, an image processing unit, a HOG + LBP feature extraction unit and an SVM classifier training detection unit, the image acquisition unit is used for acquiring images of thesurfaces of die castings; the image processing unit is used for processing the collected images to obtain images capable of extracting defect feature vectors; the HOG + LBP feature extraction unit isused for performing HOG + LBP feature extraction on the processed image; and the SVM classifier training detection unit is used for training the SVM classifier and carrying out defect identificationby using the trained SVM classifier. According to the method, HOG + LBP feature calculation is adopted, complex multi-dimensional feature calculation is effectively avoided, recognition efficiency isreduced, recognition and classification are carried out through an SVM classifier, the number of needed samples is small, and the problem that a neural network algorithm falls into a local minimum value when sample types are complex is solved.

A free sample distributing system comprises a plurality of free sample distributing devices and a free sample distribution information server. Each free sample distributing device imports identification information of a user desiring acquisition of a free sample, and sends the identification information to the free sample distribution information server. The free sample distribution information server decides a type of a free sample to be provided for the user, by searching a user information storage unit, by recognizing personal information of the user pertaining to the identification information, and by comparing the personal information with the free sample distribution conditions of free sample types. The free sample distributing device dispenses the free sample of the decided type from a housing unit and provides the user with the free sample.

The invention discloses a judgment method and device for the quality of fingerprint images. The judgment method includes the step of obtaining fingerprint image samples, the step of carrying out learning according to the fingerprint image samples by using an SVM classifier to obtain the optimal classification face, the step of obtaining the images to be judged and calculating histogram of oriented gradient (HOG) characteristics of the fingerprint images, and the step of judging the quality of the fingerprint images according to the HOG characteristics and the optimal classification face. Thus, the quality of the fingerprint images is accurately judged in small size fingerprint acquisition equipment, the work of manually determining and judging threshold values is omitted, good expansion capability is achieved, influences brought by various types of noise can be determined in the judgment mode, judgment can be completed just by inputting required sample types, an excellent effect is exerted in a lot of experiments, and a solid foundation is laid for improving the fingerprint recognition rate and lowering the false acceptance rate.

The invention relates to a power distribution network space load prediction method taking region and load property dual differences into consideration. A conventional space load prediction method does not take influences exerted by regional differences, sample types and quality on load density into consideration, and the applicability is not sufficient. First of all, a full-sample space taking the regional differences into consideration is established, and then, a typical sample is screened by verifying and carefully choosing a load through a typical daily load curve. A region where the load is disposed is clustered through weighted Euclidean distance tolerance, afterwards, a subsample space matching is carried out, a type which the sample belongs to is determined, load density of a plot to be measured is predicted by use of an SVM algorithm, and a total future load amount of the plot is calculated through the load density. The load prediction precision is quite high, and the application is facilitated.