Abstract: Implementations are directed to design advisor platform uses machine learning (ML) models (e.g., deep learning models, such as convolutional neural networks (CNNs)) to compare an input design with a set of reference designs and provide evaluation and recommendation of the input design on-the-fly (i.e., in real-time).

Abstract: A device may receive source code from a source data structure, and may receive information associated with a target data structure. The device may analyze the source code to extract statements, and may utilize natural language processing on the statements to identify functions and keywords associated with the source data structure. The device may train a machine learning model with the functions and the keywords to generate a trained machine learning model, and may process the information associated with the target data structure, with the trained machine learning model, to transform a source query to a target query compatible with the target data structure. The device may process the target query, with a neural network model, to generate an optimized target query, and may cause data from the source data structure to be migrated to the target data structure based on the optimized target query.

Abstract: Examples of a data integration and curation system are provided. The system may receive data extracting requirement related to a digital initiative and obtain digital initiative data associated with the same. The system may classify the digital initiative data into various data domains and extract metadata therefrom based on data analysis. The system may determine a word index including a plurality of words from a knowledge database. The plurality of words may be mapped with the data domains to identify a data anomaly in the digital initiative data. The system may determine an anomaly correction for resolving the data anomaly and update the plurality of data domains to include the anomaly correction. The system may identify a user parameter associated with the digital initiative. The system may associate the user parameter with the metadata to create user parameter data associated with the user parameter to generate a data extraction result.

Abstract: A portable colorimetric assay system includes an opto-mechanical reader configured to be detachably mounted to a mobile phone having a camera or other camera-containing portable electronic device. The opto-mechanical reader includes one or more light sources configured to illuminate a test sample holder and control sample holder disposed in the opto-mechanical reader along an optical path aligned with a camera of the mobile phone or other camera-containing portable electronic device. One or more serum separation membranes are disposed in the opto-mechanical reader and define a sample receiving pad configured to receive a blood sample. A moveable serum collection membrane is membrane is also disposed in the reader and is configured to contact the sample receiving pad in a first position and moveable to a second position where the serum collection membrane is disposed inside the test sample holder.

Abstract: A computational cytometer operates using magnetically modulated lensless speckle imaging, which introduces oscillatory motion to magnetic bead-conjugated rare cells of interest through a periodic magnetic force and uses lensless time-resolved holographic speckle imaging to rapidly detect the target cells in three-dimensions (3D). Detection specificity is further enhanced through a deep learning-based classifier that is based on a densely connected pseudo-3D convolutional neural network (P3D CNN), which automatically detects rare cells of interest based on their spatio-temporal features under a controlled magnetic force. This compact, cost-effective and high-throughput computational cytometer can be used for rare cell detection and quantification in bodily fluids for a variety of biomedical applications.

Abstract: Examples for enhancing veracity of data are described herein. Data from a repository may be received based on a data receiving rule. From the received data, a first dataset may be generated using statistical modeling. Also, a first data veracity score for the first dataset is generated which is indicative of a degree of usability of the dataset. Another aspect relates to identifying an anomaly in the first dataset, the corrector, for each anomaly, to identify a correction technique from amongst a plurality of correction techniques. Further, a second dataset is generated using the identified correction technique having second data veracity score higher than the first data veracity score.

Abstract: Examples of a data migration system are provided. The system may receive a data migration requirement. The system may sort the data stored in the on-premise data warehouse into a plurality of data domains. The system may map the plurality of data domains to a usage parameter index and a storage parameter index to determine a data usage pattern and a data storage pattern. The system may evaluate the data storage pattern and the data usage pattern to determine a data assessment index. The system may determine a data migration index from mapping a plurality of cloud platforms to the data assessment index. The system may determine a data migration model compatible with the data assessment index. The system may generate a data migration output comprising the layout for transferring data stored in the on-premise data warehouse to a compatible cloud platform to resolve the data migration requirement.

Abstract: A UV holographic imaging device offers a low-cost, portable and robust technique to image and distinguish protein crystals from salt crystals, without the need for any expensive and bulky optical components. This “on-chip” device uses a UV LED and a consumer-grade CMOS image sensor de-capped and interfaced to a processor or microcontroller, the information from the crystal samples, which are placed very close to the sensor active area, is captured in the form of in-line holograms and extracted through digital back-propagation. In these holographic amplitude and/or phase reconstructions, protein crystals appear significantly darker compared to the background due to the strong UV absorption, unlike salt crystals, enabling one to clearly distinguish protein and salt crystals. The on-chip UV holographic microscope serves as a low-cost, sensitive, and robust alternative to conventional lens-based UV-microscopes used in protein crystallography.

Abstract: A system for assessing a data model includes a data receiver, a model receiver, and a model assessment device. The data receiver receives training data, historical data, and production data. The model receiver receives the data model associated with the historical data and trained using the training data. The historical data includes a first outcome of the data model provided based on an input feature in the production data. The model assessment device identifies a key feature in the production data relative to the input feature based on a target category in the historical data and a statistical distribution of the input feature in the production data. The model assessment device determines a second outcome of the data model based on the key feature. In response to the second outcome being different from the first outcome, the model assessment device determines a veracity score for assessing the data model.

Abstract: Examples for enhancing veracity of data are described herein. Data from a repository may be received based on a data receiving rule. From the received data, a first dataset may be generated using statistical modeling. Also, a first data veracity score for the first dataset is generated which is indicative of a degree of usability of the dataset. Another aspect relates to identifying an anomaly in the first dataset, the corrector, for each anomaly, to identify a correction technique from amongst a plurality of correction techniques. Further, a second dataset is generated using the identified correction technique having second data veracity score higher than the first data veracity score.

Abstract: Examples of a data integration and curation system are provided. The system may receive data extracting requirement related to a digital initiative and obtain digital initiative data associated with the same. The system may classify the digital initiative data into various data domains and extract metadata therefrom based on data analysis. The system may determine a word index including a plurality of words from a knowledge database. The plurality of words may be mapped with the data domains to identify a data anomaly in the digital initiative data. The system may determine an anomaly correction for resolving the data anomaly and update the plurality of data domains to include the anomaly correction. The system may identify a user parameter associated with the digital initiative. The system may associate the user parameter with the metadata to create user parameter data associated with the user parameter to generate a data extraction result.

Abstract: Examples of systems and method for data transition are described. In an example, the present disclosure provides for automating the process of data movement from on premise to cloud, i.e., source Data warehouse (DWH) movement, ETL to cloud base DWH, ETL. The present disclosure provides for objects identification, metadata extraction, automated data type mapping, target data definition script creation, data extraction in bulk using source native optimized utilities, users and access control mapping to the target DWH, binary object movement, end-end audit report, and reconciliation reports.

Abstract: A device may receive source code from a source data structure, and may receive information associated with a target data structure. The device may analyze the source code to extract statements, and may utilize natural language processing on the statements to identify functions and keywords associated with the source data structure. The device may train a machine learning model with the functions and the keywords to generate a trained machine learning model, and may process the information associated with the target data structure, with the trained machine learning model, to transform a source query to a target query compatible with the target data structure. The device may process the target query, with a neural network model, to generate an optimized target query, and may cause data from the source data structure to be migrated to the target data structure based on the optimized target query.

Abstract: A portable colorimetric assay system includes an opto-mechanical reader configured to be detachably mounted to a mobile phone having a camera or other camera-containing portable electronic device. The opto-mechanical reader includes one or more light sources configured to illuminate a test sample holder and control sample holder disposed in the opto-mechanical reader along an optical path aligned with a camera of the mobile phone or other camera-containing portable electronic device. One or more serum separation membranes are disposed in the opto-mechanical reader and define a sample receiving pad configured to receive a blood sample. A moveable serum collection membrane is membrane is also disposed in the reader and is configured to contact the sample receiving pad in a first position and moveable to a second position where the serum collection membrane is disposed inside the test sample holder.

Abstract: Examples of a data migration system are provided. The system may receive a data migration requirement. The system may sort the data stored in the on-premise data warehouse into a plurality of data domains. The system may map the plurality of data domains to a usage parameter index and a storage parameter index to determine a data usage pattern and a data storage pattern. The system may evaluate the data storage pattern and the data usage pattern to determine a data assessment index. The system may determine a data migration index from mapping a plurality of cloud platforms to the data assessment index. The system may determine a data migration model compatible with the data assessment index. The system may generate a data migration output comprising the layout for transferring data stored in the on-premise data warehouse to a compatible cloud platform to resolve the data migration requirement.

Abstract: Examples of systems and method for data transition are described. In an example, the present disclosure provides for automating the process of data movement from on premise to cloud, i.e., source Data warehouse (DWH) movement, ETL to cloud base DWH, ETL. The present disclosure provides for objects identification, metadata extraction, automated data type mapping, target data definition script creation, data extraction in bulk using source native optimized utilities, users and access control mapping to the target DWH, binary object movement, end-end audit report, and reconciliation reports.