Abstract: Disclosed is a cochlear implant (Cl) and a method of generating stimulations for the CI. The Cl may include, at least one optical signal generator configured to generate a plurality of optical signals having a wavelength of at most 1600 nm, and a plurality of light emitters, for delivering the optical signals to different locations along a cochlear nerve. The method may further include optimizing the stimulation energy through selection of stimulation wavelengths and stimulation pulse shapes.

Abstract: An apparatus for non-invasive directional tissue treatment comprises an energy source and an array of energy delivery elements placed in a predetermined order defining a tissue treatment area such that tissue tightening obtained is higher in a first direction than in a second direction of the two-dimensional array.

Abstract: A server system may match a segment of code for a code integration request to metadata about similar segments of code, wherein the metadata qualifies one or more outcomes of previous integration requests. The server may determine usage rights and rules based on the metadata, wherein some of the usage rights and rules have previously have been approved by a multi-approval workflow that enforces a predetermined process to authorize use of the segment of code for code segment integrations. The server may analyze the metadata to predict an integration score based at least in part on the usage rights and rules of the segments of code. If the integration score of the segment of code exceeds a threshold, the system may automatically generate a data structure for deploying the segment of code, wherein the automatically generating the data structure is performed without the multi-approval workflow.

Abstract: Disclosed is a method of selecting stimulations for a cochlear implant or an auditory implant. The method may include: capturing an acoustical signal; dividing the acoustical signal into a plurality of frequency bands; determining a mean acoustical energy for each frequency band; for each frequency band: comparing the mean acoustical energy with the mean acoustical energy determined for neighboring frequency bands; merging neighboring frequency bands having a difference between the mean acoustical energies that is less than an acoustical energy threshold value; selecting one or more types of stimulation to be applied to one or more locations in a cochlea or along an auditory nerve based on bandwidths of each frequency band. The one or more types of stimulation may be selected from: electrical stimulation, optical stimulation and opto-electrical stimulation, and the one or more locations in cochlea or along the auditory nerve may correspond to specific frequencies of the acoustical signal.

Abstract: Some embodiments of the invention may be related to an apparatus for non-invasive directional tissue treatment. The apparatus includes a radiofrequency (RF) generator and an array of RF energy delivery elements in active communication with the RF generator, a power source and a controller. In some embodiments, each of the RF energy delivery elements comprises a pair of electrodes with opposite polarity such that each electrode has a first dimension and a second dimension, the first dimension perpendicular to the second dimension and to an imaginary line connecting the pair of electrodes to each other. In some embodiments, the first dimension of each electrode and the distance between the electrodes in each pair are configured to create an elongated heated volume of tissue when the RF generator is activated and at least one of the RF delivery elements is in contact with the tissue.

Abstract: The present disclosure relates to systems and methods for a machine-learning platform for the safe serialization of a machine-learning application. Individual library components (e.g., a pipeline, a microservice routine, a software module, and an infrastructure model) can be encrypted using one or more keys. The keys can be stored in a location different from the storage location of the machine-learning application. Prior to incorporation of the library component into a machine-learning model, one or more keys can be retrieved from the remote storage location to authenticate that the one or more encrypted library components are authentic. The process can reject any of the one or more component, when the encrypted library component fails authentication. If a component is rejected, the system can roll back to a previous, authenticated version of the library component. The authenticated library components can be compiled into machine-learning software.

Abstract: The present disclosure relates to systems and methods for an intelligent assistant (e.g., a chatbot) that can be used to enable a user to generate a machine learning system. Techniques can be used to automatically generate a machine learning system to assist a user. In some cases, the user may not be a software developer and may have little or no experience in either machine learning techniques or software programming. In some embodiments, a user can interact with an intelligent assistant. The interaction can be aural, textual, or through a graphical user interface. The chatbot can translate natural language inputs into a structural representation of a machine learning solution using an ontology. In this way, a user can work with artificial intelligence without being a data scientist to develop, train, refine, and compile machine learning models as stand-alone executable code.

Abstract: The present disclosure relates to systems and methods for an adaptive pipelining composition service that can identify and incorporate one or more new models into the machine learning application. The machine learning application with the new model can be tested off-line with the results being compared with ground truth data. If the machine learning application with the new model outperforms the previously used model, the machine learning application can be upgraded and auto-promoted to production. One or more parameters may also be discovered. The new parameters may be incorporated into the existing model in an off-line mode. The machine learning application with the new parameters can be tested off-line and the results can be compared with previous results with existing parameters. If the new parameters outperform the existing parameters as compared with ground-truth data, the machine learning application can be auto-promoted to production.

Abstract: The present disclosure relates to systems and methods for using existing data ontologies for generating machine learning solutions for a high-precision search of relevant services to compose pipelines with minimal human intervention. Data ontologies can be used to create a combination of non-logic based and logic-based sematic services that can significantly outperform both kinds of selection in terms of precision. Quality of Service (QoS) and product Key Performance Indicator (KPI) constraints can be used as part of architecture selection in developing, training, validating, and improving machine learning models. For data sets without existing ontologies, one or more ontologies be generated and stored for future use.

Abstract: A server system may match a segment of code for a code integration request to metadata about similar segments of code, wherein the metadata qualifies one or more outcomes of previous integration requests. The server may determine usage rights and rules based on the metadata, wherein some of the usage rights and rules have previously have been approved by a multi-approval workflow that enforces a predetermined process to authorize use of the segment of code for code segment integrations. The server may analyze the metadata to predict an integration score based at least in part on the usage rights and rules of the segments of code. If the integration score of the segment of code exceeds a threshold, the system may automatically generate a data structure for deploying the segment of code, wherein the automatically generating the data structure is performed without the multi-approval workflow.

Abstract: A server system may receive two or more Quality of Service (QoS) dimensions for the multi-objective optimization model, wherein the two or more QoS dimensions include at least a first QoS dimension and a second QoS dimension. The server system may maximize the multi-objective optimization model along the first QoS dimension, wherein the maximizing includes selecting one or more pipelines for the multi-objective optimization model in the software architecture that meet QoS expectations specified for the first QoS dimension and the second QoS dimension, wherein an ordering of the pipelines is dependent on which QoS dimensions were optimized and de-optimized and to what extent, wherein the multi-objective optimization model is partially de-optimized along the second QoS dimension in order to comply with the QoS expectations for the first QoS dimension, and whereby there is a tradeoff between the first QoS dimension and the second QoS dimension.

Abstract: The present disclosure relates to systems and methods for a self-adjusting corporation-wide discovery and integration feature of a machine learning system that can review a client's data store, review the labels for the various data schema, and effectively map the client's data schema to classifications used by the machine learning model. The various techniques can automatically select the features that are predictive for each individual use case (i.e., one client), effectively making a machine learning solution client-agnostic for the application developer. A weighted list of common representations of each feature for a particular machine learning solution can be generated and stored. When new data is added to the data store, a matching service can automatically detect which features should be fed into the machine-learning solution based at least in part on the weighted list. The weighted list can be updated as new data is made available to the model.

Abstract: A server system can receive an input identifying a problem to generate a solution using a machine-learning application. The method selects a machine-learning model template from a plurality of templates based at least in part on the input. The method analyzes one or more formats of the customer data to generate a customer data schema based at least in part a data ontology that applies to the identified problem. The method determines whether the customer data schema is misaligned with one or more key features of the selected machine-learning model template. Based on this determination, the method analyzes the metadata for the selected machine-learning model template to determine what additional information is required to re-align the customer data with the data expectations. The method can include gathering the addition information required to re-align the customer data with the data expectations of the selected machine-learning model template.

Abstract: The present disclosure relates to systems and methods for a machine learning platform that generates a library of components to generate machine learning models and machine learning applications. The machine learning infrastructure system allows a user (i.e., a data scientist) to generate machine learning applications without having detailed knowledge of the cloud-based network infrastructure or knowledge of how to generate code for building the model. The machine learning platform can analyze the identified data and the user provided desired prediction and performance characteristics to select one or more library components and associated API to generate a machine learning application. The machine learning can monitor and evaluate the outputs of the machine learning model to allow for feedbacks and adjustments to the model. The machine learning application can be trained, tested, and compiled for export as stand-alone executable code.

Abstract: Some embodiments of the invention may be related to an apparatus for non-invasive directional tissue treatment. The apparatus includes a radiofrequency (RF) generator and an array of RF energy delivery elements in monopolar configuration, in active communication with the RF generator, at least one of: a return electrode and a return pad, and a power source and a controller. In some embodiments, each of the RF energy delivery elements comprises a monopolar electrode such that each monopolar electrode has a first dimension and a second dimension, the first dimension perpendicular to the second dimension. In some embodiments, the first dimension of each monopolar electrode and the distance between the monopolar electrodes in each pair are configured to create an elongated heated volume of tissue when the RF generator is activated and at least one of the RF delivery elements is in contact with the tissue.

Abstract: Treatment systems are provided, which comprise a treatment element applying a treatment to a tissue, a stimulation element optically stimulating nerves in the tissue, a sensing unit sensing an electrical signal produced by nerves in the tissue in response to the optical stimulation, and a control unit controlling the application of the treatment according to the sensed signal. The systems and methods are used to avoid damaging nerves by sensing them during operation and immediately before local treatment application and preventing energy emission when the treatment tool is too close to specified nerves. Additional electric stimulation may be provided to enable avoidance of nerve damages on a larger scale, the treatment may be applied by a cold laser, and the control unit may control the treatment in realtime and in a closed loop and immediate prevent further treatment upon sensing optically stimulated nerves.

Abstract: Some embodiments of the invention may be related to an apparatus for non-invasive directional tissue treatment. The apparatus includes a radiofrequency (RF) generator and an array of RF energy delivery elements in active communication with the RF generator, a power source and a controller. In some embodiments, each of the RF energy delivery elements comprises a pair of electrodes with opposite polarity such that each electrode has a first dimension and a second dimension, the first dimension perpendicular to the second dimension and to an imaginary line connecting the pair of electrodes to each other. In some embodiments, the first dimension of each electrode and the distance between the electrodes in each pair are configured to create an elongated heated volume of tissue when the RF generator is activated and at least one of the RF delivery elements is in contact with the tissue.

Abstract: Treatment systems are provided, which comprise a treatment element applying a treatment to a tissue, a stimulation element optically stimulating nerves in the tissue, a sensing unit sensing an electrical signal produced by nerves in the tissue in response to the optical stimulation, and a control unit controlling the application of the treatment according to the sensed signal. The systems and methods are used to avoid damaging nerves by sensing them during operation and immediately before local treatment application and preventing energy emission when the treatment tool is too close to specified nerves. Additional electric stimulation may be provided to enable avoidance of nerve damages on a larger scale, the treatment may be applied by a cold laser, and the control unit may control the treatment in realtime and in a closed loop and immediate prevent further treatment upon sensing optically stimulated nerves.

Abstract: Various adapter brackets for detachably connecting a hinge to a boltless storage rack are presented. Brackets include a first surface having a keyhole-shaped opening and a notch, and a second surface that meets the first surface at a first angle, and having at least one of a rivet and a hole sized and dimensioned to receive a fastener. In some embodiments, at least one of the first opening and the second opening is substantially elongated having a widened area. In some brackets, instead of having a rivet or a hole sized and dimensioned to receive a fastener in the second surface, the brackets have a third surface that meets the second surface at a second angle, and at least one of a rivet and a slot sized and dimensioned to receive a fastener.

Abstract: Shelving units and accessories are disclosed that provide a secure storage of articles. One accessory is a wall having a panel and a bracket. The panel has horizontal rods and the bracket has a first and second aperture. The first and second apertures are sized and dimensioned to receive at least one horizontal rod. The bracket further includes a rivet for mounting the wall onto a storage unit. Another accessory is a container having a bracket with a hooked end portion. The hooked end portion is sized and dimensioned to receive a cross beam of the storage unit.