Abstract: Disclosed are a synonym mining method, an application method of a synonym dictionary, a medical synonym mining method, an application method of a medical synonym dictionary, a synonym mining device and a storage medium. The synonym mining method includes: performing a recognition process on corpus data to obtain a named entity set of at least one category, wherein the named entity set of each category includes a plurality of named entities; performing a clustering process on the plurality of named entities in the named entity set of the each category to obtain a synonym candidate set corresponding to the each category; and performing, based on a word from similarity and a context similarity, a filtering process on the synonym candidate set corresponding to the each category to obtain a synonym set corresponding to the each category.

Abstract: Systems and methods for the multifaceted analysis of a written work, such as an educational program admission essay, using machine learning, deep learning and natural language processing. Language, relevance, structure, and flows are evaluated for an overall impactful essay. Essay content is checked to evaluate whether the author has covered an essay's essential aspects. The essay is also analyzed for an effective structure for presenting details as per the essay type. The disclosure includes data preparation for the task, process of data tagging, feature engineering from the essay text, method for transfer learning and fine-tuning language model to adapt to the context of an essay. Finally, a process for building machine learning and deep learning models and technique for ensembling to use both models in combination is disclosed. The system may provide user-adapted feedback based on a persona created from the user profile.

Abstract: A diagnosis device (10) includes an acquirer (101) and a diagnoser (140). The acquirer (101) acquires a series of input values as an input signal to be diagnosed as to presence or absence of abnormality. The diagnoser (140) diagnoses the presence or absence of the abnormality from (i) a first index value indicating a distance between an input vector and a predetermined first reference vector, the input vector having components that are the input values of the series acquired by the acquirer (101), and (ii) a second index value indicating an angle between the input vector and a predetermined second reference vector.

Abstract: A control system comprises a memory storing a sequence of sensor data received from one or more sensors. The control system has a processor which processes the sensor data to compute a sequence of derived sensor data values. An autoencoder receives the sequence of derived sensor data values and computes a forward prediction of the sequence of derived sensor data values, the autoencoder having been trained imposing a relationship on positions of the derived sensor data values encoded in a latent space of the autoencoder. A processor initiates control of an apparatus using the forward prediction.

Abstract: Techniques are provided for detection of laser-based audio injection attacks. A methodology implementing the techniques according to an embodiment includes calculating cross correlations between signals received from microphones of an array of two or more microphones. The method also includes identifying time delays associated with peaks of the cross correlations, and magnitudes associated with the peaks of the cross correlations. The method further includes calculating a time alignment metric based on the time delays and calculating a similarity metric based on the magnitudes. The method further includes generating a first attack indicator based on a comparison of the time alignment metric to a first threshold and generating a second attack indicator based on a comparison of the similarity metric to a second threshold. The method further includes providing warning of a laser-based audio attack based on the first attack indicator and/or the second attack indicator.

Abstract: An index value assignment device comprises: a selection unit that prompts a user to select, from a sentence, one or more words that the user feels to have a same degree of a predetermined index value with respect to one or more first words for which the index value is known; a validation unit that validates the selection result by the user on a basis of the index value of a second word for which the index value is known from among the one or more words included in the selection result; and a determination unit that determines the index value with respect to a third word for which the index value is unknown from among the one or more words selected by the user, on a basis of the index value of the first word according to the selection result for which the selection result is determined to be valid. Consequently, the efficiency of assigning word familiarity is increased.

Abstract: The invention relates to a method for determining a water current velocity profile in a water column by registration of a deviation between a first position and a second position of an underwater vehicle travelling in the water column. A batch of underwater vehicles is deployed from a surface vessel into the water. The vehicle(s) steers to the first position, which for the first batch is a predefined estimated position (PEP). The vehicle is by first means recording the second position, which is the actual position (AP). The difference ?P between the predefined estimated position PEP and the actual position is registered and based on the difference a deviation data set is calculated. An updated current profile or stack of horizontal water current velocities UV is determined.

Abstract: Implementations can reduce the time required to obtain responses from an automated assistant through proactive caching, locally at a client device, of proactive assistant cache entries—and through on-device utilization of the proactive assistant cache entries. Different proactive cache entries can be provided to different client devices, and various implementations relate to technique(s) utilized in determining which proactive cache entries to provide to which client devices. In some of those implementations, in determining which proactive cache entries to provide (proactively or in response to a request) to a given client device, a remote system selects, from a superset of candidate proactive cache entries, a subset of the cache entries for providing to the given client device.

Abstract: Constructing an estimated orientation of the vehicle from a previous position and a previous orientation of the vehicle, then correcting this estimated orientation to obtain a first corrected orientation containing a corrected yaw angle of the vehicle, obtaining a measurement of the yaw angle of the vehicle, then replacing, in the first corrected orientation, the corrected yaw angle with the measured yaw angle, to obtain a second corrected orientation, then delivering the corrected second orientation by way of orientation determined for the vehicle and using, in the next execution of the constructing step, the corrected second orientation by way of previous orientation.

Abstract: Techniques are described herein for detecting and/or enrolling (or commissioning) new “hot commands” that are useable to cause an automated assistant to perform responsive action(s) without having to be first explicitly invoked. In various implementations, an automated assistant may be transitioned from a limited listening state into a full speech recognition state in response to a trigger event. While in the full speech recognition state, the automated assistant may receive and perform speech recognition processing on a spoken command from a user to generate a textual command. The textual command may be determined to satisfy a frequency threshold in a corpus of textual commands Consequently, data indicative of the textual command may be enrolled as a hot command. Subsequent utterance of another textual command that is semantically consistent with the textual command may trigger performance of a responsive action by the automated assistant, without requiring explicit invocation.

Abstract: A method for tracking non-homogeneous products on a shelf comprises monitoring weight measurement data points corresponding to the weight of the shelf and the products arranged thereupon, determining a set of weight-event parameters of a weight event, such as product identification and an action taken with respect to the product, and at least one of recording information about the results and displaying information about the results. A system for tracking non-homogeneous products on a shelf comprises processors for carrying out stored program instructions for carrying out the steps of the method.

Abstract: Provided are a semantic classification method and apparatus, a neural network training method and apparatus and a storage medium.

Abstract: Apparatuses, systems, methods, and computer program products for corn leaf disease detection are described. An apparatus may include an image sensor, an electronic display screen, a processor, and/or a memory storing computer program code executable by the processor to perform operations. An operation may include receiving an image of a corn leaf taken by an image sensor. An operation may include processing an image of a corn leaf using multiple machine learning models, each of the multiple machine learning models determining one or more likelihoods that the corn leaf has a plurality of diseases. An operation may include determining whether a corn leaf has any of a plurality of diseases based on one or more likelihoods. An operation may include displaying, in response to determining that a corn leaf has one or more of a plurality of diseases, the one or more of the plurality of diseases to a user on an electronic display screen.

Abstract: Systems and method for operating and monitoring refrigerators are described. Temperature cycles within the compartment are characterized using statistical, frequency and pattern analysis techniques to derive a steady-state characteristic of temperature within the compartment. A thermal sensor inside the conditioned area is monitored and temperature data sets can be analyzed to determine performance in comparison to a baseline, and energy consumption. Analysis of continuous temperature readings taken from individual or groups of freezers identifies patterns of variations in temperature cycles from which feedback on efficiency can be inferred. Electrical load can be determined by measuring or estimating current usage and identifying periods of time when compressors are active in the refrigerator.

Abstract: In order to provide a method for predicting process deviations in an industrial-method plant, for example a painting plant, by means of which process deviations are predictable simply and reliably, it is proposed according to the invention that the method should comprise the following: automatic generation of a prediction model; prediction of process deviations during operation of the industrial-method plant, using the prediction model.

Abstract: The present disclosure describes multi-parameter dynamic sampling methods and systems. An example method includes: configuring two sampling rates for each parameter in a set of sampling parameters; selecting one of the sampling rates for each parameters to sample it; calculating a load for each parameter at the selected sampling rate, sorting the parameters according to the loads, and determining high-loaded parameters according to a sorting result; and determining whether each parameter has data loss, and if at least one of the sampling parameters has data loss, performing down-sampling on the high-loaded sampling parameters within a range of the configured at least two sampling rates.

Abstract: Method and system are provided for efficiently populating a phase diagram for modeling of multiple substances. The method may include defining an n-way phase diagram with data points each being an n-tuple describing the n substance inputs, wherein the n-way phase diagram is defined at a user-configured resolution. The method may select an initial subset of data points and calculate their contribution to the phase diagram. The method may then generate a Bayesian model based on the initial subset of calculated data points and predicting the resultant phase and an associated uncertainty of all the uncalculated data points in the defined phase diagram. The method may select a sample subset of the data points using maximum entropy sampling and calculating a resultant phase for each of the selected data points, and incorporate the calculated phases into the Bayesian model.

Abstract: A method for invoking a user-intended Internet of Things (IoT) device amongst a number of IoT devices is disclosed. The method includes extracting by the number of IoT devices, a number of voice parameters from a voice wakeup command for waking up the device. The method includes sharing by the number of IoT devices, the number of voice parameters amongst the number of IoT devices. The method includes comparing the number of voice parameters with a number of pre-stored voice parameters in the number of IoT devices. The method includes determining, a user-intended IoT device amongst the number of IoT devices based on the voice wakeup command and at least one of a similarity between the plurality of pre-stored voice parameters and the plurality of voice parameters and a previously invoked IoT device associated with a previous voice wakeup command. The method includes invoking the user-intended IoT device selected amongst the number of IoT devices.

Abstract: The invention relates to a method for controlling preparative liquid chromatography, comprising the following steps, at least a part of said steps being implemented by a computer comprising a processor and a display screen coupled to said processor: (a) selecting an analytical liquid chromatography method from among thin layer chromatography (TLC) and high performance liquid chromatography (HPLC), (b) inputting analytical liquid chromatography data obtained by the method selected at step (a) for a product to be purified, (c) accessing a table of separating tools available to the user to implement said preparative liquid chromatography, (d) from said analytical liquid chromatography data and table of available separating tools, selecting an optimal separating tool from said table and computing preparative liquid chromatography operating conditions for said selected separating tool.

Abstract: The current document is directed to a methods and systems that use observational data collected by various devices and sensors to generate electronic-data representations of human conversations. The implementations of these methods and systems, disclosed in the current document, provide a highly extensible and generic platform for converting observational data into affect-annotated-timeline outputs that provide both a textual transcription of a conversation and a parallel set of affect annotations to the conversation. The affect-annotated-timeline outputs may be useful to researchers and developers, but also serve as inputs to any of a wide variety of downstream analytical processes and analysis systems that are, in turn, incorporated into many different types of special-purpose analysis and control systems.