Abstract: A source code correction assistance apparatus is configured to include a storage device that stores an updated source code, and an arithmetic operational device that generates, as an evaluation code template of the updated source code, a template including a conditional branch sentence related to each case of success or failure of an input condition, notifies an evaluator terminal of a request to create an evaluation code based on the template, controls an access to the updated source code by the evaluator, receives editing by the evaluator on the conditional branch sentence in the template, generates a list of input values for executing all control paths of the evaluation code after the editing, and generates an evaluation code driver that automatically executes the evaluation code by inputting the input value.

Abstract: According to one embodiment, an automatic analyzing apparatus includes a probe and a liquid level detector. The liquid level detector is electrically connected to the probe and detects contact between the probe and a liquid surface, wherein the liquid level detector comprises an adjuster configured to adjust electrostatic capacitance of one or more capacitors for circuitry for use in liquid level detection.

Abstract: A high-resolution display device is provided. A display device with both high display quality and high resolution is provided. The display device includes a first display element including a first pixel electrode, a first EL layer, and a common electrode; a second display element including a second pixel electrode, a second EL layer, and the common electrode; a first insulating layer covering an end portion of the first pixel electrode and an end portion of the second pixel electrode; a second insulating layer over the first insulating layer; and a third insulating layer over the second insulating layer. The first EL layer is placed over the first pixel electrode and the third insulating layer. The second EL layer is placed over the second pixel electrode and the third insulating layer.

Abstract: According to one embodiment, a medical image processing apparatus includes processing circuitry. The processing circuitry is configured to acquire three-dimensional thermographic image data by imaging a subject irradiated with infrared rays. The processing circuitry is configured to acquire a plurality of items of projection data by imaging the subject with tomosynthesis. The processing circuitry is configured to execute reconstruction based on the plurality of items of projection data and the three-dimensional thermographic image data.

Abstract: To make validity of a prediction model created by machine learning be able to be verified with appropriate accuracy and efficiency. A software test apparatus includes a storage device configured to store a prediction model, and an arithmetic device. The arithmetic device is configured to accept inputs of a precondition, a constraint condition, and an approximation threshold value, convert the prediction model into a logical expression, analyze an approximation range based on the approximation threshold value with respect to the logical expression to simplify the logical expression, generate an inspection expression by combining the simplified logical expression with the precondition and negation of the constraint condition, search for, as a counterexample, a value satisfying the inspection expression, input the value to the prediction model to evaluate inspection accuracy when the counterexample exists, and output a result of the evaluation.

Abstract: According to one embodiment, an automatic analyzing apparatus includes processing circuitry. The processing circuitry measures an electrical potential pertaining to a contact between a probe for dispensing a sample or a reagent and a liquid surface, and outputs the measured electrical potential as a measurement value, determines whether or not the measurement value is within a specific range, and outputs a determination result, and provides a notification on a state of a liquid related to the liquid surface according to the determination result.

Abstract: A computer implemented method of hypothesis scoring based on causal relationships is provided. The computer implemented method includes creating a causal relationship model utilizing a plurality of hypotheses and a causal relationship between each of two or more pairs of hypotheses, and obtaining pro and con sentiment scores for each hypothesis utilizing a scoring function. The computer implemented method further includes assigning the obtained pro and con sentiment scores to each hypothesis in the causal relationship model, and propagating the pro and con sentiment scores from leaf hypotheses to a root hypothesis utilizing axioms to test the propagating scores for reasonableness. The computer implemented method further includes determining a final pro and con score for the root hypothesis, and presenting the final pro and con scores representing a prediction of the hypotheses to a user.

Abstract: Example automated diagnostic analyzers and methods for using the same are disclosed herein. An example apparatus described herein includes a first carousel rotatably coupled to a base and having a first axis of rotation. The example apparatus includes a second carousel rotatably coupled to the base and vertically spaced over the first carousel such that at least a portion of the second carousel is disposed over the first carousel. In the example apparatus, the second carousel has a second axis of rotation and a plurality of vessels. The example apparatus also includes a pipetting mechanism offset from the second axis of rotation. The example pipetting mechanism is to access the first carousel and the second carousel.

Abstract: Example automated diagnostic analyzers and methods for using the same are disclosed herein. An example apparatus described herein includes a first carousel rotatably coupled to a base and having a first axis of rotation. The example apparatus includes a second carousel rotatably coupled to the base and vertically spaced over the first carousel such that at least a portion of the second carousel is disposed over the first carousel. In the example apparatus, the second carousel has a second axis of rotation and a plurality of vessels. The example apparatus also includes a pipetting mechanism offset from the second axis of rotation. The example pipetting mechanism is to access the first carousel and the second carousel.

Abstract: A source code correction assistance apparatus is configured to include a storage device that stores an updated source code, and an arithmetic operational device that generates, as an evaluation code template of the updated source code, a template including a conditional branch sentence related to each case of success or failure of an input condition, notifies an evaluator terminal of a request to create an evaluation code based on the template, controls an access to the updated source code by the evaluator, receives editing by the evaluator on the conditional branch sentence in the template, generates a list of input values for executing all control paths of the evaluation code after the editing, and generates an evaluation code driver that automatically executes the evaluation code by inputting the input value.

Abstract: To make validity of a prediction model created by machine learning be able to be verified with appropriate accuracy and efficiency. A software test apparatus includes a storage device configured to store a prediction model, and an arithmetic device. The arithmetic device is configured to accept inputs of a precondition, a constraint condition, and an approximation threshold value, convert the prediction model into a logical expression, analyze an approximation range based on the approximation threshold value with respect to the logical expression to simplify the logical expression, generate an inspection expression by combining the simplified logical expression with the precondition and negation of the constraint condition, search for, as a counterexample, a value satisfying the inspection expression, input the value to the prediction model to evaluate inspection accuracy when the counterexample exists, and output a result of the evaluation.

Abstract: A learning support device stores, as execution information, a set of an input value, an execution output value as an execution result and an expected output value, for a machine learning program. An arithmetic device generates an output value different from the expected output value as a teacher output value in accordance with a predetermined rule when the execution output value and the expected output value for a predetermined input value match each other, generates a loss function based on a difference between the teacher output value and the execution output value, generates a change value indicating a change in the loss function for each parameter in the neural network, calculates an influence degree of predetermined learning by calculating influence of an update value of the parameter obtained by the learning on the change value, and determines whether or not the update value is adopted based on the influence degree.

Abstract: A validity of a prediction model can be evaluated comprehensively. A machine learning program verification apparatus 100 includes a calculation device 104. The calculation device 104 obtains a decision tree logical expression by logically combining path logical expressions indicating decision tree paths indecision trees for a program created by machine learning, creates a combined logical expression by logically combining a verification property logical expression and an objective variable calculation logical expression with the decision tree logical expression, performs satisfiability determination by inputting the combined logical expression to a satisfiability determiner, and when a result of the determination indicates satisfaction, obtains, from a satisfaction solution of the satisfiability determination, a violation input value that is a value of an explanatory variable that violates a verification property and a violation output value that is a value of an objective variable.

Abstract: According to one embodiment, an automatic analyzing apparatus includes a probe and a liquid level detector. The liquid level detector is electrically connected to the probe and detects contact between the probe and a liquid surface, wherein the liquid level detector comprises an adjuster configured to adjust electrostatic capacitance of one or more capacitors for circuitry for use in liquid level detection.

Abstract: To efficiently verify and improve a robustness of a learning model for supervised machine learning. A data-creation assistance apparatus 100 includes: a storage device 101 configured to store a neural network model 110 and test data 120; and a computing device 104 configured to specify an uncertainty of an inference result acquired by the neural network model 110; acquire gradient information of the test data 120 by a back propagation process using the uncertainty as a loss; apply various minute changes to the test data 120 to generate a plurality of minutely changed test data, and calculate deviations between each of the plurality of pieces minutely changed test data and the test data 120; and specify, based on the uncertainty information, the gradient information, and the deviations, a minute change that increases or decreases the uncertainty.

Abstract: A method is provided for reducing memory consumption by a rule engine. The method includes receiving attack trees, each having nodes and edges. Each node represents a security event and is associated with a detection rule for detecting an occurrence thereof. Each edge connects a respective node pair. The method includes assigning a watchpoint to each leaf node. The method includes moving the watchpoint assigned to any leaf node to a next upstream node, responsive to detecting an occurrence of the security event represented by the leaf node. The method includes erasing the watchpoint assigned to all downstream nodes relative to the next upstream node, responsive to the next upstream node being connected to a next downstream node using an edge having an “OR” join type. Only the rules for nodes currently having the watchpoint assigned are loaded into a memory device during runtime, while excluding rules for remaining nodes.

Abstract: Example apparatus and methods related to automated diagnostic analyzers having rear accessible track systems are described herein. An example apparatus disclosed herein includes an analyzer to perform a diagnostic test. The analyzer has a first side and a second side opposite the first side. The example apparatus includes a loading bay disposed on the first side of the analyzer to receive a first carrier and a pipetting mechanism coupled to the analyzer adjacent the second side. The example apparatus also includes a first carrier shuttle to transport the first carrier from a first location adjacent the loading bay to a second location adjacent the pipetting mechanism and a track disposed adjacent the second side of the analyzer to transfer a second carrier to a third location adjacent the pipetting mechanism.

Abstract: A learning dataset generation support device 100 is configured to include: a storage device 101 that is configured to store a plurality of pieces of learning data used for supervised machine learning along with correct answer labels; and a computing device 104 that is configured to perform a process of sequentially acquiring the pieces of learning data from the storage device to extract feature vectors, an editing process of adding and/or deleting a feature vector according to a predetermined algorithm, and a process of generating learning data from the edited feature vectors.

Abstract: An automated analyzing apparatus according to one embodiment comprises a barcode reader and a cylindrical lens. The barcode reader emits light toward a barcode attached to at least one of a specimen container storing a test sample, a reagent container storing a reagent to be reacted with the test sample, and a specimen rack housing a plurality of the specimen containers arranged in a line, and reads the barcode on the basis of reflected light of the applied light. The cylindrical lens is placed between at least one of the specimen container, the reagent container, and the specimen rack, and the barcode reader.

Abstract: Example apparatus and methods related to automated diagnostic analyzers having rear accessible track systems are described herein. An example apparatus disclosed herein includes an analyzer to perform a diagnostic test. The analyzer has a first side and a second side opposite the first side. The example apparatus includes a loading bay disposed on the first side of the analyzer to receive a first carrier and a pipetting mechanism coupled to the analyzer adjacent the second side. The example apparatus also includes a first carrier shuttle to transport the first carrier from a first location adjacent the loading bay to a second location adjacent the pipetting mechanism and a track disposed adjacent the second side of the analyzer to transfer a second carrier to a third location adjacent the pipetting mechanism.