Abstract: Processes and materials to detect cancer from a biopsy are described. In some cases, cell-free nucleic acids can be sequenced, and the sequencing result can be utilized to detect sequences derived from a neoplasm. Detection of somatic variants occurring in phase can indicate the presence of cancer in a diagnostic scan and a clinical intervention can be performed.

Abstract: Processes and materials to detect cancer, transplant rejection, or fetal genetic abnormalities from a biopsy are described. In some cases, nucleic acid molecules, such as cell-free nucleic acids, can be sequenced, and the sequencing result can be utilized to detect sequences indicative of a neoplasm, transplant rejection, or fetal genetic abnormality. Detection of somatic variants occurring in phase and/or insertions and deletions (indels) can indicate the presence of cancer, transplant rejection, or fetal genetic abnormalities in a diagnostic scan, and a clinical intervention can be performed.

Abstract: A wireless LAN router includes a directional antenna configured to transmit and receive wireless signals to and from each device, and a processing circuit. The processing circuit learns training data indicating an incoming direction of a wireless signal from an authorized device. The processing circuit then determines whether a wireless signal of a detection target device is a wireless signal from an authorized direction, using an incoming direction of the wireless signal from the detection target device received by the directional antenna and the training data obtained by the machine learning, and outputs a result of determination.

Abstract: A detection device includes a processing circuit that is configured to acquire an imaging video of a user to be authenticated, specify categories of micro-expressions of the user using the acquired imaging video, and determine whether an appearance pattern of each specified category for the micro-expressions is normal.

Abstract: A detection device monitors a communication event including communication by humans when a legitimate user accesses sensitive data for each legitimate user. The detection device builds a profile of the user indicating normal behavior when the user accesses the sensitive data by performing machine learning on a result of the monitoring. After that, the detection device acquires a communication event when a user to be authenticated accesses sensitive data. The detection device determines whether behavior of the user to be authenticated indicated in the acquired communication event corresponds to normal behavior when the user accesses the sensitive data indicated in a profile of the user, and outputs a result of the determination.

Abstract: A computer-implemented method includes: (i) receiving location information that represents a physical location of a user; (ii) receiving a first image that has been captured by the user; (iii) in response to receiving the first image, obtaining a second image that has been captured by a camera and that depicts a particular object in an area around the physical location; (iv) determining whether the first image matches the second image; and (v) in response to determining that the first image matches the second image, determining that the user is authentic.

Abstract: A management system includes a user terminal, and a management device that manages data, wherein the management device include a memory; and a processor coupled to the memory and executes a process comprising: requesting remittance of a cryptocurrency that uses a public distributed ledger from the user terminal, upon receiving a request for accessing managed data from the user terminal, and authorizing the user terminal to access the data when a record of clearance of the remittance made by the user terminal is added to the public distributed ledger.

Abstract: A detection device includes a processing circuit that is configured to acquire an imaging video of a user to be authenticated, specify categories of micro-expressions of the user using the acquired imaging video, and determine whether an appearance pattern of each specified category for the micro-expressions is normal.

Abstract: A wireless LAN router includes a directional antenna configured to transmit and receive wireless signals to and from each device, and a processing circuit. The processing circuit learns training data indicating an incoming direction of a wireless signal from an authorized device. The processing circuit then determines whether a wireless signal of a detection target device is a wireless signal from an authorized direction, using an incoming direction of the wireless signal from the detection target device received by the directional antenna and the training data obtained by the machine learning, and outputs a result of determination.

Abstract: A detection device monitors a communication event including communication by humans when a legitimate user accesses sensitive data for each legitimate user. The detection device builds a profile of the user indicating normal behavior when the user accesses the sensitive data by performing machine learning on a result of the monitoring. After that, the detection device acquires a communication event when a user to be authenticated accesses sensitive data. The detection device determines whether behavior of the user to be authenticated indicated in the acquired communication event corresponds to normal behavior when the user accesses the sensitive data indicated in a profile of the user, and outputs a result of the determination.

Abstract: A computer-implemented method includes: (i) receiving location information that represents a physical location of a user; (ii) receiving first sensor data that has been generated by a sensor on a client device of the user; (iii) in response to receiving the first sensor data, obtaining second sensor data that has been generated by a sensor on a sensor device and that represents an environmental condition of an area around the physical location; (iv) determining whether the first sensor data matches the second sensor data; and (v) in response to determining that the first sensor data matches the second sensor data, determining that the user is authentic.

Abstract: A user authentication device includes: a collection part collecting information of a user; a generation part generating a question for the user on the basis of the information of the user collected by the collection part and a skill model of the user; a presentation part presenting the question for the user generated by the generation part to the user; a reception part receiving, from the user, a response to the question presented by the presentation part; and a determination part determining authentication of the user on the basis of the response received by the reception part.

Abstract: A determination system includes: a memory; and a processor coupled to the memory and programmed to execute a process comprising: acquiring location data representing a location of one or more user devices including a first sensor; searching for one or more public devices that is at a location corresponding to the location of the user device and that includes a second sensor having a same function as that of the first sensor included in the user device; requesting the user device to measure using the first sensor to acquire measurement data of the first sensor; acquiring measurement data of the second sensor included in the public device; and determining whether a user of the user device is legitimate based on a result of matching the measurement data of the first sensor with the measurement data of the second sensor.

Abstract: A management system includes a user terminal, and a management device that manages data, wherein the management device include a memory; and a processor coupled to the memory and executes a process comprising: requesting remittance of a cryptocurrency that uses a public distributed ledger from the user terminal, upon receiving a request for accessing managed data from the user terminal, and authorizing the user terminal to access the data when a record of clearance of the remittance made by the user terminal is added to the public distributed ledger.

Abstract: A computer-implemented method includes: (i) receiving location information that represents a physical location of a user; (ii) receiving a first image that has been captured by the user; (iii) in response to receiving the first image, obtaining a second image that has been captured by a camera and that depicts a particular object in an area around the physical location; (iv) determining whether the first image matches the second image; and (v) in response to determining that the first image matches the second image, determining that the user is authentic.

Abstract: A retaining wall counterfort includes a body having an elongate base and a rigid head extending from the base for engagement with a further retaining wall component. The base includes a front surface, which may abut a further retaining wall component, and a rear surface. A connecting loop is embedded in the base and extends away from the base, past the rear surface of the base, for engaging a head of a second counterfort.

Abstract: Technologies are generally described for systems and methods effective to output a composite image. In some examples, a processor may be configured to receive first and second display data that relate to a first and second image. The processor may identify an overlap region where the first display overlaps the second display and generate imaging instructions effective to cause the first and second image to be output on the first display and second display, respectively. The processor may further modify the first imaging instructions based on the overlap region to produce a modified first imaging instruction. The processor may send the modified first imaging instruction to the first display so that the first image is output on the first display at a first resolution. The processor may send the second imaging instruction to the second display so that the second image is output on the second display at a second resolution.

Abstract: Technologies are generally described for systems, devices and methods effective to implement a line of sight initiated handshake. In some examples, a processor in a first communication device may detect a line of sight directed from the first communication device to a second communication device. The first communication device may send a handshake request to the second communication device. The first communication device may receive a handshake acknowledgement from the second communication device. The handshake request and handshake acknowledgement may be effective to create the handshake. The first and second communication devices can thereafter share data.

Abstract: Technologies are generally described for systems, devices and methods effective to implement a line of sight initiated handshake. In some examples, a processor in a first communication device may detect a line of sight directed from the first communication device to a second communication device. The first communication device may send a handshake request to the second communication device. The first communication device may receive a handshake acknowledgement from the second communication device. The handshake request and handshake acknowledgement may be effective to create the handshake. The first and second communication devices can thereafter share data.

Abstract: Technologies are generally described for systems, devices and methods effective to implement a line of sight initiated handshake. In some examples, a processor in a first communication device may detect a line of sight directed from the first communication device to a second communication device. The first communication device may send a handshake request to the second communication device. The first communication device may receive a handshake acknowledgement from the second communication device. The handshake request and handshake acknowledgement may be effective to create the handshake. The first and second communication devices can thereafter share data.