Abstract: Methods, apparatus and systems for correlation-based wireless monitoring are described. For example, a described method comprises: detecting and monitoring motion of a first object in a first sensing task based on a first motion information (MI) computed based on a first time series of channel information (TSCI) associated with a first device pair; detecting and monitoring motion of a second object in a second sensing task based on a second MI computed based on a second TSCI associated with a second device pair; computing a correlation score based at least partially on: the first TSCI, the second TSCI, the first MI and the second MI; detecting the first object and the second object as a same object when the correlation score is greater than a first threshold; and detecting the first object and the second object as two different objects when the correlation score is less than a second threshold.

Abstract: Methods, apparatus and systems for counting and recognizing objects or people based on rhythmic motion monitoring are described. A described method comprises: obtaining N1 time series of channel information (TSCI) of a wireless multipath channel that is impacted by a rhythmic motion of an object in a venue, wherein the N1 TSCI is extracted from a wireless signal transmitted from a transmitter to a receiver through the wireless multipath channel; decomposing each of the N1 TSCI into N2 time series of channel information components (TSCIC), wherein a channel information component (CIC) of each of the N2 TSCIC at a time comprises a respective component of a channel information (CI) of the TSCI at the time, wherein N1 and N2 are positive integers; monitoring the rhythmic motion of the object based on at least one of: the N1*N2 TSCIC and the N1 TSCI.

Abstract: The present disclosure relates to compositions and methods of treating a subject having digestive tract cancer, the method comprising: administering an effective amount of a composition to the subject, the composition comprising a first population of cells comprising a first CAR binding a first antigen, and a second population of cells comprising a second CAR binding GCC, wherein the first antigen comprises a cell surface molecule of a white blood cell (WBC).

Abstract: The present disclosure provides focal adhesion kinase (FAK) splicing variants and use thereof, specifically, the use of reagents for detecting FAK splicing variants in the manufacture of diagnostic agents for diagnosis of small cell lung cancer (SCLC), and also the use of FAK splicing variants as a target in the screening and/or manufacture of a medicament for treatment of SCLC. The FAK splicing variants can be used as clinical diagnostic markers of SCLC, and are promising in clinical applications of FAK kinase inhibitors.

Abstract: Methods, apparatus and systems for vehicle wireless monitoring are described. In one example, a described method comprises: transmitting a first wireless signal from a first wireless device through a wireless multipath channel of a venue, the venue comprising a vehicle and an immediate vicinity of the vehicle; receiving a second wireless signal by a second wireless device in the venue through the wireless multipath channel, wherein the second wireless signal differs from the first wireless signal due to the wireless multipath channel and a modulation by an object undergoing a motion in the venue; obtaining a time series of channel information (TSCI) of the wireless multipath channel based on the second wireless signal; and performing a monitoring task by monitoring, based on the TSCI, at least one of: the vehicle, the object or the motion of the object.

Abstract: A method for identifying an individual of an oplegnathus punctatus based on a convolutional neural network is provided. Target initial positioning involves three continuous convolutional layers and an average pooling layer. A region of feature interest point is obtained, a hyperparameter candidate box is set to obtain a region, thereby obtaining an approximate position of a target object. II_Net backbone convolutional neural network includes six convolutional layers and four pooling layers, which includes a LeakyReLU activation function used as an activation function of the first convolutional layer, convolutional network layers of Alexnet and parameter data, and a maximum pooling layer of an overlapped pooling structure. Fully connected layers use a genetic algorithm to improve data transmission between layers. With the established model, identification of the individual of the oplegnathus punctatus is performed by using test data.

Abstract: Devices and associated methods for operating a dual-subscriber identity module (SIM) dual-standby (DSDS) user equipment device (UE) configured with a first SIM and a second SIM. The UE performs communications with a first cellular network using the first SIM and a first radio resource control (RRC) connection, and receives a request to perform a higher priority communication using the second SIM. In response to the request to perform the higher priority communication, the UE transmits a request to the first network to suspend the first RRC connection. After transmission of the request to suspend the first RRC connection, the UE receives a message from the first network to place the first RRC connection in an inactive state, and initiates a timer, wherein the timer is used to determine whether the first RRC connection remains in the inactive state or transitions to an idle state.

Abstract: Methods, apparatus and systems for wireless vital sign monitoring are described. In one example, a described system comprises: a transmitter configured to transmit a wireless signal through a wireless channel of a venue; a receiver configured to receive the wireless signal through the wireless channel that is being impacted by an object motion of an object in the venue; and a processor. At least one of the transmitter or the receiver comprises an array of antennas used to transmit or receive the wireless signal. The object motion comprises at least one non-periodic body motion of the object and at least one periodic vital-sign motion of the object.

Abstract: Methods, apparatus and systems for wireless sensing are described. In one example, a described system in a wireless data communication network comprises: a transmitter configured to transmit a time series of at least one wireless sounding signal (WSS) based on a standard wireless network protocol associated with the wireless data communication network, and a receiver. The wireless data communication network comprises a physical (PHY) layer, a medium access control (MAC) layer, and at least one higher layer. The receiver is configured to: receive the time series of at least one WSS (TSWSS) based on the standard wireless network protocol through a wireless channel of a venue, and perform a plurality of wireless sensing measurements based on the received TSWSS to obtain sensing measurement results based on the standard wireless network protocol.

Abstract: Methods, apparatus and systems for wireless sensing are described. In one example, a described system in a wireless data communication network comprises: a transmitter configured to transmit a time series of at least one wireless sounding signal (WSS) based on a standard wireless network protocol associated with the wireless data communication network, and a receiver. The wireless data communication network comprises a physical (PHY) layer, a medium access control (MAC) layer, and at least one higher layer. The receiver is configured to: receive the time series of at least one WSS (TSWSS) based on the standard wireless network protocol through a wireless channel of a venue, and perform a plurality of wireless sensing measurements based on the received TSWSS to obtain sensing measurement results based on the standard wireless network protocol.

Abstract: Methods, apparatus and systems for wireless sensing based on deep learning are described.

Abstract: In an example embodiment, a deep learning algorithm is introduced that operates on a transition matrix formed from user activities in an online network. The transition matrix records the frequencies that particular transitions between paths of user activity have occurred (e.g., the user performed a login activity, which has one path in the network, and then performed a profile view action, which has another path in the network). Each transition matrix corresponds to a different user's activities.

Abstract: Methods, apparatus and systems for wireless sensing are described. In one example, a described system in a wireless data communication network comprises: a transmitter configured to transmit a time series of at least one wireless sounding signal (WSS) based on a standard wireless network protocol associated with the wireless data communication network, and a receiver. The wireless data communication network comprises a physical (PHY) layer, a medium access control (MAC) layer, and at least one higher layer. The receiver is configured to: receive the time series of at least one WSS (TSWSS) based on the standard wireless network protocol through a wireless channel of a venue, and perform a plurality of wireless sensing measurements based on the received TSWSS to obtain sensing measurement results based on the standard wireless network protocol.

Abstract: Methods, apparatus and systems for wireless sensing are described. In one example, a described system in a wireless data communication network comprises: a transmitter configured to transmit a time series of at least one wireless sounding signal (WSS) based on a standard wireless network protocol associated with the wireless data communication network, and a receiver. The wireless data communication network comprises a physical (PHY) layer, a medium access control (MAC) layer, and at least one higher layer. The receiver is configured to: receive the time series of at least one WSS (TSWSS) based on the standard wireless network protocol through a wireless channel of a venue, and perform a plurality of wireless sensing measurements based on the received TSWSS to obtain sensing measurement results based on the standard wireless network protocol.

Abstract: Methods, apparatus and systems for wireless sensing are described. In one example, a described system in a wireless data communication network comprises: a transmitter configured to transmit a time series of at least one wireless sounding signal (WSS) based on a standard wireless network protocol associated with the wireless data communication network, and a receiver. The wireless data communication network comprises a physical (PHY) layer, a medium access control (MAC) layer, and at least one higher layer. The receiver is configured to: receive the time series of at least one WSS (TSWSS) based on the standard wireless network protocol through a wireless channel of a venue, and perform a plurality of wireless sensing measurements based on the received TSWSS to obtain sensing measurement results based on the standard wireless network protocol.

Abstract: Methods, apparatus and systems for wireless sensing are described. In one example, a described system in a wireless data communication network comprises: a transmitter configured to transmit a time series of at least one wireless sounding signal (WSS) based on a standard wireless network protocol associated with the wireless data communication network, and a receiver. The wireless data communication network comprises a physical (PHY) layer, a medium access control (MAC) layer, and at least one higher layer. The receiver is configured to: receive the time series of at least one WSS (TSWSS) based on the standard wireless network protocol through a wireless channel of a venue, and perform a plurality of wireless sensing measurements based on the received TSWSS to obtain sensing measurement results based on the standard wireless network protocol.

Abstract: Methods, apparatus and systems for wireless human-nonhuman motion detection are described.

Abstract: Methods, apparatus and systems for wireless motion recognition are described. In one example, a described system comprises: a transmitter configured for transmitting a first wireless signal through a wireless multipath channel of a venue; a receiver configured for receiving a second wireless signal through the wireless multipath channel; and a processor. The second wireless signal differs from the first wireless signal due to the wireless multipath channel that is impacted by a motion of an object in the venue. The processor is configured for: obtaining a time series of channel information (TSCI) of the wireless multipath channel based on the second wireless signal, tracking the motion of the object based on the TSCI to generate a gesture trajectory of the object, and determining a gesture shape based on the gesture trajectory and a plurality of pre-determined gesture shapes.