Abstract: An electronic device for determining global attention in a deep learning model is provided. The electronic device includes a hardware accelerator, a low-complex global attention generator, a parallel switch, and a series switch. The hardware accelerator is configured to process each tile of a full-frame image and the low complex global attention generator is configured to generate a channel attention map of the full-frame image. The parallel switch is configured to bypass a connection of the channel attention map with the hardware accelerator and a series switch, configured to gate the connection of the channel attention map with the hardware accelerator.

Abstract: The present disclosure provides materials and methods to link imaging and sequencing measurements of a single cell. Sequencing information can be linked with phenotypic measurements that are not directly encoded in the genome such as morphological features, protein expression & localization, organelle dynamics, or the metabolic composition of a cell.

Abstract: Business goals may be achieved using adaptive rewarding for the personalization of contents. In response to receiving user information, personalized contents for the user can be recommended using a reinforcement learning algorithm. In response to presenting the personalized content to the user, an action by the user selecting a particular content may be received. A reward value can be calculated for the action based on a reward function. The reward function can be based, at least in part, upon the action, the selected content, and/or the user. The reward function can be based upon one or more business goals, such as user engagement, monetization, and/or security. The calculated reward value can be provided to the reinforcement learning algorithm, which can be adapted based upon the reward value for future selection of personalized contents.

Abstract: Business goals may be achieved using adaptive rewarding for the personalization of contents. In response to receiving user information, personalized contents for the user can be recommended using a reinforcement learning algorithm. In response to presenting the personalized content to the user, an action by the user selecting a particular content may be received. A reward value can be calculated for the action based on a reward function. The reward function can be based, at least in part, upon the action, the selected content, and/or the user. The reward function can be based upon one or more business goals, such as user engagement, monetization, and/or security. The calculated reward value can be provided to the reinforcement learning algorithm, which can be adapted based upon the reward value for future selection of personalized contents.

Abstract: One implementation of the present disclosure is a system including a data network, a source device, and a target device. The data network is configured to wirelessly communicate data, the source device is configured to wirelessly communicate data, and the target device is configured to wirelessly communicate data. The target device and the source device utilize a first medium access control (MAC) protocol during a first time interval of a duty cycle and a second MAC protocol during a second time interval of the duty cycle.

Abstract: A method for managing a retail environment includes identifying a plurality of shopping carts traveling through an aisle of a retail environment; retrieving information of respective times of the plurality of shopping carts entering the aisle, and respective times of the plurality of shopping carts leaving the aisle; associating the plurality of shopping carts with respective transaction identifications; generating a database comprising the transaction identifications and respective items, the items of each transaction identification comprising at least a dwell time class, respective purchase states of one or more products deployed along the aisle, and respective query states of the one or more product; calculating a respective product conversion rate of each of the transaction identifications based on the database; and providing an aisle product conversion rate for managing product placements in the retail environment based on the respective product conversion rate of each of the transaction identifications.

Abstract: One implementation of the present disclosure is a system including a data network, a source device, and a target device. The data network is configured to wirelessly communicate data, the source device is configured to wirelessly communicate data, and the target device is configured to wirelessly communicate data. The target device and the source device utilize a first medium access control (MAC) protocol during a first time interval of a duty cycle and a second MAC protocol during a second time interval of the duty cycle.