A research team led by Prof. HU Honglin and Prof. XU Tianheng at Shanghai Advanced Research Institute (SARI) provided a novel spectrum sensing technique, seeking a feasible way to combine the reinforcement learning concept with advanced spectrum sensing methods so as to optimize the performance of the cognitive radio network under multifarious scenarios in 5G communications.
Prof. Tiger H. Tao, Prof. DING Guqiao and their team from Shanghai Institute of Microsystem and Information Technology have developed a "self-matched" tribo-piezoelectric nanogenerator composed of genetically engineered recombinant spider silk protein and piezoelectric poly(vinylidene fluoride) (PVDF).
A team from Center of Marine Information Technology and Engineering at Shenyang Institute of automation put forward a method to improve the endurance of autonomous underwater vehicles. By using porous media as the surface layer of pressure shell and reducing the drag, autonomous underwater vehicle can "swim" further without changing its shape and battery capacity.
Researchers at the Shenyang Institute of Automation and their collaborators developed a novel deep reinforcement learning (DRL)-based control system to achieve autonomous mobile manipulation in dynamic and unstructured environments.
Prof. WU Tianzhun's group from the Shenzhen Institutes of Advanced Technology proposed an accelerated deposition process using ultraviolet (UV) irradiation with the existence of nanotitanium dioxide (nano-TiO2) to realize a rapid and stable synthesis of polydopamine (PDA) films.
A research team led by Prof. CHEN Shixiong from the Shenzhen Institutes of Advanced Technology proposed a high-density (HD) sEMG technique using dense arrays of individual electrodes to acquire muscle activities over a relatively large area with a rich set of information for adequate motion classification.
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