Surface plasmon applications - microscopy and spatial light modulation

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Energy-Efficient Communication in Wireless Networks

This chapter describes the evolution of, and state of the art in, energy‐efficient techniques for wirelessly communicating networks of embedded computers, such as those found in wireless sensor network (WSN), Internet of Things (IoT) and cyberphysical systems (CPS) applications. Specifically, emphasis is placed on energy efficiency as critical to ensuring the feasibility of long lifetime, low‐maintenance and increasingly autonomous monitoring and control scenarios. A comprehensive summary of link layer and routing protocols for a variety of traffic patterns is discussed, in addition to their combination and evaluation as full protocol stacks

A micromachined zipping variable capacitor

Micro-electro-mechanical systems (MEMS) have become ubiquitous in recent years and are found in a wide range of consumer products. At present, MEMS technology for radio-frequency (RF) applications is maturing steadily, and significant improvements have been demonstrated over solid-state components. A wide range of RF MEMS varactors have been fabricated in the last fifteen years. Despite demonstrating tuning ranges and quality factors that far surpass solid-state varactors, certain challenges remain. Firstly, it is difficult to scale up capacitance values while preserving a small device footprint. Secondly, many highly-tunable MEMS varactors include complex designs or process flows. In this dissertation, a new micromachined zipping variable capacitor suitable for application at 0.1 to 5 GHz is reported. The varactor features a tapered cantilever that zips incrementally onto a dielectric surface when actuated electrostatically by a pulldown electrode. Shaping the cantilever using a width function allows stable actuation and continuous capacitance tuning. Compared to existing MEMS varactors, this device has a simple design that can be implemented using a straightforward process flow. In addition, the zipping varactor is particularly suited for incorporating a highpermittivity dielectric, allowing the capacitance values and tuning range to be scaled up. This is important for portable consumer electronics where a small device footprint is attractive. Three different modelling approaches have been developed for zipping varactor design. A repeatable fabrication process has also been developed for varactors with a silicon dioxide dielectric. In proof-of-concept devices, the highest continuous tuning range is 400% (24 to 121 fF) and the measured quality factors are 123 and 69 (0.1 and 0.7 pF capacitance, respectively) at 2 GHz. The varactors have a compact design and fit within an area of 500 by 100 μm.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Broadband vibration energy harvesting from underground trains for self-powered condition monitoring

A broadband vibration energy harvester tailored for self-powered condition monitoring of underground trains is proposed and developed using mechanical non-linearity and integrated multi-mode vibration. A datadriven approach is adopted for harvester design using operational vibration data on a train bogie. The harvester is designed to be unobtrusive while exhibiting good performance in harvesting energy over a wide bandwidth. In this work, the on-site vibration data are first analysed with the design goals identified. Then, a broadband harvester is proposed, implemented and evaluated. The harvester consists of a pre-stretched hosting beam and a group of micro-beams with repulsive magnetic forces on their free ends. A multiple vibration-mode harvester with non-linear dynamics is obtained in such a design. This harvester exhibits good performance over a broad bandwidth in frequency sweep and pseudo-random tests, illustrating its capability in self-powered condition monitoring applications.</div

Generating and Evaluating Tests for K-12 Students with Language Model Simulations: A Case Study on Sentence Reading Efficiency

Developing an educational test can be expensive and time-consuming, as each item must be written by experts and then evaluated by collecting hundreds of student responses. Moreover, many tests require multiple distinct sets of questions administered throughout the school year to closely monitor students' progress, known as parallel tests. In this study, we focus on tests of silent sentence reading efficiency, used to assess students' reading ability over time. To generate high-quality parallel tests, we propose to fine-tune large language models (LLMs) to simulate how previous students would have responded to unseen items. With these simulated responses, we can estimate each item's difficulty and ambiguity. We first use GPT-4 to generate new test items following a list of expert-developed rules and then apply a fine-tuned LLM to filter the items based on criteria from psychological measurements. We also propose an optimal-transport-inspired technique for generating parallel tests and show the generated tests closely correspond to the original test's difficulty and reliability based on crowdworker responses. Our evaluation of a generated test with 234 students from grades 2 to 8 produces test scores highly correlated (r=0.93) to those of a standard test form written by human experts and evaluated across thousands of K-12 students.Comment: Accepted to EMNLP 2023 (Main

Advanced medical micro-robotics for early diagnosis and therapeutic interventions

Recent technological advances in micro-robotics have demonstrated their immense potential for biomedical applications. Emerging micro-robots have versatile sensing systems, flexible locomotion and dexterous manipulation capabilities that can significantly contribute to the healthcare system. Despite the appreciated and tangible benefits of medical micro-robotics, many challenges still remain. Here, we review the major challenges, current trends and significant achievements for developing versatile and intelligent micro-robotics with a focus on applications in early diagnosis and therapeutic interventions. We also consider some recent emerging micro-robotic technologies that employ synthetic biology to support a new generation of living micro-robots. We expect to inspire future development of micro-robots toward clinical translation by identifying the roadblocks that need to be overcome

Dual Quaternion Based Finite-Time Tracking Control for Mechatronic Systems with Actuation Allocation

This paper investigates the tracking control performance regulation and actuation allocation of mechatronic systems subject to coupling motions. In particular, the kinematic and dynamic model is described by dual quaternion, which captures the coupling effect between translation and rotation movements. Considering external disturbances and system uncertainties, a non-singular fast terminal sliding controller is then developed to ensure finite-time tracking performance. In addition, the unwinding problem caused by the redundancy of dual quaternion is addressed with the help of a novel attitude error function. Furthermore, an improved simplex method is designed for distributing the developed control commands to proper actuators. Numerical simulations demonstrate the effectiveness with respect to disturbance suppression, fast tracking, high accuracy, and finite-time stability of the proposed method

Deep Reinforcement Learning-Based Control Framework for Multilateral Telesurgery

The upper boundary of time delay is often required in traditional telesurgery control design, which would result in infeasibility of telesurgery across regions. To overcome this issue, this paper introduces a new control framework based on deep deterministic policy gradient (DDPG) reinforcement learning (RL) algorithm. The developed framework effectively overcomes the phase difference and data loss caused by time delays, which facilitates the restoration of surgeon’s intention and interactive force. Kalman filter (KF) is employed to blend multiple surgeons’ commands and predict the final local commands, respectively. The control framework ensures synchronization tracking performance and transparency. Prior knowledge of time delay is therefore not required. Simulation and experiment results have demonstrated the merits of the proposed framework

Anthropomorphic Dual-Arm Coordinated Control for a Single-Port Surgical Robot Based on Dual-Step Optimization

Effective teleoperation of the small-scale and highly-integrated robots for single-port surgery (SPS) imposes unique control and human-robot interaction challenges. Traditional isometric teleoperation schemes mainly focus on end-to-end trajectory mapping, which is problematic when applied to SPS robotic control, especially for dual-arm coordinated operation. Inspired by the human arm configuration in boxing maneuvers, an optimized anthropomorphic coordinated control strategy based on a dual-step optimization approach is proposed. Theoretical derivation and solvability of the problem are addressed, and the effectiveness of the method is further demonstrated in detailed simulation and in-vitro experiments. The proposed control strategy has been shown to perform dexterous SPS bimanual manipulation more effectively, involving less instrument-interference and is free from singularities, thereby improving the safety and efficiency of SPS operations

High Frequency Inductive Power Transfer Through Soil for Agricultural Applications

This work was supported by the UK Research and Innovation (UKRI), reference numbers: NE/ T011467/1 and NE/T011068/1, and the National Science Foundation (NSF), award no. 1935632: SitS NSF-UKRI: Wireless In-Situ Soil Sensing Network for Future Sustainable Agriculture’. (Corresponding author: Juan M. Arteaga.)Peer reviewedPublisher PD