Miracle-dz/UniFAR-FTUs huggingface dataset:
A Control Method of Robotic Arm Based on Improved Deep Deterministic Policy Gradient

With the continuous development of Machine Learning, Reinforcement Learning has achieved excellent results in many fields. An improved Deep Deterministic Policy Gradient (DDPG) algorithm is proposed in this paper to optimize Reinforcement Learning control performance, because of the issue of sparse rewards during training in continuous action spaces such as robotic arms, leading to slow convergence and low success rates. The algorithm merges the DDPG algorithm with the Hindsight Experience Relay (HER) algorithm, enabling the agent to learn from the failed experience when learning. Moreover, a double experience replay buffer is introduced, comprising a primary buffer and a secondary buffer containing high-reward experiences, which enhances the sampling probability of high-quality samples. At long last, a PyBullet simulation environment was utilized to execute a simulation experiment. The robotic arm using the improved DDPG algorithm achieved a success rate of nearly 100% in about 220 epochs of training, and the algorithm convergence speed was greatly improved. The trained robotic arm can reach any target point in the workspace. The efficacy of the improved DDPG algorithm is demonstrated by the outcomes, providing a valuable reference for further exploration into the intelligent control of robotic arms for object grasping.
Simulation Study of Gate-all-around Nanosheet Devices Based on SOI Structure

Owing to the excellent controllability of the Gate-All-About Nanosheet (GAANS) device, it’ s the most promising technology to achieve 3 nm technology node. However, there are few reports on electrical performances of GAANS devices on SOI substrates. In this article, the influences of device structural parameters on electrical characteristics are investigated by TCAD simulations. It’s concluded that with the increase of channel thickness and interface trap density, the sub-threshold swing and the peak transconductance increases, owing to the increase in effective channel width and the degradation in carrier mobility at the interface. Nevertheless, SOI substrates are effective in suppressing gate leakage.
The role of cultural values on the perception of advertising as offensive : a case study of Chinese tertiary students in Auckland

i Declaration ii Acknowledgments iii CHAPTER 1 1 Research Purpose and Rationale 2 Research Questions 3 Chinese in New Zealand 4 The New Zealand Advertising Industry 5 Thesis Outline 7 CHAPTER 2 8 Cross Cultural Communication 8 Theoretical Consideration 9 Hofstede’s Cultural Dimensions 11 Edward T Hall’s Lowand HighContext Culture 13 Limitations 14 Characteristics of Confucianism 14 Harmony 15 Virtue 16 Ritual 17 Filial Piety 17 Learning 18 Further Consideration 19 Advertising Perceived as Offensive 20 Current Research 21 Research in Asia 21 Demographic Profile of Audience 23 Cross Cultural Analysis 23 Gaps in the Literature 25 Conclusion 25 CHAPTER 3 27 Methodology 27 Data Collection 30 Survey 30
1.5kW LLC Resonant Converter with improved interleaved winding structure and core structure

In recent years, the power supply of the data center is increasing day by day. The new power supply architecture uses 48V bus to supply power to the subsequent VRM, so as to reduce I2R loss. Because of its soft switching characteristics, LLC resonant converter can meet the requirements of high power density and high efficiency, and is used in isolated DC-DC converter. In this paper, a magnetic integrated transformer is proposed to reduce winding loss and core loss. The windings and magnetic cores are optimized in local detail. A 1500W module was made in the experiment, achieving 97.8% peak efficiency and 97.6% efficiency at full load.
Power Injection Compensation for PSK Modulation in IPT Systems

Phase shift keying (PSK) is a modulation scheme which allows a single inductive link to achieve simultaneous wireless power and data transmission (SWPDT). However, the phase shift modulation may result in significant power reduction during the period where the link settles to a new steady state after each phase shift. In this paper, a power injection compensation method is developed to temporarily increase the duty cycle such that power transfer is controlled at the correct average level during PSK modulation. This paper presents a design method for power injection compensation based on an approximated transient model of IPT system. The design method is tested in an experimental converter operating a 1.0MHz. The experimental results show that for 90˚ phase modulation, the power injection control system increases the average load power from 72% to 98% of the unmodulated value. This is done without communication and compensation from the secondary side showing that the compensation technique can be implied to the primary converter to compensate for power transfer reduction during high modulation rates where feedback delays from the secondary limit performance.
Vibration Suppression of Dual Three-Phase Permanent Magnet Synchronous Motor in Five Degree of Freedom Magnetic Levitation System

A vibration suppression strategy for the dual three-phase permanent magnet synchronous motor (PMSM) in five degree of freedom (DOF) magnetic levitation system is proposed in this paper. Firstly, magnetic bearings (MBs) are designed to support the high-speed operation of the dual three-phase PMSM. Secondly, in order to suppress the vibration caused by the motor, the radial electromagnetic forces generated by the air gap magnetic field interaction are analyzed. After that, to suppress the vibration of the whole rotating shaft, fifth and seventh harmonics are injected in the windings of the dual three-phase PMSM by synchronous frame PI regulators. Amplitude and phase of harmonic currents are adjusted to counteract the radial electromagnetic forces, and then the vibration can be suppressed accordingly. Simulation results verify the effectiveness of the proposed strategy.
Generative Neural Network Approach to Designing Dynamic Inductive Power Transfer Systems

Generative Neural Networks (GNN) have demonstrated remarkable power in creating novel graphic design images from text-to-image training. This work applies GNNs to design dynamic inductive power transfer systems to make charging electrical vehicles (EVs) more convenient and cheaper. Discovering optimal and safe coil implementations (for EV and road) is challenging because of the combinatorial explosion of possible configurations, along with multiple conflicting objective functions, such as maximizing the output power, while minimizing stray magnetic fields and the volume of windings and magnetic cores. To solve the problem, a differentiable simulator and evaluator define loss functions that train a generative neural network to only produce configurations that satisfy eight given design criteria. Before training, the rate of finding successful designs is 0.005%, but within 500 training epochs, the rate becomes 98% (about 30 seconds run time). Solution diversity and quality may be further improved by applying loss functions trained on pairwise Pareto-optimal generated examples.
Low Complexity Lossy Compression Using Polar Codes

When the code length tends to infinity, polar codes have been proved to achieve the rate-distortion bounds of binary and Gaussian sources. However, the ideal conditions cannot be achieved in reality. In this paper, we propose a source coding scheme for binary sources based on polar codes, which has good performance for short-codes. As for Gaussian sources, a low-complexity source coding algorithm is proposed. In this scheme, we combine the characteristics of source polar coding with variable code rate and design a quantization algorithm suitable for Gaussian sources, which makes the system has lower complexity compared to the existing continuous source lossy compression system, and maintains good compression performance.
Execution Time Oriented Design of an Adaptive Controller for Mobile Machines

Mobile and stationary mechatronic systems are often driven by hydraulic actuators which are controlled using valves. Hydraulic systems have a high power density, are robust and cost-effective in the application and can work reliably under rough environmental conditions. For many years, PID controllers build the state-of-the-technology for valve control. Although PID controllers are easy to synthesize and can be executed on low-performing devices, the demand for more adaptive control approaches to deal with non-linearities in hydraulic circuits is increasing. Adaptive controllers tend to be more computationally expensive than PID controllers, so the capability of common hardware devices to execute the algorithms in real-time must also be considered. This paper contributes a feasibility study examining whether adaptive control approaches can be used for valve control in hydraulic-driven mobile machines. Thus, a literature review on adaptive valve control approaches is conducted and a model-based linear adaptive control approach consisting of system identification and control logic execution is extracted. The adaptive controller is applied to a hydraulic testbed and the controller performance is measured in dependence on the cycle time of the controllers to estimate the worst-case execution time. It is investigated whether common control units in mobile machines can reach the execution times and how many valves can be controlled by one control unit in terms of the execution time.
Multi-hop Precaching scheme with Relaying in Intermittently Connected Vehicular Networks

Due to the rapid development of smart vehicles such as self-driving cars, the mobile data traffic for vehicle users increases to the extent that a base station cannot handle, and it causes delays in content provision. The burden of the base station can be alleviated through roadside units (RSUs) to distribute the demands, but still, the outage zone, which the communication range of RSUs cannot cover, exists due to their high deployment cost. However, since the existing schemes for covering the outage zone only considered single-hop relaying vehicles to provide the precached content, the outage zone cannot be minimized by an insufficient number of candidate vehicles. Therefore, we propose a scheme for minimizing the outage zone by maximizing the precached content through multi-hop relaying vehicles. The proposed scheme optimally selects relaying vehicles through our numerical model to calculate the amount of the precached content and progresses the process of multi-hop relaying through comparing the connection time of vehicles with the dark area time in the outage zone. To prevent much overhead due to frequent precaching vehicle handover, the proposed scheme limits vehicles with a short communication time compared with a precaching restriction indicator in the multi-hop relaying vehicle selection process. Simulation results show that our scheme is superior to the representative scheme based on single-hop relaying.
Study on Inter-Layer Overlay of Stitching Lithography Technology

The interlayer overlay shift during semiconductor process may lead to a series of serious failure problems including short circuit, open circuit, and graphics failure. Furthermore, existing compensatory techniques are incapable of completely controlling the OVL shift induced by the stitching lithography process for large-area devices. In this paper, inline overlay reveal that the displacement of overlay marks on stitching mask significantly affects the process feedback and interlayer alignment. Therefore, a design rule of overlay mark dedicated to stitching reticle, which states the arrangement of overlay marks in the same exposure image, was proposed to improve the alignment for stitching lithography process.
A partial-variable-frequency modulation scheme for DAB converter for the all-ZVS operation in the full power range

With the wide application of dual active bridge (DAB) DC-DC converters in high-frequency scenarios, the realization of zero voltage switching (ZVS) becomes more important for efficiency improvement. However, the existing control strategy is difficult to realize all-ZVS in medium load, which results in lower efficiency. In this paper, a partial-variable-frequency modulation scheme based on medium load frequency regulation is proposed, which could realize the all-ZVS operation. Herein, a mathematical model is proposed to regulate switching frequency and a smooth transition is achieved in the medium load, by which the all-ZVS operation can be maintained. Finally, a DAB prototype has been built to verify the validity of the theoretical analysis and the all-ZVS operation is successfully achieved in the full power range.
An Online Efficiency Optimization Strategy Based on Variable-Frequency Phase-Shift Modulation for Dual-Active-Bridge Converters

The DC transformer (DCT) is a key equipment of the power router. To improve the DCT efficiency, this paper proposes a variable-frequency phase-shift modulation (VFPSM) strategy for the dual-active-bridge (DAB) converter which operates at the fixed voltage-transfer-ratio. The optimal switching frequency can be calculated by the VFPSM strategy online through the proposed loss model to ensure that the total of switching loss, conduction loss, and core loss is the minimum under different output powers. Besides, the frequency control and phase-shift control are decoupled by using the proposed frequency compensation factor, which would not affect the characteristics of the original DAB control method. Experimental results show that compared with conventional fix switching frequency control, the proposed VFSPM strategy can improve efficiency over a wide power range, and efficiency can be improved by up to 7.4%.
Multi Detection and Segmentation Coconut Shell for Charcoal Briquette Using Mask R-CNN

Coconut shell are the raw material for making high-quality charcoal briquettes, and their quality dramatically affects the quality of the final product. Therefore, assessing and determining the quality of coconut shells is very important in production. This research uses the Mask R-CNN instance segmentation algorithm with ResNet 101 to detect and classify coconut shell quality as a raw material for charcoal briquettes. Our model consists of four object classes: clean and dry coconut shell, fibrous coconut shell, wet coconut shell, and both wet and fibrous coconut shell. Researchers collected a dataset consisting of 651 images with a total of 8922 annotated objects directly from various sources of waste: traditional markets, coconut entrepreneurs, and household waste, which were then divided into 520 images for training and 131 images for validation. The research shows that the model achieves a mean precision value (mAP) of 0.98 on the training data and 0.94 for the validation data, indicating good prediction accuracy. Overall, the Mask RCNN model trained in this research shows excellent potential for use in producing high-quality charcoal briquettes.
Safety Analysis of Metasurface-Based Near-field Wireless Power Transfer System for Deep Implant

Wireless power transfer is a method for energizing future implantable medical electronics. In this study, a metasurface-based near-field magnetic wireless power transfer system for deep implants is presented, and electromagnetic safety parameters, including field distributions, specific absorption rate (SAR), and temperature variations, are evaluated. The power transfer is modeled for a receiver implant at a distance of 8.5 cm from the designed metasurface. Based on the results, a maximum localized SAR of 0.072 mW/kg is achieved when the efficiency is 1.62 %. Moreover, continuous power transfer shows that the local tissue temperature rises by less than 1.1°C.
Concept of a causality-driven fault diagnosis system for cyber-physical production systems

The automated production of individualized products in a cyber-physical production system (CPPS) requires the combined automation of software and machine components. While this leads to increased productivity, the complexity of the CPPS may result in long unplanned downtimes when faults occur, and no system model is available to guide the maintenance team. Knowledge-driven, data-driven or hybrid modeling are available approaches in the literature to obtaining a system model. While expert-driven and data-driven modeling face limited applicability to CPPS, hybrid models, combining both approaches can offer a solution. This paper proposes a causality-driven hybrid model for fault diagnosis in complex CPPS, represented in a causal knowledge graph (CKG). The CKG serves as a transparent system model for collaborative human-machine fault diagnosis. We provide a concept for the continuous hybrid learning of the CKG, a maturity model to classify the resulting CKG’s fault diagnosis capabilities, and the industrial setting inspiring the approach.
Excitation of semiconductor nanowires using individually addressable micro-LED arrays

Optical pumping of nanowire emitters, embedded in polymeric waveguides is achieved using a micro-LED array at 410 nm. The micro-LED-on-CMOS chip allows for individual pixel control and therefore parallel pumping of multiple emitters simultaneously. The nanowires are integrated on-chip using high-accuracy transfer-printing and laser lithography.
A Novel Control Method of Maximum Efficiency Point Tracking for Series-Series Wireless Power Transfer System

The efficiency of an inductive power transfer (IPT) system is dependent on its equivalent load. Specifically, the efficiency decreases very rapidly as the output power decreases. In this study, a maximum efficiency point tracking (MEPT) controller for a series-series tuned IPT (SS-IPT) system is proposed. Based on the load voltage and current observers in the literature, the equivalent load is controlled to a rated value that makes the efficiency to its maximum irrespective of the output power of the SS-IPT system. The proposed MEPT controller is designed by considering the cross-coupled and cascaded relationships between the state variables defined by the synchronous rotating reference frame (RRF) model of the SS-IPT system. Since the proposed MEPT controller utilizes estimated dynamic states by the state observers in the literature, voltage and current sensors of the receiver coil and the wireless communication are not required.
The Virtual Admittance Control of Sending End Converter for Offshore Wind Farm Integration

In the voltage source converter-based high voltage direct current (VSC-HVDC) system with offshore wind farm (OWF) integration, the sending end converter (SEC) needs to operate in V/f controlling mode to provide stable AC voltage and frequency for the OWF. At present, the SEC mainly adopts the dual closed-loop control, i.e., the outer AC voltage loop and inner AC current loop. However, this control structure may suffer from coupling problems when applied in the modular multilevel converter (MMC) due to the absence of the AC-side filtering capacitor. Therefore, a virtual admittance-based control strategy is proposed in this paper to enhance the steady-state and dynamic control performance of the SEC. The small signal stability and the parameter design of the proposed method are introduced in this paper as well. Finally, the performance of the proposed control strategy is compared with the conventional dual closed-loop control in PSCAD/EMTDC. The simulation results show the effectiveness of the proposed control strategy.
Rare Earth Materials Reduction in a Hypercar Propulsion System

Low-usage and rare earth free high-performance machines are in high demand, pushed by increasing costs and supply issues of rare earth materials. High torque density and high efficiency are key requirements in traction field. The challenge is designing propulsion systems which achieve such objectives while pursuing a global optimization logic in costs. This paper fits into this context by proposing a solution in which the same interior permanent magnet motor design is used for a four-wheel drive of a hypercar. A proper adaptation in axial length and magnets arrangement of the rear axle motor makes it suitable for the front axle requirements. Electromagnetic finite element analyses are performed to test different solutions with and without ferrite magnets. Torque, torque ripple, base speed, efficiency and rare earth reduction are the outputs under investigation. The best configurations are further studied via finite element structural analyses, as well as they are subjected to vibrational considerations. Different eligible solutions are found out with good performance while achieving a reduction in rare earth usage by 45.5%.
Structural Design and Experiment of a Small Wheel-legged Mobile Robot with Variable Configuration

In this paper, we made an improved design on the traditional quadruped robot structure and developed a new small wheel-legged mobile robot structure. It has four legged configurations, which can be selected according to different situations, improving the mobility and operability of the robot. In wheeled mode, the robot can adjust its center of gravity according to actual needs. Including the rotational degree of freedom of the wheel, each leg has four degrees of freedom. Each leg adopts a series structure and moves the knee drive motor to the fuselage position using a parallel four-link mechanism and is symmetrically arranged with the hip drive motor. A wheel is installed at the end of the shank, and a DC brushless motor is built inside it, enabling the robot to have the function of wheeled motion. This article introduces the details of the wheel-legged robot, emphasizing the innovative design of the physical structure and the diversity of deformation. The forward kinematics was analyzed. Based on the full-elbow configuration (a type of legged configuration), a cycloidal motion optimization simulation was completed for the single leg structure. Simulation experiment has proven that the optimized robot’s single leg motion is smoother. Finally, we conducted a typical experiment using an embedded controller to control single leg motion. The experimental results verify that the optimized cycloidal motion of the robot meets the desired motion effect.
The Performance Evaluation of Static Obstacle Recognition by Underwater Pressure Characteristics for Underwater Spherical Robot

Underwater spherical robots are flexible and often perform tasks in narrow, dark and complex environments. The artificial lateral line system inspired by the lateral line system of fish can recognize obstacles. However, currently, the recognition of obstacles under the artificial lateral line system is mainly based on the vibration characteristics of obstacles. Based on the blank recognition of static obstacles, this paper analyzes the feasibility of recognition static obstacles. A polynomial regression model is proposed to detect static obstacles (walls) by moving robots. Finally, the effectiveness of obstacle recognition is verified by experiment and simulation.