Design of Spot Welding Robot

Welding robot has played an extremely important role in the welding production of high-quality, high-efficiency. The paper designed the hardware structure and software of spot welding robot. The hardware design mainly includes the major modules of arm and base; the hardware design includes two parts: manual mode and automatic mode. Manual mode is generally used for the robot system installation, commissioning and troubleshooting, and the major modules are controlled by the start of the corresponding button; automatic mode is mainly used for production stage. The welding robot uses PLC for controlling; the system runs faster and has a short production cycle. DOI: http://dx.doi.org/10.11591/telkomnika.v11i11.289

Unsupervised Learning of Long-Term Motion Dynamics for Videos

We present an unsupervised representation learning approach that compactly encodes the motion dependencies in videos. Given a pair of images from a video clip, our framework learns to predict the long-term 3D motions. To reduce the complexity of the learning framework, we propose to describe the motion as a sequence of atomic 3D flows computed with RGB-D modality. We use a Recurrent Neural Network based Encoder-Decoder framework to predict these sequences of flows. We argue that in order for the decoder to reconstruct these sequences, the encoder must learn a robust video representation that captures long-term motion dependencies and spatial-temporal relations. We demonstrate the effectiveness of our learned temporal representations on activity classification across multiple modalities and datasets such as NTU RGB+D and MSR Daily Activity 3D. Our framework is generic to any input modality, i.e., RGB, Depth, and RGB-D videos.Comment: CVPR 201

Study on defects detection of a structure undergoing dynamic load

Damages detection method of a long span beam was studied. The beam was designed to subject vibration in order to simulate service station of a real structure. The distributed dynamic strain on the beam was studied. Firstly, in order to reduce the dynamic data discriminate time, a new BOTDA method using amplitude transfer of BFS was applied. At the level of spatial resolution of 10 cm and the sampling interval of 5 cm of the BOTDA system, a sampling frequency for dynamic strain of about 13 Hz was achieved. Secondly, a cracks detection system based on distributed dynamic strain was provided. Most of the time, a real structure is undergoing dynamic load, therefore crack detection system of analyzing distributed dynamic strain was concerned. The work is unlike former research that was based on the distributed static strain analysis. Thirdly, a free vibration experiment was performed on a beam of 15 meters long in order to verify the dynamic crack detection system. In order to local the crack easily, the data from BOTDA were processed. Fourier Transform Analysis was adopted to transfer the distributed dynamic strains from time domain into frequency domain. Test results indicated that the distributed frequency amplitude analysis method provided a practical means to recognize the simulated cracks on the beam undergoing dynamic displacement

Towards Vision-Based Smart Hospitals: A System for Tracking and Monitoring Hand Hygiene Compliance

One in twenty-five patients admitted to a hospital will suffer from a hospital acquired infection. If we can intelligently track healthcare staff, patients, and visitors, we can better understand the sources of such infections. We envision a smart hospital capable of increasing operational efficiency and improving patient care with less spending. In this paper, we propose a non-intrusive vision-based system for tracking people's activity in hospitals. We evaluate our method for the problem of measuring hand hygiene compliance. Empirically, our method outperforms existing solutions such as proximity-based techniques and covert in-person observational studies. We present intuitive, qualitative results that analyze human movement patterns and conduct spatial analytics which convey our method's interpretability. This work is a step towards a computer-vision based smart hospital and demonstrates promising results for reducing hospital acquired infections.Comment: Machine Learning for Healthcare Conference (MLHC

Differentially Private Video Activity Recognition

In recent years, differential privacy has seen significant advancements in image classification; however, its application to video activity recognition remains under-explored. This paper addresses the challenges of applying differential privacy to video activity recognition, which primarily stem from: (1) a discrepancy between the desired privacy level for entire videos and the nature of input data processed by contemporary video architectures, which are typically short, segmented clips; and (2) the complexity and sheer size of video datasets relative to those in image classification, which render traditional differential privacy methods inadequate. To tackle these issues, we propose Multi-Clip DP-SGD, a novel framework for enforcing video-level differential privacy through clip-based classification models. This method samples multiple clips from each video, averages their gradients, and applies gradient clipping in DP-SGD without incurring additional privacy loss. Moreover, we incorporate a parameter-efficient transfer learning strategy to make the model scalable for large-scale video datasets. Through extensive evaluations on the UCF-101 and HMDB-51 datasets, our approach exhibits impressive performance, achieving 81% accuracy with a privacy budget of epsilon=5 on UCF-101, marking a 76% improvement compared to a direct application of DP-SGD. Furthermore, we demonstrate that our transfer learning strategy is versatile and can enhance differentially private image classification across an array of datasets including CheXpert, ImageNet, CIFAR-10, and CIFAR-100

Plasma surface functionalization of carbon nanofibres with silver, palladium and platinum nanoparticles for cost-effective and high-performance supercapacitors

Due to their relatively low cost, large surface area and good chemical and physical properties, carbon nanofibers (CNFs) are attractive for the fabrication of electrodes for supercapacitors (SCs). However, their relatively low electrical conductivity has impeded their practical application. To this end, a novel active-screen plasma activation and deposition technology has been developed to deposit silver, platinum and palladium nanoparticles on activated CNFs surfaces to increase their specific surface area and electrical conductivity, thus improving the specific capacitance. The functionalised CNFs were fully characterised using scanning electron microscope (SEM), energy dispersive X-ray analysis (EDX) and X-ray diffraction (XRD) and their electrochemical properties were evaluated using cyclic voltammetry and electrochemical impedance spectroscopy. The results showed a significant improvement in specific capacitance, as well as electrochemical impedance over the untreated CNFs. The functionalisation of CNFs via environmental-friendly active-screen plasma technology provides a promising future for cost-effective supercapacitors with high power and energy density

Investigation of Electrode Electrochemical Reactions in CH3 NH3 PbBr3 Perovskite Single-Crystal Field-Effect Transistors.

Optoelectronic devices based on metal halide perovskites, including solar cells and light-emitting diodes, have attracted tremendous research attention globally in the last decade. Due to their potential to achieve high carrier mobilities, organic-inorganic hybrid perovskite materials can enable high-performance, solution-processed field-effect transistors (FETs) for next-generation, low-cost, flexible electronic circuits and displays. However, the performance of perovskite FETs is hampered predominantly by device instabilities, whose origin remains poorly understood. Here, perovskite single-crystal FETs based on methylammonium lead bromide are studied and device instabilities due to electrochemical reactions at the interface between the perovskite and gold source-drain top contacts are investigated. Despite forming the contacts by a gentle, soft lamination method, evidence is found that even at such "ideal" interfaces, a defective, intermixed layer is formed at the interface upon biasing of the device. Using a bottom-contact, bottom-gate architecture, it is shown that it is possible to minimize such a reaction through a chemical modification of the electrodes, and this enables fabrication of perovskite single-crystal FETs with high mobility of up to ≈15 cm2 V-1 s-1 at 80 K. This work addresses one of the key challenges toward the realization of high-performance solution-processed perovskite FETs