Automatic gauge detection via geometric fitting for safety inspection

For safety considerations in electrical substations, the inspection robots are recently deployed to monitor important devices and instruments with the presence of skilled technicians in the high-voltage environments. The captured images are transmitted to a data station and are usually analyzed manually. Toward automatic analysis, a common task is to detect gauges from captured images. This paper proposes a gauge detection algorithm based on the methodology of geometric fitting. We first use the Sobel filters to extract edges which usually contain the shapes of gauges. Then, we propose to use line fitting under the framework of random sample consensus (RANSAC) to remove straight lines that do not belong to gauges. Finally, the RANSAC ellipse fitting is proposed to find most fitted ellipse from the remaining edge points. The experimental results on a real-world dataset captured by the GuoZi Robotics demonstrate that our algorithm provides more accurate gauge detection results than several existing methods

Model Compression for DNN-based Speaker Verification Using Weight Quantization

DNN-based speaker verification (SV) models demonstrate significant performance at relatively high computation costs. Model compression can be applied to reduce the model size for lower resource consumption. The present study exploits weight quantization to compress two widely-used SV models, namely ECAPA-TDNN and ResNet. Experimental results on VoxCeleb show that weight quantization is effective for compressing SV models. The model size can be reduced multiple times without noticeable degradation in performance. Compression of ResNet shows more robust results than ECAPA-TDNN with lower-bitwidth quantization. Analysis of the layer weights suggests that the smooth weight distribution of ResNet may be related to its better robustness. The generalization ability of the quantized model is validated via a language-mismatched SV task. Furthermore, analysis by information probing reveals that the quantized models can retain most of the speaker-relevant knowledge learned by the original models.Comment: Accepted by INTERSPEECH202

System-on-a-Chip Based Nano Star Tracker and Its Real-Time Image Processing Approach

The star tracker is one of the most accurate components for satellite attitude determination. With the development of the nano star tracker, it is compatible for application on small satellites. However, the drawback in dynamic property of nano star tracker has limited its extensive applications. The principal objective of this study is to introduce a system-on-a-chip (SOC) based nano star tracker with enhanced dynamic property. A morphology based image processing approach was realized based on single FPGA to achieve real-time star extraction, even from a blurred image. Such nano star tracker has been developed and tested, and field experiment results indicated that its dynamic range was up to 4°/s with a data update rate of 30Hz. Moreover, the orientation of the satellite with developed nano star tracker on board has been analyzed based on the telemetry data. Thus, such nano star tracker could promote its applications on small or agile satellites

Preparation and Properties of 1, 3, 5, 7-Tetranitro-1, 3, 5, 7-Tetrazocane-based Nanocomposites

A new insensitive explosive based on octahydro-1, 3, 5, 7-tetranitro-1, 3, 5, 7-tetrazocine (HMX) was prepared by spray drying using Viton A as a binder. The HMX sample without binder (HMX-1) was obtained by the same spray drying process also. The samples were characterised by Scanning Electron Microscope, and X-ray diffraction. The Differential Scanning Calorimetry and the impact sensitivity of HMX-1 and nanocomposites were also being tested. The nanocomposite morphology was found to be microspherical (1 μm to 7 μm diameter) and composed of many tiny particles, 100 nm to 200 nm in size. The crystal type of HMX-1 and HMX/Viton A agrees with raw HMX. The activation energy of raw HMX, HMX-1 and HMX/Viton A is 523.16 kJ mol-1, 435.74 kJ mol-1 and 482.72 kJ mol-1, respectively. The self-ignition temperatures of raw HMX, HMX-1 and HMX/Viton A is 279.01 °C, 277.63 °C, and 279.34 °C, respectively. The impact sensitivity order of samples is HMX/Viton A < HMX-1 < raw HMX from low to high.Defence Science Journal, Vol. 65, No. 2, March 2015, pp.131-134, DOI:http://dx.doi.org/10.14429/dsj.65.784

Limit cycle judder for new type of drum brake with foldable cam lever actuation device and layered lining

The vibration and noise of brakes have always been prevalent and difficult problems in the automobile industry and its related academic circle. The current study mainly focuses on the groan of the drum brake with a foldable cam lever actuation device strainer. The groan of the limit cycle generated by friction reappears after building its model in the ADAMS. Accordingly, a rigid flexible coupling model with a multi-layer friction plate is built. A simulation analysis shows that the model exhibits good braking stability and can reduce the amplitude of a brake groan through a comparison of the vibration characteristics of the drum brake and foldable cam lever with a conventional cam. A virtual prototyping analysis method for the dynamics characteristics of the foldable cam lever brake is also presented

SOOD: Towards Semi-Supervised Oriented Object Detection

Semi-Supervised Object Detection (SSOD), aiming to explore unlabeled data for boosting object detectors, has become an active task in recent years. However, existing SSOD approaches mainly focus on horizontal objects, leaving multi-oriented objects that are common in aerial images unexplored. This paper proposes a novel Semi-supervised Oriented Object Detection model, termed SOOD, built upon the mainstream pseudo-labeling framework. Towards oriented objects in aerial scenes, we design two loss functions to provide better supervision. Focusing on the orientations of objects, the first loss regularizes the consistency between each pseudo-label-prediction pair (includes a prediction and its corresponding pseudo label) with adaptive weights based on their orientation gap. Focusing on the layout of an image, the second loss regularizes the similarity and explicitly builds the many-to-many relation between the sets of pseudo-labels and predictions. Such a global consistency constraint can further boost semi-supervised learning. Our experiments show that when trained with the two proposed losses, SOOD surpasses the state-of-the-art SSOD methods under various settings on the DOTA-v1.5 benchmark. The code will be available at https://github.com/HamPerdredes/SOOD.Comment: Accepted to CVPR 2023. Code will be available at https://github.com/HamPerdredes/SOO

Substrate-Favored Lysosomal and Proteasomal Pathways Participate in the Normal Balance Control of Insulin Precursor Maturation and Disposal in β-Cells

Our recent studies have uncovered that aggregation-prone proinsulin preserves a low relative folding rate and maintains a homeostatic balance of natively and non-natively folded states (i.e., proinsulin homeostasis, PIHO) in β-cells as a result of the integration of maturation and disposal processes. Control of precursor maturation and disposal is thus an early regulative mechanism in the insulin production of β-cells. Herein, we show pathways involved in the disposal of endogenous proinsulin at the early secretory pathway. We conducted metabolic-labeling, immunoblotting, and immunohistochemistry studies to examine the effects of selective proteasome and lysosome or autophagy inhibitors on the kinetics of proinsulin and control proteins in various post-translational courses. Our metabolic-labeling studies found that the main lysosomal and ancillary proteasomal pathways participate in the heavy clearance of insulin precursor in mouse islets/β-cells cultured at the mimic physiological glucose concentrations. Further immunoblotting and immunohistochemistry studies in cloned β-cells validated that among secretory proteins, insulin precursor is heavily and preferentially removed. The rapid disposal of a large amount of insulin precursor after translation is achieved mainly through lysosomal autophagy and the subsequent basal disposals are carried out by both lysosomal and proteasomal pathways within a 30 to 60-minute post-translational process. The findings provide the first clear demonstration that lysosomal and proteasomal pathways both play roles in the normal maintenance of PIHO for insulin production, and defined the physiological participation of lysosomal autophagy in the protein quality control at the early secretory pathway of pancreatic β-cells

Efficient Red Organic Light Emitting Diodes of Nona Coordinate Europium Tris(β-diketonato) Complexes Bearing 4'-Phenyl-2,2':6',2''- terpyridine

Two novel nona-coordinated Eu(III) complexes [Eu(btfa) 3(Ph-TerPyr)] (Eu-1) and [Eu(NTA) 3(Ph-TerPyr)] (Eu-2) have been synthesized and characterized. The structure of the complexes was elucidated by density functional theory (DFT) methods. The experimental photophysical properties of the complexes were investigated and complemented with theoretical calculations. Effective energy transfer (ET) pathways for the sensitized red luminescence is discussed. The complexes were tested as emitting layers (EML) in organic light emitting diodes (OLEDs). At the optimum doping concentration of 4 wt.%, the double-EML OLEDs of Eu-1 exhibited red electroluminescence (EL) with an EQE of 4.0 % and maximum brightness (B)=1179 cd/m 2, maximum current efficiency (η c)=5.64 cd/A, and maximum power efficiency (η p)=4.78 lm/W at the current density (J) of 10 mA/cm 2. Interestingly, the double-EML OLEDs of Eu-2 at the optimum concentration of 3 wt.%, displayed an outstanding EL performance with EQE of 7.32 % and B=838 cd/m 2, η c=10.19 cd/A and η p=10.33 lm/W at J=10 mA/cm 2. The EL performance of this device is among the best reported for devices incorporating a europium complex as a red emitter.</p

Efficient Red Organic Light Emitting Diodes of Nona Coordinate Europium Tris(β-diketonato) Complexes Bearing 4'-Phenyl-2,2':6',2''- terpyridine

Two novel nona-coordinated Eu(III) complexes [Eu(btfa) 3(Ph-TerPyr)] (Eu-1) and [Eu(NTA) 3(Ph-TerPyr)] (Eu-2) have been synthesized and characterized. The structure of the complexes was elucidated by density functional theory (DFT) methods. The experimental photophysical properties of the complexes were investigated and complemented with theoretical calculations. Effective energy transfer (ET) pathways for the sensitized red luminescence is discussed. The complexes were tested as emitting layers (EML) in organic light emitting diodes (OLEDs). At the optimum doping concentration of 4 wt.%, the double-EML OLEDs of Eu-1 exhibited red electroluminescence (EL) with an EQE of 4.0 % and maximum brightness (B)=1179 cd/m 2, maximum current efficiency (η c)=5.64 cd/A, and maximum power efficiency (η p)=4.78 lm/W at the current density (J) of 10 mA/cm 2. Interestingly, the double-EML OLEDs of Eu-2 at the optimum concentration of 3 wt.%, displayed an outstanding EL performance with EQE of 7.32 % and B=838 cd/m 2, η c=10.19 cd/A and η p=10.33 lm/W at J=10 mA/cm 2. The EL performance of this device is among the best reported for devices incorporating a europium complex as a red emitter.</p

M-estimation in Low-rank Matrix Factorization: a General Framework

Many problems in science and engineering can be reduced to the recovery of an unknown large matrix from a small number of random linear measurements. Matrix factorization arguably is the most popular approach for low-rank matrix recovery. Many methods have been proposed using different loss functions, for example the most widely used L_2 loss, more robust choices such as L_1 and Huber loss, quantile and expectile loss for skewed data. All of them can be unified into the framework of M-estimation. In this paper, we present a general framework of low-rank matrix factorization based on M-estimation in statistics. The framework mainly involves two steps: firstly we apply Nesterov's smoothing technique to obtain an optimal smooth approximation for non-smooth loss function, such as L_1 and quantile loss; secondly we exploit an alternative updating scheme along with Nesterov's momentum method at each step to minimize the smoothed loss function. Strong theoretical convergence guarantee has been developed for the general framework, and extensive numerical experiments have been conducted to illustrate the performance of proposed algorithm