WavNet — Visual saliency detection using Discrete Wavelet Convolutional Neural Network

In the recent advancements in image and video analysis, the detection of salient regions in the image becomes the initial step. This plays a crucial role in deciding the performance of such algorithms. In this work, a Multi-Resolution Feature Extraction (MRFE) technique that makes use of Discrete Wavelet Convolutional Neural Network (DWCNN) for generating features is employed. An Enhanced Feature Extraction (EFE) module extracts additional features from the high level features of the DWCNN, which are used to frame both channel as well as spatial attention models for yielding contextual attention maps. A new hybrid loss function is also proposed, which is a combination of Balanced Cross Entropy (BCE) loss and Edge based Structural Similarity (ESSIM) loss that effectively identifies and segments the salient regions with clear boundaries. The method is tested exhaustively with five different benchmark datasets and is proved superior to the existing state-of-the-art methods with a minimum Mean Absolute error (MAE) of 0.03 and F-measure of 0.956.     

Influence of aluminum phosphate on the tribocorrosion performance of chemically bonded phosphate ceramic coatings

In this study, chemically bonded phosphate ceramic coatings (CBPCCs) with different contents of aluminum phosphate (AP) are prepared on stainless steel (AISI 304L). Differential scanning calorimetry, X-ray diffraction, contact angle test, and a tribocorrosion experiment are carried out to clarify the role of AP in the tribocorrosion performance of CBPCCs. The results show that, with the increase in the AP content, the enthalpy of curing increases because of the greater formation of the bonding phase AlPO₄. Both in static corrosion and in tribocorrosion, the corrosion current density of CBPCCs achieves the lowest value when the weight ratio of AP to polytetrafluoroethylene is about 0.78. Additionally, the influence mechanism of AP on tribocorrosion is clarified. AlPO₄ from the reaction between AP and Al₂O₃ has excellent mechanical properties and can enhance the wear resistance of CBPCCs by reducing the mechanical wear and the increased wear due to corrosion. The alumina particles wrapped by AlPO₄ can form a dense and smooth surface and change the direction of electrolyte propagation, which leads to the increase in the tribocorrosion resistance of CBPCCs.     

Vulnerable objects detection for autonomous driving: A review

Object detection performed by Autonomous Vehicles (AV)s is a crucial operation that comes ahead of various autonomous driving tasks, such as object tracking, trajectories estimation, and collision avoidance. Dynamic road elements (pedestrians, cyclists, vehicles) impose a greater challenge due to their continuously changing location and behaviour. This paper presents a comprehensive review of the state-of-the-art object detection technologies focusing on both the sensory systems and algorithms used. It begins with a brief introduction on the autonomous driving operations and challenges. Then, different sensory systems employed on existing AVs are elaborated while illustrating their advantages, limitations and applications. Also, sensory systems employed by different research are reviewed. Moreover, due to the significant role Deep Neural Networks (DNN)s are playing in object detection tasks, different DNN-based networks are also highlighted. Afterwards, previous research on dynamic objects detection performed by AVs are reviewed in tabular forms. Finally, a conclusion summarizes the outcomes of the review and suggests future work towards the development of vehicles with higher automation levels.     

Electrodeposition of B,Ni co-doped diamond-like carbon films on AZ91D magnesium alloy: Corrosion and wear resistance

Diamond-like carbon (DLC) possesses brilliant and excellent properties, including excellent corrosion resistance as well as outstanding wear resistance. Ni and B co-doped DLC films were deposited on AZ91D magnesium alloy by electrodeposition under mild conditions (300 V and 25°C). Uniform and dense morphology of co-doped DLC films were observed, and Ni and B were uniformly incorporated into the carbon-based films. Among all the electrodeposits, the appearance of D and G peaks near 1330 and 1570 cm⁻¹ revealed that the as-deposited films were typical DLC films. As the addition of Ni was increased to 0.05 g, the highest microindentation hardness, the lowest friction coefficient, and wear loss were achieved to be 164.5 HV, 0.3, and 0.6 × 10⁻⁵ kg/m, respectively. The amorphous carbon films fabricated at 0.05 g Ni had the lowest corrosion current density and the most positive corrosion potential, which was mainly due to the small and dense granular structure effectively hindering the penetration of corrosion media.     

食品安全国家标准中维生素的测定方法及进展

人体所必需的营养素除了蛋白质、脂类、糖类等能量物质外,维生素也是不可或缺的营养物质,是评价其营养质量的关键指标。检测食品中的维生素含量,是有效保证其质量与安全的必要条件。因此,对现有国家标准食品中维生素的检测方法进行综述,总结各方法的前处理及检出限等,为增强检测工作效率,以及食品检测方法的研究和发展提供参考。     

Transmission line detection in aerial images: An instance segmentation approach based on multitask neural networks

Camera-based transmission line detection (TLD) is a fundamental and crucial task for automatically patrolling powerlines by aircraft. Motivated by instance segmentation, a TLD algorithm is proposed in this paper with a novel deep neural network, i.e., CableNet. The network structure is designed based on fully convolutional networks (FCNs) with two major improvements, considering the specific appearance characteristics of transmission lines. First, overlaying dilated convolutional layers and spatial convolutional layers are configured to better represent continuous long and thin cable shapes. Second, two branches of outputs are arranged to generate multidimensional feature maps for instance segmentation. Thus, cable pixels can be detected and assigned cable IDs simultaneously. Multiple experiments are conducted on aerial images, and the results show that the proposed algorithm obtains reliable detection performance and is superior to traditional TLD methods. Meanwhile, segmented pixels can be accurately identified as cable instances, contributing to line fitting for further applications.     

A comprehensive survey on computer vision based concepts,methodologies, analysis and applications for automatic gun/knife detection

The ability to detect gun and gun held in hand or other body parts is a typical human skill. The same problem presents an imperative task for computer vision system. Automatic observer independent detection of hand held gun or gun held in the other body part, whether it is visible or concealed, provides enhance security in vulnerable places and initiates appropriate action there. Compare to the automatic object detection systems, automatic detection of gun has very few successful attempts. In the present scope of this paper, we present an extensive survey on automatic detection of gun and define a taxonomy for this particular detection system. We also describe the inherent difficulties related with this problem. In this survey of published papers, we examine different approaches used in state-of-the-art attempts and compare performances of these approaches. Finally, this paper concludes pointing to the possible research gaps in related fields.     

Wear and thermal behavior of basalt fiber reinforced rice husk/polyvinyl chloride composites

Plant fiber reinforced polymer composites (PFRPs) in practical application are often subjected to both complex friction and variable temperature environments. The present work explores the possibility of reinforcing rice husk/polyvinyl chloride (RH/PVC) composites with basalt fibers (BF) for developing a new wear resistant material with improved thermal stability. The results showed that the structural strength and wear resistance of the composites increased at first and then decreased with an increasing ratio of BF/RH, the highest value occurred at a BF/RH ratio of 8/42. The thermal stability of composites had a positive relationship with BF/RH ratio. The composites added with BF all possessed improved performance in comparison with unadded composites. Hence, the findings of this article proposed some new perspectives on improving the wear resistance and thermal stability of PFRPs that would broaden their practical application.     

基于光刀图像的机器人示教纠偏方法

为了解决机器人辅助在线检测系统示教过程中效率低、人为干预多的问题,针对孔类特征,提出一种通过处理光刀图像获取机器人位姿纠正参数的方法。在该方法中,纠偏过程按照将图像光刀线调整为水平方向、将被测特征调整至图像中央、根据不同特征调整最优扫描方向3个步骤进行。根据光刀图像可以求出测量坐标系与被测特征的位姿关系,并得到该位姿与理想测量位姿的偏差。经过坐标变换即可得到在机器人基坐标系下的调整参数。另外,可利用电脑控制机器人运动,从而实现了纠偏过程的自动化。实验结果表明,该方法可将初始的示教位姿修正为理想位姿,且比传统方式效率更高。     

Embedding carbon dots in Eu3+-doped metal-organic framework for label-free ratiometric fluorescence detection of Fe3+ ions

Fluorescent detection is a new spectroscopic measurement for ions sensing due to the advantages of real-time determination with high selectivity, accuracy, and low cost. However, chemosensors based on fluorescent detection are usually determined by absolute intensity from a monochromatic emission signal, which is easy to be fluctuated by the external environment, especially for Fe³⁺ detection in complex fluids. Herein, we rationally design a dual-emission Eu³⁺: CDs@ZIF-8 to construct a ratiometric fluorescent sensor with self-calibrating ability for Fe³⁺ determination. High efficient carbon dots (CDs) are embedded in europium ions (Eu³⁺)-doped MOF by simple stirring preparation at room temperature. The label-free ratiometric fluorescent probe (I_CDs@ZIF-8/I_Eu) exhibits simultaneous blue and red emission under the same excitation at 365 nm. Remarkably, Eu³⁺: CDs@ZIF-8 displays the superiority of high selectivity to Fe³⁺, which shows ratiometric fluorescence characteristics (I₀/I) in a range of 0-6 μmol\L with a low limit of detection (LOD) of 0.897 μmol\L. Besides, the CDs-MOF nanocomposite holds good aqueous dispersibility and low cytotoxicity, which shows great potential applications in medical aid including biological detection and clinical diagnosis.