Search

In the defect detection of hot-rolled strip steel, there are often problems of too small target size and unclear features that lead to wrong detection and missed detection, for which a YOLOv5-based defect detection method for hot-rolled strip steel is proposed in this paper. Firstly, the overall architecture of the method is proposed, and then the algorithm implementation process is highlighted. Experimental analysis shows that the average detection accuracy using YOLOv5 is improved by 11.9% compared to YOLOv4 improved, with stronger generalization capability, faster detection speed, and lower error and miss detection rate.

Tensors are increasingly ubiquitous in various areas of applied mathematics and computing, and tensor decompositions are of practical significance and benefit many applications in data completion, image processing, computer vision, collaborative filtering, etc. Recently, Kilmer and Martin propose a new tensor factorization strategy, tensor singular value decomposition (t-svd), which extends the matrix singular value decomposition to tensors. However, computing t-svd for high dimensional tensors costs much computation and thus cannot efficiently handle large scale datasets. Motivated by advantage of quantum computation, in this paper, we present a quantum algorithm of t-svd for third-order tensors and then extend it to order-p tensors. We prove that our quantum t-svd algorithm for a third-order N dimensional tensor runs in time  N polylog ( N ) if we do not recover classical information from the quantum output state. Moreover, we apply our quantum t-svd algorithm to context-aware multidimensional recommendation systems, where we just need to extract partial classical information from the quantum output state, thus achieving low time complexity.

Herein, Ti3C2T x MXene/N-doped reduced graphene oxide (MXene/N-rGO) composite was employed as the electrocatalyst to construct a new electrochemical sensing platform for the determination of adrenaline (AD). The MXene/N-rGO was synthesized via a facile one-step hydrothermal method, where ethylenediamine acted as a reducing agent and N source. The doped N in rGO served as a bridge between MXene and rGO through tight hydrogen bonds. Scanning electron microscopy showed that large numbers of MXenes with accordion-like morphology were distributed on the surface of the N-rGO. The MXene/N-rGO composite displayed a synergetic catalytic effect for oxidizing AD, originating from the unique catalytic activity of N-rGO and the large surface area and satisfactory conductivity of MXene. These characteristics of composite material led to a remarkable effect on signal amplification for the detection of AD, with a wide linear range from 10.0 nM to 90.0 μM and a low detection limit of 3.0 nM based on a signal to noise ratio of 3. Moreover, the MXene/N-rGO electrode displayed good stability, repeatability, and reproducibility. Additionally, the proposed sensor was successfully applied for voltammetric sensing of AD in urine with recoveries from 97.75% to 103.0%.

Preparation of activated carbon from biomass ash residue can effectively treat solid waste and improve the economics of the biomass power generation industry. However, the low thermal conductivity of activated carbon (AC) cannot make it widely used. A strategy was reported herein modify the activated carbon by AlN increase its thermal conductivity. Effects of reaction temperature, nitriding time, and nitrogen flow rate on the formation AlN and summarized the optimal process of AlN modified activated carbon. The result showed that the optimal preparation process is to inject nitrogen at a rate of 300 ml/min, under the condition of 1550°C, nitriding reaction for 50 min. The thermal conductivity of AlN-modified activated carbon prepared by this process is twice that of unmodified activated carbon.

In recent years, high entropy ceramics have become one of the research hot spots in the ceramic field due to its superior high entropy characteristics, and the use of blast furnace slag as high entropy material is also in line with the general trend of energy conservation and emission reduction in today’s society. This paper will briefly introduce the preparation and properties of several common porous ceramics by studying the low thermal conductivity mechanism of traditional ceramic materials. The high entropy ceramic materials are further introduced. By introducing its low thermal conductivity principle, preparation process and its low thermal conductivity related experiments, the superior performance of low thermal conductivity high entropy ceramic materials compared with traditional porous materials is demonstrated, the development trend of low thermal conductivity ceramic materials is analyzed, and finally the application prospect of blast furnace slag in high entropy materials is prospected.

The safe and stable operation of the power system has always been a common problem related to social stability and economic development in the world. To adapt to the development of “Internet +" and energy Internet, to ensure the information security of the power industrial control side, the power industrial control system Information security raises higher requirements. First, the ICS communication model is abstracted, the security risks and threats faced by ICS are sorted out, the most urgent and critical security requirements are clarified, and then a communication enhancement scheme is designed without affecting functions, efficiency, and rapid deployment. This includes one-way authentication and integrity checking of critical communication messages, combined with a timestamp mechanism and registration mechanism. Finally, through the security analysis of the enhanced scheme, it proves that it can resist common attacks such as camouflage, tampering and replay.

We report a ground X-ray calibration of two X-ray telescope prototypes at the PANTER X-ray Test Facility, of the Max-Planck-Institute for Extraterrestrial Physics, in Neuried, Germany. The X-ray telescope prototypes were developed by the Institute of Precision Optical Engineering (IPOE) of Tongji University, in a conical Wolter-I configuration, using thermal glass slumping technology. Prototype #1 with 3 layers and Prototype #2 with 21 layers were tested to assess the prototypes' on-axis imaging performance. The measurement of Prototype #1 indicates a Half Power Diameter (HPD) of 82" at 1.49 keV. As for Prototype #2, we performed more comprehensive measurements of on-axis angular resolution and effective area at several energies ranging from 0.5-10 keV. The HPD and effective area are 111" and 39 cm^2 at 1.49 keV, respectively, at which energy the on-axis performance of the prototypes is our greatest concern., 11 pages, 9 figures

Industrial control system is widely used in social production activities and its security is directly related to national security and social stability. In this paper, the security threats and protection status of power industry control system are analyzed. A framework of information security evaluation system for power industry control system is proposed, which consists of three parts: experimental verification environment, product detection capability and security service capability, and the construction scheme of the system is discussed. A hardware-in-the-loop simulation and verification platform is constructed to realize the simulation and verification of power industry control system tools. The vulnerability of power industry control protocol can be found in depth. The problem of ambiguous attack mechanism and lack of verification means of power industry control system is discussed, which can provide support for the research of attack and protection of power industry control system.

In this study, a flexible and highly sensitive carbon nanotube buckypaper(BP) sensor was fabricated and validated which can be embedded in the composite reinforcement to real-time monitor flowing and infiltration of the resin for vacuum assisted liquid composite molding(VARI). The BP sensors were prepared by the spray-vacuum filtration method with mono-dispersion of multi-wall carbon nanotubes. It turns out that the excellent properties of the BP sensors can be obviously characterized; for example, conductivity, sensitivity and permeability, which were confirmed through contrasting the penetration of acetone and resin to the BP sensor. The utility of this novel technology about BP sensor monitoring resin flow front had been demonstrated through penetration evaluation experiment. The change in resistance with time obtained by BP sensors described the advancement of resin flow front with time, and comparing with the information recorded by a camera and a stopwatch, the results were basically the same. Additionally, because the permeability is an important process parameter during infiltration, affecting manufacturing cycle and product quality, four different conditions for the number of layers about the laid glass-fiber-reinforced were investigated. The comparison results of different permeability were gained from the information collected by BP sensors in real-time monitoring and combined with Darcy's law. This paper not only reveals the ability of BP sensor as a new method in real-time monitoring, but also provides a new way to avoid defects and optimize production in VARI processes.

Overdispersion is a widespread phenomenon in most count data sets. The negative binomial distribution is commonly adopted to fit over-dispersed count data. On the other hand, the mixture model always plays an important role in unsupervised classification. However, when estimating the parameters in the mixture of negative binomial models, the typical generalized Expectation Maximization (EM) algorithm which involves additional iterative procedures in M-step increases computational time. Hence, there remains a need for an efficient algorithm that can speed up the procedure of parameter estimation. For this purpose, here we develop a novel EM algorithm that successfully avoids the typical numerical solution in M-step for the mixture of negative binomial models. We extend further this EM algorithm to the zero-inflated negative binomial model. In the simulation studies, we focus on the runtimes and the classification performance of our proposed algorithm implemented in the mixture of negative binomial model. We found that our proposed EM algorithm can reduce the runtime of maximum likelihood estimation effectively, while achieving the similar classification performance in comparison with the typical EM algorithm. The mixture of negative binomial model and the proposed EM algorithm finally illustrates their good performance of fitting the real earthquake count data.

Electrochemical methods have been deemed effective strategies for the detection of dye additive sunset yellow (SY) owing to their low cost, good stability, and high sensitivity. However, the application of the existing sensors with single electrical signal response is limited by their inadequate sensitivity and large background interference. Herein, a ratiometric electrochemical strategy with a dual signal was developed to detect SY. The strategy had an intrinsic built-in correction to the effects from the system, and thus reduced the influence of environmental change. 3D polyethyleneimine functionalized reduced graphene oxide aerogels@Au nanoparticles/SH-β-cyclodextrin (PEI-rGAs@AuNPs/SH-β-CD) was used as the sensing material due to its 3D macroporous microstructure with high specific surface area and excellent electronic conductivity. Guest molecule methylene blue (MB) was chosen as a probe molecule, which formed an inclusion host-guest complex with a SH-β-CD host in advance. The target molecule SY displaced MB from the CD cavities, resulting in the decrease of MB current and the increase of SY current. With the logarithmic value of ISY/IMB as the readout signal, the detection limit of the developed ratiometric electrochemical sensor reached as low as 0.3 nM, confirming the excellent sensitivity. Furthermore, this strategy exhibited good selectivity and repeatability, and could be used for the detection of SY in a real sample.

This paper proposes a vision-based online fruit and vegetable inspection system. This system consists of two parts: the online detection of fruits and vegetables and the online weighing measurement of fruits and vegetables. Online detection system can detect the species of fruits and vegetables, and through the database to get the unit price of fruits and vegetables. The image processing includes image pre-processing, filtering, background removal, noise filtering and hole filling for recognition, and analysis of blocks. The weight of the fruits and vegetables is obtained by gravity sensor. Prices of fruits and vegetables can be displayed in real time in order to achieve the goal of unattended retail. This study built an online fruits and vegetables detection system which may be accelerated in the future for commercial uses.

In order to solve the problems of long adjustment time and weak anti-interference, a brushless DC motor speed control system based on neuron PID was proposed. Improved Hebb learning algorithm with property of self-learning and self-organizing was applied for the online adjust of PID control parameters. The step response of brushless DC motor speed control system was measured when the control system parameters change dynamically. The three parameters of the PID controller can be adjusted in real time and the rotational speed of the brushless DC motor can be effectively controlled. The results show that this control method has strong adaptability to coupling system and strong anti-interference ability.

Multi-walled carbon nanotubes and single-walled carbon nanotubes show great potential for the application as an electromagnetic interference shielding material. In this paper, the electromagnetic interference shielding the effectiveness of a composite surface coated single/multi-walled carbon nanotube hybrid buckypaper was measured, which showed an average shielding effectiveness of ~55 dB with a buckypaper thickness of 50 µm, and bukypaper density of 0.76 g cm−3, it is much higher than other carbon nanotube/resin materials when sample thickness is on the similar order. The structural, specific surface area and conductivity of the buckypapers were examined by field-emission scanning electron microscopy, specific surface area analyzer and four probes resistance tester, respectively.