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In the process of knowing and understanding the world, the traditional media of books and paper have always played a very important role. However, with the emergence of new media and the skilled use of digital media technology, the traditional medium of book and paper media has gradually faded away in the eyes of mankind. Stereoscopic paper media is a three-dimensional paper media that can display three-dimensional virtual scenes on the display device based on the traditional paper books by using the camera of the display device to identify the logo card or the real scene, and then collect the virtual information and the real scene. In this paper, under Windows 10 operating system, the program is written by VC++ and ARtoolKit software development kit development tool, and based on augmented reality technology, virtual 3D scenes are built through 3D model modeling to achieve matching and integration with real scenes of paper books and realize 3D interaction. Based on this, a 3D interactive augmented reality system with a high degree of realism is realized. The main research contents include: customizing the paper media markers, reducing the system's misjudgment rate of the markers by combining the single-response matrix and calculating the image matching value with an optimization algorithm, realizing and tracking the recognition of the markers in real time; and optimizing the image segmentation method of the ARtoolKit software development kit, using the marker card to rotate 45° relative to the camera's position to simulate the situation when the scene has changed significantly. We use the minimum error method to calculate the gaps in real time to realize augmented reality; build a 3D model with animation effects based on the ARtoolKit software development tool and Unity development platform; accurately align the recognized markers with the virtual 3D model; add audio to the 3D model to match the content and add interactive functions to realize the control of 3D animation. Stereoscopic paper media breaks the traditional paper book book reading method, no longer just read the content of paper books, you can see and content-related virtual information on the display device of the mobile terminal, such as three-dimensional scenes, videos and so on. Stereoscopic paper media improves the reader's interest in reading and gives the reader a vivid and realistic reading experience.

EUV lithography enters the high-volume manufacturing stage, and the semiconductor industry considers a lithography-wavelength- matched actinic patterned mask inspection (APMI) tool to be a crucial infrastructure for EUV mask qualification. ACTISTM, the world’s first high-sensitivity actinic patterned mask inspection system, was released in 2019. ACTIS detects lithographic impact defects that cannot be seen with the existing DUV inspection tools. The actual results of production mask inspection show that only an actinic EUV inspection system can visualize small surface topography and phase changes that propagate through multilayer stacks. In this paper, we present the progress of ACTIS inspection technology, defect sensitivity, die-to-database inspection and through pellicle inspection. For technology nodes beyond N3, a high-NA EUV anamorphic lithography system will be used. The mask structure in the high-NA era will be different from the current configuration. For inspection tool design, it is necessary to adopt a different magnification of mask-to-wafer projection in the vertical and horizontal directions. ACTIS has the extendibility to a high-NA system since its projection NA area has room for extension in one direction. The high-NA EUV inspection tool will be discussed in this paper as well.

This paper discusses pressure control for the OASIS primary antenna element, A1. This discussion is centered around the evaluation of pressure changes and what might drive them. A1 is created from thin polyimide film and from its orbital position near Sun-Earth L1, is subject to many environmental effects, the solar wind, radiation pressure, charging and micrometeoroids. This paper begins by describing the architecture of the pressure control system. We show that the solar wind and radiation pressure are too small to impact A1’s performance. We also discuss the need to connect the A1 to system ground for solid technical and programmatic reasons. A large section discusses the micrometeoroid environment and how recent mission data shows that the flux faced by OASIS is likely larger by factor of ~3 than might be expected from naive application of the traditional models.

The national development and reform commission proposed to pilot promote the large-scale development of distributed photovoltaic in the whole village, town and county, and pointed out that promoting the pilot of large-scale development of distributed photovoltaic in the whole county is an important measure to implement the strategic goal and task of "carbon peak and carbon neutralization".In order to carry out in-depth analysis and research on the impact of roof distributed photovoltaic construction in the whole county, provide suggestions and decisions for the company and Energy Bureau to promote roof photovoltaic construction, this paper This paper takes village level roof photovoltaic as the research object, carries out research from the aspects of village overview, photovoltaic access overview, load and electricity of village, photovoltaic income and impact of photovoltaic access on Power Grid.

Wilga 2021 Summer Symposium on Photonics Applications and Web Engineering was the 48th edition of the research and technical meetings series [1,2]. Traditionally, the whole week lasting annual series of technical conferences and topical sessions was scheduled to be held on 26 May – 02 June 2020 in Wilga resort near Warsaw, owned by the Warsaw University of Technology. Nearly 150 participants took part in all of the Wilga 2021 events, most of them being young researchers active in all aspects of photonics, electronics and ICT science and technology. Wilga Symposium also embraces hardware and software technologies associated with photonics like optics, optical engineering, optoelectronics, electronics and electrical engineering, mechatronics, chemical and material engineering, applied physics, industrial solutions and applications. Around 100 papers were presented during Wilga 2021, oral and poster. Out of this number, some papers chosen by authors are published in this volume of Proc. SPIE mostly related to photonics. The major change was that during Wilga 2020 and 2021 Symposia, during summer editions, no traditional large young researcher sessions at large were possible to be organized.

This paper mainly studies the energy management of regional integrated energy system with high proportion of renewable energy access. This paper proposes an energy management optimization strategy for regional high proportion renewable energy systems. The goal of this strategy is to minimize the comprehensive electricity cost in the region within a certain time period, and consider diversified distributed power sources and load types, such as wind power generation, photovoltaic power generation, fuel type controllable power generation, battery storage, electric vehicle and interruptible charge. In this paper, a high proportion of renewable energy system in a region is taken as an example to carry out case analysis, the results show that: the strategy can fully tap the renewable energy power generation space, maximize the local consumption of renewable energy power generation, and the strategy has a certain engineering practicability.

This paper presents a novel type of underwater AUV energy charging platform. The platform integrates hydrogen oxygen fuel cell system and lithium battery system to form a hybrid energy power supply system. At the output load side, it has two wireless energy transmission device, which can supply energy to two AUVs at the same time. The platform adopts DC power supply network which is controlled by master slave control method. For the voltage stability and energy scheduling, a multi-mode energy coordination control strategy is proposed. The control strategy relies on the DC networking, and the energy is scheduled according to the different working modes of the platform. The proposed control strategy can not only realize the stable operation of DC power supply network, but also effectively improves the energy utilization efficiency. The new AUV charging platform is introduced, the model of each energy source in the system is analysed in the paper. On the basis of DC network, the energy scheduling algorithm under different working modes is derived, and energy dispatch process is designed. The simulation of energy supply platform and energy coordination scheduling algorithm is carried out by matlab/simulink simulation platform. It verifies the effectiveness of the proposed supply platform and energy scheduling strategy.

With the rapid development of the new generation of information technology, the foundation and core role of software are becoming more and more prominent, with more and more applications and complex functions, larger and larger code scale, more and more software quality problems, and more and more software quality data are generated in the software life cycle. In today's big data era, through the effective collection, management and application of these software quality data, the utilization of software quality data can be effectively improved, so as to improve software quality. Based on this, this paper studies the whole life cycle quality data of software, including fault data for software quality improvement, process data for software quality risk prevention and evaluation data for software quality evaluation, for the concept, development, testing, use and maintenance, decommissioning stages of software life cycle. At the same time, this paper studies the requirements definition, collection, transmission, processing, storage, application and sharing of software quality data lifecycle management methods. This can support the construction of software quality data resources, provide decision-making basis for software quality management activities, and help to improve software quality.

Steel coil winding film packaging is an important part of steel coil packaging, but the current packaging method is mainly manual operation, which has the disadvantages of poor packaging quality and low packaging efficiency. Based on the analysis of packaging technology and packaging process, this paper designs the large steel coil through core winding packaging machine, and completes the mechanical structure design and three-dimensional modeling. This machine includes fixed frame, moving beam system, lifting beam system, C-shaped track system and through winding trolley system. In addition, this paper completes the finite element analysis of key parts and the modal analysis of the whole machine, and obtains the low-order natural frequency and vibration mode of the whole machine. The analysis results show that the material selection of key parts is reasonable, and the ultimate stress under working state meets the actual performance requirements.

In a smoke environment, the laser is susceptible to be scattered and absorbed by smoke particles, which in turn affects the detection performance of the pulsed laser fuze. Combining the analytic hierarchy process and the fuzzy evaluation method, this paper establishes the evaluation system of the target layer, the criterion layer and the index layer. The fuzzy evaluation criteria of each index are given, and combined with specific examples, the backscattering characteristics of pulsed laser fuzes in smoke environments are evaluated, and the evaluation results of backscattering characteristics under this example are obtained. A basis can be provided by the paper for the use of pulsed laser fuzes in smoke environments.

During the on-orbit operation of space spacecraft, it is easy to be affected by the small vibration from the satellite platform, especially the key sensitive loads carried by the spacecraft. The traditional method is to install a passive damping vibration isolation system between the platform and the sensitive loads. However, the passive vibration isolation system only has a good suppression effect on the high-frequency and large amplitude vibration, and can suppress the low-frequency and large amplitude vibration below 10Hz，the vibration isolation effect in the resonance section is poor. Therefore, in order to solve this problem, an active vibration isolation system of 6-DOF Stewart platform driven by piezoelectric actuator is proposed in this paper. Firstly, the characteristics of Stewart platform are analyzed and modeled, and on this basis, the deformation and displacement of each leg are obtained through decoupling calculation, and each leg is servo controlled with high precision; Secondly, the inherent hysteresis nonlinearity of piezoelectric ceramics has a serious impact on the positioning accuracy. By analyzing the hysteresis mechanism of piezoelectric actuator, a phenomenal hysteresis mathematical model based on Maxwell-Slip operator is established. Finally, the feedforward inverse compensation and feedback linearization methods are proposed, and the system verification test is established. The test results show that, the active and passive vibration isolation system designed in this paper greatly improves the positioning accuracy of piezoelectric actuator and the active vibration isolation performance of the platform.

Quantum cascade laser (QCL) is a new type of unipolar semiconductor laser. It has the advantages of narrow line width, tunable wavelength, high output power, etc. The QCL is widely used in gas detection, medical diagnosis, petrochemical industry, environmental pollution prevention and control, communications and military fields. Because it is difficult to cover the absorption peaks of multiple gases, a single QCL laser cannot detect and identify multiple different gases at the same time. Therefore, beam combination of multiple QCL laser is a feasible solution to achieve simultaneous online detection of multiple gases. This paper demonstrates a multi-wavelength QCL laser system based on spatial parallel beam combination. Four QCL lasers with wavelengths of 1274.70 cm-1, 1606.68 cm-1, 1831.84 cm-1, and 2226.18 cm-1 are integrated. The power of a single QCL reaches more than 100mW, and the total output power reaches 0.81W. By controlling the temperature of the heat sink, the wavelength tuning ranges of 9.65nm, 6.54nm, 7.54nm, and 10.45nm can be achieved respectively. The temperature tuning coefficients are 0.85nm/℃, 1.06 nm/℃, 1.25 nm/℃, 0.80 nm/℃, and the wavelength tuning accuracy is 85pm, 106pm, 125pm, 80pm. The system designed in this paper can simultaneously detect the gas whose absorption peak locates at the above four wavelength ranges, and can also customize a QCL laser with matched wavelength according to the absorption peak of the gas to be measured, which has good scalability.

Because it is not possible to integrate the light source on the silicon-based photonic chips, it is necessary to study the efficient coupling method to coupling the light from the fiber into the chip. In order to ensure the high coupling efficiency, the edge coupling method is adopted in this paper. The simulation is carried out in the COMSOL software. The incident light is set as a Gaussian beam with a waist diameter of 2.5 μm and a wavelength of 1550 nm to simulate the light emitted from the lensed fiber. The incident region of the waveguide adopts an inverse-nanotaper design, that is along the direction of light propagation, the width and height of the waveguide in the taper region gradually increase and keep constants in the bus waveguide region. In this paper, the specific size of the designed inverse-nanotaper coupler is given, and the coupling efficiency of the edge couplers under different conditions is analyzed, which lays a certain foundation for on-chip integration of related devices.

Atmospheric correction is the basis for quantitative analysis of satellite remote sensing images, such as monitoring land surface changes. However, precise atmospheric correction is still challenging. Landsat 8 is a satellite used for surface monitoring launched by the United States National Aeronautics and Space Administration (NASA) in 2013, with good spatial resolution. Rich spectral information. In this paper, an improved dense dark vegetation(DDV)aerosol retrieval algorithm is developed, and the retrieved AOD map will be used to process the aerosol impact factor of remote sensing images. Atmospheric correction is performed based on a lookup table generated by the 6SV model. Validation with the Land Surface Reflectance Code (LaSRC) algorithm produced atmospheric correction images, correction images of the paper algorithm showed a good agreement with high correlation(Correlation R exceeds 95%). Meanwhile, a reliable software prototype system for processing atmospheric correction on Landsat 8 OLI images was developed. This system is based on C++ language and can perform atmospheric correction automatically, low-latency, and accuracy. The data products corrected by the software prototype are helpful for the widespread application of remote sensing data in emergency response, environmental monitoring, and national defense.

In this paper, the deployment systems of a deployable space telescope for CubeSat are proposed. This telescope can achieve a ground resolution less than 1 meter at an orbital altitude of 400 km. Both the primary and secondary mirrors of it can be stowed in 3U volume（100mm×100mm×300mm）during launching period. The functions of the deployment systems include the locking of the primary and secondary mirrors when stowed, the deployment on-orbit, and the active adjustment of the primary mirror segments after deployment. In this paper, firstly, the optical system of deployable telescope is described, then the deployment systems of the telescope are designed. Finally, the modal analysis is carried out using finite element method.

Edge extraction of weld pool image is the key to realize on-line detection and control of laser cladding during the process of industrial laser manufacturing,and the accuracy of on-line control of cladding layer quality is largely determined by the accuracy of extracted weld pool edge.In this paper, a laser cladding pool image detection system based on machine vision is built to collect the molten pool image in the process of laser cladding. According to the characteristics of laser cladding pool image, the image is preprocessed. In this paper, an improved multi-structure, multi-scale and multi-directional morphological operator is proposed to process the molten pool image, and the accuracy and anti-noise ability of different edge detection methods are compared and analyzed. the improved mathematical morphology edge detection method can not only suppress noise but also extract the edge of laser cladding pool image more accurately.

This paper studied the classification method of tea using portable Laser Induced Breakdown Spectroscopy (LIBS) system to distinguish different kinds of tea with similar appearances from each other. The basic classification algorithm was Random Forests, and an improved data processing method of spectroscopies was presented to increase the classification accuracy. The provenance of tea was set as the classification label because that tea produced in some specific areas may have higher economic value. Fifteen kinds of green tea were collected from the market, of which nine were produced in Guizhou Province and the other six were produced in six other provinces. The spectral integral normalization method, and element window filtering method were proposed to process spectral normalization and screening. The parameters of Random Forests algorithm were optimized to achieve both high accuracy and low time cost. Finally, the classification accuracy of green tea from Guizhou Province was 97.75%, and green tea from different provinces was 100%. The research results of this paper made it a bright future of LIBS in application of tea quality appraisal and other food industry.

With the wide application of micro-nano structures in various fields, micro-nano technology has been developed continuously. Among them, micro-nano surface morphology detection technology has become a research hotspot, because the surface geometry and morphology of micro-nano devices determine the functional level and service life of devices. With the increasing complexity of micro nano device surface morphology and the increasing sharp edges, the detection technologies are facing severe challenges. Among various detection methods, structured illumination microscopy (SIM) has attracted many research interests due to the characteristics of high accuracy, strong adaptability and high efficiency. The existing SIM are mainly based on phase-shift technique, Hilbert transform technique and global Fourier transform technique. However, for complex-surface and steep-edge measurements, it is difficult for traditional SIM to achieve both high accuracy and high efficiency. In this paper, a method based on SIM which combines vertical scan and phase-shift is proposed. In this proposed measurement system, vertical scanning of the object is synchronized with the switching of the phase-shifted fringe pattern and only one fringe pattern needs to be projected, which enables a point-to-point processing defined as local Fourier transform method in this paper to be utilized to extract the modulation information which will reserve high-frequency information of the image so it can be applied to both smooth and rough surfaces. Simulation and experiment are carried out to demonstrate that the proposed method can successfully realize fast and accurate detection of complex-surface and steep-edge.

With the advantages of large detection and abundant information, time-domain electromagnetic survey has become the most potential and significant method technology in the field of electromagnetic survey. However, this technology is still under development in China, there is no system with practical detection been formed at present. This paper has proposed a method of building the airborne time-domain electromagnetic system based on fixed-wing UAV, which aims to realize the information and intelligent detection in the complex area through "manned platform with manned system". The system is designed as follows. The transmitter wires which are designed into three circle are fixed on the UAV nose, wing tip and belly fin, which can transmit once electromagnetic field to detect and whose maximum emission moment can reach 62100A·㎡. The receiving system which is fixed under the UAV belly can receive the secondary electromagnetic field from ground. The collection monitoring system which is fixed in the UAV belly is used to data recording and states monitoring including the power of transmitter wires, the positon of receiving system and the tension of towing current conversion and data recording. The circle and length of the transmitter wires could be intelligently adjusted with the UAV and application tasks and the releasing program will be intelligently started in emergency. Above all, the research proposed in this paper can provide a good conference for the application and practical of time-domain electromagnetic survey.

This paper combines the information processing technology for target detection with the sensor parameter design. A design method which is suitable for the staring infrared sensor in geosynchronous orbit has been proposed. The signal-to-noise ratio (SNR) has been introduced to evaluate the detection performance. The sensor temporal-spatial noise and background clutter time-domain residual have been comprehensively analyzed. First, the temporal noise and the spatial noise have been separated and compared, and then the background clutter and time-domain residual with different ground sample distance (GSD) have been analyzed based on the on-orbit remote sensing image. The results showed that selecting the appropriate GSD and applying the target detection method of time domain correlation, under the background-limited photodetection (BLIP), the design threshold of the noise equivalent target (NET) can be improved, and the detection and information processing efficiency can be maximized. The method proposed in this paper provide information for the design and optimization of space-based staring infrared sensor parameter.

This paper reconsiders the SECI model proposed by Ikujiro Nonaka, and points out the inconformity between theory and practice in the original model when knowledge conversion is based on the theoretical basis and the actual situation, that is, socialization or combination can not be realized directly, but can only be realized indirectly through the combination of internalization and externalization. On this basis, the model is improved, and the spatial vector model of knowledge conversion is proposed. The SECI model is innovated, which provides theoretical support for the subsequent research on knowledge conversion. Through the establishment of knowledge conversion model in the spatial vector coordinate system, the specific transformation mode between explicit knowledge and tacit knowledge is embodied, and the inner conversion mode of combinatorial and socialized is refined. Through the study of knowledge conversion model, this paper holds that there are two direct ways of knowledge conversion, namely externalization and internalization.

In the 21st century, one of the most important technologies must be artificial intelligence. It may bring us a whole new kind of people and technology, people and machines, or changes between people. So anthropological research is closely related to artificial intelligence research. This paper makes an infometric analysis to study 72 papers indexed in Thomson Reuters’s Web of Science by the perspectives of categories of researches, high frequency keywords, keywords co-occurrence and classifications of research topics. We uses VOSviewer to make a keywords co-occurrence map of the intersection of AI and anthropology which showed that artificial intelligence and interaction of anthropology focuses on the human spirit, body, technology improvement, the challenge of the moral and ethical aspects of the application, research is focused on the theory research and applied research. Researches of AI in anthropology mainly include two parts that the theoretical researches and the applied researches. The theoretical researches focuses on the relationship between human and AI, featuring the development of human beings in the future. The applied researches mainly includes the following three aspects: The application of AI in academic research, the application of AI in institutional service and the application of AI in people's daily life.

The paper comprehensively illustrates the research hotspots, core institutions and collaborative networks in the field of China’s architectural industrialization with visualized analysis method provided by CitespaceV, which takes 2318 relative articles provided by CNKI database as sample. After analyzing its development history and present situation, and summarizing the research characteristics from the perspective of literature, the paper predicts the key fields of its future development of China’s architectural industrialization.

Our cities are on the verge of a radical transformation, a revolution driven by smart city technology from tranportation, engery, water supply to intelligent construction. Infrastructure is the backbone of cities and its relevant policy plays an essential role in the development of smart city. The appraisal for the policy is indispensable, however, which is often ignored. The research attempts to explore appraisal of major infrastructure policy of the UK through scenario-based multicriteria analysis (SMCA) and discuss impact of major infrastructure policy and projects on social, ecnomic, and enviroment factors of cities. This paper finds different scenarios can be incorporated into multi-criteria analysis (MCA) to investigate future uncertainty for the policy statement appraisal. However, the hybrid approach through combining scenario planning and MCA increases the complexity of the sustainability appraisal. Although more and more research has focused on comparing the strengths and weaknesses of SMCA and existing methods, the research results in the paper provide evidence that SMCA might be a more useful tool in appraising major infrastructure planning policy and projects of smart city in the furture.

Nowadays, bridge design is completed by bridge software, but the process of bridge software modelling is very cumbersome and heavy workload. Using the elastic foundation beam algorithm, this paper deduces the internal force calculation formulas of strut, beam, suspender and arch rib of half through arch bridge under the condition of considering self weight. When designing half through arch bridge, the results can be obtained quickly by applying the formula in this paper. The algorithm can check each other with the bridge software algorithm. Using this algorithm for calculation in the project pre-evaluation stage can highlight its fast advantage.

The current full-scale development of information technology in construction projects has attracted the attention of the Ministry of Housing and Urban-Rural Development and the Ministry of Science and Technology. my country’s 14th Five- Year Plan has clarified the general strategy for the development of construction engineering informatization, which is to fully integrate information technology into the traditional construction industry. To achieve the overall goal of informatization construction, the development of appropriate informatization application tools is a key step. For this reason, this article starts from the convenience of the most basic 3D model informatization tools. In this paper, the application of BIM 3D model in design collaboration and construction management is studied based on BIM model technology and programming software. According to the requirements of using BIM by all staff in the decoration project, the technical route of product research, product function description and application method are put forward, and a handy BIM model application tool is designed and developed. The effect is analyzed combined with project examples. The results show that the handy BIM tool developed in this paper can be widely applied in the whole process management of decoration project.

With the popularization of the 5G (fifth generation), cloud computing and Internet of Things, China has developed an multi-dimensional and all-round smart tourism system, which has become China's development trend in tourism industry. Based on the background of post-pandemic of COVID-19, this paper analyzed the present research and application status of tourism. This paper analyzed the research status in the field of AR in tourism based on AR (Artificial Intelligence) technology. It studied the future how AR visualization technology could be applied in China's smart tourism development and how would the tourists be endowed with various feelings with the use of the technology

In this paper, using the elastic foundation beam algorithm, the calculation method of internal force of side span of longspan suspension bridge considering self weight is proposed, and the calculation method of side cable sag is also proposed. The internal force calculation method proposed in this paper is simple and fast. This method can check each other with the bridge software calculation method. Nowadays, there is no recognized calculation method of side cable sag in the world, and most of the side cable sag of built bridges are unreasonable values. In this paper, the engineering example of Kanmonkyo Bridge in Japan is taken. The comparative calculation shows that the side cable sag calculation method proposed in this paper is very reasonable, and the bridge designed by this method is safer and more economical.

Inverse Lithography Technology (ILT) has become one of the key computational lithography solutions, which may produce mask output that results in better process latitude and CD control on wafer than the one using conventional OPC. However, the curvilinear inverse lithography recipe parameter tuning is a non-trivial task, which involves optimization for various common objectives such as common DOF, NILS, and pvband (process variability band) [1]. It is known that test patterns used for recipe development play a critical role in achieving optimized ILT masks in terms of mask-friendliness, OPC convergence or multi-structure common focus range. The traditional way of test pattern selection is usually a clip-level manual search by taking into account of design rules, which inevitably may cause lack of critical design representations. In this paper, we introduce Mentor Graphic’s Calibre SONR[2], a Machine Learning (ML) method to implement design layouts clustering and automatic pattern selections for ILT recipe tuning on a full-chip level. Calibre SONR leverages design layouts and process models to create necessary features as input and then combine with a proprietary clustering algorithm to fully analyze and cluster a full layout in feature vector space. The degree of pattern reduction is controlled by an adjustable similarity metric[2]. The paper has four parts: the first part is on the feature generation and data collection based on the design layout, the lithography and etch process models. A wide range of over 100 features are extracted to represent the layout and process etc. The second is on the SONR model building and pattern selection from the full-chip; the third on the ILT recipe creation process with patterns selected from SONR and the traditional method; the fourth on the pattern coverage analysis and verification by evaluating the recipe quality through OPCV checks, and compare the results between SONR-based and traditional pattern selection methods.

In the recent years a number of FPGA manufacturers have developped System-on-Chip (SoC) devices which integrate FPGA fabric with ARM cores and ADCs/DACs. At the same time, following the rising popularity of deep learning, deep-learning frameworks using FPGA SoCs have emerged which can be used to easily deploy complex neural network models for in-the-field inference. The following paper describes how synthetic-appertureradar satellites based on modern FPGA SoCs can leverage these new developments and gain on-board detection capabilities. In the first section the synthetic aperture radar system is introduced, and modern FPGA SoC features are discussed and the reasoning behindenabling on-board sythetic aperture radar detection capabilities is presented. The next section describes a ship detection system which could be impemented on existing SoCbased radar payloads. The paper is concluded with a few observations on how implementing such a system could affect existing radar platforms.

In order to improve high efficiency for light-color conversion, this paper studies a high-efficiency light recycled structure for quantum dot color conversion (QDCC) based on a distributed Bragg reflector (DBR). The difference of optical performance is discussed between the QDCC structure employing a DBR and an absorptive color filter (ACF). Traditional quantum dot color conversion layer (QDCCL) has inherent limitations of blue light leakage and low light utilization rate. To solve this, an optical structure of QDCCL is proposed and discussed in detail, which uses a DBR instead of the traditional color filter and realizes efficient light-color conversion. Different structures are compared via experimental preparation and measurement, such as light-emitting intensity, color gamut, and light utilization rate. Results show that the structure of QDCCL combining a DBR can not only achieve a high color gamut of 124 NTSC%, but also increase the light utilization rate over twice than the traditional ACF structure. More importantly, the light emission intensity of red and green sub-pixels is increased by 2.2 and 2.3 times, respectively. In general, the structure proposed in this paper is of great significance to the development of the display industry.

This paper proposes a large depth-of-field (DOF) imaging method, which uses an image acquisition system equipped with a liquid lens. This paper also establishes the relationship between the focusing distance and the current value to estimate the object distance. The proposed method firstly uses a liquid lens to capture multi-focus images. Then the different objects in the scene are segmented by image processing algorithm. Then we apply an effective blur estimation algorithm on each object to determine the clearest image from all multi-focus images and obtain the corresponding current value. Finally, the clear images of different objects are combined to obtain a large DOF image, and meanwhile, the distances of different objects can be estimated, respectively. Experimental results show that the proposed method can effectively achieve large DOF imaging and measure approximate object distances.

The defect inspection in traditional metal processing usually adopts the manual visual inspection, which is easy to cause problems such as false detection and leakage. Besides, the detection rate of existing metal defect inspection has been affected by the high reflectivity of metal surface. For avoiding the problems of existing detection algorithms, a metal defect detection system based on laser triangulation and laser vision is given. The system is composed of industrial camera and strip light source. In order to avoid the interference of metal reflection on defect detection, the green strip light is used as the light source of the system. Based on the proposed system, this paper presents a metal surface detection algorithm with three primary color channels, that is, metal surface defects are identified by identifying the RGB values of metal surface pixels. Finally, through static experiments, the detection rate of the metal defect surface detection system based on laser vision is 100%. The defect detection method proposed in this paper can effectively avoid the influence of high reflectivity of metal surface on the detection rate, and can be widely used in the field of metal processing.

In the past few years, the development of natural language processing has been able to deal with many issues such as emotional analysis, semantic analysis, and so on. This review first introduces the development of natural language processing, and then summarizes their applications in financial technology, which mainly focuses on public opinion analysis, financial prediction and analysis, risk assessment, intelligent question answering, and automatic document generation. The analysis shows that natural language processing can give full play to its advantages in the financial field. Moreover, this paper also discusses the problems and challenges for financial technology that are developed based on natural language processing. Finally, this paper presents two developing trends of natural language processing in financial technology: deep learning and knowledge graph.

Depression is a kind of mood disorder disease characterized by significant and lasting depression, which seriously affects people's physical and mental health. In recent years, the number of people suffering from depression has gradually increased. In order to improve the recognition rate of depression and reduce the workload of doctors, this paper proposes to apply the deep learning algorithm BiLSTM (Bi-directional Long Short-Term Memory) and Attention to recognize depression. Among them, BiLSTM is used to extract contextual temporal information of text features and facial features. Attention is used to learn the correlation between vision and text modalities. This paper undertakes extensive experiments to demonstrate the network's effect. The experimental results show that this method has certain practical application value for depression recognition.

As the information technology develops rapidly, the large-scale personal data such as sensors or IoT (Internet of Things) equipment is kept in the cloud or data centers. Sometimes, the data owner in cloud center needs to publish the data. Therefore, in the face of the risk of personal information leakage, how to take full advantage of data has become a hot research topic. When data is published many times, personal privacy is also disclosed. Thus, this paper puts forward a new clustering algorithm based on singular value decomposition to finish the clustering process. The ideas of distance and information entropy are considered to flexibly adjust data availability and privacy protection in this way. Secondly, this paper also puts forward a dynamic update mechanism to ensure that personal data will not be leaked after multiple releases and minimize information loss. Finally, the effectiveness and superiority of this method are verified by experiments.

With the construction of smart grid, a large number of user-side power data has been accumulated. This paper proposes a method for analyzing the user’s power behavior based on clustering algorithm. Firstly, the user load data is classified according to the season, and the user’s seasonal power characteristics are analyzed according to the typical daily load curve of the season. Then the average temperature plus load data is used as the feature, and K-means clustering algorithm is used to explore the influence of temperature and holidays on users’ electricity behavior in summer and winter respectively. This paper proposes a method of classifying and analyzing different power consumption modes of a single user, which provides data support for the subsequent load prediction model training for similar days, as well as the formulation of fine management and demand side management decisions for the power grid.

Error calibration is one of the most important factors to realize the quadri-wave lateral shearing interferometer (QWLSI) with high accuracy. The misalignment errors of QWLSI, such as the tilt of grating and the tilt of charge coupled device (CCD), will affect the measurement accuracy. The astigmatism errors induced by the tilt of grating and CCD during the alignment process of QWLSI, which are neglected in previous studies, are analyzed and presented in analytical expressions in this paper. Firstly, the additional phase difference in X and Y directions induced by the tilt of grating and CCD are analyzed using the optical wave interference theory. Representing the phase difference in the two directions and the test wavefront with the combinations of Zernike polynomials respectively, we further obtain the analytical expressions between the Zernike coefficients of the phase difference and the Zernike coefficients of the test wavefront, according to the wavefront reconstruction theory. Then the analytical expressions for the measurement errors induced by the tilt of grating and CCD, which are mainly astigmatism, can be obtained. The analytical results show that the misalignment induced astigmatism errors are inversely proportional to the shearing ratio and proportional to the tilt angle of grating and CCD. The alignment experiment of a home-made QWLSI under null test condition is conducted to verify the correctness of the theoretical analysis. With different shearing ratios for the QWLSI, the astigmatism errors, which are induced by the tilt of grating in experimental results, are consistent with the theoretical analysis results. This paper can provide technical support for the alignment of QWLSI with small shearing ratio and high precision.

The paper optimizes the YOLOv4 detection model incorporating on the unmanned vehicle detection scenario. A hybrid attention mechanism combined channel and spatial attention mechanisms is introduced into the backbone network of the detction model. The high level semantic feature map and the shallow fine-grained feature map are merged into the detection neck network. The hybrid attention mechanism strengthens the process of screening the fine-grained features. The effect of using hybrid attention mechanism is better than that of using channel attention mechanism. Through the experiments, the results were drawn: (1) For the CSPDarknet-53 network, the effect of using hybrid attention mechanism is better than that of using channel attention mechanism. (2) On VOC 2007+2012 dataset, the model combined shallow layer feature maps and hybrid attention mechanism in this paper can improve can improve the detection accuracy by about 4%, compared with the original YOLOV4 object detection model. At the same time, for the KITTI dataset images closed to the actual scene, the image are used to verify the actual driving scene. The improved model achieves excellent detection effect on KITTI dataset.

With the rapid development of wireless communication technology, modern electronic map has gradually changed to many aspects, such as information transmission, map display, dynamic map and so on. Therefore, the traditional two-dimensional map can’t meet the needs of society, which needs to constantly improve the online dynamic map. Based on browser technology, WebGL technology has become a new tool, which can help the web to realize new map engine functions. Based on GIS technology, we can design a real-time, efficient, scalable, safe and reliable map engine. Through WebGL technology, we can draw massive vector data, which can also improve the loading speed of the server. Firstly, this paper analyzes the function of online dynamic map. Then, this paper lists some algorithms. Finally, this paper constructs an online dynamic map service framework.

The classification and detection of glomeruli of kidney tissue is a key process for correct diagnosis of diseases in renal pathology. However, it is still a big problem to perform comprehensive and accurate glomerular ultramicroscopic pathological diagnosis based on high-resolution whole-field digital slices (whole Slide Image). The reason lies in the grayscale image texture corresponding to the glomerular ultrastructure. Complicated, there are many types of related lesions, and it is difficult to identify and judge subtle pathological changes. The traditional semantic segmentation model cannot achieve the ideal segmentation effect. Based on this, this paper proposes a semantic segmentation method FEU-Net (FCN-Efficient U-Net) for pathological slices, which improves the accuracy of glomerular region segmentation and realizes end-to-end segmentation. FEU-Net uses EfficientNet, which has undergone transfer learning, as the encoder part to enhance image feature extraction capabilities. The decoder uses U-Net to promote the fusion of deep and shallow features while reducing the amount of network parameters, and redesign the convolution module to improve the gradient transfer capability. Compared with other classic methods in the SEED data set, it verifies that some classic models are difficult to fit in this segmentation task. At the same time, experiments show that modifying the feature extraction method can greatly improve the results. Among them, the modified method in this article is in the accuracy of segmentation. This is an increase of 18.968.96% over the original U-Net. At the same time, this article conducted ablation experiments on the ZENODO data set and the mendeley data set, verifying that each module in the improved algorithm helps to improve the segmentation effect of pathological slices. In the SEED data set, the FEU-Net method in this paper improves the Dice coefficient, accuracy rate and recall rate by 5.175.17%, 2.72.7%, 3.693.69%, 4.084.08% respectively compared with the benchmark model; in the BOT data set, The three indicators of the method in this paper have increased by 0.47%, 0.060.06%, 4.304.30%, and 6.086.08% respectively. The FEU-Net proposed in this paper improves the accuracy of segmentation of the pathological slices of gastric cancer and has good generalization performance.

Nowadays, real-time video is widely used in many fields such as video calling, live video broadcasting. The delivery latency and reliability requirements for live video are stringent, and using wireless access network to provide real-time video services brings great challenges to the provision of such services. In order to solve these problems, this paper proposes a mechanism to support real-time video service on multi-interface wireless devices by utilizing two selective redundancies simultaneously. The mechanism dynamically adjusts the video encoding rate and uniformly FEC encodes, then copies some video frames selectively according to the survival time of the video frames and the impact on the quality of the video, and further arranges their transmission (or part of them) with the help of the neighbor devices. In order to achieve the highest quality of video streaming service when the maximum allowable network bandwidth is given, the mechanism proposed in this paper will dynamically optimize encoding rate, copy number per frame and FEC encoding mode. In order to evaluate the quality based on the original quality and duration of distortion effects, this paper also proposes an evaluation model. The numerical results show that, compared with the existing methods, this method can reduce the video distortion to a certain extent when the network load capacity is low compared with other methods mentioned in this paper.

In the context of high proportion of wind power access, the stability of wind power as a power source has always been paid attention to, and the voltage stability of full-power conversion wind turbines is closely related to the control strategy of its converter control system. This paper proposes a new grid-side converter control strategy to maintain the stability of the grid-connected wind turbines. The contributions of this paper are: 1) Analyse the grid-side converter and establish its mathematical model to study the control of the wind turbine; 2) Add a voltage coupling controller to maintain the stability of the DC bus voltage; 3) Analyze the difference between the grid-connected voltage, current, active and reactive state variables before and after the wind turbine failure. The proposed control scheme for grid-side converter voltage coupling control will be tested in the full power conversion wind turbine set up in MATLAB/SIMULINK. The simulation results show the effectiveness and good dynamic performance of the scheme. The voltage oscillation has been alleviated to a large extent, and the DC bus voltage can basically be restored to its rated value.

High-resolution 3D optical imaging is important for unmanned underwater vehicles (UUVs) in the applications of target detection and recognition, underwater engineering, automatic navigation, scientific research, and natural resources exploration. Compared with stereo camera and 3D laser scanning imaging, 3D range-gated imaging (3D RGI) has longer detection range and higher spatial resolution at the same time. This paper presents a survey on 3D range-gated imaging methods for underwater detection. Up to now, there are two main methods developed, including time slicing method and gated range intensity correlation method. The literature about 3D RGI has been reviewed in different detection applications for UUV. We also introduce our works in 3D gated range-intensity correlation imaging for fishing net detection and marine life in-situ detection. This paper is beneficial for the 3D RGI technique in underwater detection applications for UUV.

A sampling inspection using non-patterned wafer and photomask has been dedicated to classical inspection technology for monitoring trend of particle variation at mass production. Total cost of sampling inspection method decreases the overall equipment effectiveness in mass production because equipment usage time and raw material cost. Nevertheless, customer mass production yield requirements for high-grade photomask and extreme ultraviolet photomask by sampling inspection method will be difficult to satisfy. To overcome sampling inspection's low reliability, this paper intended to describe an application of real-time monitoring for mass production equipment and verification of evaluated case by case. Optimization of real-time monitoring setup requires that sensor's install location with a considered mean free path in vacuum chamber, avoid to particle and bubble in chemical tube line and filter, and digital image process comparing method for nozzle height and parts location. An emergence of many by-products in a vacuum chamber, chemical tube line, and chemical filter is an unexpected danger. Application of real-time monitoring contributes to observing particles that in vacuum chamber using plasma, in tube line using chemical and chemical filters, sensing of mechanical drift and twist are also applicable with real-time detection technology using high-resolution cameras. As mentioned above, saved real-time big data can use proactive control to improve yield loss and cost of ownership. The specific suggestion about using real-time monitoring method is as follows 1. Detected increase rapidly trend of particle. Stop a process and start a particle removing recipe. 2. Observed particle rising. Stop process and start a cure recipe, and change other best path. 3. Sensed abnormal action. Stop process and do preventive maintenance after all substrate out. Both real-time monitoring data and yield data can analyze correlations that improve to become low cost of ownership by figuring out a root cause and drop in quality. A photomask industry is small compare to semiconductor industries, less than 1 percent by number of tools and production capacity. A photomask industry hard to make a big data due to little seed or small volume data. This paper shows how to make big data using real-time monitoring technology and how to defend a yield loss by unexpected situation at photomask tools.

Comprehensive disposition of reticle defects is critical for process and yield control. Misjudging a real defect on mask may not only reduce its lithography process window but also kill thousands of wafers causing unbearable economic loss. With the development of OPC and ILT technology, manual judgement of reticle defects has become more challenging. The situation is even worse in advanced logic fab, especially for foundry, where pattern complexity and diversity vary from worldwide fabless upstream firms. Working with KLA, USCXM adopted and reported ADC (Automated Defect Classification) and DPM (Defect Progressing Monitor) solutions to avoid defect misclassification and to alarm defects degrading [1]. These solutions run smoothly and shorten the cycle time in daily routine production. However, both functions cannot well predict the defect printability on wafer when there are questionable mask defects. Usually, the problematic mask has to be sent back to mask shop, where an AIMSTM tool evaluates printing risk, leading to a very time-consuming verification cycle. Thus, a cutting-edge technology called LPR (Lithography Printability Review) has been fully qualified and applied in a logic foundry for the first time. Using the optical mask inspection images, with LPR, the aerial image CD error can be accurately modeled thereby eliminating possibility of any related yield loss, while also dramatically shortening the cycle time for verifying such defects. In this paper, we introduce a series of strict qualification processes for LPR adoption. The qualification flow involves both PDM (Programmed Defect Mask) and production mask with respective purpose. The PDM verification covers various defect types while the production mask provides abundant pattern geometry. The LPR vs AIMSTM simulation efficiency is over 90% without missing one killer defect. Furthermore, LPR operates as part of an integrated solution with ADC and DPM. Typical production cases are also presented in this paper to demonstrate its invaluable contribution to avoiding yield loss. The RA (Reticle Analyzer) product including ADC, DPM and LPR, is the only mature solution, and is now deployed in full volume mask manufacturing production, driving intelligent automation with zero misoperation, shortened cycle time, and increased fab productivity.

Thermal imaging is considered as one of the most powerful and easier method that is used in observation applications. Since it can provide users with images that contain a lot of details about the observed scenarios in day and night also during bad atmospheric conditions. But by the fact of aging during the operation of Thermal Imaging Systems (TIS), the TIS main parameters and characteristics’ nominal values are deviated which has a high impact on the TIS tactical performance. These aged TIS are still working but in a lower efficiency, and consequently the observation capability will be decreased. Field performance evaluation of the TIS is one of the powerful measuring methods that is used to determine the actual discrimination ranges under different atmospheric conditions. This paper is devoted to offer a methodology for evaluating the aged TIS at the field. An experimental determination of TIS’s Minimum Resolvable Temperature Difference (MRTD) is performed by using an Inframet DT-150 test station. The discrimination range process (Detection, Recognition and Identification) is executed with the aid of MODTRAN software to simulate the real conditions for the atmospheric scenarios. Our presented methodology has enabled us to stand on the aged TIS actual performance to detect, recognize and identify different standard NATO (vehicle and human) targets. Moreover, redefining the aged TIS new missions according to their actual abilities. Finally, this paper was concluded with a real evaluation for an aged TIS (Bidentifier 100) as a case study. This method can be applied to any TIS whether it operates in mid or long wave Infrared (IR) spectral band.

This paper mainly explores the application of thermal signals generated by sequential laser pulses in the detection of metal material defects. Here we use flat bottom holes with different sizes on stainless steel as our sample. Sequential laser pulses are used as thermal excitation source and the surface temperature field is recorded by infrared thermal imager.By analyzing the relationship between the surface temperature of the defect area under sequential pulse excitation, the defect aspect ratio can be obtained due to different 3D thermal diffusion process. The experimental scheme and data processing method described in this paper provide a new method and theoretical basis for the measurement of metal defects size by sequential laser pulses, and have certain reference value for the detection and research of other metal material defects

Digital interferometer is widely used for evaluating optical surfaces due to its outstanding sub-nanometer accuracy and precision. In this paper, we will summarize its advantages and then describe its applications in industry, especially in both absolute flat and cylindrical surface and measurements. Transmission flat has normally 1/20 wavelength PV. However, when a flat surface under test is better or much better than the transmission flat, we need the absolute flat measurement. We developed a method to be easily able to achieve the accuracy of 1/100 wavelength PV. Two different measurement methods are proposed for the surface shape measurement of the inner surface and the outer surface of the cylinder, and the circular data is converted into rectangular data. For off-axis aspheric surfaces, we also propose a new measurement method. We have dedicated our efforts to do so. The theoretical analysis and experimental validation are presented in the paper.

Infrared character of aircraft is one important factor to estimate the ability of breaching the defense of enemy, this paper firstly analyzed the method of infrared calibration with collimator and energy factors composing the sky background, propose one method of deleting energy of background within current image; furthermore, the paper points out that the parameters of calibration with collimator can’t be directly applied to computing Infrared character of flying target, and based on that propose the method of deleting energy of background with another background image measured before mission.