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Owing to historical reasons and investment restrictions, China’s aerospace industry initially focused on space technology and application, with insufficient emphasis on space science; therefore, space science, technology, and application developed independently. The development of space technology should be deeply integrated into space science and application, thus to strengthen China’s aerospace industry and create new opportunities and achievements. This study explores the implications of space science, space technology, and space application and clarifies their interrelationships. Moreover, it systematically analyzes the development trend in space science, technology, and application worldwide and reviews the development situation of space-related fields in China. Based on this, it examines the necessity for coordinating the development of space science, technology, and application in China and summarizes the major challenges. Considering their overlapping needs and mutual promotion, space science, technology, and application should be coordinated throughout the process of planning, deployment, and implementation. First, the advantages of the new national system should be exploited to conduct top-level planning under unified management. Second, the innovation-driven development strategy should be insisted to promote the international competitiveness of China’s aerospace industry through technological progress. Third, basic research in the space field should be strengthened and high-level scientists and engineers should be cultivated. Lastly, resource planning and coordination should be strengthened to promote the rational opening and full utilization of space application data.

For improving the test system, it needs to build measuring carrier and optimize shell design. To obtain valid and reliable test data, it needs the measurement uncertainty of test system with 3dB.But the test results show the measurement of results between the inside and outside the shell are quite different. This has great impact on the measurement results. This paper carried out cause analysis from five links of people, machine, material, method, environment for sound transmission performance of FRP housing. It found out the main reason of poor sound transmission of FRP housing, Single side vacuum adsorption molding method have been taken, good results and expected purpose have been achieved.

Promoting the application of new energy technologies in marine ports is an important way to realize the carbon peaking and carbon neutrality goals and achieve the sustainable development of ports in China. This study summarizes the current situation and trends of energy consumption in marine ports of China and analyzes the basic attributes of the application of new energy technologies in marine ports from three dimensions: economical efficiency, demand, and maturity; it involves ffshore wind power, photovoltaic power generation, hydrogen energy, tidal energy, and biomass energy. Factors that constrain the application of new energy technologies in China’s marine ports are further discussed from three aspects: technology, economical efficiency, and technological policy. Our research indicates that the mismatch between the development level and application needs of new energy technologies, lack of centralized technology-developmentplatforms, inadequate profit models, and imperfect standards and policies collectively constrain the application of new energy sources in marine ports of China. Therefore, we propose the following suggestions: (1) establishing a collaborative research and development system for key core technologies to overcome technical difficulties and reduce application costs, (2) issuing guidance on multi-energy integration networks for ports to establish a multi-energy-complementary energy supply system, (3) optimizing the incentive mechanism for the application of new energy technologies in ports to enhance the enthusiasm of ports to apply new energy sources, and (3) improving the standards and norms for renewable energy application in ports to build a novel energy-storage supporting mechanism.

Nickel resources are vital for national economic development. As the largest consumer of nickel metal worldwide, China faces a scarcity of nickel metal raw materials which depend highly on imports. Therefore, it is necessary to achieve breakthroughs in nickel resource exploration, promote the comprehensive development and utilization of nickel resources, and broaden import channels, to ensure a secure and stable supply of nickel resources. Based on the analysis of the latest data of the nickel industry, this study reviews the nickel resource endowments and the status of nickel supply and demand in China and abroad, and summarizes the genetic types, spatiotemporal distribution, and prospecting potentials of nickel ore deposits. It also analyzes the issues facing the development and supply security of China’s nickel resource industry, and proposes key technologies for nickel exploration as well as development paths for the comprehensive utilization of nickel resources. To ensure the stable supply and safe development of nickel resources in China, countermeasures are proposed from both international and domestic aspects. Internationally, it is necessary to stabilize the important nickel resource import markets represented by Indonesia and the Philippines, increase investment in mining projects overseas to enhance the international competitiveness of Chinese enterprises, and strengthen international cooperation to diversify the channels for nickel resource imports. Domestically, the following suggestions are proposed: (1) increasing nickel resource exploration, (2) promoting the comprehensive utilization of nickel resources to increase the utilization rate of recycled nickel resources, (3) optimizing traditional technical processes and adjusting the industrial structure, (4) strengthening nickel reserve bases to ensure effective increase in reserves; and (5) encouraging research on mining technologies of potential nickel ores such as ferromanganese nodules on the ocean floor.

Currently, the digital transformation of the financial industry in China has moved from multiple breakthroughs into a new stage of deepening and high-quality development, which necessitates a collaborative governance mechanism that coordinates multiple parties including governments, enterprises, and individuals. In view of the new, complex, and potentially harmful financial risks arising in the context of digital transformation, the financial industry urgently needs to improve its financial risk monitoring and earlywarning capabilities to effectively protect financial security. This study analyzes the progress of digital transformation of the financial industry as well as the implications and characteristics of new financial risks through literature research and theoretical analysis. It also investigates the mainstream financial risk monitoring and early-warning technologies in China and abroad, and clarifies the prominent problems regarding risk characterization and recognition, transmission and tracking, and inference assessment. Furthermore, we propose the overall framework, innovative research methods, and improving paths for the financial risk monitoring and earlywarning system in the context of digital transformation. This study reveals that financial risks have new characteristics in the context of digital transformation, such as faster update and iteration, higher risk frequency, and stronger concealment. Existing financial risk monitoring and early-warning technologies have numerous deficiencies and face multiple challenges in dealing with new financial risks, such as difficulty in characterizing, tracking, and assessing risks. Therefore, to improve the financial risk prevention capability of China and guarantee national financial security, it is proposed to develop cross-industry sharing standards for financial data, establish a knowledge representation paradigm and a cross-industry transmission mechanism of financial risks, and build a large model regarding financial risk monitoring and early warning.

The construction industry is shifting towards sustainability, emphasizing the need for innovative materials. Recycled Aggregate Concrete (RAC), utilizing recycled aggregates, emerges as a promising eco-friendly solution to minimize waste and resource utilization. However, accurately predicting its compressive strength (CS) is challenging due to varying composition and properties. This study addresses this issue by employing machine learning models, specifically five gradient boosting algorithms: Gradient Boosting Machine (GBM), LightGBM, XGBoost, Categorical Gradient Boost (CGB), and HistGradientBoosting (HGB). A total of 314 mixes from relevant published literature were aggregated to train the models. These models are meticulously fine-tuned through hyperparameter optimization for optimal predictive performance. The study also introduces SHAP (SHapley Additive exPlanations) algorithms for model interpretability, elucidating feature contributions to predictions. The results revealed that among the five gradient boosting models, CGB demonstrated the highest R2 value of 92% on the testing set, while LightGBM exhibited the lowest Coefficient of Determination (R2) value of 88%. Additionally, CGB achieved the lowest Root Mean Square Error (RMSE) of approximately 4.05, whereas XGBoost showed the highest RMSE of around 4.8. Furthermore, for Mean Absolute Error (MAE), LightGBM recorded the lowest value of approximately 3.16, while HGB yielded the highest MAE of about 3.8. The SHAP analyses reveal influential features impacting RAC strength, highlighting the significance of cement, water, sand, and recycled aggregate water absorption in predicting RAC compressive strength.

Considering the implication of radar sensors in our daily life and environment. Localizing and identifying drones are becoming a research with a greater focus in recent years. Consequently, when an unmanned aerial vehicle is used with bad intention, this can lead to a serious public safety and privacy probem. This study investigate pratical use of spectrum range for multistatic passive radar (MSPR) signal processing . Firstly, signal processing is performed after MSPR sensing detection range ,this include multipath energy detection, reference signal extraction, and receiving antenna configuration. Secondly, based on the MSPR nature, the reference signal is extracted and analyzed. In addition,taking into consideration the vulnerability of passive radar when comes to a moving target localization and real time tracking detection ,a novel method for spectrum sensing and detection which relies on Gaussian filter is proposed. The main goal is to optimize the use of the reference signal extracted with minimum interference as the shared reference signal in spectrum sensing. This will improve the system detection capability and spectrum access. Finally, a recursive method based on Bernoulli random filter is proposed, this takes consideration of drone’s present and unknown states based on time. Moreover, a system is developed meticulously to track and enhance detection of the target. A careful result of the experiment demonstrated that spectral detection can be achieved accurately even when the drone is moving while chasing its position. It shows that Cramer Rao lower error bounds remains significantly within 3% range.

The concept and technologies of computing-network integration are still in the early stage of development. Research on computing task scheduling and network interconnection are still inadequate. Therefore, it is urgent to understand the developmental trend of the intelligent connection computing network technology (ICCNT) and propose a strategic conception and development routes for the independent innovation of ICCNT in China. This study analyzes the major challenges faced by the existing information network technologies and summarizes the developmental trends of computing-network integration. It also proposes a core architecture of the ICCNT and clarifies its development goals and expected performance. The development path of ICCNT is explored, covering key technologies such as diversified protocol support, integrated control of network, storage, and computing, intelligent arrangement of service functions, and endogenous security structure, as well as demonstration applications in the smart park network, vertical industry network, and data center network scenarios. Furthermore, we suggest innovating ICCNT systems, expanding the demonstration applications of ICCNT, and accelerating the implementation of ICCNT products, thereby promoting the evolution and application of ICCNT.

Cyber resiliency engineering is a technical approach embraced by countries and regions such as the United States and Europe to implement digital transformation and address network security challenges under new circumstances. It aims to keep the barriers to entry high for digital technologies based on the cyber resilience standard and to improve the digital infrastructure security capability of China from both the application service and device supply sides. This study focuses on the impact and challenges brought by the initiatives of cyber resiliency engineering in the United States and Europe on the development of new-generation network information technology in China. It starts from a concept introduction of resilience, cyber resilience, and cyber resiliency engineering. Subsequently, it elaborates on the application progress of cyber resiliency engineering in the United States and Europe in terms of policy drivers, strategic considerations, and development dilemmas. Moreover, the study goes further to propose a dynamic heterogeneous redundancy architecture based on an endogenous security and safety (ESS) theory. It describes and illustrates the intrinsic mechanism, basic concepts, and application methods of cyber resilience empowered by ESS. Furthermore, we propose that China should accelerate innovation to offset the combined effects of cyber resiliency engineering in developed countries, introduce a cyber resilience policy and law system with Chinese characteristics, establish corresponding regulatory systems to clarify the network security responsibilities, establish a quantifiable, verifiable, and credible testing and evaluation system, and boost the holistic implementation of cyber resilience with a multi-pronged approach including financial marketization, hoping to ystematically enhance the cyber resilience and strength of China.

In recent years, the promotion of nearly zero-energy buildings (NZEBs) in China has emerged as a crucial step for the building industry in shifting towards a green and low-carbon future. Starting from scratch, the development of NZEBs in China has included the application and fundamental research, the compilation of national and local standards, and the rapid emergence of projects encompassing 23.89 million square meters nationwide. These efforts have yielded preliminary results in national standards, technology systems, technical roadmaps, and large-scale project demonstrations. However, challenges, including further reducing incremental costs, developing industries for retrofitting existing buildings into NZEBs, and expanding the range of policy incentives, remain to be addressed. This article provides an overview of the last decade’s progress in NZEBs in China, covering key technological research, policy development, engineering demonstrations, and the current industrial development status. Finally, the prospects of the NZEB industry are discussed.

Optimal scheduling of renewable energy sources and building energy systems serves as a pivotal strategy for achieving zero carbon emission. However, the coordination of zero carbon building energy systems (ZCBS) is still challenging due to the complicated interactions among multi-energy hybrid storage and the complex coordination between seasonal and daily scheduling. Therefore, this study develops a coordination scheduling approach for ZCBS. An operation model and a seasonal-daily scheduling approach are developed to optimize the operation of hydrogen, geothermal, and water storage devices. The performance of the developed method is demonstrated using numerical case studies. The results show that the ZCBS can be achieved by using renewable energy sources with the system flexibility provided by hydrogen, geothermal, and water storage devices. It is also found that the developed scheduling approach reduces operation costs by more than 43.4% under the same device capacity, compared with existing scheduling approaches.

Cancer is a serious threat to human life and health. Along with the development of medical informatization in China, healthcare institutions have cumulated a great quantity of clinical data in oncology; however, these data have not been fully explored owing to the disunity of data standards and great difficulties in data management. Hence, establishing a national clinical big data management system for oncology based on artificial intelligence could potentially promote the application of clinical data in oncology, further improving the quality and efficiency of clinical management for oncology. This study conducted an in-depth analysis of the problems and challenges of clinical data management and application for oncology and presented the significant values of an oncology clinical data management system. Considering the complexity of multi-source and multi-modal data in oncology, we explored the possible mechanisms and pathways of applying artificial intelligence to the management and research of clinical data for oncology Furthermore, a full-circle solution was designed, and the construction framework and technology systems were promoted for the clinical data management system for oncology, including the development of common data models for oncology, data collection and security management, data standardization and structuring, data analysis and application, and data quality control. Besides, we validated the feasibility and benefits of the promoted system in clinical practice by taking the clinical data management for lung cancer in a tertiary hospital as an example. Finally, we proposed some suggestions on the research directions of the clinical big data management system for oncology.

Flexible all-solid-state supercapacitors (FASS) are energy supplies for wearable electronic devices and power devices. Graphene nanosheets have unique two-dimensional (2D) structures, strong mechanical properties, and an excellent electrical conductivity, which are widely used in paper-like flexible electrodes. The essential feature of the double-layer electric performance for the simple graphene nanosheet-based FASS restricts the improvement of their capacitive performance and practical applications. FASS based on the ultralarge graphene nanosheets and the ultrathin boron nitride (BN) nanosheets are investigated. The nacre-like structures could efficiently integrate both merits of pseudocapacitive BN nanoflakes and conducting graphene, thereby exhibiting an excellent electrochemical performance in FASS. After 5000 charge-discharge cycles, the highest areal specific capacitance of FASS reaches 325.4 mF/cm2, with a high capacity retention rate of about 86.2% and a high energy density of 22.8 W·h/kg (1 W·h=3.6 kJ) at a power density of 85.7 W/kg.

An informationtized, digitalized, and intelligent emergency response mode is currently required in China to address the weaknesses and low efficiency in public health emergency management in the aspects of quick response mechanism, multi-department collaboration, and information interaction; this new mode can promote the response capabilities of China’s public security sector. A descriptive research method is adopted to analyze the status quo of public health emergency response systems and intelligent emergency response development in other countries, and summarize the requirements, current status, and main problems of health emergency management in China. The development goals, major research tasks, and technological approaches are further proposed. To develop a preventative public health emergency response network in China, we suggest that a major national biological monitoring and early-warning project should be established for health emergency response, relevant laws and regulations promulgated and revised, data integration and sustainable development of the emergency management mechanism maintained, an intelligent health emergency response industry encouraged, and professionals for medical care and preventative medicine integrated.

Aimed at the problem of group data anomaly detection with no data labels, a k-nearest neighbor (kNN) algorithm is proposed to detect group data anomalies in the unsupervised mode. In order to reduce false negatives and false positives caused by the mutual interference between abnormal and normal values, a reverse k-nearest neighbor (RkNN) method is proposed to filter the abnormal group data in reverse. First, the RkNN algorithm uses statistical distance as the similarity measure between different groups of data. Then, the anomaly scores of each group and the initial abnormality are obtained by using the kNN algorithm. Finally, the initial abnormality is filtered by using the RkNN method. The experiment results show that the algorithm proposed can not only effectively reduce the false negatives and false positives, but also has a high anomaly detection rate and good stability.

The ever-increasing demand for new businesses and the continuous development of the Internet economy have increasingly demanded network communications and service capabilities, and the infrastructure and the deriving technology system of the existing network still face a series of major challenges. New network architectures and key technologies have become the core of a new round of technological revolution and industrial upgrading in the world. Therefore, studying the strategic conception and development paths of new network technology innovation becomes an urgent need for China. In this article, we analyze the challenges faced by the current network technology, discuss the development status of new network fields in China and abroad, and summarize the development trend of new network technologies. Subsequently, we summarize the gaps and development goals of China in the new network field. Finally we propose the key technologies for the new network development in China, including new network architecture, network fulldimension definable technology, polymorphic addressing and routing technology, network intelligence technology, and endogenous security structure. From the aspect of technology roadmap, we suggest that an open, integrated, and secure new architecture should be established to build a new network environment that is intelligent, diversified, personalized, robust, and efficient. From the aspect of national policy, we suggest that support policies should be formulated regarding technology research and development, industrial ecology construction, and market access.

With Industry 4.0 being promoted globally, the technical status, challenges, and upgrading directions need to be clarified for China’s traditional fermented food industry; strategies and policy suggestions are required for the upgrading of the industry. Field research, questionnaire survey, and literature analysis reveal that China’s traditional fermented food industry is decentralized, intelligent manufacturing has not been properly applied to the industry, and a green manufacturing system has not yet been completed. Meanwhile, the industry faces many challenges such as weak capability in independent research and development of core technologies and equipment as well as lack of a clear upgrading path. Therefore, key technologies should be enhanced by unearthing the fermentation metabolism mechanism and developing independent complete equipment, and standardization shall be strengthened to promote end-toend integration. To establish a novel fermented food industry, China should strengthen top-level design and strategic guidance, promote breakthroughs in key theoretical and technological foundations, nurture a new model of shared manufacturing, encourage policies and support measures, and improve industry standards and ecosystems.

A self-developed strip-type high-temperature friction and wear test device was used to simulate the high-temperature friction process of uncoated 22MnB5 boron steel under actual hot stamping conditions. The mold was preheated to simulate the temperature increase of the die in the hot stamping process. The effects of mold temperature on the friction behavior and mechanism of uncoated boron steel were studied by using the friction coefficient test, surface wear morphology observation, and cross-section and matrix structure chart of hot stamping boron steel. The results show that the friction coefficient between the uncoated boron steel and the H13 steel is basically stable at 0.5 when the temperature of the mold is low, and the wear mechanism is mainly classified to abrasive wear and adhesive wear. Besides, when the mold temperature exceeds 100 ℃,the friction coefficient of the uncoated boron steel decreases from 0.474 to 0.414 with an increase of temperature from 150 ℃ to 200 ℃,inferring that the adhesive wear is weakened. The Vickers hardness of the boron steel matrix is approximately close to 430 from room temperature to 100 ℃. Moreover, with the temperature further rising to 150 ℃ and 200 ℃,the hardness decreases to 413.5 and 399.7 respectively, which indicates that the mold temperature has a significant effect on the mechanical behavior of formed parts.

With the development of "Internet + Education", higher education management has entered a new stage of intelligent and intelligent development. By giving full play to the advantages of modern information technology, actively restructuring the process of university education management, innovating the mode of university education management and the thinking of governance, the quality of university education management will be substantially improved, better realize the consistent integration of wisdom education and all-round education. This paper analyzes the background and advantages of the application of modern information technology in higher education management, and puts forward some suggestions on the reform of the mode.

With the development and application of the "double reduction" policy becoming more and more mature, and with the continuous advancement of Information Technology 2.0, we are making full use of information technology to promote the reform of kindergarten education and improve the quality of kindergarten running, it has become an important way to make full use of the advantages of information technology and adapt to the new trend of teaching reform. In order to improve the quality of kindergarten teaching, management and education, it is necessary to take the advantage of the application of Internet technology as the basis, and design a stable function and smooth interface kindergarten information management system, improving the quality of preschool education. Through the analysis of the background of the design of the kindergarten information management system under the internet background, this paper puts forward the system design ideas and implementation path.

The training and management of Students' learning is a dynamic and continuous optimization process, which is the comprehensive result of combining students' reality and growing environment. In the network environment, with the continuous advancement of intelligence education, the application of computer technology to give full play to the advantages of positive change and innovation in student learning training and management strategies, will be on the basis of improving the education ecology, to provide students with high-quality learning resources to achieve the fundamental optimization of student training process. This paper analyzes the influence of computer technology on the cultivation and management of Students' study under the network environment, and advances some corresponding suggestions.

In the work of traditional education management, the efficiency of education management is affected by the lack of comprehensive understanding of the connotation of information management, the weak foundation of information construction and the unsound management system. To this end, we should correctly understand the value of education management information construction, through the use of computer technology, accelerate the process of education management information construction. This paper analyzes the value of computer technology in the construction of educational management information system, and puts forward some practical strategies.

The construction of information-based leadership is of great practical significance in driving the development of higher education. By giving full play to the application advantages of modern information technology, an educational system covering all levels of higher education is constructed, we will comprehensively improve the level of informationization and intellectualization of higher education, and help to realize high-quality development of higher education. This paper analyzes the role of modern information technology in improving the leadership of information-based education in colleges and universities, and puts forward some relevant strategies to improve the leadership of information-based education in colleges and universities by using modern information technology.

MIL-101 (Fe) was modified by amino group and doped by Cu and Co elements by microwave hydrothermal method. The effect of SCR denitrification at low temperature was investigated with high concentration of NOx as adsorption object. The results show that when the flue gas temperature is 200 °C and the NOx concentration is up to 1640 mg/m3, the removal efficiency of NOx can reach 86% under the optimal conditions, which is 1.5 times higher than that before modification. In addition, the characterization results indicated that the specific surface area of the modified catalyst increased, the thermal stability was good at low temperature, the selective adsorption capacity of NO was enhanced, and the doping played a synergistic catalytic role. It can be used for flue gas denitration in various industries.

In view of the limitation of “hard assignment” of clusters in traditional clustering methods and the difficulty of meeting the requirements of clustering efficiency and clustering accuracy simultaneously in regard to massive data sets, a load classification method based on a Gaussian mixture model combining clustering and principal component analysis is proposed. The load data are fed into a Gaussian mixture model clustering algorithm after principal component analysis and dimensionality reduction to achieve classification of large-scale load datasets. The method in this paper is used to classify loads in the Canadian AMPds2 public dataset and is compared with K-Means, Gaussian mixed model clustering and other methods. The results show that the proposed method can not only achieve load classification more effectively and finely, but also save computational cost and improve computational efficiency.

Since the outbreak of COVID-19, all countries have taken certain measures to restrain the spread of COVID-19. It is a complex and practical issue to study the measures and effects of the epidemic prevention and control. The spread of the epidemic in different countries has certain characteristics, and the prevention and control models and effects in different countries are also different. In this paper, the key factors affecting the prevention effect of COVID-19 were analyzed by integrating multiple data and using interdisciplinary methods of mathematics, statistics and information management science on the basis of public management, and the system model of influencing factors of COVID-19 was constructed.

NDVI (Normalized Vegetation Index) is an important characteristic index to study regional vegetation change, which is greatly influenced by meteorological data. Based on the analysis of the trend change and correlation between NDVI and PWV (Precipitable Water Vapor), precipitation and temperature in four geographical regions of China, this paper constructs a model between NDVI and PWV, precipitation and temperature in each geographical region according to multiple regression, and predicts NDVI through meteorological data. The results show that:(1) NDVI and meteorological factors have the same changing trend, and the maximum value appears in every region from June to September, and the value of NDVI in southern region is relatively large. (2) The correlation between rainfall and NDVI is the highest in Qinghai-Tibet region, the correlation between temperature, PWV and NDVI is the highest in northern region, the correlation between NDVI and rainfall, temperature and PWV is the lowest in southern region. (3)According to the meteorological data ,NDVI prediction can be achieved better, and the prediction effect in southern region is the best and the model accuracy is the highest. (4) NDVI is negatively related to El Niño event, positively related to La Nina event, and the stronger El Niño and La Nina events are, the higher the correlation is.

Zhou Shan voltage source converter multi-terminal HVDC system (VSC-MTDC) enhances the receptiveness of wind power and improves the reliability of power supply. Electrical energy transfers flexibly between the islands in Zhou Shan. Restricted by the half-bridge sub module and disconnector, Zhou Shan VSC-MTDC cannot realies fast DC fault recovery. In order to solve this problem, damping fast recovery system and DC breaker are added. Meanwhile, the corresponding control strategy is proposed. It is verified by experimental results that the control strategy will realise fast DC fault recovery and improve the reliability of Zhou Shan VSC-MTDC dramatically.

In this paper, evolutionary algorithm is used to optimize the flicker function of band-limited Gaussian noise interference, which disturbs the convergence of adaptive algorithm based on LMS in GPS receiver, so that the average null depth of GPS receiver under equal power is lower, and better jamming effect is achieved. The simulation results show that the jamming algorithm in this paper has better jamming effect than the band-limited Gaussian noise jamming in different jamming quantity.

Global position systems (GPS) receiver based on least mean square (LMS) could resist the interference by null jamming direction. Considering that the existing band-limited Gaussian noise jamming signals were easily suppressed by LMS-based GPS receivers, a time domain random flicker band-limited Gaussian noise jamming algorithm was proposed to improve its performance. By disturbing the convergence of LMS, it could achieve the purpose of suppressing the LMS-based GPS. Simulation result shows that the proposed algorithm has an average performance gain of 2.7dB~4.6dB under different number of interferences compared with band-limited Gaussian noise.

In order to improve the anti-attack performance of the watermark to meet the requirements of copyright protection and content forensics. This paper proposes a digital watermarking hybrid algorithm based on color images. The specific process is to adopt the idea of multi-algorithm layered embedding, choose the algorithm based on discrete cosine transform (DCT) algorithm, discrete wavelet transform_singular value decomposition (DWT_SVD) algorithm, and hologram algorithm, these three algorithms with robust complementary functions, then embed the same watermark image into the color image R, G and B layers to complete the watermark embedding. Compared with the single-algorithm embedded watermark, the hybrid algorithm can achieve blind extraction, at the same time, the algorithm has better robustness and can resist more types and higher intensity attacks. In the process of digital image transmission, the integrity of the watermark information of the carried picture can be guaranteed to achieve copyright protection, content forensics and other purposes.

Heat exchanger is a universal process equipment, which is widely used in chemical industry, oil refining, thermal power and other industries. Shell-and-tube heat exchangers often fail prematurely due to flow-induced vibration. In this paper, aiming at the problem of severe vibration of shell-and-tube heat exchanger in an enterprise, the vibration acceleration sensors are used to measure the vibration of shell and tube side of heat exchanger. Through the analysis of the measurement results, it is found that when the flow rate on the shell side of the heat exchanger is greater than 50000 Nm3/h, the flow-induced vibration of the tube bundle occurs, and the vibration frequency is 57Hz, which is close to the natural frequency of the tube bundle. And the greater the flow rate on the shell side, the more intense the vibration. In order to reduce the vibration of heat exchanger, the damping measure of inserting baffles between tubes is adopted.

A time-frequency analytical method is presented to analyze physical mechanism of coaxial helicopter ground resonance. Eigenvalue calculation and numerical integration of disturbance equations of motions are used to obtain modal characters and time-domain response characters of coaxial helicopter ground resonance, and the interaction between rotors and body is revealed according to response of various DOFs. The analysis results show that regressive lag mode with upper rotor character is the most instability mode. In dynamic instability region, coaxial helicopter ground resonance is mainly due to energy transferred between periodic lag motion of upper rotor and body roll rotation. For this instability mode, energy transferred between periodic lag motion of lower rotor and body roll rotation is also existed, and it can enhance ground resonance instability of coaxial helicopter.

Wood presentation of modern wood building facades relating to the expression of the essential characteristics of architecture, utilization efficiency of wood and acceptance of architectural image,etc. However, relevant studies are obviously insufficient. This paper makes a statistical analysis of outstanding wood structure space cases which be selected, tries to reveal the expression rule of major timber application variables of wood coverage, materials collocation, wood form and wood color under the limitation of the main influencing factors of building function, building form and building scale.The purpose of this study is to explore the wood presentation rule of modern wood building Facades under the influence of building factors.

In order to reveal the fluctuation effect of equilibrium moisture content of low subgrade in hot and humid climatic regions, the effect of temperature on the fluctuation of the equilibrium moisture content of subgrade was analysed. Taking the typical climate and the subgrade soil in Fujian province as an example, three technological methods - theoretical analysis, numerical simulation and indoor simulation experiment - were adopted in the investigation of the fluctuation effect of equilibrium moisture content of subgrade. The results show that, computing results from the formula of the equilibrium moisture content of subgrade, the numerical simulation results are closer to each other in consideration of the temperature effect. The test results can not reflect the relationship between the equilibrium moisture content and the height of embankment. The maximum fluctuation range of the equilibrium moisture content of the cement concrete pavement is less than 2 percent in Fujian area, and this phenomenon presents the effect of the moist-hot climate on the equilibrium moisture content. Equilibrium moisture content presents a declining trend with the increment of the temperature and the compactness. So, if matric potential considering temperature indirectly reflects the influence of thermal potential, then the equilibrium moisture content of low subgrade under high groundwater level can be estimated approximately. The fluctuation range of equilibrium moisture content in different layers of subgrade can be reduced effectively with the increment of the roadbed compaction degree.

In this paper, we consider the Cauchy problem of non-stationary motion of heatconducting incompressible viscous fluids in ℝ3. About the heat-conducting incompressible viscous fluids, there are many mathematical researchers study the variants systems when the viscosity and heat-conductivity coefficient are positive. For the heat-conductive system, it is difficulty to get the better regularity due to the gradient of velocity of fluid own the higher order term. It is hard to control it. In order to get its global solutions, we must obtain the a priori estimates at first, then using fixed point theorem, it need the mapping is contracted. We can get a local solution, then applying the criteria extension. We can extend the local solution to the global solutions. For the two dimensional case, the Gagliardo-Nirenberg interpolation inequality makes use of better than the three dimensional situation. Thus, our problem will become more difficulty to handle. In this paper, we assume the coefficient of viscosity is a constant and the coefficient of heat-conductivity satisfying some suitable conditions. We show that the Cauchy problem has a global-in-time strong solution (u,θ) on ℝ3 ×(0, ∞).

Concerning the traditional way of micro-thrust measurement cannot get the transient thrust value with high precision and the measuring process of piezoelectric sensors is sensitive to the electromagnetic interference, this paper builds one new measurement method basing on the acoustic elasticity theory. The acoustoelastic element is the core of the whole system as it can transform the thrust changes into the variation of acoustic time. Thus adopting a timer to record such variation so that the thrust changes in real-time could be obtained, which is helpful for studying the mechanism of micro thrusters. This method built in this paper is not only non-contact and non-destructive but also easy to operate with simple structure and high precision.

With the development of aerospace technology, the flight control system is getting more and more important for a UAV (Unmanned Aerial Vehicle) flying safely and efficiently. For collecting the experimental data without delay, this paper briefly reviews the design of the communication scheme, and provides the implemented results. Through using the controller LPC1768 to expand the serial port, and the Ethernet controller DP83848 to complete the communication by UDP protocol, it turns out that this method is able to reach the real-time requirements of the UAV semi-physical simulation.

Apparent discharge quantity is usually recognized as judgement standard for severity of partial discharge in the field of electrical equipment insulation diagnosis. In recent years, the ultra-high-frequency (UHF) method has been widely used due to its unique advantages on on-line monitoring and positioning, but the relationship between UHF partial discharge signals and discharge quantity is still a difficult problem of UHF method. In order to research relationship between UHF partial discharge signals and discharge quantity in GIS, a large number of experiments, based on four kinds of typical insulation defects in the GIS, are carried out. Degree of correlation, between parameters including UHF energy, quadratic integral, peak voltage, peak-to-peak value, wave area and discharge quantity, the square of discharge quantity, is studied based on coefficient of determination. The experimental results show there is linear relation between UHF signal energy and the square of discharge quantity with high related degree.

As a high-speed and reliable serial communication bus, the FlexRay bus has gradually become the mainstream of vehicle network systems. In order to verify the feasibility of the bus technology in aerospace applications, this paper designs a FlexRay communication node based on TI's high-performance microcontroller TMS570LS3137 for security systems. In the whole system, with the DSP of core, the FlexRay communication protocol is achieved by using the bus controller TJA1080 to carry out data transmission. This method is suitable for data transmission of pint and medium-sized UAV (unmanned air vehicles) flight control system with high integration and high transmission rate.

With the development of computer version, deep learning and artificial neural networks approaches like SPP-net, Faster-RCNN and YOLO are proposed. This paper compares them in terms of efficiency and effectiveness. By analyzing the network architecture, SPP-net is more complex than Faster-RCNN and YOLO. By analyzing the experiments, SPP-net and Faster-RCNN are more accurate than YOLO in static detection while opposite in real-time system. Therefore, in real-time pedestrian detection situation, YOLO can perform better. In static pedestrian detection situation, Faster-RCNN or SPP-net can perform better.

Recordings of extracellular spikes have been widely used in various fields ranging from basic neuroscientific research to clinical applications. However, in the extracellular recording system, how to accurately detect spikes from the recorded signal in real time is still a major challenging work. Although the existing algorithms for online spike detection have made great progress, there still remains much room for improvement in terms of accuracy. In this paper, we propose a new method for high accuracy and real time spike detection. Concretely, differential operator is firstly employed to accentuate spikes in the signal for its simplicity and strong capacity to detect significant changes. Then, by exploiting the structural features of spikes, the resolution parameter is introduced to improve the performance of differential operator. Finally, a simple and effective measure is utilized to further reduce the influence of background noise, which makes spike detection more accurate. The results of simulated and real data show that the proposed method is able to precisely detect spikes while maintaining low computational complexity.

Currently, pattern recognition technique is widely applied in human identity recognition while there are shortages remaining in most kinds of such techniques. In order to overcome these problems, a novel algorithm is proposed to apply in identity recognition course in new field-static gait recognition field. Two combined features are going for static gait recognition: the distance between each part of center pressure and overall foot and the side length of outline triangle of human foot. Then through the comparison of different classifier, the best course for recognition can be obtained.

Extreme learning machine (ELM) is a new novel learning algorithm for generalized single-hidden layer feedforward networks (SLFNs). Although it shows fast learning speed in many areas, there is still room for improvement in computational cost. To address this issue, this paper proposes an improved ELM (FRCFELM) which employs the full rank Cholesky factorization to compute output weights instead of traditional SVD. In addition, this paper proves in theory that the proposed FRCF-ELM has lower computational complexity. Experimental results over some benchmark applications indicate that the proposed FRCF-ELM learns faster than original ELM algorithm while preserving good generalization performance.

The process of rainfall and runoff in the watershed is nonlinear which strongly depends on precipitation, evaporation, infiltration and hydrodynamic characteristics of soil. Due to the random and complex nature of the natural state of runoff, the temporal and spatial variability of rainfall and runoff in the watershed is extremely complicated. In view of the ability of system dynamics to describe multivariate, high order, multi-loop, strong nonlinear and complex feedback relationships, and to analyze the feedback between variables, the water cycle dynamics model is established by using system dynamics method. According to the dynamic characteristics of hydrological process, the dynamic process of rainfall to runoff is analyzed, and the relationships between the variables in the model are characterized by specific differential equations. The case study in the Zhexi watershed shows that this model can accurately simulate the process of water cycle in the watershed which also performs well on hydrological forecasting. It has certain practical significance for expanding new idea on hydrological forecasting modeling.

The proposed channel estimation system is based on the collaboration with nearby users channel estimation information. Channel status condition is inaccurate while the estimating pilot sequence applied is undersized to avoid overloading the system throughput and bandwidth efficiency. In this study, we have tried to ascertain the indoor channel varying conditions by way of nearby users’ channel estimated statistics. The distance of the surrounding nearby users has very high correlation to the channel frequency response profile. We have examined the channel profile performance under the proposed nearby channel condition estimations in both line-of-sight (LOS) and non-line-of sight (NLOS) indoor environments statuses.

In view of the current social background of power system becoming more and more complicated, and the current research situation of related fields, this paper discusses the common methods of power system risk assessment, including the method of hierarchy analysis, Markov chain model, Monte Carlo method, fuzzy comprehensive evaluation and related research progress. The advantages and disadvantages of the four methods are enumerated respectively. It is considered that the power system should be evaluated synthetically in the practical application and the effective risk assessment method should be adopted rationally.

The paper studies a problem of optimal control synthesis for curing a large composite structure using open die moulding in an autoclave. The necessary control should eliminate early hard skin formation, emergence of resin-rich or resin-dry areas, insufficient consolidation, and uneven cure. This purpose is achieved through providing uniform distribution of degree of cure and temperature within the cured part volume. The used approach is illustrated on the example of the large CFRP aircraft panel manufactured by means of two-stage curing cycle. The forward problem combines the heat transfer and autocatalytic kinetic equations, which are linked by the specific heat capacity, thermal conductivity coefficient and by the exothermal heat source that depend on the prepreg’s degree of cure. The control synthesis problem is formulated as a multi-objective optimization problem where minimized objectives are deviations of temperature and degree of cure within a cured part, considering constraints imposed by thermal-kinetic properties of prepreg and manufacturing requirements. The Pareto-based optimization algorithm, which executes the mapping of a subset of design space to the objectives space by the cyclic calling the forward problem implemented as a finite element model, allows estimating the best achievable quality indicators of manufactured composite parts, finding satisfactory parameters of the control law, and decision-making considering all imposed constraints.

The use of machine vision to track the receiver aircraft’s receptacle is one of the key steps in automated aerial refueling. Traditional Meanshift tracking algorithm’s kernel bandwidth is fixed, when the target size changes, it will produce with the bias even with the loss of the situation. Aiming at this problem, this paper proposes a kernel bandwidth adaptive algorithm based on corner matching. First, use backward tracking method to amend the core window center. Then according to the Harris algorithm to detect the corner, use small-scale approach for the two points between frames to match and regression analysis, namely determine the update parameters of nuclear window width. Experiments show that the algorithm can track the target accurately when the size of tracking target change, and the kernel window width can be better suited to the target size.