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There is a centralization of the core content in the text information of the new crown epidemic notification. This paper proposes a joint learning text information extraction method: TBR-NER (topic-based recognition named entity recognition) based on topic recognition and named entity recognition to predict the labeled risk areas and epidemic trajectory information in text information. Transfer learning and data augmentation are used to solve the problem of data scarcity caused by the initial local outbreak of the epidemic, and mutual understanding is achieved by topic self-labeling without introducing additional labeled data. Taking the epidemic cases in Hebei and Jilin provinces as examples, the reliability and effectiveness of the method are verified by five types of topic recognition and 15 types of entity information extraction. The experimental results show that, compared with the four existing NER methods, this method can achieve optimality faster through the mutual learning of each task at the early stage of training. The optimal accuracy in the independent test set can be improved by more than 20%, and the minimum loss value is significantly reduced. This also proves that the joint learning algorithm (TBR-NER) mentioned in this paper performs better in such tasks. The TBR-NER model has specific sociality and applicability and can help in epidemic prediction, prevention, and control. [ABSTRACT FROM AUTHOR]

In this paper, a multisensor data acquisition system based on FPGA is designed to provide an overview of the current development of the company based on the theoretical knowledge of enterprise development strategy. Through a comprehensive investigation of the company's internal environment, the advantages and disadvantages of the company at this stage are clarified, and the opportunities and threats to the company's development are analyzed in the context of the external macroenvironment and industry development. The coupling coordination degree from 2011 to 2025 was measured using the coupling coordination degree model based on the original data and the prediction results, and the results showed that from 2011 to 2025, the coupling coordination degree of Hebei Province showed a continuous growth and experienced the transition from low coordination, basic coordination, to medium coordination in the coupling coordination stage, aiming at the most innovative fields, mastering the most advanced technologies, cooperating with industry giants, innovating, and building digital ecology, creating, and forming core competitiveness based on core independent products and platform-based solutions, and further promoting transformation and upgrading and high-quality development. In this paper, the data acquisition system is tested by building an experimental platform. The main purpose is to test the stability and accuracy of each module of the data acquisition system. After each module test of the system meets the design requirements, the parallel mechanism attitude transformation test experiment is completed, including the moving platform moving test experiment and the moving platform rotation test experiment. The experimental results show that the designed data acquisition system has stable program and reliable function. [ABSTRACT FROM AUTHOR]

With the development of global economy, the evaluation of industrial clusters has become an important method to scientifically analyze the advantages and disadvantages of industrial development. The current research model uses the traditional evaluation method, which leads to the problem of unsatisfactory evaluation results and low effect. This paper proposes an evaluation model based on the BP neural network combined with the LM algorithm, which has the advantages of fast convergence speed and strong application ability. The comprehensive evaluation model of industrial clusters is put forward from the comprehensive application of the scale, benefit, and 27 related evaluation indexes of industrial clusters. This paper takes Beijing, Tianjin, and Hebei industrial clusters for BP-LM evaluation and analysis, which fully illustrates the advantages of this method. The evaluation results show that the evaluation target value and the average error of the overall parity have obvious advantages compared with those of other models, which provides application guidance for local economic development and policy formulation. [ABSTRACT FROM AUTHOR]

Recycling of construction waste has been a hot issue in road engineering research, and microscopic characteristics and composition of construction waste-recycled aggregate (RA) significantly influence their macroscopic service characteristics. In this paper, the composition, microstructure, and strength formation mechanism of natural aggregate (NA), recycled concrete aggregate (RCA), and recycled brick (RCB) were systematically studied by X-ray diffraction analysis (XRD), scanning electron microscopy (SEM), fractal dimension and porosity determination, unconfined compressive strength test, and indirect tensile test. The results showed that RA's microscopic morphological characteristics and chemical components were analyzed by combining XRD and SEM electron microscopy techniques. RA has prominent fractal features, and the smaller bulk density and more extensive crushing value index of RA correspond to its larger porosity as well as fractal dimension. The attributes of RA lead to the peak of 7 d unconfined compressive strength and 7 d splitting strength of the mix. The reasonable control of RA admixture benefits the improvement of mix strength. This study relies on engineering to carry out theoretical and experimental research, which provides essential support and guarantee for the application of construction waste in the field of highway transportation in Hebei Province. [ABSTRACT FROM AUTHOR]

The volatility of solar energy, geographic location, and weather factors continues to affect the stability of photovoltaic power generation, reliable and accurate photovoltaic power prediction methods not only effectively reduce the operating cost of the photovoltaic system but also provide reliable data support for the energy scheduling of the light storage microgrid, improve the stability of the photovoltaic system, and provide important help for the optimization operation of the photovoltaic system. Therefore, it is an important study to find reliable photovoltaic power prediction methods. In recent years, researchers have improved the accuracy of photovoltaic power generation forecasting by using deep learning models. Compared with the traditional neural network, the Transformer model can better learn the relationship between weather features and has good stability and applicability. Therefore, in this paper, the transformer model is used for predicting ultra-short-term photovoltaic power generation, and the photovoltaic power generation data and weather data in Hebei are selected. In the experiment, the prediction result of the transformer model was compared to the GRU and DNN models to show that the transformer model has better predictive ability and stability. Experimental results demonstrated that the proposed Transformer model outperforms the GRU model and DNN model by a difference of about 0.04 kW and 0.047 kW in the MSE value, and 22.0% and 29.1% of the MAPE error. In addition, the public DC competition dataset is selected for control experiments to demonstrate the general applicability of the transformer model for PV power prediction in different regions. [ABSTRACT FROM AUTHOR]

Based on the PSR conceptual evaluation model of urban green and low-carbon development competitiveness, this paper evaluates the green and low-carbon development competitiveness of 13 cities in Beijing-Tianjin-Hebei from 2010 to 2019 and reveals their spatial effects and obstacle factors combined with the spatial autocorrelation and obstacle model. The results show the following: (1) In terms of the overall situation, the evaluation index of urban green and low-carbon development competitiveness in the Beijing-Tianjin-Hebei region shows a fluctuating upward trend as a whole from 2010 to 2019. Among them, the comprehensive evaluation indexes of Beijing, Zhangjiakou, and Tianjin are very competitive, while Hengshui, Handan, and Xingtai are relatively weak. (2) In terms of spatial data analysis, the global and local Moran's I of Beijing-Tianjin-Hebei cities from 2010 to 2019 were positive and passed the 1% significant level test. This shows that the comprehensive evaluation index of urban green low-carbon development competitiveness of Beijing-Tianjin-Hebei cities has a positive spatial correlation, and the spatial agglomeration effect is significant. On the whole, it presents a spatial agglomeration pattern of "high in the north, partial jump, and low in the south". (3) In the aspect of obstacle factor analysis, the proportion of the tertiary industry output value in GDP, energy consumption of ten thousand yuan of GDP, the urban green technology innovation level, and industrial soot emission of ten thousand yuan of GDP are the main obstacle factors restricting the improvement of urban green low-carbon development competitiveness in Beijing-Tianjin-Hebei cities. [ABSTRACT FROM AUTHOR]

There are still some problems in China's ice and snow environmental sports industry, such as an unbalanced industrial structure and insufficient utilization of ecological resources. In order to achieve leap-forward development, the ice and snow sports industry needs to further optimize the allocation of input-output resources, enhance the overall technical capability, and improve the efficiency level of the industry. This study takes five cities of Heilongjiang, Jilin, Liaoning, Hebei, and Beijing as the research objects, constructs the input-output evaluation system of the ice-snow sports industry, measures the input-output-efficiency level of ice-snow environmental sports industry in China, and studies and analyzes the relationship between efficiency level and industrial input-output. Furthermore, this paper compares and analyzes the traditional total factor productivity and green total factor productivity of the ice and snow environmental sports industry and discusses the influencing mechanism of ecosystem efficiency of the ice-snow sports industry. The results show that the input/output ratio of different regions in 2018 was Heilongjiang (1.12) > Liaoning (1.09) > Beijing (1.08) > Hebei (1.06) > Jilin (0.81). The change in input and output level is the direct influencing factor leading to the change of efficiency, while efficiency is the core to promote the development of the ice and snow environmental sports industry. Comparing traditional and green total factor productivity, it can be found that the GameMaker Language (GML) index of green total factor productivity in Heilongjiang, Jilin, Liaoning, Hebei, and Beijing has increased by 10.50%, 9.59%, 12.22%, 11.34%, and 20.29%, respectively, in 2013. In most cases, the green total factor productivity is higher than the traditional total factor productivity, showing an environment-friendly development. The development of the ice and snow environmental sports industry, talents in the ice and snow tourism industry, urbanization level and promotion of sports cultural products in the ice and snow environment are the main external influencing factors, while the internal influencing factors are mainly reflected in the industrial structure, ownership structure, industrial relevance, industrial agglomeration degree, industrial layout, industrial scale, and differentiation of industrial product. [ABSTRACT FROM AUTHOR]

At present, many colleges attach more and more importance to the cultivation of scientific research ability of college students. However, there is no unified standard to effectively measure the cultivation effect. The current performance inference method cannot comprehensively evaluate the scientific research ability of college students. Few scholars have directly analyzed the college students' scientific research ability from the internal and external influencing factors. Therefore, this paper tries to design and implement a neural network analysis system for scientific research ability evaluation of college students. After surveying the status quo of scientific research ability evaluation of college students in northern China's Hebei Province, a hierarchical evaluation index system was constructed for college students' scientific research ability, referring to the existing evaluation index systems, and the weights were designed for the evaluation indices. Next, the backpropagation (BP) neural network was optimized by chaotic sine-cosine grasshopper optimization algorithm (CSCGOA) and used to establish a neural network analysis system for scientific research ability evaluation of college students. The proposed system was proved effective through experiments. The relevant results effectively enhance the scientific level and accuracy of the evaluation of college students' scientific research ability, improve the cultivation of college students, and provide a scientific basis for colleges to understand the scientific research ability of their students. [ABSTRACT FROM AUTHOR]

This article aims to improve the accuracy and predictability of rebound method in compressive strength evaluation of concrete members of the Yanchong Expressway, which is an important traffic guarantee project for the 2022 Winter Olympics Games in Zhangjiakou city, Hebei Province, China. For this purpose, concrete specimens were prepared by the mixing ratios of C35, C40, and C50. First of all, the paper investigated the effects of curing age, types, and dosage of mineral admixtures (fly ash and slag) on concrete rebound number and compressive strength. Then, the special testing strength curves of 7 d and 90 d curing age were proposed. The results showed that the average relative errors of the special testing strength curves were reduced by 35.99% and 20.26% respectively, compared with the national testing strength curve. Fly ash and slag were beneficial to the growth of concrete rebound numbers but cannot contribute to the growth of concrete compressive strength (except for fly ash single-mixed with 15% dosage). The present results can provide a significant reference for the compressive strength evaluation and later maintenance of concrete members of the Yanchong Expressway or other projects with tight construction period in this area. [ABSTRACT FROM AUTHOR]

Multiscale brings great benefits for people to observe objects or problems from different perspectives. Multiscale clustering has been widely studied in various disciplines. However, most of the research studies are only for the numerical dataset, which is a lack of research on the clustering of nominal dataset, especially the data are nonindependent and identically distributed (Non-IID). Aiming at the current research situation, this paper proposes a multiscale clustering framework based on Non-IID nominal data. Firstly, the benchmark-scale dataset is clustered based on coupled metric similarity measure. Secondly, it is proposed to transform the clustering results from benchmark scale to target scale that the two algorithms are named upscaling based on single chain and downscaling based on Lanczos kernel, respectively. Finally, experiments are performed using five public datasets and one real dataset of the Hebei province of China. The results showed that the method can provide us not only competitive performance but also reduce computational cost. [ABSTRACT FROM AUTHOR]

Rural ecotourism is of great significance to the construction of new countryside, including promoting rural social progress, adjusting agricultural industrial structure, and increasing farmers' income. Starting with the basic concepts of rural ecotourism and new rural construction, this study compares and analyzes the development background and main characteristics of rural ecotourism at home and abroad and evaluates the development of rural ecotourism based on the Internet. This study takes Shahe City in Hebei Province as an example to develop rural ecotourism in the new rural construction and analyzes its tourism development status combined with the Internet+. Combined with its development orientation and basic conditions, this study summarizes the main measures for the development of rural ecotourism in Shahe City, Hebei Province, in order to improve the effectiveness of new rural construction. The results showed that the income of Shahe tourism increased by 31.5%, and the income of outbound tourism increased by 8.9%. This shows that the new rural construction can promote the development of rural ecotourism, increase the passenger flow, and improve the per capita income. The new rural construction and rural ecotourism development complement each other. [ABSTRACT FROM AUTHOR]

The accurate and objective quantitative evaluation of hot spring landscape resources is helpful to understand the value of the resources, has great practical significance for their protection, exploitation, and utilization, and is also an important basis for the exploitation and planning of the hot spring resources. On the basis of summarizing and analyzing previous research works, this study expounded the research status and significance of the exploitation of spring landscape resources, elaborated the development, background, current status, and future challenges of the quantitative evaluation of landscape resources' exploitable value, introduced the methods and principles of analytic hierarchy process and fuzzy synthesis process, formulated the evaluation index scoring standards for the exploitable value of hot spring landscape resources, analyzed the grading standard of comprehensive evaluation value, conducted the process analysis of quantitative evaluation of the exploitable value of hot spring landscape resources, established the evaluation index system of the exploitable value of hot spring landscape resources, determined evaluation index weight coefficient, constructed a quantitative evaluation model of the exploitable value of hot spring landscape resources, and finally carried out a case application and its result analysis by taking Chicheng Hot Spring in Chicheng County, Hebei Province, northern China as an example. The study results show that the three categories of factor weights in the subobjective layer of comprehensive evaluation system of hot spring landscape resources are landscape resource quality, environmental conditions, and resource exploitation and construction conditions. The purpose of quantitative evaluation of hot spring landscape resources is to use mathematical methods to quantify the fuzzy attributes of landscape resources so that some vague evaluations become relatively accurate, thereby improving the objectivity and reliability of evaluation results. Therefore, the establishment of a tourism preference index based on the hot spring tourism market and the subjective will of tourists as the evaluation standard has played a role in market restrictions, combining the evaluation of hot spring tourism resources with the dynamics and trends of the hot spring tourism market, and establishing comprehensive evaluation system of hot spring landscape resources. Those results of this study are expected to provide a reference for further research on the quantitative evaluation model for exploitable value of hot spring landscape resources. [ABSTRACT FROM AUTHOR]

A forecast approach of water structure based on GM (1, 1) of the gray system is proposed. Based on economic and water information of Hebei Province from 2000 to 2018, the water use structure of Hebei's industrial sector form 2019 to 2030 is forecasted according to the composition data and gray system GM (1, 1) model. The forecasting results by the proposed approach shows that the water structure of the tertiary industry has changed from 62.8 : 10.3 : 26.9 in 2018 to 60.5 : 10.2 : 29.3 in 2030. The proportion of water used in the primary and secondary industries has decreased slightly, the proportion of water used in the tertiary industry has increased, and the proportion of water used in the tertiary industry has not changed significantly. [ABSTRACT FROM AUTHOR]

In order to quickly evaluate the quality of Tremella fuciformis, the volatile components of T. fuciformis from 4 provinces in China, including Hebei, Henan, Fujian, and Sichuan, were analyzed by electronic nose combined with gas chromatography-mass spectrometry (GC-MS), and the key aroma compounds were determined by relative odor activity value (ROAV). The results showed that the electronic nose combined with the principal component analysis method could distinguish the samples from four regions with good discrimination. At least 117 volatile components were detected in T. fuciformis by GC-MS and a total of 58, 59, 62, and 55 volatile components were identified from Hebei, Henan, Fujian, and Sichuan, respectively, of which there were 18 common components. The volatile components in T. fuciformis were mainly hydrocarbons, followed by aldehydes, acids, and esters, while acetic acid and hexanal were relatively rich in T. fuciformis. Based on the ROAV, 8 key components affecting the aroma of T. fuciformis strongly were found. Among them, hexanal, nonanal, and pentanal were the common components of T. fuciformis, while butyrolactone, 1-octen-3-ol, and 2-carene were the unique key aroma components of T. fuciformis in Hebei Province. Besides, octanal and butyrolactone were the special key components absent in the Sichuan and Henan samples, respectively. [ABSTRACT FROM AUTHOR]

Water resource is an important factor restricting social-economic development. Hebei Province is one of the regions suffering from severe water shortage in China. Based on the Water Resources Assessment and Planning model, population growth, economic growth, water-saving, and integrated scenarios were established. The water demand and supply in Hebei Province in 2025 and 2035 were forecasted in this study. The research results show that agriculture is the main unmet water demand sector. In the absence of large-scale population inflows, the local population growth has little impact on the changes in water supply-demand. Economic development is one of the main factors affecting water balance. The water-saving scenario has the greatest impact on water supply-demand. Compared to population and economic growth scenarios, the simulation results of water demand and unmet water demand were the smallest. Under an integrated scenario, the current situation of water shortage in Hebei has been greatly improved, but there is still a demand shortage of 44.12 × 10 8 m3 in 2030. It is necessary to take measures to improve the carrying capacity of water resources in various regions of Hebei Province and narrow the regional gap. This study provided a reference for the rational utilization of water resources. [ABSTRACT FROM AUTHOR]

Summary: Bridges play an important role in the highway transportation network. There is an increasing concern that highway bridges have been suffering from structural degradation and deficiency due to severe environment, overloading, initial structural defects, and other factors. Ensuring the safety of a large number of regional bridges at the network level becomes a major challenge. This study proposes an entire data‐driven condition assessment framework for network‐level bridges, including data integration, condition assessment, and maintenance management. The periodic bridge inspection reports in China could provide quite a few condition‐related information to reveal the time‐variant bridge condition deterioration and effect of maintenance behaviors. The proposed framework is applied to a real highway bridge network located in Hebei province, China. Inspection data are obtained from thousands of bridges over quite a few years. The established regional deterioration model could effectively predict the bridge future condition based on the extracted hidden features. The regional maintenance strategies are optimized to satisfy the economic and performance constraints, which allows bridge managers to select the most appropriate one for implementation. It is shown that the proposed data‐driven approach can provide a guideline to bridge managers to estimate the future condition and allocate the maintenance resources. [ABSTRACT FROM AUTHOR]