Domination on graphs is an important part in Graph Theory. According to different practical application backgrounds, many kinds of domination are presented. Italian domination is a new kind of domination on graphs. To determine the Italian domination number of a graph is a non-deterministic polynomial problem (i.e. NP-hard problem) . In this research, the decomposition and combination chain method in extenics is used to prove that the lower bound of the Italian domination number of a graph is equal to the upper bound, so that the Italian domination number can be determined. The method has good portability and can be used to determine different domination numbers of various graphs.

In this paper, a circumvention design method which taking patent group as target, function requirement as the basis for circumvention and the extension theory as the theoretical tool was proposed. Firstly, online product reviews were used as requirement acquisition resources, which were transformed into several functional requirements by using natural language processing technology and extension primitive model. Secondly, the target patent group was researched by the keywords from the online reviews and IPC classification code, then the patent group function model was built by analyzing each patent text. Thirdly, the obtained function requirements were matched with the patent group function model to confirm the contents in patent group function model to be circumvented. Fourthly, the function requirements were guided by the extension analysis as the path for circumvention analysis, and the extension transformation was used to express the circumvention solution operation, then the new scheme was determined whether exists the technical features of infringement. Finally, a medicine storage box patent group was taken as case study to confirm the feasibility of the above process of patent group circumvention design. Taking functional requirements as the basis for circumvention can help reduce the influence of subjective judgment in confirming the content to be circumvented in the process of patent group circumvention, and at the same time ensure that the subsequent circumvention solution is carried out in the direction of satisfying users’ function requirements.

Aiming at the problems of small defect targets and complex backgrounds, which leads to low accuracy in insulator burst defect detection, an improved detection algorithm YOLOv4-MP based on YOLOv4 is proposed. First, the Shuffle Attention module is included in the feature extraction network to limit the interference of complicated background, enabling the model to extract more effective feature information. Then, the spatial pyramid pooling is enhanced by the dilated pooling layer, which effectively increases the receptive field and improves the effect of feature fusion. Finally, the Mish function is utilized as the activation function of the path enhancement network to limit the loss of low-level information. The experimental results show that the mean average precision of YOLOv4-MP reaches 93.60%, which is 6.37% higher than that of the YOLOv4 algorithm. Compared with the commonly used detection algorithms, YOLOv4-MP has better detection performance and has high application value for the detection of insulator burst defects.

A new method is proposed for self-supervised monocular depth estimation. Although recent methods have been able to produce high-precision depth maps, previous work has ignored channel-wise information in the image. To solve this problem, Channel Attention is introduced and improvements made in two aspects of the network structure: (a) a Squeeze-and-Excitation (SE) block is injected into the corresponding networks to capture the channel relation in feature map; (b) a Channel Attention Dense Connection (CADC) block is applied to combine multi-scale features and recalibrate channel-wise feature. Experiments on the KITTI dataset show the effectiveness of the proposed approach, which outperforms quantitatively and qualitatively the state-of-the-art Self-Supervised Depth Estimation methods.

China has become the largest consumer of industrial robots in the world, but the gap of related technical talents is expanding year by year. The important reason is the high cost and dangerous operation of industrial robots, which leads to difficulties in teaching and programming of robots. To solve this problem, based on HTC Vive (a VR device jointly developed by HTC and VALVE), a virtual industrial robot teaching programming system is developed by combining virtual reality (VR) technology with robot teaching programming. First, the VR environment characteristics of the system is analyzed, and a three-dimensional UI (User Interface) designed for the main interface interaction of the system. Then the kinematic modeling of the robot is carried out to realize the teaching method of dragging the robot directly. Using lexical analysis, syntax analysis and sentence execution mechanism, the virtual interpreter is developed, and the program editing mode of inserting instructions quickly is realized. Finally, the system realizes the robot instruction programming function which can carry out complex trajectory motion. Experimental tests show that the system has good interactivity and can be used for virtual robot teaching and programming. The system is safe to operate, and can reduce the cost of robot teaching and programming, contribute to the training of robot related talents, provide solutions for robot simulation in industrial production, and help the development of China’s manufacturing industry.

In order to improve the clustering accuracy and applicability of spectral clustering, a spectral clustering algorithm based on Fréchet distance (called FSC) is proposed. Firstly a similarity matrix is constructed by Fréchet distance, then the reconstructed similarity matrix is applied to the spectral clustering. Using Fréchet distance to measure the similarity of data feature dimensions can extend the applicability of typical spectral clustering algorithms. FSC is not only suitable for data with clear low-dimensional manifold structure, but also for high-dimensional or sparse data, such as hyperspectral images. The experimental results on three hyperspectral images show that the FSC algorithm effectively improves the accuracy of hyperspectral images clustering.

In practical applications, speech separation models are often disturbed by unknown noise, resulting in serious degradation of generalization performance. To solve this problem, Single channel speech separation method based on separate SNR regression estimation and adaptive frequency modulation network is proposed. Firstly, the scale invariant SNR of test signal separation results is estimated by prediction network to calculate the cognitive uncertainty of the model; Then, an adaptive frequency modulation network is designed to adjust the spectrum of signals with high uncertainty to reduce the cognitive uncertainty of the model, so as to improve the generalization ability of the model in the face of unknown noise. The experimental results show that compared with the Conv-Tasnet, the proposed method improves the SI-SNR (Scale Invariant SNR) from 2.72 dB to 4.57 dB, with an increase of 67.94%, and has a great improvement in generalization ability. Compared with Conv-Tasnet with Soft-Mask, the SI-SNR is increased from 3.32 dB to 4.57 dB, with an increase of 37.65%, indicating that this method has better generalization ability than soft mask mechanism. It effectively alleviates the serious degradation of generalization ability of speech separation network in the face of unknown noise.

In this paper, considering a class of nonlinear systems with full state constraints and actuator faults, an adaptive neural network output feedback fault-tolerant control algorithm with prescribed performance is proposed. A state observer is constructed to solve the unmeasurable states problem. Unknown nonlinear functions in the systems are approximated by radial basis function neural networks (RBF NNs) . By introducing the nonlinear mapping, the systems with state constraints are transformed into novel systems without state constraints. Moreover, a novel performance function is utilized to guarantee that the tracking error converges within a preset time. Meanwhile, the convergence speed can be adjusted through the parameter design. Finally, it is proved that the control algorithm ensures that all signals in the closed-loop systems are semi-globally uniformly ultimately bounded. The effectiveness of the algorithm is verified by a numerical simulation.

The proposal and development of the Energy Internet makes it possible to convert different energy network. Therefore, by expanding the demand response of the power system to the gas network, a coordinated market and operation framework for power demand response resources is established to support the demand of gas networks cross grid. In the proposed framework, the gas turbine is used as the coupling point of the electricity-gas dual grid, and the grid demand response resources are used to replace part of the output of the coupling point gas unit, so that the gas turbine saves part of the amount of natural gas, which is equivalent to converting power into gas. A cost model for cross-grid support of power demand response resources has been established to obtain the “Cost-Equivalent Gas Volume” of these resources to participate in the gas market competition. At the same time, the bid-winning equivalent gas volume of this demand response resources in the gas market will also be allocated to the resource owners participating in the process in accordance with the principle of lowest cost. Finally, the feasibility of the proposed model and framework is verified through numerical analysis. The framework provides good suggestions for power grid demand response resources to support natural gas network operation.

The rapid development of wearable electronic devices has promoted the research of flexible supercapacitors. Conducting polymers have shown great application potential in flexible supercapacitors due to their high conductivity, fast and reversible redox reaction, and flexibility similar to traditional polymer materials. Pure conducting polymers electrodes exhibit limited electrochemical performance (short cycling life and low actual capacity), and the formation of composite materials with emerging two-dimensional materials can improve their electrochemical performance. The preparation and assembly strategies of two-dimensional materials (graphene, transition metal chalcogenides, and transition metal carbon/nitride) composites from one to three dimensions is discussed firstly, and then the latest progress in their application in flexible supercapacitors with different structures (fiber structure, sandwich structure and planar interdigital structure) is reviewed. Finally, the challenges and future development trend of conducting polymer matrix composites in flexible supercapacitors are presented.

An electrochemical model of proton-conducting solid oxide fuel cells(H-SOFCs) is built for investigating the electrochemical performance, Faraday efficiency and energy efficiency of co-generation of electric energy and ethylene in H-SOFCs. The simulation results show that ethylene production based on H-SOFCs needs external energy. Increasing the temperature is beneficial for improving the conversion rate of ethane and reducing the polarization loss of fuel cells. For the simulated H-SOFCs, the ohmic and activation over potentials are dominant, and the concentration over potential is almost negligible. The non-negligible electronic conductivity in the proton-conducting electrolyte layer leads to the internal short circuit of the fuel cells and the formation of leakage current. The leakage current density increases with the output voltage, resulting in the decrease of Faraday efficiency and energy efficiency.

The Sr₂GdSbO₆:Eu³⁺ red phosphor with double perovskite structure was successfully prepared by high temperature solid phase method and its XRD, photoluminescence spectrum and fluorescence decay lifetime were characterized. The XRD of the Sr₂Gd_0.8SbO₆:0.2Eu³⁺ phosphor is basically consistent with the peak position of the standard card, indicating that the doping of Eu³⁺did not change the crystal structure of the matrix. The crystal parameters after Rietveld refinement also verify the result. The photoemission spectrum shows that the sample has a wide excitation area centered at 340 nm in the ultraviolet region; under the excitation of a 340 nm light source, the strongest emission of the sample is an orange-red emission band with a center wavelength of 593 nm. Using Dexter theory to analyze the concentration quenching mechanism of the sample is the dipole-dipole interaction. The fluorescence decay life of Sr₂Gd_0.8SbO₆:0.2Eu³⁺ phosphors at room temperature is 4.202 ms, and the external quantum efficiency is 24.8%. When the temperature is raised to 150 ℃, the external quantum efficiency remains 68.8% of that at room temperature. The calculated color purity of Sr₂GdSbO₆:Eu³⁺ phosphor can reach 99.5%. Sr₂Gd_0.8SbO₆:0.2Eu³⁺ phosphor, blue phosphor, green phosphor and 365 nm UV chip package were made into LED devices which can emit bright white light. These results indicate that Sr₂GdSbO₆:Eu³⁺ phosphor is a potential red phosphor for white LED.

In order to clarify the effect of T622 hindered amines light stabilizer (T622) on the anti-ultraviolet aging performance of base asphalt, T622 decay-delayed modified asphalt was prepared. Based on the three major indicators of asphalt, the basic properties of asphalt after UV aging treatment were studied, the apparent viscosity was analyzed by Brookfield viscosity test, and the thermophysical properties and functional group composition of base asphalt and modified asphalt were evaluated by means of thermogravimetric and infrared combined technology. The test results show that the addition of T622 modifier can significantly reduce the influence of ultraviolet aging on the basic properties of the base asphalt, significantly increase the apparent viscosity of the asphalt, and effectively improve the anti-ultraviolet aging performance of the asphalt material. The maximum infrared absorption peak temperature, initial decomposition temperature and functional group index of the base asphalt increases significantly with the aging time, while the relevant indexes of T622 modified asphalt remains in a stable range, and the functional group index is smaller than that of the base asphalt, which verifies from the microscopic level the excellent anti-ultraviolet aging performance of T622 modified asphalt.

CiteSpace is used to compare and analyze the knowledge atlas of Chinese and foreign periodicals, taking the BIM technology included in CNKI and Web of Science as the research sample. The results show that the application of Building Information Modeling (BIM) technology in engineering cost has developed rapidly in recent years, and the research is divided into four stages: development stage, extension stage, transition stage and innovation stage. “Construction Engineering” and “Management” are the common research hot spots at home and abroad. The future trends abroad are “Sustainable Development” and “Periodic Evaluation”, while “Fine Management” and “Personnel Training” are the future research trends at home and abroad. Based on this, the representative BIM technology (Lu Ban software and Innovaya) at home and abroad is described in detail. The research results can be used for reference to understand the application of BIM technology in engineering cost.

The study of consumer involvement in products has become a hot issue, yet obtaining competitive intelligence from the structure of the product competitive market has been neglected. To gain a more comprehensive understanding of the competitive market structure of products, product consideration sets are constructed from an involvement theory perspective using online user behavior data as the object. Complex network clustering method is used to visualize the asymmetric competitive market of the product. The results show that the consideration set consisting of consumers' attention involvement of products is the most representative for mapping the product asymmetric competition market. The structure map of the product asymmetric competition market mapped by the complex network clustering method is concise and clear. This market structure map not only identifies the competitors with the focal product, but also maps the degree of asymmetric competition with the competitors of the focal product. In addition, it shows insights such as the popularity of different submarkets, the high level of product competition within the submarkets and the low level of product competition between the external ones. This study demonstrates that this research model is more interpretable than traditional models.

In order to explore the spatial optimization strategy of outdoor thermal comfort environment of university campus in hot summer and cold winter regions, a university in Shanghai was taken as the research object, and field measurement of meteorological parameters conducted under typical spatial morphology conditions of university campus. At the same time, combined with the thermal comfort questionnaire of college students, the physiological equivalent temperature (PET) of the subjects was calculated by using Rayman software. This study performed temperature and humidity movement measurement, time correction, and spatial interpolation of the data to obtain the temperature and humidity distribution of the entire campus, and then the correlation between the temperature and humidity of the campus and the characteristic parameters of the surface morphology were analyzed. The results showed that the “neutral” PET value of university students in summer was 30.60 ℃, and PET index was negatively correlated with air temperature and positively correlated with relative humidity, and air temperature was more correlated with PET index. The sky view factor and pervious surface fraction have a significant positive correlation with air temperature, and there is a significant negative correlation between aspect ratio, building surface fraction, height of roughness elements and air temperature. In the planning and design of campus building and landscape, the rise of air temperature can be alleviated by reasonably designing the surface morphological characteristics, with the goal of enhancing students' thermal comfort. This study can provide an optimized reference for the outdoor space planning of university campus in hot summer and cold winter regions, which is helpful to improve the thermal comfort environment of campus.

With the wide application of the digital technology in the fashion design, digital restoration has become an effective means of the traditional clothing restoration, but the restoration effect evaluation is still in the exploratory stage. Accordingly, taking the representative style of the Hakka cardigan as the research object, the three-dimensional digital restoration of the Hakka cardigan was realized by the digital technology, and the restoration effect evaluation was carried out based on the multi-level fuzzy comprehensive evaluation method. First of all, the 3D digital restoration of the Hakka cardigan was realized with the comprehensive application of clothing digital technologies. Secondly, the index system for evaluating the effect of the digital restoration of the Hakka cardigan was established by adopting the Analytic Hierarchy Process, and then the weight coefficient was calculated. Finally, the fuzzy comprehensive evaluation method was used to evaluate the effect of each index. The research results show that the application of clothing digital technology can quickly realize the 3D digital restoration of the Hakka cardigan, and the multi-level fuzzy comprehensive evaluation method can effectively realize the digital restoration effect evaluation of the Hakka cardigan. The research provides a new research idea for the digital restoration of the traditional clothing and its effect evaluation.