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The quality governance level of an industry is a multi-index evaluation problem that must consider multiple dimensions and factors. This study is the first to construct a comprehensive quality governance evaluation model for the civil aircraft industry of China (CAIC). The index system for the quality governance evaluation of CAIC was established using a literature review, enterprise investigation, expert interviews, and questionnaire surveys. An Analytic Hierarchy Process (AHP) was employed to determine index weights. Based on the evaluation model, data from 53 aviation manufacturing enterprises were collected, and the quality governance level of the CAIC was empirically evaluated; thus, quantitative and qualitative evaluation results were obtained. This empirical study shows that the quality governance of the CAIC is currently at a "medium to low" level. Furthermore, critical factors and bottleneck indices restricting the quality governance level of the CAIC were identified. [ABSTRACT FROM AUTHOR]

The energy consumption of air conditioners (ACs) in buildings is particularly high during summer, thus placing high demands on indoor thermal comfort. However, previous studies have only focused on a single factor either AC energy consumption or indoor thermal comfort, and only a few comprehensive analyses have attempted to optimize the AC energy consumption and indoor thermal comfort in buildings during summer. In this study, the comprehensive evaluation model was introduced to quantitatively evaluate the performance of different ventilation and cooling systems. A total of 48 orthogonal tests were conducted to evaluate cooling efficiency under different working conditions. The degree of door and window opening/closing and the AC setpoint temperature were considered in the test, and the degree–power index was proposed as an evaluation metric. The effects of multiple working conditions on the energy consumption and thermal comfort of a single AC office were estimated using the Gray-Technique for Order Preference by Similarity to an Ideal Solution (GRA-TOPSIS) model. Results show that, AC energy consumption is positively correlated with the degree of door and window opening/closing, especially at an AC setpoint temperature of 28 ℃. The increase in energy consumption is especially significant, thereby highlighting the importance of window and door management in controlling the energy consumption of buildings at high summer temperatures. Meanwhile, reducing the AC setpoint temperature improved the comfort of the indoor environment. Opening one window at an AC setpoint temperature of 26 ℃ provides the best balance between energy saving and thermal comfort. The experiments demonstrate that optimizing the degree of door and window opening/closing and setting rational AC temperatures not only ensure thermal comfort but also effectively reduce energy consumption in buildings. [ABSTRACT FROM AUTHOR]

As a coastal city with rapid urbanization and high-intensity human activities, Shenzhen, China has carried out a series of comprehensive treatments for water pollution control and ecological restoration in recent years. However, the restoration effect is mainly reflected in the improvement of water quality and riparian landscape, and there is still a big gap in reaching the river's ecological restoration goals. Therefore, it is necessary to make a full investigation and evaluation of river aquatic systems that focuses on the restoration of aquatic communities and ecosystem health. We surveyed forty-seven sampling sites in nine basins to investigate water quality and aquatic organisms (algae and macroinvertebrates) during the low-water period in 2019. Under the guidance of the EU Water Framework Directive (WFD), the urban river ecosystem health assessment system, with a total of twenty indicators from six criteria layers, was established. We addressed the bioremediation objectives in this system and aquatic organism indicators as high-weight characteristic indicators. The results showed that the degradation of the river ecosystem in Shenzhen is serious, which is mainly reflected in the simple structure of the aquatic biological community and the low biodiversity. Only one "healthy" sample site, accounting for 2% of the total sampling sites; six sites of "sub-health" level, accounting for 13%; twenty-four "poor" sample points, accounting for 51%; sixteen "extremely poor" sample points, accounting for 34%. From the perspective of spatial distribution, the river ecological status of Daya Bay Basin and Dapeng Bay Basin is good, which is at the level of "health" to "sub-health"; the Guanlan River Basin, Maozhou River Basin, Shenzhen River Basin, Shenzhen Bay Basin, Pingshan River Basin, and most of the Longgang River Basin are of "poor to extremely poor" grade; the Pearl Estuary basin is of "extremely poor" grade. This assessment system can be used as an effective tool to monitor the ecological health status, especially the enhancement of biodiversity and ecosystem function of rivers. Moreover, it could provide important decision-making guidance for river management affected by high-intensity human activities. [ABSTRACT FROM AUTHOR]

The quality governance level of an industry is a multi-index evaluation problem that must consider multiple dimensions and factors. This study is the first to construct a comprehensive quality governance evaluation model for the civil aircraft industry of China (CAIC). The index system for the quality governance evaluation of CAIC was established using a literature review, enterprise investigation, expert interviews, and questionnaire surveys. An Analytic Hierarchy Process (AHP) was employed to determine index weights. Based on the evaluation model, data from 53 aviation manufacturing enterprises were collected, and the quality governance level of the CAIC was empirically evaluated; thus, quantitative and qualitative evaluation results were obtained. This empirical study shows that the quality governance of the CAIC is currently at a “medium to low” level. Furthermore, critical factors and bottleneck indices restricting the quality governance level of the CAIC were identified.

[Objective] This paper reveals the heterogeneity of physical and chemical properties in soils under different land use patterns in the lower reaches of Fenhe River basin, and expounds its influence on the development of preferential flow. [Methods] Three land use types in the lower reaches of the Fenhe River basin were selected in the field staining and tracing experiments to evaluate the development degree of preferential flow and analyze the differences of soil properties between preferential flow areas and non-preferential flow areas and their effects on preferential flow characteristics. [Results] The development degrees of preferential flow indicated by the index of preferential flow under different land use types were grassland (1.18), cropland (1.12) and orchard (0.88), respectively. Soil properties other than pH were significantly affected by land use types, soil layers, and preferential flow areas (p＜0.05). The increase of soil organic matter, total porosity, capillary porosity and saturated hydraulic conductivity, and the decrease of bulk density contributed to the development of preferential flow. The multiple stepwise regression analysis showed that the organic matter and total porosity in preferential flow areas were the main factors affecting the dyeing area ratio, while the organic matter, bulk density and sand particles in non-preferential flow areas were the main factors affecting the non-dyeing area ratio. [Conclusion] Compared with farmland and orchard, the soil physical and chemical properties of grassland have higher heterogeneity in soil layers and preferential flow areas, which has a greater impact on the development of preferential flow. [ABSTRACT FROM AUTHOR]

Copyright of New Building Materials / Xinxing Jianzhu Cailiao is the property of New Building Materials Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Ion-adsorption rare earth mining areas are located in southern China's ecologically fragile red soil hills region. For a long time, under the influence of multiple factors such as low mining technology and indiscriminate mining, this area has experienced serious environmental problems. Therefore, it is crucial for the ecological management and restoration of mining areas to accurately conduct a quantitative evaluation of ecological restoration status. We used remote sensing and geographic information data to establish an ecosystem resilience evaluation index system consisting of five criteria (land stress, vegetation conditions, surface conditions, biodiversity, and air pollution) and 17 evaluation factors. The Lingbei rare earth mining area in Dingnan County in the red soil hill region was used as a case study since it is a representative ion adsorption rare earth mining area. The restoration status of the mining area was evaluated from 2000 to 2020. The results showed the following: (1) From 2000 to 2020, the ecological resilience level of the mining area was 0.695, 0.685, 0.664, 0.651, and 0.657, exhibiting a decrease followed by an increase. (2) Spatially, the ecological resilience was low at the mine site and increased with increasing distance, indicating that rare earth mining adversely affected ecological resilience in the mining area. (3) The regional ecological resilience has improved over time due to the implementation of green development policies. However, the rate of improvement is slow and ecological restoration of mining areas will remain an ongoing challenge in the future. This study can provide a scientific basis and practical reference for the ecological protection and restoration of mining areas. [ABSTRACT FROM AUTHOR]

In western high altitude areas, strong ultraviolet radiation and high frequency freeze-thaw cycles and their coupling effects are the direct causes of asphalt concrete bridge pavement cracks. The purpose of this paper is to analyze the attenuation laws of cracking resistance of asphalt mixture under high altitude environment with multiple indices, and to propose a new comprehensive index. Firstly, laboratory tests were designed to simulate the aging effects of high altitude environment on asphalt mixture. Secondly, semi-circular bending (SCB) tests were used to investigate the performance attenuation of asphalt mixture under different coupling schemes. Finally, the monotonic relationship between each anti-cracking evaluation index and independent variables was explained by statistical analysis, and the cracking resistance index in high altitude region (HAR-CRI) was proposed. The results showed that the reduction of cracking resistance of asphalt mixture per unit of freeze-thaw cycle is 4.6 times higher than that of ultraviolet radiation, due to the surface property of ultraviolet aging; the maximum damage deepening values of G f , R C , BCI, FEI, FI and CRI can reach 5.6 %, 7.6 %, 5.0 %, 4.3 %, 3.6 % and 2.0 % respectively, indicating that mutually deepening environmental factors had the greatest reduction in R C. According to correlation and difference analysis: FEI, R C and BCI were recommended to study the effects of temperature, freeze-thaw cycles frequency and ultraviolet radiation duration on cracking resistance of asphalt mixture respectively; ultraviolet radiation duration only had significant effects on FI and CRI in the three-factor interaction. Based on the principal component analysis, a comprehensive index (HAR-CRI) covering more than 98 % of multiple-index information was proposed. It can effectively reflect the strength properties of materials, and can be used to predict and rank the cracking resistance of asphalt mixtures under different environmental conditions in high altitude areas. • FEI, R C and BCI were recommended to study the effects of temperature, freeze-thaw cycles frequency and ultraviolet radiation duration. • Mutually deepening environmental factors had the greatest reduction in R C. • A new SCB index (HAR-CRI) was established through statistical analysis. • HAR-CRI can predict and rank the cracking resistance of asphalt mixture. [ABSTRACT FROM AUTHOR]

The purpose of the paper is to evaluate the processes of welding aluminum alloys in terms of their applicability to the process of prefabrication of ship structures. The prefabrication process requires solving a number of problems related to the welding processes used (e.g. the problem of welding incompatibilities, deformations). Therefore, the key issue is to choose the right welding process, which is complex and difficult. It requires analysis of the process considering many points of view (e.g. technological, economic, security) in order to maximize the objectivity of the choice. Therefore, an attempt at a comprehensive view requires the formulation of a set of accurate evaluation criteria. The multi-indicator expert assessment presented in the article makes it possible to make such a choice. Currently used methods of welding aluminum alloys, both those from the group of conventional and innovative methods, were assessed. As a result of the analysis, the so-called technological hierarchy that allows to rank the assessed processes in terms of their suitability in the process of prefabrication of ship structures. [ABSTRACT FROM AUTHOR]

Copyright of Advances in New & Renewable Energy is the property of Editorial Office of Advances in New & Renewable Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The mine fire risk evaluation method has problems of single evaluation dimension, incomplete evaluation index and unreliable evaluation result. In order to solve the above problems, based on the analytic hierarchy process, a staged multi-index comprehensive evaluation method for fire risk of coal working face is put forward. In order to analyze the coal working face internal fire, the method selects spontaneous combustion tendency, spontaneous combustion period, million-ton ignition rate, coal seam thickness, coal seam dip angle, geological structure, coal seam gas grade, coal mine process, goaf treatment method, upper and lower traveling wind pressure difference of the coal working face, the effectiveness of fire prevention and extinguish measures, self-heating period stage and Graham index as evaluation indexes. The method calculates the evaluation index score by adopting an interpolation method and gives weight to each evaluation index. Then the fire risk scores of the three stages including incubation period, self-heating period and combustion period are obtained. When the risk score of the incubation period of the internal fire in the coal working face is more than 50 points, the score is taken as the final score of the internal fire risk of the coal working face. Otherwise, it will enter the risk evaluation of the self-heating period. When the risk score of the self-heating period of the internal fire in the coal working face is greater than 50 points, this score will be taken as the final score of the internal fire risk of the coal working face. Otherwise, it will enter the risk evaluation of the combustion period. When entering the risk evaluation of combustion period, the internal fire risk score of the coal working face is directly set as zero. Aiming at the external fire risk of the coal working face, this study relies on the fire online monitoring, risk graded management and control and hidden danger investigation mechanism. The study takes the following factors as the evaluation indexes to score the external fire risk of the coal working face. The factors include temperature, oxygen volume fraction, carbon monoxide volume fraction, overdue hidden danger without receiving orders, overdue hidden danger without rectification, unqualified hidden danger review, overdue risk control measures without feedback, overdue risk control measures without review, unqualified risk control measures review. The lowest risk score of internal and external fire in the coal working face is taken as the fire risk score of the coal working face. The higher the score, the lower the fire risk of coal working face.

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Device to device (D2D) data sharing has become a promising solution to offload cellular network traffic, but the privacy vulnerability and service instability of data sharing partners affect the quality of shared services. To solve this problem, a D2D data sharing partner selection mechanism based on degree of privacy degree and stability degree (named PSUS) was proposed. Firstly, the privacy information of the provider was abstracted and summarized, and the privacy measurement method was built according to the privacy preferences of the provider and the historical records of shared services, and the privacy degree of the provider in different shared services was obtained. Then, the data sharing process was designed based on privacy degree, and the provider cached data under the constraints of privacy preferences and participates in sharing services with low privacy to meet the provider's privacy requirements. Finally, on the basis of the provider who has satisfied the privacy requirements, a multi-index evaluation method was designed to evaluate the service stability of providers to select stable sharing partners. The feasibility of the proposed mechanism was demonstrated by analysis of performance.

Device to device (D2D) data sharing has become a promising solution to offload cellular network traffic,but the privacy vulnerability and service instability of data sharing partners affect the quality of shared services.To solve this problem,a D2D data sharing partner selection mechanism based on degree of privacy degree and stability degree (named PSUS) was proposed.Firstly,the privacy information of the provider was abstracted and summarized,and the privacy measurement method was built according to the privacy preferences of the provider and the historical records of shared services,and the privacy degree of the provider in different shared services was obtained.Then,the data sharing process was designed based on privacy degree,and the provider cached data under the constraints of privacy preferences and participates in sharing services with low privacy to meet the provider's privacy requirements.Finally,on the basis of the provider who has satisfied the privacy requirements,a multi-index evaluation method was designed to evaluate the service stability of providers to select stable sharing partners.The feasibility of the proposed mechanism was demonstrated by analysis of performance.

With development of grid-connected wind power, data-driven wind turbine power curve (WTPC) becomes vital for many valuable applications whereas it is hugely affected by the potential outliers in supervisory control and data acquisition (SCADA) system. In this paper, high-fidelity WTPC modeling and its application on condition monitoring are deeply studied. Firstly, through irregular space-division and nonlinear space-mapping, stepwise data cleaning procedure is proposed. On this basis, the cleaned data are used for high-fidelity modeling where optimized least square support vector machine (LSSVM) is chosen for deterministic WTPC modeling and conditional kernel density estimation (CKDE) is selected for uncertainty modeling after comparison where the models are updated via the sliding time window mechanism. Using the consistency of historical data-driven models in a certain future time window, a daily condition monitoring system, including daily multi-index system and improved fuzzy comprehensive evaluation method (FCEM), is established to monitor future wind turbine condition. Finally, measured data from a wind farm in north China are acquired for validation. The results show that the outliers are effectively cleaned for high-fidelity WTPC modeling. The daily condition monitoring system including daily raw data preprocessing, multi-index system and FCEM algorithm can provide efficient daily rating score. • A versatile way for outlier identification in two-dimensional space is proposed. • Periodically updated deterministic and uncertainty WTPC modeling are presented. • A daily multi-index system is provided to capture different features of WTPC. • Daily comprehensive rating system of wind turbine power generation is realized. [ABSTRACT FROM AUTHOR]

Cloud–edge-device collaborative computation offloading can provide flexible and real-time data processing services for massive resource-constrained devices in power internet of things (PIoT). However, the computation offloading optimization in PIoT still faces several challenges such as high computation offloading delay caused by uncertain information, coupling between task offloading and computation resource allocation, and degraded optimization performance due to the lack of multi-index consideration. To address the above challenges, we formulate a joint optimization problem of task offloading and computation resource allocation to minimize the average computation offloading delay. Specifically, a multi-index evaluation learning-based two-stage computation offloading (MINCO) algorithm is proposed to decouple the joint optimization problem into two-stage subproblems and solve them with evaluation and learning of multiple indexes including data flow characteristic, service priority, empirical average computation offloading delay, and empirical arm selection times. Simulation results show that compared with the baseline 1 and baseline 2 algorithms, MINCO improves the average computation offloading delay by 14.67% and 30.71%. Moreover, MINCO can evaluate different service priorities and data flow characteristics to meet different requirements of computation offloading delay. [ABSTRACT FROM AUTHOR]

As the tunnel excavation and resource exploitation go deeper into the Earth, increasing number of rockburst occur all over the world. However, the understanding of rockburst prediction and rockburst proneness evaluation is still at its infancy. In this paper, to accurately and efficiently predict rockburst proneness, a multi-index evaluation method for rockburst proneness of deep underground rock openings is established, verified and applied. The multi-index evaluation method is put forward based on attribute recognition model and combined weighting method. Eight discriminate indexes are taken into account, i.e., in-situ stress, rock brittleness, elastic deformation energy, maximum storage elastic strain energy, rock integrity, groundwater condition, section design size and site construction status. Through analyzing a variety of practical engineering cases, the weight values of each index are evaluated by combined method of analytic hierarchy process and random forest algorithm. It is found that the groundwater condition, in-situ stress, rock integrity and elastic deformation energy are the most important evaluation indexes. The attribute recognition model of rockburst proneness is established with weight evaluation and the attribute measure function of each index, where the attribute measure function is developed by analyzing the rockburst proneness of each index and setting up the standards for risk classes. The accuracy and applicability of the proposed multi-index evaluation method are verified through analyzing rockburst cases of twenty engineering projects. It is then applied to the rockburst hazard evaluation of the Caoguoshan Tunnel. Results showed that the predictions for rockburst proneness are consistent with the actual rockburst occurrence. The findings in this paper could facilitate evaluating of rockburst proneness for deep underground rock opening and be of great significance for rockburst risk prediction. [ABSTRACT FROM AUTHOR]

The evaluation of node importance has great significance to complex network, so it is important to seek and protect important nodes to ensure the security and stability of the entire network. At present, most evaluation algorithms of node importance adopt the single-index methods, which are incomplete and limited, and cannot fully reflect the complex situation of network. In this paper, after synthesizing multi-index factors of node importance, including eigenvector centrality, betweenness centrality, closeness centrality, degree centrality, mutual-information, etc., the authors are proposing a new multi-index evaluation algorithm of identifying important nodes in complex networks based on linear discriminant analysis (LDA). In order to verify the validity of this algorithm, a series of simulation experiments have been done. Through comprehensive analysis, the simulation results show that the new algorithm is more rational, effective, integral and accurate. [ABSTRACT FROM AUTHOR]

Seismic performance assessment of water distribution systems (WDSs) based on hydraulic simulation is essential for resilience evaluation of WDSs under earthquake disasters. The assessment is mainly to determine how the water supply will be affected due to pipe breaks caused by the earthquake, with the water supply loss estimated based on the loss of supply to nodes. Existing research works usually use the average or overall performance metric of all user nodes as the system performance indicator without considering user nodes' individual performance and criticality. This paper proposes a framework to evaluate the importance of user nodes considering post-earthquake rescue service and the seismic performance of individual user nodes in the WDS, which supports the pipeline renovation plan to improve the performance of critical user nodes. The importance of user nodes is evaluated by a multi-index model, including the indices for daily service, post-earthquake rescue service, and network topology influence of user nodes. These indices evaluate the importance of user nodes in terms of their roles for daily water service, emergent rescue service, and water transmission to other nodes, respectively. Fragility model of pipelines evaluates the earthquake-induced damages of the WDS, and the seismic performance assessment of the WDS system is performed by the hydraulic model of the WDS with pipeline damages. The proposed framework is implemented in an actual WDS; the results show that the importance classification to user nodes by multi-index approach can identify the critical user nodes for post-earthquake rescue service, which traditional methods may ignore. The importance classification and seismic performance of individual user nodes make it feasible to check the seismic performance of critical user nodes and formulate a targeted pipeline renovation plan to focus limited resources on critical user nodes. [ABSTRACT FROM AUTHOR]

In China, relevant standards about building energy efficiency and green buildings have resulted in corresponding requirements for the envelope thermal performance. However, improvement of the thermal performance of the envelope is accompanied by an increase of the environmental impact and cost. This study quantitatively analyzed the thermal performance, environmental impact, and cost of the green building envelope in cold areas and established a common practice database, as well as a multi-index evaluation model. The results show that the best thermal performance improvements are 40% in residential buildings and 30% in public buildings, respectively, based on the relevant standards. The exterior walls and windows have the greatest impact on building heat consumption. There is no significant correlation between the heat consumption and the comprehensive heat transfer coefficient of 10 green buildings. Therefore, the comprehensive heat loss coefficient is corrected. The verification results show that all errors except project 10 are within 15%. Additionally, the projects with balanced thermal performance improvement of exterior walls and windows showed a better performance. Finally, the best combination of residential building envelopes in the cold area was selected, using the evaluation model and quantitative database to calculate the comprehensive score. [ABSTRACT FROM AUTHOR]

The floods have undermined the sustainable construction of cities because of their sudden and destruction. To reduce the losses caused by floods, it is necessary to make a reasonable evaluation for historical floods and provide scientific guidance for future precaution. Previous research mainly used subjective/objective weights or barely made static analysis without considering the uncertainty and ambiguity of floods. Therefore, this study proposed a variable fuzzy recognition model, based on combined weights, to evaluate floods, including the determination of index weights and the choice of evaluation model. To make the index weights reflect both subjective experience and objective data, the combined weights were proposed and calculated based on the principle of minimum identification information. Then, the relative membership degree matrix and evaluation results can be worked out by the variable fuzzy recognition model. Conclusions indicated that the combined weights were more convincing than simply subjective or objective weights. Moreover, the variable fuzzy recognition model, by changing model parameters, got stable evaluation results of the sample data. Therefore, the model can improve the credibility of evaluation and the conclusions can provide reasonable suggestions for management departments., Competing Interests: The authors declare that they have no competing interests.

To determine the process parameters of optimal water-extraction and ethanol precipitation method for Xuanbi'antong (XBF) extract, which is a clinically experience formula for coronary disease. Orthogonal test L9(34) was conducted for the study of XBF water-extraction and ethanol precipitation process. Extractum, salvianolic acid B, rhizoma coptidis alkaloid, paeoniflorin, puerarin, ginsenoside Rb₁, ginsenosides and echinacoside were selected as marker components and multi-index comprehensive weighted score was used to select and verify optimal water-extraction and ethanol precipitation process. The optimal extraction process was as follows： XBF was added with 10 times distilled water, decocted for half an hour for 3 times. The best ethanol-precipitation process was established where the ethanol was added up to 70% and precipitated for 24 hours in 1.12 extract density (20 ℃). The optimized water-extraction and ethanol precipitation method is stable and reliable, and can provide reference for further development and utilization of the formula., Competing Interests: The authors of this article and the planning committee members and staff have no relevant financial relationships with commercial interests to disclose., (Copyright© by the Chinese Pharmaceutical Association.)