Reasonable Allocation Research Articles

A networking-economic model to enhance the cultural value in small towns

Purpose The paper aims to provide a decision-support model to ensure a proper use of the limited resources, financial and not, for the enhancement of the cultural heritage and comprehensive development of small towns from sustainable perspective.Design/methodology/approach The assessment model is set up using a multi-criteria method that combines elements of linear planning with a performance indicators system that may represent the complexity of the territory’s cultural identity as a result of existing cultural-historical assets.Findings The model reliability is tested in a case study in a Municipality in southern Italy. The case study’s findings highlight the advantages for the public/private operators, who can consciously choose which preservation and restoration projects to fund while taking into account the effects those decisions will have on the economic, social and environmental context of reference.Research limitations/implications Due to the suggested operational approach and the selection of variables for accounting economic, social and environmental impacts by the renewal project, the research findings may not be generalizable. Therefore, it is recommended that researchers look into the suggested theories in more detail.Practical implications The study offers implications for designing a user-friendly tool to help decision-making processes from a private–public viewpoint in a reasonable allocation of financial resources among investments for cultural property asset enhancement.Originality/value The suggested operational approach provides a reliable information apparatus to depict the decision-making process under small-town development in accordance with sustainability dimensions.

Dynamic multiobjective two-stage fuzzy stochastic strategy for optimal water allocation in inter-basin water division under changing environment: A case study of Hanjiang-to-Weihe water division in Shaanxi Province, China

Extensive environmental changes increase the complex uncertainty surrounding water allocation systems, and irrational water allocation further exacerbates competition among users, posing formidable challenges to achieving dynamic and sustainable water resource management in inter-basin water diversion (IBWD) projects. This study established a dynamic multi-objective water allocation framework to address environmental change, uncertainty of water systems, and coordination between water allocation and deficit risk. The proposed framework focuses on water allocation as a continuous, multi-period decision-making process and considers reasonable water allocation from the individual to the overall multidimensionality. The feasibility and practicality of the framework were verified by long-term water allocation planning of the Hanjiang-to-Weihe IBWD in Shaanxi Province, China. The framework integrates the Soil and Water Assessment Tool model, three classical scenarios of the Coupled Model Intercomparison Project Phase 6, and optimization models to realize future sustainable water allocation optimal planning. The study found that the framework enables sustainable water allocation management and provides decisions for decision-makers under different water deficit conditions. Global optimal water allocation and the maximization of system benefits were achieved using multi-objective dynamic modeling. The average satisfaction level exceeded 0.9, and the Gini coefficient was below 0.05, both of which have a synergistic effect, with the former enhancing satisfaction within each subarea, and the latter ensuring equity among the subareas. The proposed framework aims to manage water resources of IBWD sustainably and provide optimal water allocation schemes to decision-makers under changing environments, which will alleviate water scarcity and interregional competition to promote regional sustainable development.

Resource allocation and route planning under the collection price uncertainty for the biomass supply chain

The escalating severity of global warming has drawn worldwide attention to ecological problems. Nevertheless, with the introduction of environmental policies, biomass resources have been effectively developed as a renewable energy source. This paper investigates an advanced biomass supply chain design wherein biomass resources are initially converted into bio-oil through widely distributed fast pyrolysis facilities, and are subsequently transported to a centralised biorefinery for further refining into biofuels. This novel biomass supply chain addressed three key issues: (1) The number of fast pyrolysis facilities, (2) The allocation of resources, and (3) The routes of resources transport. In respect of these problems, a two-stage stochastic mixed integer programming model is established to minimise the total cost of the biomass supply chain considering the uncertainty collection price of fast pyrolysis facilities. A hybrid simulated annealing algorithm which incorporates the sample average approximation method is proposed to solve the stochastic model and is effectiveness for large-scale examples. Finally, a sensitivity analysis is performed using the proposed algorithm and the results show that the proposed stochastic model outperforms the deterministic model under uncertain collection price. The model allows optimising the biomass supply chain economic performances and minimise financial risk on investment by determining the fast pyrolysis facility locations, reasonable resource allocation and optimal transport routes under uncertain collection price.

Willingness of healthcare providers to perform population-based cancer screening: a cross-sectional study in primary healthcare institutions in Tianjin, China

ObjectiveTo evaluate the willingness of healthcare providers to perform population-based screening in primary healthcare institutions in China.MethodsHealthcare providers of 262 primary healthcare institutions in Tianjin were invited to fill out...

Study of distribution network loss allocation with high photovoltaic penetration ratio

With the rapid development of renewable energy, the penetration ratio of photovoltaic (PV) in the distribution network is getting higher and higher. The fair and reasonable allocation of high loss caused by high PV penetration in the distribution network is of great significance to the healthy development of distribution systems. In order to study the loss allocation in distribution networks with high PV penetration, based on the cooperative game theory, combined with the power flow algorithm, the power flow and loss of the 72-node active distribution network in agricultural and pastoral areas were analyzed. Three scenarios were included: no PV, low PV penetration, and high PV penetration. The allocated loss of the distribution network with high PV penetration and multiple distributed generators was computed. The results show that the loss allocation method, which takes into account the power as well as the network topology, is applicable to distribution networks with multiple distributed generators. In distribution networks with high PV penetration, distributed generators are the main cause of high loss. If the network contains the extreme reverse power flow concerned in this paper, the loss allocated to DGs accounts for more than 95% of the total network power loss.

Modeling and analysis method for carbon emission flow in integrated energy systems considering energy quality

AbstractWhile proposing dual carbon strategy goals, research on carbon reduction in integrated energy systems (IESs) has become a focus of attention. Traditional IES carbon emission flow is mostly based on energy flow, without considering the differences in energy quality. Exergy can be used as a reasonable measure of energy quality. Combining the theory of exergy flow and carbon emission flow, a modeling and analysis method for IES carbon emission flow considering energy quality is proposed. First, exergy flow models for electric and natural gas systems, equivalent exergy flow models for heat systems, and exergy hub models are introduced. Afterward, the exergy branch losses are allocated to the nodes at both ends. A networked modeling method for the carbon emission flow of energy stations is proposed. A unified matrix calculation model for IES carbon emission flow considering energy quality is established. On this basis, an IES carbon emission flow calculation method considering energy quality is proposed. Finally, this method is applied to the test IES, and the results show that the carbon emission flow calculation results reflect the distribution of carbon emissions borne by the effective energy supplied by the source and consumed by the load in the system, taking into account both the quantity and quality of energy. The reasonable allocation of new energy is conducive to synchronously improving the energy efficiency, exergy efficiency, and cleanliness of the system.

Artificial Intelligence and Scientific Research:Prospects and Risks———Synthesis of the session “Artificial Intelligence and Paradigm Change in Science and Technology Innovation” in Tianjin Forum 2023

In the sub-forum “Transformation of Artificial Intelligence and Paradigm in Science and Technology Innovation” of Tianjin Forum 2023, scholars from both China and abroad discussed the impact of artificial intelligence. With the deepening development of the new technological revolution and industrial transformation, new-generation artificial intelligence technology is continuously making breakthroughs in research and application. AI not only promotes the transformation of material productivity, but also gradually emerges as a critical engine for enhancing the knowledge productivity. Since the emergence of the concept of "AI for Science", it has become an obvious proposition generally accepted by the academic community for its tremendous enabling capabilities for knowledge production. Artificial intelligence technology continues to achieve breakthroughs and gain widespread infiltration into the scientific research field, introducing new elements and momentum into scientific research and significantly catalyzing the enhancement of scientific research efficiency and paradigm shifts. AI-driven scientific research has become a new frontier in the global application of artificial intelligence. However, as artificial intelligence triggers paradigm shifts in social science research, the issues of data security, ethics, and value alignment that it brings about need to draw attention from the social science community. Scholars participating in the forum generally concurred that, in regulating the enabling role of AI in scientific research, it is imperative to take into account the specificities of various disciplines and stages, and comprehensively reasonable rational risk allocation mechanisms, platform. support mechanisms, and collaborative participation frameworks to achieve prudent, agile, and full lifecycle regulation of AI for Science.

Modeling and simulation of fire evacuation considering guiding factors: a case study of Shenyang subway interchange station

In case of fire, effective evacuation guidance can reduce evacuees’ hesitation time and improve evacuation efficiency. In this paper, an improved model of fire evacuation (guided fire cellular automata, GF-CA) is provided. First, the parameters of the improved model are quantified and analyzed to determine the parameter calculation method and variation law. Second, a typical subway interchange station in Shenyang is used as an example for evacuation simulation. Then, a lightweight building information modeling (BIM) is constructed and applied to the example combining the evacuation simulation software of Pathfinder and virtual reality technology for personnel evacuation simulation. Three types of simulation scenarios are examined, including simulation without guiding factors, simulation with guiding factors based on the improved model, and simulation based on the virtual reality experiment with guiding factors. The results show that the evacuation efficiency is increased by 75.63% after effective guidelines through personnel diversion and reasonable exit allocation, noting that the path results of the model are highly similar to those of the virtual reality experiment, which has good validity and rationality. Meanwhile, we analyze the guiding scheme and propose that we should pay attention to the position of the sign and the configuration of the conductor, and flexibly use the composite scheme, which provides effective technical support for improving evacuation safety and evacuation efficiency.

Federated Learning Incentive Mechanism Setting in UAV-Assisted Space–Terrestrial Integration Networks

The UAV-assisted space–terrestrial integrated network provides extensive coverage and high flexibility in communication services. UAVs and ground terminals collaborate to train models and provide services. In order to protect data privacy, federated learning is widely used. However, the participation of UAVs and ground terminals is not gratuitous, and reasonable incentives for federated learning need to be set up to encourage their participation. To address the above issues, this paper proposes a federated reliable incentive mechanism based on hierarchical reinforcement learning. The mechanism allocates inter-round incentives at the upper level to ensure the maximisation of the server’s utility, and performs inter-client incentive allocation at the lower level to ensure the minimisation of each round’s latency. The reasonable incentive allocation enables the central server to achieve higher model training accuracy under the limited incentive budget, which reduces the cost of model training. At the same time, an attack detection mechanism is implemented to identify malicious clients participating in federated learning, preventing their involvement in aggregation and revoking their incentives. This better ensures the security of model training. Finally, we conducted experiments on Fmnist, and the results indicate that this method effectively improves the accuracy and security of model training.

Reducing the length of stay for patients stranded in the emergency department: A single-center prospective study of 18,631 patients in China.

The purpose of this study was to reduce the length of stay (LOS) for patients stranded in the emergency department (ED) of a Grade III A hospital in China, and to improve patient flow and increase bed capacity. We utilized a pre-/postintervention design and employed the Six Sigma methodology, which is based on the DMAIC cycle (define, measure, analyze, improve, and control), to evaluate and improve the existing process. Data from 18,631 patients who were stranded in the ED were collected and analyzed. The median LOS for stranded patients decreased from 17.21 (6.22, 27.36) hours to 13.45 (5.56, 25.85) hours (P < .05). Similarly, the median LOS for admitted patients decreased from 19.64 (7.77, 27.68) hours to 15.92 (6.19, 26.24) hours (P < .05). The median LOS for patients with an ED triage Level IV decreased from 16.15 (5.80, 26.62) hours to 12.59 (5.20, 24.97) hours (P < .05). In addition, the average hospitalization days of hospitalized patients decreased from 0.92 days to 0.82 days (P < .05). Furthermore, the bed utilization rate increased from 66.79% to 72.29% (P < .05). The number of bed turnovers in the ED resuscitation room increased from 20.30 to 21.96 (P < .05). We had effectively met our goal of minimizing ED patient LOS. Six Sigma method can effectively shorten patient LOS by measuring and analyzing the key factors affecting patient LOS, and by implementing measures such as strict implementation of emergency classification and triage system, establishment of multidisciplinary cooperative team, reasonable allocation of human resources, information management of bed resources, and improvement of performance appraisal scheme to improve and control the effectiveness of patient LOS.

Optimal allocation of soil and water resources in agriculture under the total regional evapotranspiration indicator: A case study in Guangping, China

There is a mismatch between crop water demand, the spatial and temporal distribution of natural rainfall, surface water sources, and arable land resources in the North China Plain. This has been compensated for by massive groundwater exploitation, and as a result, ground water levels have continuously declined and groundwater landing funnels have formed in some areas. Consequently, there is an urgent need for the rational allocation of soil and water resources. In this study, regional soil types and the corresponding crops in Guangping County, Hebei Province, China, alongside the regional annual average total water consumption were used to determine reasonable allocations for crop planting structures, with an aim of maximizing the water utilization efficiency and economic benefits while also achieving a regional groundwater dynamic equilibrium. Daily meteorological data from 1973 to 2021, including precipitation, temperature, sunshine hours, wind speed, and humidity, as well as crop data, including irrigation systems and crop growth status, were collected. Water consumption models for eight soil types and seven typical crops forming 56 calculation partitions were established to obtain annual average water consumption values for the different crops. The maximum economic benefit and water-use efficiency were then used as the objective functions and total water consumption as the control condition for the non-dominated sorted genetic algorithm-Ⅱ (NSGA-II), to optimize the allocation of soil and water resources in the region; the adjusted quantities for the different crops cultivated under different soil types in the study area were obtained. The areas growing sweet potato and vegetable-fruits were found to increase by 0.5255 km2 and 4.4452 km2, respectively, when compared to the pre-optimization period, whereas the areas with winter wheat-summer maize, millet, peanut, cotton, and summer maize decreased by 1.3481 km2, 0.1812 km2, 0.7316 km2, 2.0896 km2, and 0.62 km2, respectively. The economic benefit increased from 810.37 to 853.64 million yuan, while the water-use efficiency increased from 1.5426 kg/m3 to 1.5859 kg/m3. The results provide a basis for soil and water resource management in the region and a technical reference for similar areas to improve agricultural water-use efficiency and economic benefits.

Resource Scheduling in URLLC and eMBB Coexistence Based on Dynamic Selection Numerology

This paper focuses on the resource allocation problem of multiplexing two different service scenarios, enhanced mobile broadband (eMBB) and ultrareliable low latency (URLLC) in 5G New Radio, based on dynamic numerology structure, mini-time slot scheduling, and puncturing to achieve optimal resource allocation. To obtain the optimal channel resource allocation under URLLC user constraints, this paper establishes a relevant channel model divided into two convex optimization problems: (a) eMBB resource allocation and (b) URLLC scheduling. We also determine the numerology values at the beginning of each time slot with the help of deep reinforcement learning to achieve flexible resource scheduling. The proposed algorithm is verified in simulation software, and the simulation results show that the dynamic selection of numerologies proposed in this paper can better improve the data transmission rate of eMBB users and reduce the latency of URLLC services compared with the fixed numerology scheme for the same URLLC packet arrival, while the reasonable resource allocation ensures the reliability of URLLC and eMBB communication.

GIS-Based Ecological Restoration Planning for Densely Populated Areas of Hangjiahu River Network in the Context of the Internet of Things

Abstract In order to better protect the ecosystem of Hangjia Lake, repair ecological problems, and improve biodiversity, this article takes the ecosystem of Hangjia Lake area as the research object and proposes a geographic information system (GIS)-based ecological restoration planning method under the Internet of Things. The ArcGIS software was used to analyze the rainfall, soil pollution, water pollution, and land use in Hangjiahu area, and evaluate the current status of ecosystem. Moreover, the weight of the influencing factors of ecosystem was calculated. In addition, the ecological restoration was planned from the perspective of optimizing resources and reasonable allocation. Furthermore, Hangjiahu area was planned reasonably based on land suitability and vegetation spatial pattern. The potential and limitation of dense waterway net region of Hangjiahu were analyzed by the multi-factor evaluation method. Finally, the planning was carried out from the aspects of soil and water conservation, biodiversity, and vegetation selection. Experimental results show that the proposed method has good effect on soil and water conservation and many biological species, so it can realize the efficient restoration for the ecosystem in Hangjiahu area.

Research on dual robot collaboration method based on improved double ant colony algorithm

Purpose This study aims to propose an efficient dual-robot task collaboration strategy to address the issue of low work efficiency and inability to meet the production needs of a single robot during construction operations. Design/methodology/approach A hybrid task allocation method based on integer programming and auction algorithms, with the aim of achieving a balanced workload between two robots has been proposed. In addition, while ensuring reasonable workload allocation between the two robots, an improved dual ant colony algorithm was used to solve the dual traveling salesman problem, and the global path planning of the two robots was determined, resulting in an efficient and collision-free path for the dual robots to operate. Meanwhile, an improved fast Random tree rapidly-exploring random tree algorithm is introduced as a local obstacle avoidance strategy. Findings The proposed method combines randomization and iteration techniques to achieve an efficient task allocation strategy for two robots, ensuring the relative optimal global path of the two robots in cooperation and solving complex local obstacle avoidance problems. Originality/value This method is applied to the scene of steel bar tying in construction work, with the workload allocation and collaborative work between two robots as evaluation indicators. The experimental results show that this method can efficiently complete the steel bar banding operation, effectively reduce the interference between the two robots and minimize the interference of obstacles in the environment.

Productivity Decomposition of Chinese Energy Generation Enterprises: an Index Calculation Approach Embedded in the Data Envelopment Analysis Framework

To explore the development of China's energy power generation enterprises, undertake reasonable resource allocation and optimization, and promote sustainable development. We apply an index calculation approach within the data envelopment analysis framework, collecting data from 50 enterprises in 2007-2022, resulting in a total of 800 observations (16*50) for the in-depth analysis of productivity decomposition. The results highlight that during the study years, the sample enterprises experienced the following changes on average per year: an increase of 0.244% in efficiency change (effch), a decline of 0.293% in technical progress (techch), an increase of 0.119% in pure efficiency change (pech), an increase of 0.134% in scale efficiency change (sech), and a decline of 0.057% in total factor of productivity (tfpch). These findings suggest an ongoing improvement in overall efficiency, indicating that energy generators are achieving better results in terms of operations, resource utilization, and scale effects, but need to focus on research and adoption of new technologies while seeking opportunities to further enhance productivity.

Optimal scheduling of electric-hydrogen integrated charging station for new energy vehicles

In this paper, a novel model of electric-hydrogen integrated charging station (ICS) is proposed, which is composed of battery swapping station (BSS) and hydrogen station (HS). The BSS model, which mainly includes user adaptive response model, battery allocation and scheduling strategy, is established to realize the reasonable management and allocation of batteries. The HS model mainly includes hydrogen production module, hydrogen storage module, hydrogen charging module, fuel cell module and hydrogen scheduling strategy to optimize scheduling from hydrogen production to use. In addition, the BSS can provide energy for HS, and both BSS and HS can feed back the stored energy to the power system during peak load, which is beneficial to the stable operation of the power system. Simulation shows the rationality and correctness of the proposed optimization model. The proposed model and optimization strategy can improve the flexibility and economy of ICS, and help the power system to cut peak and fill valley.

Distribution of hepatitis C virus in eastern China from 2011 to 2020: a Bayesian spatiotemporal analysis.

This study aimed to evaluate the spatiotemporal distribution of patients with hepatitis C virus (HCV) and the factors influencing this distribution in Jiangsu Province, China, from 2011 to 2020. The incidence of reported HCV in Jiangsu Province from 2011 to 2020 was obtained from the Chinese Information System for Disease Control and Prevention (CISDCP). R and GeoDa software were used to visualize the spatiotemporal distribution and the spatial autocorrelation of HCV. A Bayesian spatiotemporal model was constructed to explore the spatiotemporal distribution of HCV in Jiangsu Province and to further analyze the factors related to HCV. A total of 31,778 HCV patients were registered in Jiangsu Province. The registered incidence rate of HCV increased from 2.60/100,000 people in 2011 to 4.96/100,000 people in 2020, an increase of 190.77%. Moran's I ranged from 0.099 to 0.354 (P < 0.05) from 2011 to 2019, indicating a positive spatial correlation overall. The relative risk (RR) of the urbanization rate, the most important factor affecting the spread of HCV in Jiangsu Province, was 1.254 (95% confidence interval: 1.141-1.376), while other factors had no significance. The reported HCV incidence rate integrally increased in the whole Jiangsu Province, whereas the spatial aggregation of HCV incidence was gradually weakening. Our study highlighted the importance of health education for the floating population and reasonable allocation of medical resources in the future health work.

Acoustic mechanisms and tonal noise control of contra-rotating ducted fan by rotating speed regulation

The contra-rotating ducted fan (CRDF) involves more tonal noise modes compared with rotor/stator and single-rotor ducted fans. According to the present experiment on small-scale CRDF the dominant tone is concentrated at the harmonics of blade passing frequencies of front-rotor and rear-rotor as the modes of (m,0) and (0,n), as well as the modes (m,m) respectively. To investigate the flow mechanisms and sound propagation characteristics of these three types of tonal noise, unsteady three-dimensional numerical simulation was implemented under different rotational speed matching for CRDF and isolated rotor. Steady load and thickness noise were systematically analyzed using Hanson model. And the generation mechanisms of wake interaction noise and their contribution ratios were analyzed utilizing the duct sound model.It was indicated that tonal noise at the mode of (m,0) (0,n) of CRDF is primarily determined by the blade thickness and steady load. Compared with the single-rotor, the contra-rotating rotors could improve the load allocation between the front and rear rotor, resulting in the forward noise reduction with the constant thrust. Increasing the rear rotor speed enhances the contribution of potential flow interaction noise from the front rotor. Subsequently the front rotor load and wake interference are weakened, leading to noise reduction of approximately 0.3 dB for the rear rotor. However, the potential flow disturbance is intensified which causes noise increase by approximately 3.5 dB on the front rotor. But, increasing the front rotor speed will strengthen both the potential flow interference intensity on the pressure surface of the front rotor blade and the wake disturbance intensity on the leading edge of the rear rotor blade. This generates approximately 3 dB and 3.5 dB noise level increases for the front and rear rotors, respectively. As a result, appropriately raising the rear rotor speed can achieve a reasonable load allocation, and balance the potential flow interaction and wake interaction to realize the whole noise reduction without thrust loss.

高质量发展背景下普惠性幼儿园面临的挑战及其发展策略

Under the background of high-quality development, the construction and development of inclusive kindergartens are particularly important. This is not only about educational equity, but also an important embodiment of social progress and population policy. Inclusive kindergartens aim to narrow the education gap between urban and rural areas and between regions and provide equal educational opportunities, especially for children from low- and middle-income families. The main challenges include the unbalanced distribution of resources between urban and rural areas, the structural imbalance of financial input, and the significant differences in the management system of parks. The key to solving these challenges lies in the fine allocation of resources, the establishment of early warning and cooperation mechanism between demand and supply, the optimization of fair and reasonable resource allocation mechanism, and the use of policy tools to build a sound incentive mechanism. In addition, it is essential to strengthen quality assessment and content development, and improve the level of education and childcare services.

Multi-objective cooperative optimization of reservoir scheduling and water resources allocation for inter-basin water transfer project based on multi-stage coupling model

The efficient coupling of a water allocation model with a reservoir operation model is key to maximizing the benefits of inter-basin water transfer (IBWT) projects. Most existing studies of IBWT operations and management do not account for matching water transfer and demand, and instead seek to optimize either the water allocation model or the reservoir scheduling model. In this paper, we propose a multi-stage joint optimization framework for reservoir scheduling and water allocation models that considers the key operation indicators of the project in the water source area and the multi-dimensional objectives in the receiving area. We derived a functional relationship that balances considerations regarding water, the economy, and ecology (WEE) in the receiving area and applied it to the water allocation model. The reservoir operation model was developed by considering the multiple benefits of water transfer and power generation in the water resource area. To reduce the complexity of the model and the tightness of its coupling, the model was divided into multiple stages of optimization and solved using the Multi-objective Evolutionary Algorithm Based on Decomposition (MOEA/D) algorithm. The results showed the allocation schemes of water resources influenced the competition between the economic and ecological benefits. Using the WEE model, a more reasonable water transfer and allocation method can be selected according to different development needs. As such, the water shortage rate of each user in the receiving area is kept below 8%, and there is significant improvement in all indicators compared with the conventional scheme. In addition, this model enables the reservoir group to achieve a power generation capacity of more than 5.64 kWh with the goal of meeting the water transfer demand, maintaining the reservoir empty rate at about 10%, and reducing the risk of water shortages. Our study can serve as a reference for effectively addressing the challenges associated with IBWT projects, and it can inform socioeconomic development in receiving areas while optimizing water transmission and allocation.