The COVID-19 pandemic has forced many governments around the world to implement strict lockdown measures and order citizens to stay at home, which has caused a major change in travel patterns. This study leveraged ele...
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ISBN:
(纸本)9781665434263
The COVID-19 pandemic has forced many governments around the world to implement strict lockdown measures and order citizens to stay at home, which has caused a major change in travel patterns. This study leveraged electric vehicle charging big data in Hefei, Anhui Province, China to estimate electric vehicle charging demand in the absence of the COVID-19 pandemic using multi-layer perceptron model, which quantified the impact of the COVID-19 pandemic. In addition, we employed the vector autoregressive model to investigate the dynamic relationships between the changes in charging demand and various explanatory factors. The results suggest that the daily average charging demand in Hefei decreased by 78.3 % compared to the predicted value during the pandemic. Furthermore, according to the variance decomposition and impulse response function analysis, national confirmed COVID-19 cases play a dominant role in reducing charging demand. The number of daily hospitalizations and Migration Scale Index also have significant and robust effect on the decrease in charging demand. The Air Quality Index and Baidu Index are susceptible to external factors and do not have a direct impact on the change in charging demand. Findings support a better understanding of changes in travel behavior during the pandemic and provide policy makers with references to deal with similar events.
This paper introduces Copula approach, which has been widely used in statistical field, to the construction of OLAP cubes for the first time. Based on this approach, a novel scheme is proposed to compress data and ans...
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This paper introduces Copula approach, which has been widely used in statistical field, to the construction of OLAP cubes for the first time. Based on this approach, a novel scheme is proposed to compress data and answer any OLAP query without accessing raw data. The procedure of this scheme can be generally divided into three steps. Firstly, find the proper distribution functions to fit the marginal distribution of each attribute. Secondly, employ Copula approach to catch the intra relationship among attributes in a data set. Finally, use the probability density function of joint distribution to calculate the aggregation function. Empirical evidence shows that this Copula-based model can not only drastically reduce storage requirements but also save the query response time, while the accuracy is bounded under a given level.
Currently, the earlier detection, diagnosis and treatment to breast cancer still mainly depend on physicians' experience and knowledge. Case-Based Reasoning(CBR) mimics oncologists' real thinking process and t...
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ISBN:
(纸本)9783037851555
Currently, the earlier detection, diagnosis and treatment to breast cancer still mainly depend on physicians' experience and knowledge. Case-Based Reasoning(CBR) mimics oncologists' real thinking process and therefore is appropriate to the diagnosis decisionmaking. In CBR, weight derivation as a key step is commonly conducted by expert score approaches using Delphi method. The accuracy of case matching largely changes with the selection and experience of experts. In this paper, information entropy for weight determination is introduced into the CBR. We conduct experimental studies to compare the performance of Delphi method and information entropy. The results suggest that: generally, information entropy is a better approach to weight derivation.
Pignistic probability distance can describe evidence distance accurately. The paper calculates the similarity of evidence based on Pignistic probability distance, then determines the relative weight of evidence. In th...
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Previous studies recognize pain expressions based on the entire face, for example, Prkachin and Solomon Pain intensity (PSPI). However, the patients face is often masked by instruments in an intensive care unit (ICU),...
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ISBN:
(纸本)9781665481106
Previous studies recognize pain expressions based on the entire face, for example, Prkachin and Solomon Pain intensity (PSPI). However, the patients face is often masked by instruments in an intensive care unit (ICU), such as respirator, and gauzes, just name a few, which causes the agent cannot measure the pain intensity using PSPI directly. To tackle this problem, we explore the pain intensity recognition from masked face. First, we conducted four levels of pain measurement experiments with four types of masked face using Swin-Transformer. Experiment results show that the accuracy of pain measurement is more than 90%, even masking a large part of facial Action Units (AU) related to the pain on the UNBC-McMaster dataset. Furthermore, we pre-train the pain recognition model with masked face dataset, such that the model can capture facial features contributed to the pain. Results on binary and four-level pain intensity measurement tasks show our model outperforms recent state-of-the-art performance, achieving 97.38% and 95.25% accuracy, respectively.
Marine high-end equipment reflects a country's comprehensive national strength. The safety assessment of it is very important to avoid accident either from human or facility factors. Attribute structure and assess...
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From the perspective of supporting decisionmaking, a statistical model is built in this paper in order to realize the tradeoff between the accuracy of OLAP queries and the efficiency of OLAP processes. Kernel density...
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Service supply chain features human players as service vendor, service integrator, customer and service resource. It tends to be digitally connected, such as consulting, e-business and integrated enterprises. Our stud...
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Service supply chain features human players as service vendor, service integrator, customer and service resource. It tends to be digitally connected, such as consulting, e-business and integrated enterprises. Our study uses a formal model and simulations to develop the effect of a service supply chain on equilibrium computation. Two insights arise on how a network can obtain equilibrium computation: forming the network structure of service supply chain; exploring entities behavior and equilibrium conditions. These results highlight the importance for service supply chain of adapting its network structure to equilibrium and application.
A previous study conducted in Anhui Province by collecting data from 56 county-level governments in 2009 has shown that the factors of demographic, financial and geographical area have linear relationship with governm...
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作者:
Jin PengZhang Shu ChuSchool of Management
Key Laboratory Process Optimization and Intelligent Decision-Making Ministry of Education Hefei University of Technology Hefei Anhui China
This study presents a new hybrid ant colony algorithm (HACO) to solve an in integer linear programming formulation of the Cutting Stock Problem(CSP). The CSP is an important class combinatorial problem. It is appropri...
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ISBN:
(纸本)9781424490875
This study presents a new hybrid ant colony algorithm (HACO) to solve an in integer linear programming formulation of the Cutting Stock Problem(CSP). The CSP is an important class combinatorial problem. It is appropriate to minimize the raw material used by industries for fulfilling customer's demands. In such cases, classic models for solving the cutting stock problem are useless. HACO consists of GDCP procedure and modified ACO (MACO). GDCP procedure provides dominative cutting patterns as MACO solution components, in MACO the pheromone trail is put on cutting patterns instead of items. MACO preserves cutting patterns and frequencies information under ants building solution procedure. Results obtained from computational experiments for ten benchmarks demonstrate that the performance of MACO is compared to that obtained using existing mete-heuristic algorithm.
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