scholarly journals Exploring Urban Taxi Drivers’ Activity Distribution Based on GPS Data

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Xiaowei Hu ◽  
Shi An ◽  
Jian Wang
Keyword(s):  
Large Scale ◽  
Behavior Pattern ◽  
Rapid Development ◽  
Activity Space ◽  
Space Distribution ◽  
Distribution Characteristics ◽  
Taxi Drivers ◽  
Activity Distribution ◽  
Time Operation ◽  
The Difference

With the rapid development of information communication technology and data mining technology, we can obtain taxi vehicle’s real time operation status through the large-scale taxi GPS trajectories data and explore the drivers’ activity distribution characteristics. Based on the 204 continuous hours of 3198 taxi vehicles’ operation data of Shenzhen, China, this paper analyzed the urban taxi driver’s activity distribution characteristics from different temporal and spatial levels. In the time level, we identified the difference with taxi daily operation pattern (weekday versus weekends), continuous time in one day, passengers in vehicle time, and taxi drivers’ operation frequency; in the space level, we explored the taxi driver’s searching pattern, including searching activity space distribution and the relationship between the pick-up locations and the drop-off locations. This research can be helpful for urban taxi drivers’ operation and behavior pattern identification, as well as the contribution to the geographical activity space analysis.

scholarly journals GeoSOT-Based Spatiotemporal Index of Massive Trajectory Data

2019 ◽  
Vol 8 (6) ◽  
pp. 284 ◽  
Author(s):  
Chunyao Qian ◽  
Chao Yi ◽  
Chengqi Cheng ◽  
Guoliang Pu ◽  
Xiaofeng Wei ◽  
...  
Keyword(s):  
Large Scale ◽  
User Behavior ◽  
Behavior Pattern ◽  
Rapid Development ◽  
Range Query ◽  
Space Time ◽  
Trajectory Data ◽  
Time Dimension ◽  
Growth Trend ◽  
Query Efficiency

With the rapid development of global positioning technologies and the pervasiveness of intelligent mobile terminals, trajectory data have shown a sharp growth trend both in terms of data volume and coverage. In recent years, increasing numbers of LBS (location based service) applications have provided us with trajectory data services such as traffic flow statistics and user behavior pattern analyses. However, the storage and query efficiency of massive trajectory data are increasingly creating a bottleneck for these applications, especially for large-scale spatiotemporal query scenarios. To solve this problem, we propose a new spatiotemporal indexing method to improve the query efficiency of massive trajectory data. First, the method extends the GeoSOT spatial partitioning scheme to the time dimension and forms a global space–time subdivision scheme. Second, a novel multilevel spatiotemporal grid index, called the GeoSOT ST-index, was constructed to organize trajectory data hierarchically. Finally, a spatiotemporal range query processing method is proposed based on the index. We implement and evaluate the index in MongoDB. By comparing the range query efficiency and scalability of our index with those of the other two space–time composite indexes, we found that our approach improves query efficiency levels by approximately 40% and has better scalability under different data volumes.

Antarctica and environmental change: closing remarks

1992 ◽  
Vol 338 (1285) ◽  
pp. 329-334
Keyword(s):  
Data Collection ◽  
Numerical Modelling ◽  
Large Scale ◽  
Rapid Development ◽  
Polar Regions ◽  
Data Collection And Analysis ◽  
The Difference ◽  
Improved Technology ◽  
The Antarctic

The purpose of this contribution is to summarize the papers and discussions, to bring out the highlights, and to focus on outstanding problems and uncertainties. Sixteen years ago Sir Vivian Fuchs and I organized a similar meeting on research in the Antarctic. Since then there has been an explosion of interest in all branches of environm ental science in this region. There have been major advances in theory, and improved technology made possible by the rapid development of electronics has made data collection and analysis easier; but above all the difference between the two meetings is in the development of large-scale numerical modelling as a tool. Also there has been an increasing realization of the value of comparisons between the two polar regions, which is brought out by the contributions to this meeting. The meeting has been distinguished by the quality of the science, the clarity of exposition and excellent visual presentations. It is also striking how much crossfertilization between disciplines has occurred

scholarly journals Emission Characteristics and Ozone Formation Potential Assessment of VOCs from Typical Metal Packaging Plants

Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 57
Author(s):  
Hailin Wang ◽  
Song Xue ◽  
Run Hao ◽  
Li Fang ◽  
Lei Nie
Keyword(s):  
Large Scale ◽  
Methylene Chloride ◽  
Rapid Development ◽  
Emission Characteristics ◽  
Ozone Formation ◽  
Formation Potential ◽  
Ozone Formation Potential ◽  
Water Based ◽  
The Difference ◽  
Vocs Emission

With the rapid development of metal packaging, volatile organic compounds (VOCs) emissions from the packaging processes are also increasing gradually. It is necessary to research the characteristics of VOCs emissions from such important industrial source and its impact on the possible ozone formation. In this research, three typical metal packaging plants were selected, VOCs emission characteristics were investigated, and their ozone formation potential were evaluated by using maximum incremental reactivity (MIR) coefficient method. The results showed that the VOCs emission characteristics of the selected targets were obviously different. VOCs emitted from plant A and B were mainly oxygenated hydrocarbons, which accounted for 85.02% and 43.17%, respectively. Olefins (62.75%) were the main species of plant C. 2-butanone (82.67%), methylene chloride (23.00%) and ethylene (36.67%) were the major species of plant A, plant B and plant C, respectively. The OFP (ozone formation potential) value of plant B (120.49 mg/m3) was much higher than those values of plant A (643.05 mg/m3) and plant C (3311.73 mg/m3), in which para-xylene, meta-xylene, acetaldehyde and ethylene were the main contributors. The difference in OFP values indicated that water-based ink and water-based coatings should be recommended for large scale application due to less VOCs emission and low ozone formation contribution.

Relationship between total plasma homocysteine and the risk of aneurysms – a meta-analysis

VASA ◽  
2020 ◽  
pp. 1-6
Author(s):  
Hanji Zhang ◽  
Dexin Yin ◽  
Yue Zhao ◽  
Yezhou Li ◽  
Dejiang Yao ◽  
...  
Keyword(s):  
Large Scale ◽  
Meta Analysis ◽  
Single Species ◽  
Total Plasma ◽  
Control Groups ◽  
Randomized Controlled ◽  
Randomized Controlled Studies ◽  
The Difference ◽  
The Relationship ◽  
Healthy Participants

Summary: Our meta-analysis focused on the relationship between homocysteine (Hcy) level and the incidence of aneurysms and looked at the relationship between smoking, hypertension and aneurysms. A systematic literature search of Pubmed, Web of Science, and Embase databases (up to March 31, 2020) resulted in the identification of 19 studies, including 2,629 aneurysm patients and 6,497 healthy participants. Combined analysis of the included studies showed that number of smoking, hypertension and hyperhomocysteinemia (HHcy) in aneurysm patients was higher than that in the control groups, and the total plasma Hcy level in aneurysm patients was also higher. These findings suggest that smoking, hypertension and HHcy may be risk factors for the development and progression of aneurysms. Although the heterogeneity of meta-analysis was significant, it was found that the heterogeneity might come from the difference between race and disease species through subgroup analysis. Large-scale randomized controlled studies of single species and single disease species are needed in the future to supplement the accuracy of the results.

Research on behavior recognition based on feature fusion of automatic coder and recurrent neural network

2020 ◽  
Vol 39 (6) ◽  
pp. 8927-8935
Author(s):  
Bing Zheng ◽  
Dawei Yun ◽  
Yan Liang
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Behavior Pattern ◽  
Rapid Development ◽  
Video Data ◽  
Support Vector ◽  
Behavior Recognition ◽  
Learning Methods ◽  
The Impact ◽  
Internet Of Things Technology

Under the impact of COVID-19, research on behavior recognition are highly needed. In this paper, we combine the algorithm of self-adaptive coder and recurrent neural network to realize the research of behavior pattern recognition. At present, most of the research of human behavior recognition is focused on the video data, which is based on the video number. At the same time, due to the complexity of video image data, it is easy to violate personal privacy. With the rapid development of Internet of things technology, it has attracted the attention of a large number of experts and scholars. Researchers have tried to use many machine learning methods, such as random forest, support vector machine and other shallow learning methods, which perform well in the laboratory environment, but there is still a long way to go from practical application. In this paper, a recursive neural network algorithm based on long and short term memory (LSTM) is proposed to realize the recognition of behavior patterns, so as to improve the accuracy of human activity behavior recognition.

TO THE PROBLEMS OF COMBATING CORRUPTION IN MODERN RUSSIA AND INTERNATIONAL COOPERATION IN THE FIELD OF ANTI-CORRUPTION

2020 ◽  
Author(s):  
Angela Dranishnikova
Keyword(s):  
Large Scale ◽  
The State ◽  
Point Of View ◽  
Modern Life ◽  
Existing Problems ◽  
Moral Point ◽  
Material Goods ◽  
The Russian Federation ◽  
The Difference ◽  
The Government

In the article, the author reflects the existing problems of the fight against corruption in the Russian Federation. He focuses on the opacity of the work of state bodies, leading to an increase in bribery and corruption. The topic we have chosen is socially exciting in our days, since its significance is growing on a large scale at all levels of the investigated aspect of our modern life. Democratic institutions are being jeopardized, the difference in the position of social strata of society in society’s access to material goods is growing, and the state of society is suffering from the moral point of view, citizens are losing confidence in the government, and in the top officials of the state.

scholarly journals Large-Scale Analysis of the Spatiotemporal Changes of Net Ecosystem Production in Hindu Kush Himalayan Region

2021 ◽  
Vol 13 (6) ◽  
pp. 1180
Author(s):  
Da Guo ◽  
Xiaoning Song ◽  
Ronghai Hu ◽  
Xinming Zhu ◽  
Yazhen Jiang ◽  
...  
Keyword(s):  
Large Scale ◽  
Net Primary Production ◽  
Carbon Sink ◽  
Carbon Sources ◽  
Spatial Dynamics ◽  
Tibet Plateau ◽  
Geostatistical Model ◽  
Hindu Kush ◽  
Temporal And Spatial ◽  
The Difference

The Hindu Kush Himalayan (HKH) region is one of the most ecologically vulnerable regions in the world. Several studies have been conducted on the dynamic changes of grassland in the HKH region, but few have considered grassland net ecosystem productivity (NEP). In this study, we quantitatively analyzed the temporal and spatial changes of NEP magnitude and the influence of climate factors on the HKH region from 2001 to 2018. The NEP magnitude was obtained by calculating the difference between the net primary production (NPP) estimated by the Carnegie–Ames Stanford Approach (CASA) model and the heterotrophic respiration (Rh) estimated by the geostatistical model. The results showed that the grassland ecosystem in the HKH region exhibited weak net carbon uptake with NEP values of 42.03 gC∙m−2∙yr−1, and the total net carbon sequestration was 0.077 Pg C. The distribution of NEP gradually increased from west to east, and in the Qinghai–Tibet Plateau, it gradually increased from northwest to southeast. The grassland carbon sources and sinks differed at different altitudes. The grassland was a carbon sink at 3000–5000 m, while grasslands below 3000 m and above 5000 m were carbon sources. Grassland NEP exhibited the strongest correlation with precipitation, and it had a lagging effect on precipitation. The correlation between NEP and the precipitation of the previous year was stronger than that of the current year. NEP was negatively correlated with temperature but not with solar radiation. The study of the temporal and spatial dynamics of NEP in the HKH region can provide a theoretical basis to help herders balance grazing and forage.

Dynamic network intelligent hybrid recommendation algorithm and its application in online shopping platform

2021 ◽  
pp. 1-13
Author(s):  
Yuxuan Gao ◽  
Haiming Liang ◽  
Bingzhen Sun
Keyword(s):  
Online Shopping ◽  
Rapid Development ◽  
Dynamic Network ◽  
Topsis Method ◽  
Recommendation Algorithm ◽  
Time Periods ◽  
The Difference ◽  
Relationship Of ◽  
Hybrid Recommendation ◽  
Novel Model

With the rapid development of e-commerce, whether network intelligent recommendation can attract customers has become a measure of customer retention on online shopping platforms. In the literature about network intelligent recommendation, there are few studies that consider the difference preference of customers in different time periods. This paper proposes the dynamic network intelligent hybrid recommendation algorithm distinguishing time periods (DIHR), it is a integrated novel model combined with the DEMATEL and TOPSIS method to solved the problem of network intelligent recommendation considering time periods. The proposed method makes use of the DEMATEL method for evaluating the preference relationship of customers for indexes of merchandises, and adopt the TOPSIS method combined with intuitionistic fuzzy number (IFN) for assessing and ranking the merchandises according to the indexes. We specifically introduce the calculation steps of the proposed method, and then calculate its application in the online shopping platform.

scholarly journals Can Mandatory Disclosure Policies Promote Corporate Environmental Responsibility?—Quasi-Natural Experimental Research on China

2021 ◽  
Vol 18 (11) ◽  
pp. 6033
Author(s):  
Yue Liu ◽  
Pierre Failler ◽  
Liming Chen
Keyword(s):  
Property Rights ◽  
Large Scale ◽  
Environmental Responsibility ◽  
Mandatory Disclosure ◽  
Corporate Environmental Responsibility ◽  
Disclosure Policy ◽  
Protection Information ◽  
The Difference ◽  
Csr Disclosure ◽  
Corporate Social

Corporate environmental responsibility (CER) is an important component of the corporate social responsibility (CSR) report, and an important carrier for enterprises to disclose environmental protection information. Based on the corporate micro data, this paper evaluates the effect of a mandatory CSR disclosure policy on the fulfillment of corporate environmental responsibility by adopting the difference-in-differences model (DID) with the release of a mandatory disclosure policy of China in 2008 as a quasi-natural experiment. The study draws the following conclusions: First, a mandatory CSR disclosure policy can promote the fulfillment of CER. Second, after the implementation of a mandatory CSR disclosure policy, enterprises can improve their CER level through two channels: improving the quality of environmental management disclosure and increasing the number of patents. Third, the heterogeneity of the impacts of mandatory CSR disclosure on CER is reflected in three aspects: different CER levels, different corporate scales and a different property rights structure. In terms of the CER level, there is an inverted U-shaped relationship between the CER level and mandatory CSR disclosure effect. In terms of the corporate scale, mandatory disclosure of CSR plays a greater role in large-scale enterprises. In terms of the structure of property rights, mandatory CSR disclosure has a greater effect on non-state-owned enterprises.

Sign in / Sign up

Export Citation Format

Share Document