Traffic peak period detection using traffic index cloud maps

2020 ◽  
Vol 553 ◽  
pp. 124277
Author(s):  
Yuni Li ◽  
Jianli Xiao
Keyword(s):  
Peak Period ◽  
Period Detection

scholarly journals Traffic Peak Period Detection from an Image Processing View

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Jianli Xiao ◽  
Hang Li ◽  
Xiang Wang ◽  
Shangcao Yuan
Keyword(s):  
Image Processing ◽  
Corner Detection ◽  
Time Interval ◽  
Detection Problem ◽  
Peak Period ◽  
Peak Point ◽  
Processing Strategies ◽  
Period Detection ◽  
Point Detection ◽  
And Control

Traffic peak period detection is very important for the guidance and control of traffic flow. Most common methods for traffic peak period detection are based on data analysis. They have achieved good performance. However, the detection processes are not intuitional enough. Besides that, the accuracy of these methods needs to be improved further. From an image processing view, we introduce a concept in corner detection, sharpness, to detect the traffic peak periods in this paper. The proposed method takes the traffic peak period detection problem as a salient point detection problem and uses the image processing strategies to solve this problem. Firstly, it generates a speed curve image with the speed data. With this image, the method for detection of salient points is adopted to obtain the peak point candidates. If one candidate has the lowest speed value, this candidate is the peak point. Finally, the peak period is gotten by moving forward and backward the corresponding time of the peak point with a time interval. Experimental results show that the proposed method has achieved higher accuracy. More importantly, as the proposed method solves the traffic peak period detection problem from an image processing view, it has more intuition.

scholarly journals Measuring Accessibility Based on Improved Impedance and Attractive Functions Using Taxi Trajectory Data

2020 ◽  
Vol 13 (1) ◽  
pp. 112
Author(s):  
Helai Huang ◽  
Jialing Wu ◽  
Fang Liu ◽  
Yiwei Wang
Keyword(s):  
Waiting Time ◽  
Urban Areas ◽  
Transportation Systems ◽  
Trajectory Data ◽  
Peak Period ◽  
Important Indicator ◽  
Destination Attractiveness ◽  
Urban Accessibility ◽  
Spatio Temporal ◽  
Taxi Trajectory

Accessibility has attracted wide interest from urban planners and transportation engineers. It is an important indicator to support the development of sustainable policies for transportation systems in major events, such as the COVID-19 pandemic. Taxis are a vital travel mode in urban areas that provide door-to-door services for individuals to perform urban activities. This study, with taxi trajectory data, proposes an improved method to evaluate dynamic accessibility depending on traditional location-based measures. A new impedance function is introduced by taking characteristics of the taxi system into account, such as passenger waiting time and the taxi fare rule. An improved attraction function is formulated by considering dynamic availability intensity. Besides, we generate five accessibility scenarios containing different indicators to compare the variation of accessibility. A case study is conducted with the data from Shenzhen, China. The results show that the proposed method found reduced urban accessibility, but with a higher value in southern center areas during the evening peak period due to short passenger waiting time and high destination attractiveness. Each spatio-temporal indicator has an influence on the variation in accessibility.

scholarly journals Impact of the COVID-19 pandemic and its related psychological effect on orthopedic surgeries conducted in different types of hospitals in Taiwan

2021 ◽  
Vol 29 (1) ◽  
pp. 230949902199607 ◽  
Author(s):  
Chia-Lung Shih ◽  
Peng-Ju Huang ◽  
Hsuan-Ti Huang ◽  
Chung-Hwan Chen ◽  
Tien-Ching Lee ◽  
...  
Keyword(s):  
Community Hospital ◽  
University Hospital ◽  
Total Knee Arthroplasties ◽  
Peak Period ◽  
Number Of Patients ◽  
Total Knee ◽  
Investigation Period ◽  
Orthopedic Diseases ◽  
The University ◽  
The Impact

Aim: Taiwan’s response to the coronavirus disease 2019 (COVID-19) differed in that it successfully prevented the spread without having to shutdown or overburden medical services. Patients’ fear regarding the pandemic would be the only reason to reduce surgeries, so Taiwan could be the most suitable place for research on the influence of psychological factors. This study aimed to assess the impact of patients’ fear on orthopedic surgeries in Taiwan amid the peak period of the COVID-19 pandemic. Patients and Methods: The investigation period included the COVID-19 pandemic (March 2020 to April 2020) and the corresponding period in the previous year. The following data on patients with orthopedic diseases were collected: outpatient visits, hospital admission, and surgical modalities. Results: The COVID-19 pandemic led to a 22%–29% and 20%–26% reduction in outpatients, 22%–27% and 25%–37% reduction in admissions, and 26%–35% and 18%–34% reduction in surgeries, respectively, at both hospitals. The weekly mean number of patients was significantly smaller during the COVID-19 pandemic for all types of surgery and elective surgeries at the university hospital, and for all types of surgery, elective surgeries, and total knee arthroplasties at the community hospital. Further, patients visiting the community hospital during the pandemic were significantly younger, for all types of surgery, elective surgeries, and total knee arthroplasties. Conclusions: The reduction in orthopedic surgeries in Taiwan’s hospitals during COVID-19 could be attributed to patients’ fear. Even without restriction, the pandemic inevitably led to a reduction of about 20%–30% of the operation volume.

scholarly journals Comprehensive Wind and Wave Statistics and Extreme Values for Design and Analysis of Marine Structures in the Adriatic Sea

2021 ◽  
Vol 9 (5) ◽  
pp. 522
Author(s):  
Marko Katalinić ◽  
Joško Parunov
Keyword(s):  
Adriatic Sea ◽  
Extreme Values ◽  
Wave Climate ◽  
Offshore Structures ◽  
Model Parameters ◽  
Peak Period ◽  
Significant Wave ◽  
Wave Statistics ◽  
Wave Heights ◽  
Almost All

Wind and waves present the main causes of environmental loading on seagoing ships and offshore structures. Thus, its detailed understanding can improve the design and maintenance of these structures. Wind and wave statistical models are developed based on the WorldWaves database for the Adriatic Sea: for the entire Adriatic Sea as a whole, divided into three regions and for 39 uniformly spaced locations across the offshore Adriatic. Model parameters are fitted and presented for each case, following the conditional modelling approach, i.e., the marginal distribution of significant wave height and conditional distribution of peak period and wind speed. Extreme significant wave heights were evaluated for 20-, 50- and 100-year return periods. The presented data provide a consistent and comprehensive description of metocean (wind and wave) climate in the Adriatic Sea that can serve as input for almost all kind of analyses of ships and offshore structures.

scholarly journals Coordination of Multiple Electric Vehicle Aggregators for Peak Shaving and Valley Filling in Distribution Feeders

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 352
Author(s):  
Saad Ullah Khan ◽  
Khawaja Khalid Mehmood ◽  
Zunaib Maqsood Haider ◽  
Muhammad Kashif Rafique ◽  
Muhammad Omer Khan ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Power Distribution ◽  
Distribution System ◽  
Energy Demand ◽  
Minimum Energy ◽  
Peak Shaving ◽  
Peak Period ◽  
Actual Distribution ◽  
Load Profile ◽  
System Load

In this paper, a coordination method of multiple electric vehicle (EV) aggregators has been devised to flatten the system load profile. The proposed scheme tends to reduce the peak demand by discharging EVs and fills the valley gap through EV charging in the off-peak period. Upper level fair proportional power distribution to the EV aggregators is exercised by the system operator which provides coordination among the aggregators based on their aggregated energy demand or capacity. The lower level min max objective function is implemented at each aggregator to distribute power to the EVs. Each aggregator ensures that the EV customers’ driving requirements are not relinquished in spite of their employment to support the grid. The scheme has been tested on IEEE 13-node distribution system and an actual distribution system situated in Seoul, Republic of Korea whilst utilizing actual EV mobility data. The results show that the system load profile is smoothed by the coordination of aggregators under peak shaving and valley filling goals. Also, the EVs are fully charged before departure while maintaining a minimum energy for emergency travel.

scholarly journals Instrumental Odour Monitoring System Classification Performance Optimization by Analysis of Different Pattern-Recognition and Feature Extraction Techniques

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 114
Author(s):  
Tiziano Zarra ◽  
Mark Gino K. Galang ◽  
Florencio C. Ballesteros ◽  
Vincenzo Belgiorno ◽  
Vincenzo Naddeo
Keyword(s):  
Pattern Recognition ◽  
Feature Extraction ◽  
Performance Optimization ◽  
Industrial Plant ◽  
Mathematical Treatment ◽  
Extraction Techniques ◽  
Peak Period ◽  
Linear Discriminant ◽  
Artificial Neural

Instrumental odour monitoring systems (IOMS) are intelligent electronic sensing tools for which the primary application is the generation of odour metrics that are indicators of odour as perceived by human observers. The quality of the odour sensor signal, the mathematical treatment of the acquired data, and the validation of the correlation of the odour metric are key topics to control in order to ensure a robust and reliable measurement. The research presents and discusses the use of different pattern recognition and feature extraction techniques in the elaboration and effectiveness of the odour classification monitoring model (OCMM). The effect of the rise, intermediate, and peak period from the original response curve, in collaboration with Linear Discriminant Analysis (LDA) and Artificial Neural Networks (ANN) as a pattern recognition algorithm, were investigated. Laboratory analyses were performed with real odour samples collected in a complex industrial plant, using an advanced smart IOMS. The results demonstrate the influence of the choice of method on the quality of the OCMM produced. The peak period in combination with the Artificial Neural Network (ANN) highlighted the best combination on the basis of high classification rates. The paper provides information to develop a solution to optimize the performance of IOMS.

scholarly journals Sea State Monitoring by Ship Motion Measurements Onboard a Research Ship in the Antarctic Waters

2021 ◽  
Vol 9 (1) ◽  
pp. 64
Author(s):  
Silvia Pennino ◽  
Antonio Angrisano ◽  
Vincenzo Della Corte ◽  
Giampaolo Ferraioli ◽  
Salvatore Gaglione ◽  
...  
Keyword(s):  
Transfer Functions ◽  
Wave Spectrum ◽  
Weather Forecast ◽  
Ship Motion ◽  
State Monitoring ◽  
Sea State ◽  
Peak Period ◽  
Research Ship ◽  
Antarctic Waters ◽  
The Antarctic

A parametric wave spectrum resembling procedure is applied to detect the sea state parameters, namely the wave peak period and significant wave height, based on the measurement and analysis of the heave and pitch motions of a vessel in a seaway, recorded by a smartphone located onboard the ship. The measurement system makes it possible to determine the heave and pitch acceleration spectra of the reference ship in the encounter frequency domain and, subsequently, the absolute sea spectra once the ship motion transfer functions are provided. The measurements have been carried out onboard the research ship “Laura Bassi”, during the oceanographic campaign in the Antarctic Ocean carried out in January and February 2020. The resembled sea spectra are compared with the weather forecast data, provided by the global-WAM (GWAM) model, in order to validate the sea spectrum resembling procedure.

scholarly journals Gastrointestinal endoscopy during the coronavirus pandemic in the New York area: results from a multi-institutional survey

2020 ◽  
Vol 08 (12) ◽  
pp. E1865-E1871
Author(s):  
Srihari Mahadev ◽  
Olga C. Aroniadis ◽  
Luis H. Barraza ◽  
Emil Agarunov ◽  
Michael S. Smith ◽  
...  
Keyword(s):  
New York ◽  
Clinical Care ◽  
Patient Characteristics ◽  
Feeding Tube ◽  
Tube Placement ◽  
Peak Time ◽  
City Region ◽  
Peak Period ◽  
Hospital System ◽  
The Impact

Abstract Background and study aims The coronavirus disease 2019 (COVID-19), and measures taken to mitigate its impact, have profoundly affected the clinical care of gastroenterology patients and the work of endoscopy units. We aimed to describe the clinical care delivered by gastroenterologists and the type of procedures performed during the early to peak period of the pandemic. Methods Endoscopy leaders in the New York region were invited to participate in an electronic survey describing operations and clinical service. Surveys were distributed on April 7, 2020 and responses were collected over the following week. A follow-up survey was distributed on April 20, 2020. Participants were asked to report procedure volumes and patient characteristics, as well protocols for staffing and testing for COVID-19. Results Eleven large academic endoscopy units in the New York City region responded to the survey, representing every major hospital system. COVID patients occupied an average of 54.5 % (18 – 84 %) of hospital beds at the time of survey completion, with 14.5 % (2 %-23 %) of COVID patients requiring intensive care. Endoscopy procedure volume and the number of physicians performing procedures declined by 90 % (66 %-98 %) and 84.5 % (50 %-97 %) respectively following introduction of restricted practice. During this period the most common procedures were EGDs (7.9/unit/week; 88 % for bleeding; the remainder for foreign body and feeding tube placement); ERCPs (5/unit/week; for cholangitis in 67 % and obstructive jaundice in 20 %); Colonoscopies (4/unit/week for bleeding in 77 % or colitis in 23 %) and least common were EUS (3/unit/week for tumor biopsies). Of the sites, 44 % performed pre-procedure COVID testing and the proportion of COVID-positive patients undergoing procedures was 4.6 % in the first 2 weeks and up to 19.6 % in the subsequent 2 weeks. The majority of COVID-positive patients undergoing procedures underwent EGD (30.6 % COVID +) and ERCP (10.2 % COVID +). Conclusions COVID-19 has profoundly impacted the operation of endoscopy units in the New York region. Our data show the impact of a restricted emergency practice on endoscopy volumes and the proportion of expected COVID positive cases during the peak time of the pandemic.

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