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Journal articles on the topic 'General traffic patterns'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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1

O’Sullivan, Rory. "Traffic patterns." Canadian Family Physician 69, no. 1 (2023): 47–48. http://dx.doi.org/10.46747/cfp.690147.

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B. Gaididei, Yuri, Carlos Gorria, Rainer Berkemer, et al. "Stochastic control of traffic patterns." Networks & Heterogeneous Media 8, no. 1 (2013): 261–73. http://dx.doi.org/10.3934/nhm.2013.8.261.

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3

Jing, Binbin, and Jianmin Xu. "A General Maximum Progression Model to Concurrently Synchronize Left-Turn and through Traffic Flows on an Arterial." Mathematical Problems in Engineering 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/2453246.

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In the existing bandwidth-based methods, through traffic flows are considered as the coordination objects and offered progression bands accordingly. However, at certain times or nodes in the road network, when the left-turn traffic flows have a higher priority than the through traffic flows, it would be inappropriate to still provide the progression bands to the through traffic flows; the left-turn traffic flows should instead be considered as the coordination objects to potentially achieve better control. Considering this, a general maximum progression model to concurrently synchronize left-t

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Lo Verde, John, Wayland Dong, Samantha Rawlings, and McCall Edwards. "Statistical evaluation of noise due to changes in pandemic traffic patterns." Journal of the Acoustical Society of America 153, no. 3_supplement (2023): A22. http://dx.doi.org/10.1121/10.0018013.

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Vehicular traffic noise for free-flowing roadways and highways generally follows statistically predictable flow rates and vehicular mix. The authors’ earlier work in this area examined long-term variations in traffic noise level with the purpose of establishing maximum hourly levels for vehicular sources (“Defining vehicular noise levels to manage risk associated with exterior façade design,” LoVerde, Dong, Rawlings, Internoise 2014 Melbourne) and general average sound level (“Noise prediction of vehicle sources on arterials using measured sound data,” LoVerde, Dong, Rawlings, ASA 2014 Provide

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Dobler, Gregory, Jordan Vani, and Trang Tran Linh Dam. "Patterns of urban foot traffic dynamics." Computers, Environment and Urban Systems 89 (September 2021): 101674. http://dx.doi.org/10.1016/j.compenvurbsys.2021.101674.

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Patil, Vrushal. "Traffic Signal Pattern Algorithm." International Journal for Research in Applied Science and Engineering Technology 11, no. 12 (2023): 126–28. http://dx.doi.org/10.22214/ijraset.2023.57249.

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Abstract: Every day we are witnessing a rapid increase in traffic volume on roads. Traffic signals are made to manage the traffic to get less disturbance during the journey and to avoid collisions. Sometimes these traffic signals might become a reason for a delay due to poor time management at signal timings. The old traffic signal patterns are the main cause of this issue and hence this project of new signalling patterns will help in using traffic signals more efficiently. In the traditional pattern at a crossover only one signal can be opened but using our pattern algorithm more than one sig

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Deng, Lei, Chih-Chun Wang, Minghua Chen, and Shizhen Zhao. "Timely Wireless Flows With General Traffic Patterns: Capacity Region and Scheduling Algorithms." IEEE/ACM Transactions on Networking 25, no. 6 (2017): 3473–86. http://dx.doi.org/10.1109/tnet.2017.2749513.

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Baade, S. C. "SNA route generation using traffic patterns." IBM Systems Journal 30, no. 3 (1991): 250–58. http://dx.doi.org/10.1147/sj.303.0250.

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Ren, Guoqiang, Guang Cheng, and Nan Fu. "Accurate Encrypted Malicious Traffic Identification via Traffic Interaction Pattern Using Graph Convolutional Network." Applied Sciences 13, no. 3 (2023): 1483. http://dx.doi.org/10.3390/app13031483.

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Telecommuting and telelearning have gradually become mainstream lifestyles in the post-epidemic era. The extensive interconnection of massive terminals gives attackers more opportunities, which brings more significant challenges to network traffic security analysis. The existing attacks, often using encryption technology and distributed attack methods, increase the number and complexity of attacks. However, the traditional methods need more analysis of encrypted malicious traffic interaction patterns and cannot explore the potential correlations of interaction patterns in a macroscopic and com

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Maio, Sara, Sandra Baldacci, Marzia Simoni, et al. "Longitudinal Asthma Patterns in Italian Adult General Population Samples: Host and Environmental Risk Factors." Journal of Clinical Medicine 9, no. 11 (2020): 3632. http://dx.doi.org/10.3390/jcm9113632.

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Background: Asthma patterns are not well established in epidemiological studies. Aim: To assess asthma patterns and risk factors in an adult general population sample. Methods: In total, 452 individuals reporting asthma symptoms/diagnosis in previous surveys participated in the AGAVE survey (2011–2014). Latent transition analysis (LTA) was performed to detect baseline and 12-month follow-up asthma phenotypes and longitudinal patterns. Risk factors associated with longitudinal patterns were assessed through multinomial logistic regression. Results: LTA detected four longitudinal patterns: persi

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V, Prajwal, Abhay R, Rohith Gowda D, and Savitha G. "AI-Driven Urban Traffic Optimization to Assess Complex Traffic Patterns for Public Traffic Control and Mobility." International Journal for Research in Applied Science and Engineering Technology 11, no. 11 (2023): 794–98. http://dx.doi.org/10.22214/ijraset.2023.56630.

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Abstract: The project "AI for Urban Traffic Optimization" is a major and novel method for addressing the issues of modern urban transportation networks. This research study highlights the potential of artificial intelligence (AI) in transforming traffic management by merging AI with the Internet of Things (IoT). It has several advantages, such as efficient traffic flow optimization, predictive congestion analysis, adaptive traffic signal management, speedy accident detection and reaction, public transit optimization, and enhanced traffic enforcement. These developments have the potential to re

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Boyarshinov, M. G., and A. S. Vavilin. "PATTERNS OF TRAFFIC CONGESTION INDICATOR AT SOME INTERSECTIONS OF THE ROAD NETWORK." Intellect. Innovations. Investments, no. 1 (2024): 95–115. http://dx.doi.org/10.25198/2077-7175-2024-1-95.

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The average speed and density of road transport are used as indicators of the congestion situation, but do not allow tracking the evolution (stages of formatting, progressing, and vanishing) of traffic congestion. The authors proposed and justified a quantitative indicator of traffic congestion, which allows in an automated mode to identify the congestion situation on the urban road network using hardware and software video recording systems. The purpose of this study is due to the need to study the quantitative characteristics of the proposed indicator at characteristic intersections of urban

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HUANG, DING-WEI. "COMPLETE TRAFFIC PATTERNS AROUND A T-SHAPED INTERSECTION." International Journal of Modern Physics C 21, no. 02 (2010): 189–204. http://dx.doi.org/10.1142/s0129183110015063.

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We propose Asymmetric Simple Exclusion Processes to analyze the traffic states around a T-shaped intersection. The system consists of six roadways connected by the intersection. There are nine control-parameters separated into three categories: injection αi, removal βi, and turning Pi, (where i = 1, 2, 3). As these nine parameters change, traffic states on each roadway reveal a two-phase transition: free flow (F) and jam (J). Together, there can be 64 (=26) possible combinations for the traffic phases. We observe 63 distinct phases. We analyze three major causes of congestion: (1) increase of

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Shahsavari Pour, N., H. Asadi, and M. Pour Kheradmand. "Fuzzy Multiobjective Traffic Light Signal Optimization." Journal of Applied Mathematics 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/249726.

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Traffic congestion is a major concern for many cities throughout the world. In a general traffic light controller, the traffic lights change at a constant cycle time. Hence it does not provide an optimal solution. Many traffic light controllers in current use are based on the “time-of-the-day” scheme, which use a limited number of predetermined traffic light patterns and implement these patterns depending upon the time of the day. These automated systems do not provide an optimal control for fluctuating traffic volumes. In this paper, the fuzzy traffic light controller is used to optimize the

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Kohan, Mariano, and Juan M. Ale. "Discovering traffic congestion through traffic flow patterns generated by moving object trajectories." Computers, Environment and Urban Systems 80 (March 2020): 101426. http://dx.doi.org/10.1016/j.compenvurbsys.2019.101426.

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GOMES, LUIZ H., VIRGILIO A. F. ALMEIDA, JUSSARA M. ALMEIDA, FERNANDO D. O. CASTRO, and LUÍS M. A. BETTENCOURT. "QUANTIFYING SOCIAL AND OPPORTUNISTIC BEHAVIOR IN EMAIL NETWORKS." Advances in Complex Systems 12, no. 01 (2009): 99–112. http://dx.doi.org/10.1142/s0219525909002088.

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Email graphs have been used to illustrate the general properties of social networks of communication and collaboration. However, increasingly, the majority of Internet traffic reflects opportunistic rather than symbiotic social relations. Here we use email data drawn from a large university to construct directed graphs of email exchange that quantify the differences between social and opportunistic behavior, represented by legitimate messages and spam, respectively. We show that while structural characteristics typical of other social networks are shared to a large extent by the legitimate com

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Ando, Ruo, Youki Kadobayashi, Hiroki Takakura, and Hiroshi Itoh. "Understanding Traffic Patterns of Covid-19 IoC in Huge Academic Backbone Network SINET." International Journal of Network Security & Its Applications 13, no. 6 (2021): 23–36. http://dx.doi.org/10.5121/ijnsa.2021.13603.

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Recently, APT (Advanced Persistent Threats) groups are using the COVID-19 pandemic as part of their cyber operations. In response to cyber threat actors, IoCs (Indicators of Compromise) are being provided to help us take some countermeasures. In this paper, we analyse how the coronavirus-based cyber attack unfolded on the academic infrastructure network SINET (The Science Information Network) based on the passive measurement with IoC. SINET is Japan's academic information infrastructure network. To extract and analyze the traffic patterns of the COVID-19 attacker group, we implemented a data f

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Afonin, Maksym, and Mykola Postranskyy. "Patterns of changes in the acoustic characteristics on public transport linear segments." Transport technologies 2022, no. 2 (2022): 41–51. http://dx.doi.org/10.23939/tt2022.02.041.

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The problem of noise pollution in cities becomes quite acute as soon as it comes to increasing the level of motorization. However, most researchers study the negative impact of traffic noise in general. In the era of sustainable mobility, there will be a trend to reduce the number of private vehicles on city streets. Still, the problem of acoustic load in residential areas will not be solved since public transport is a rather powerful source of traffic noise. The article solves the problem of determining the patterns of changes in the acoustic load from public transport vehicles at different s

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Gasparyan, G. A., and M. V. Kulakov. "Optimization of standard arrival procedures at Sheremetyevo airport using rnav path terminators." Civil Aviation High Technologies 24, no. 6 (2021): 17–26. http://dx.doi.org/10.26467/2079-0619-2021-24-6-17-26.

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Holding patterns are established at international airports to make the arriving traffic flow smooth and efficient. One of the main aims of holding patterns is to extend the aircraft arrival route, which allows ATC units to arrange the sequence on the arrival routes more effectively. The article considers the current methods and offers new ideas to improve the efficiency of the inbound traffic flow management using Paths and Terminators concept with HA holding patterns for standard arrival routes at Sheremetyevo Airport. As the main idea for optimizing air traffic management on this stage and r

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Chong, Kyusoo. "Spatiotemporal Influence Analysis Through Traffic Speed Pattern Analysis Using Spatial Classification." Applied Sciences 15, no. 1 (2024): 196. https://doi.org/10.3390/app15010196.

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This study introduces a method for classifying traffic flow segments on expressways to estimate impact zones in merging/diverging sections and accident-prone sites. I propose a spatiotemporal dynamic segmentation approach that enables real-time identification of traffic hazard sections, reflecting changes in traffic flow, as opposed to traditional traffic analysis based on predefined segments in a node–link network. This methodology uses high-resolution vehicle trajectory data to precisely identify unstable and low-speed traffic sections. Using the geohash algorithm, the area is hierarchically

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Li, Jian, and Kaan Ozbay. "Hurricane Irene Evacuation Traffic Patterns in New Jersey." Natural Hazards Review 16, no. 2 (2015): 05014006. http://dx.doi.org/10.1061/(asce)nh.1527-6996.0000154.

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Heshtaut, P., and S. Huznei. "Road accidents involving wild animals: Patterns and comparative analysis." Science and Innovations, no. 8 (September 12, 2023): 70–75. http://dx.doi.org/10.29235/1818-9857-2023-08-70-75.

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Quantitative characteristics and a comparative analysis of traffic accidents involving wild animals in Belarus and other countries are given. The patterns of distribution of the ungulates number killed in road accidents are presented by seasons, days of the week, sex and age structure. It has been established that the places of accidents concentration are road sections adjacent to large settlements, as well as highways with high traffic.

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Raju, Gangavarapu Deva, and Mary Sowjanya Gaddala. "Injury Patterns and Factors Responsible in Fatal Motorcyclist’s Road Traffic Accidents: A Forensic Perspective." Indian Journal of Forensic Medicine and Pathology 14, no. 4 (2021): 793–98. http://dx.doi.org/10.21088/ijfmp.0974.3383.14421.2.

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Road traffic accidents are the major cause of premature death and disability all over the world and motorized two-wheelers accidents account for the majority of such cases particularly in developing countries like India. The aim of the present study is to analyze the pattern of injuries with a focus on head injuries and the environmental factors leading to events. Methodology:A cross-sectional analytic study was conducted in the Department of Forensic Medicine at Osmania General Hospital, Afzalgunj Hyderabad during the period January 1st, 2018 to December 31st, 2018. Results: Abigmajorityofvic

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Ji, Soo-Yeon, Bong Keun Jeong, and Dong H. Jeong. "An Analysis of Temporal Features in Multivariate Time Series to Forecast Network Events." Applied Sciences 13, no. 18 (2023): 10411. http://dx.doi.org/10.3390/app131810411.

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Analyzing network traffic over time is crucial for understanding the changes in network activity. To properly examine network traffic patterns over time, multiple network events in each timestamp need to be converted to time series data. In this study, we propose a new approach to transform network traffic data into time series formats by extracting temporal features to analyze normal/attack patterns. The normal patterns indicate network traffic occurred without any intrusion-related activities, whereas the attack patterns denote potential threats that deviate from the normal patterns. To eval

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Sun, Tuo, Shihao Zhu, Ruochen Hao, Bo Sun, and Jiemin Xie. "Traffic Missing Data Imputation: A Selective Overview of Temporal Theories and Algorithms." Mathematics 10, no. 14 (2022): 2544. http://dx.doi.org/10.3390/math10142544.

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A great challenge for intelligent transportation systems (ITS) is missing traffic data. Traffic data are input from various transportation applications. In the past few decades, several methods for traffic temporal data imputation have been proposed. A key issue is that temporal information collected by neighbor detectors can make traffic missing data imputation more accurate. This review analyzes traffic temporal data imputation methods. Research methods, missing patterns, assumptions, imputation styles, application conditions, limitations, and public datasets are reviewed. Then, five represe

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Sundresh, Ashutosh. "Unveiling Complex Traffic Patterns: Applying Chaos Theory to Understand Non-Linear Dynamics in Congestion." International Journal of Science and Research (IJSR) 12, no. 9 (2023): 156–59. http://dx.doi.org/10.21275/mr23830183842.

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Wiwekananda, Agus Bhayu W., I. Wayan Arimbawa, and Ratna Rayeni Natasha Roosseno. "The characteristics and patterns of maxillofacial fractures at Mangusada general hospital, Badung-Bali." International Journal of Research in Medical Sciences 7, no. 6 (2019): 2318. http://dx.doi.org/10.18203/2320-6012.ijrms20192520.

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Background: Trauma is one of the leading causes of death among people under 40 years of age and approximately 10 percent of the cases have been maxillofacial trauma. There was limited number of studies on maxillofacial fractures in Indonesia. Thus, this research attempted to investigate the characteristics and patterns of maxillofacial fractures at Mangusada General Hospital in Badung-Bali.Methods: This research was a cross-sectional descriptive study which conducted at Mangusada General Hospital in the period of 1 January 2016 - 31 December 2017. The 127 samples selected using non-probability

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Akinfala, Olanrewaju Oluwafemi, Emmanuel Enyeribe Ege, and Ladi Folorunso Ogunwolu. "ARRIVAL PATTERNS AND TRAFFIC FLOW CHARACTERISTICS AT SIGNALIZED INTERSECTIONS." FUTA JOURNAL OF ENGINEERING AND ENGINEERING TECHNOLOGY 15, no. 1 (2021): 11–28. http://dx.doi.org/10.51459/futajeet.2021.15.1.208.

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Traffic arrivals at signal intersection approaches is inherently stochastic. This variability is typically reflected by I-ratio and there is a general consensus that the presence or absence of nearby upstream signal affects Variance to Mean Ratio (I-ratio). However, the effect of time resolution on arrival variability and the interaction effect between upstream signal and time resolution is yet to be examined in detail. This can lead to model misspecification and invariably, erroneous outcomes. This work examines the effect of time resolution and intersection type and their interaction on I-ra

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Neizvestnyi, Sergyi. "DETERMINATION OF THE PERIOD OF EFFICIENT FUNCTIONING OF A ROAD." Dorogi i mosti 2023, no. 27 (2023): 245–52. http://dx.doi.org/10.36100/dorogimosti2023.27.245.

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Introduction. One of the reasons for ordering the reconstruction of a road or part of it is the deterioration of the safety of traffic flows, as a result of which the number of victims and material losses in road traffic accidents (traffic accidents) increases. Interchanges at the same level have the greatest influence on the traffic intensity on the highway, as traffic flows are redistributed at them. Depending on the intensity of traffic on them, the maximum possible intensity of traffic on the road section as a whole will be determined. Problem statement. The analysis of determining the nee

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Delavary, Milad, Zahra Ghayeninezhad, and Martin Lavallière. "Evaluating the Impact of Increased Fuel Cost and Iran’s Currency Devaluation on Road Traffic Volume and Offenses in Iran, 2011–2019." Safety 6, no. 4 (2020): 49. http://dx.doi.org/10.3390/safety6040049.

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Trends and underlying patterns should be identified in the timely distribution of road traffic offenses to increase traffic safety. In this study, a time series analysis was used to study the incidence rate of road traffic violations on Iranian rural roads. Road traffic volume and offenses data from March 2011 to October 2019 were aggregated. Interrupted time series were used to evaluate the impact of increasing fuel cost in June of 2013 and July of 2014 and the currency devaluation of Rial vs. US dollars in July of 2017 on trends and patterns, traffic volume, and number of offenses. A change-

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Jeong, Dong Hyun, Bong-Keun Jeong, and Soo-Yeon Ji. "Multi-Resolution Analysis with Visualization to Determine Network Attack Patterns." Applied Sciences 13, no. 6 (2023): 3792. http://dx.doi.org/10.3390/app13063792.

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Analyzing network traffic activities is imperative in network security to detect attack patterns. Due to the complex nature of network traffic event activities caused by continuously changing computing environments and software applications, identifying the patterns is one of the challenging research topics. This study focuses on analyzing the effectiveness of integrating Multi-Resolution Analysis (MRA) and visualization in identifying the attack patterns of network traffic activities. In detail, a Discrete Wavelet Transform (DWT) is utilized to extract features from network traffic data and i

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Xiong, Liyan, Weihua Ding, Xiaohui Huang, and Weichun Huang. "CLSTAN: ConvLSTM-Based Spatiotemporal Attention Network for Traffic Flow Forecasting." Mathematical Problems in Engineering 2022 (July 11, 2022): 1–13. http://dx.doi.org/10.1155/2022/1604727.

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Traffic flow forecasting is the essential part of intelligent transportation sSystem (ITS), which can fully protect traffic safety and improve traffic system management capability. Nevertheless, it is still a challenging problem, which is influenced by many complex factors, including regional distribution and external factors (e.g., holidays and weather). To combine various factors to forecast traffic flow, we presented a novel neural network structure called ConvLSTM-based Spatiotemporal Attention Network (CLSTAN). Specifically, our proposed model is composed of four modules: a preliminary fe

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Tišljarić, Leo, Sofia Fernandes, Tonči Carić, and João Gama. "Spatiotemporal Road Traffic Anomaly Detection: A Tensor-Based Approach." Applied Sciences 11, no. 24 (2021): 12017. http://dx.doi.org/10.3390/app112412017.

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The increased development of urban areas results in a larger number of vehicles on the road network, leading to traffic congestion, which often leads to potentially dangerous situations that can be described as anomalies. The tensor-based methods emerged only recently in applications related to traffic anomaly detection. They outperform other models regarding simultaneously capturing spatial and temporal components, which are of immense importance in traffic dataset analysis. This paper presents a tensor-based method for extracting the spatiotemporal road traffic patterns represented with the

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Priambodo, Bagus, Rabiah Abdul Kadir, and Azlina Ahmad. "Clustering Urban Roads Using Local Binary Patterns to Enhance the Accuracy of Traffic Flow Prediction." International Journal on Advanced Science, Engineering and Information Technology 14, no. 5 (2024): 1514–20. http://dx.doi.org/10.18517/ijaseit.14.5.11269.

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Many studies employ a dynamic statistical approach to model the relationship between roads for predicting traffic flow. Statistical relationships among roads pertain to the associations between road segments in nearby areas. Roads with similar traffic patterns usually define the relationship. Previous studies have shown that adjacent roads demonstrated a similar traffic pattern on the same day and time interval. Studying similar patterns between roads in surrounding areas provides information about the traffic state among roads in a cluster. Furthermore, the results of this finding may be cons

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Einbeck, Jochen, and Jo Dwyer. "Using principal curves to analyse traffic patterns on freeways." Transportmetrica 7, no. 3 (2011): 229–46. http://dx.doi.org/10.1080/18128600903500110.

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Liu, Jingru, Rusong Wang, and Jianxin Yang. "A scenario analysis of Beijing's private traffic patterns." Journal of Cleaner Production 15, no. 6 (2007): 550–56. http://dx.doi.org/10.1016/j.jclepro.2006.06.002.

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Qu, Sirou, and Fengxiang Guo. "Behavioral Patterns of Drivers under Signalized and Unsignalized Urban Intersections." Applied Sciences 14, no. 5 (2024): 1802. http://dx.doi.org/10.3390/app14051802.

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Under the general trend of mixed traffic flow, an in-depth understanding of the driving behaviors of traditional vehicles is of great significance for the design of autonomous vehicles and the improvement in the safety and acceptance of autonomous vehicles. This study first obtained microdata on the behaviors of drivers through driving simulation experiments and conducted research in stages. Then, generalized linear mixed-effects models were constructed to study the main effects and interaction effects of driver attributes and traffic conditions on driving behaviors. The data analysis shows th

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Cividini, J., C. Appert-Rolland, and H. J. Hilhorst. "Diagonal patterns and chevron effect in intersecting traffic flows." EPL (Europhysics Letters) 102, no. 2 (2013): 20002. http://dx.doi.org/10.1209/0295-5075/102/20002.

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Herrmann, Dominik, Christian Banse, and Hannes Federrath. "Behavior-based tracking: Exploiting characteristic patterns in DNS traffic." Computers & Security 39 (November 2013): 17–33. http://dx.doi.org/10.1016/j.cose.2013.03.012.

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Lehmann, H. "Directed and diffusive contributions to urban traffic flow patterns." Europhysics Letters (EPL) 64, no. 2 (2003): 288–94. http://dx.doi.org/10.1209/epl/i2003-00502-1.

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Owolafe, Otasowie, and Aderonke F. Thompson. "Analysis of Crypto-Ransomware Using Network Traffic." Journal of Information Security and Cybercrimes Research 5, no. 1 (2022): 72–79. http://dx.doi.org/10.26735/jvuj3498.

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Ransomware is a form of malware attack that makes use of encryption to make information inaccessible for the motive of gathering a specified amount of payment. Many victims of this attack who couldn’t recover their information from backups have been compelled to decide between losing the information or paying the sum requested by the attacker. This research shows some of the various samples of ransomware, the phases of attack, and the chance of recognizing ransomware by the network traffic patterns it generates. Traffic generated from the infected system was considered. Experimental results fr

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Li, Mingqian, Panrong Tong, Mo Li, Zhongming Jin, Jianqiang Huang, and Xian-Sheng Hua. "Traffic Flow Prediction with Vehicle Trajectories." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 1 (2021): 294–302. http://dx.doi.org/10.1609/aaai.v35i1.16104.

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This paper proposes a spatiotemporal deep learning framework, Trajectory-based Graph Neural Network (TrGNN), that mines the underlying causality of flows from historical vehicle trajectories and incorporates that into road traffic prediction. The vehicle trajectory transition patterns are studied to explicitly model the spatial traffic demand via graph propagation along the road network; an attention mechanism is designed to learn the temporal dependencies based on neighborhood traffic status; and finally, a fusion of multi-step prediction is integrated into the graph neural network design. Th

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Pan, Ren-Hao, Nien-Tzu Chang, Dachen Chu, et al. "Epidemiology of Orthopedic Fractures and Other Injuries among Inpatients Admitted due to Traffic Accidents: A 10-Year Nationwide Survey in Taiwan." Scientific World Journal 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/637872.

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To investigate the major injury patterns associated with traffic accidents and evaluate the risk factors of the main injury, a survey of Taiwan’s national insurance admission data between 2002 and 2011 was performed. The incidence of traffic-accidents-related hospitalization was between 9.17% and 11.54% and the average mortality rate of the inpatients admitted due to traffic accidents was 0.68%. Of all inpatients due to road traffic accidents in Taiwan, orthopedic fractures were the most common injuries that accounted for 29.36% of them. There were a total of 391,197 cases of three orthopedic

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Muñoz-Organero, Mario. "Using Traffic Sensors in Smart Cities to Enhance a Spatio-Temporal Deep Learning Model for COVID-19 Forecasting." Mathematics 11, no. 18 (2023): 3904. http://dx.doi.org/10.3390/math11183904.

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Respiratory viruses, such as COVID-19, are spread over time and space based on human-to-human interactions. Human mobility plays a key role in the propagation of the virus. Different types of sensors in smart cities are able to continuously monitor traffic-related human mobility, showing the impact of COVID-19 on traffic volumes and patterns. In a similar way, traffic volumes measured by smart traffic sensors provide a proxy variable to capture human mobility, which is expected to have an impact on new COVID-19 infections. Adding traffic data from smart city sensors to machine learning models

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Macioszek, Elżbieta, and Agata Kurek. "Extracting Road Traffic Volume in the City before and during covid-19 through Video Remote Sensing." Remote Sensing 13, no. 12 (2021): 2329. http://dx.doi.org/10.3390/rs13122329.

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Continuous, automatic measurements of road traffic volume allow the obtaining of information on daily, weekly or seasonal fluctuations in road traffic volume. They are the basis for calculating the annual average daily traffic volume, obtaining information about the relevant traffic volume, or calculating indicators for converting traffic volume from short-term measurements to average daily traffic volume. The covid-19 pandemic has contributed to extensive social and economic anomalies worldwide. In addition to the health consequences, the impact on travel behavior on the transport network was

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Afonin, Maksym. "Patterns of the noise level change at different speeds for mixed traffic flows." MATEC Web of Conferences 390 (2024): 02005. http://dx.doi.org/10.1051/matecconf/202439002005.

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The study describes the problems of determining the normative levels of traffic noise on city main streets. The main statements and preliminary laws that are taken into account when determining the acoustic characteristics of the urban environment in the current building regulations are considered. It was established that the main factor that determines the acoustic load on city streets is the type of covering. The dynamics of the level of traffic noise of mixed flows, taking into account different types of coverage at different speed regimes, are also determined. The obtained results partiall

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Astaiza Hoyos, Evelio, Héctor Fabio Bermúdez Orozco, and Diego Fernando Salgado Castro. "Performance evaluation of self-similar models for traffic on IEEE 802.11 networks - study of case for the QRD network." ITECKNE 9, no. 2 (2012): 33–39. http://dx.doi.org/10.15332/iteckne.v9i2.2755.

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This paper evaluates the performance of fractal or self-similar traffic models in IEEE 802.11 networks. This study is focused on the “Quindio Región Digital” (QRD) network. Performance evaluation of the traffic models is performed in three stages. In the first stage, we obtain the statistical characteristics of the current traffic on the QRD network. In the second stage, the most suitable traffic models are selected for the current characteristics of the QRD network such as outof-saturation operation and management of heterogeneous traffic. In the third stage, we define a performance metric th

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WANG, JING, PENGJIAN SHANG, and XIAOJUN ZHAO. "A NEW TRAFFIC SPEED FORECASTING METHOD BASED ON BI-PATTERN RECOGNITION." Fluctuation and Noise Letters 10, no. 01 (2011): 59–75. http://dx.doi.org/10.1142/s0219477511000405.

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Short-term traffic forecasting has played a key role in supporting the need of proactive and dynamic traffic control system. K-nearest neighbor (KNN) nonparametric regression models have been widely used in traffic prediction. KNN models give predictions based on the future state of traffic speed that is completely determined by the current state, but with no dependence on the past sequences of traffic speed that produced the current state. In fact, traffic speed is not completely random in nature, and some patterns repeat in the traffic stream. In this paper, we proposed a methodology called

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Hernández-Vega, Henry, and Carolina Matamoros-Jiménez. "Clustering Approach to Generate Pedestrian Traffic Pattern Groups." Ciencia e Ingeniería Neogranadina 31, no. 2 (2021): 41–60. http://dx.doi.org/10.18359/rcin.4403.

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    This study shows the development of patterns of temporal hourly volume distributions in an urban area in Costa Rica, based on a cluster analysis of pedestrian data. This study aims to establish specific pattern groups for the temporal variation of weekday pedestrian volumes applying cluster analysis in the central business district of Guadalupe in San José. For 46 counting sites, vectors with the weekday hourly factors, the proportion of the daily pedestrian traffic, were estimated. A hierarchical cluster method was implemented to group the vectors of hourly factor

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Jean, L. M., L. Swee Han, V. Anantharaman, and Y. Allen. "Patterns of injuries sustained by pedestrians in road traffic accidents at the singapore general hospital." Annals of Emergency Medicine 44, no. 4 (2004): S129. http://dx.doi.org/10.1016/j.annemergmed.2004.07.413.

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