Method for Determining the Maximum Allowable Pavement Rutting from the Condition of Ensuring the Safety of Traffic in Rainy Weather

2021 ◽  
Author(s):  
Yu. V. Kuznetsov ◽  
D. A. Moiseenko ◽  
P. V. Plotnikov
Keyword(s):  
Rainy Weather

scholarly journals Prediction and Analysis of the Severity and Number of Suburban Accidents Using Logit Model, Factor Analysis and Machine Learning: A case study in a developing country

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Meisam Ghasedi ◽  
Maryam Sarfjoo ◽  
Iraj Bargegol
Keyword(s):  
Machine Learning ◽  
Factor Analysis ◽  
Logit Model ◽  
Predictive Power ◽  
Dominant Role ◽  
Learning Approaches ◽  
Lighting Condition ◽  
Rainy Weather ◽  
Pedestrian Accidents ◽  
Effective Principal

AbstractThe purpose of this study is to investigate and determine the factors affecting vehicle and pedestrian accidents taking place in the busiest suburban highway of Guilan Province located in the north of Iran and provide the most accurate prediction model. Therefore, the effective principal variables and the probability of occurrence of each category of crashes are analyzed and computed utilizing the factor analysis, logit, and Machine Learning approaches simultaneously. This method not only could contribute to achieving the most comprehensive and efficient model to specify the major contributing factor, but also it can provide officials with suggestions to take effective measures with higher precision to lessen accident impacts and improve road safety. Both the factor analysis and logit model show the significant roles of exceeding lawful speed, rainy weather and driver age (30–50) variables in the severity of vehicle accidents. On the other hand, the rainy weather and lighting condition variables as the most contributing factors in pedestrian accidents severity, underline the dominant role of environmental factors in the severity of all vehicle-pedestrian accidents. Moreover, considering both utilized methods, the machine-learning model has higher predictive power in all cases, especially in pedestrian accidents, with 41.6% increase in the predictive power of fatal accidents and 12.4% in whole accidents. Thus, the Artificial Neural Network model is chosen as the superior approach in predicting the number and severity of crashes. Besides, the good performance and validation of the machine learning is proved through performance and sensitivity analysis.

scholarly journals Winter Wheat Straw Decomposition under Different Nitrogen Fertilizers

Agriculture ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 83
Author(s):  
Gabriela Mühlbachová ◽  
Pavel Růžek ◽  
Helena Kusá ◽  
Radek Vavera ◽  
Martin Káš
Keyword(s):  
Winter Wheat ◽  
Wheat Straw ◽  
Soil Surface ◽  
Weather Conditions ◽  
Mineral Nitrogen ◽  
Nitrogen Fertilizers ◽  
Pig Slurry ◽  
Straw Decomposition ◽  
Rainy Weather ◽  
N Fertilisers

The climate changes and increased drought frequency still more frequent in recent periods bring challenges to management with wheat straw remaining in the field after harvest and to its decomposition. The field experiment carried out in 2017–2019 in the Czech Republic aimed to evaluate winter wheat straw decomposition under different organic and mineral nitrogen fertilizing (urea, pig slurry and digestate with and without inhibitors of nitrification (IN)). Treatment Straw 1 with fertilizers was incorporated in soil each year the first day of experiment. The Straw 2 was placed on soil surface at the same day as Straw 1 and incorporated together with fertilizers after 3 weeks. The Straw 1 decomposition in N treatments varied between 25.8–40.1% and in controls between 21.5–33.1% in 2017–2019. The Straw 2 decomposition varied between 26.3–51.3% in N treatments and in controls between 22.4–40.6%. Higher straw decomposition in 2019 was related to more rainy weather. The drought observed mainly in 2018 led to the decrease of straw decomposition and to the highest contents of residual mineral nitrogen in soils. The limited efficiency of N fertilisers on straw decomposition under drought showed a necessity of revision of current strategy of N treatments and reduction of N doses adequately according the actual weather conditions.

scholarly journals Precipitation Characteristics of Warm Season Weather Types in the Southeastern United States of America

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1001
Author(s):  
Jian-Hua Qian ◽  
Brian Viner ◽  
Stephen Noble ◽  
David Werth
Keyword(s):  
United States ◽  
El Niño ◽  
Gulf Coast ◽  
El Nino ◽  
River Valley ◽  
Northern Great Plains ◽  
Ohio River ◽  
Fair Weather ◽  
Weather Types ◽  
Rainy Weather

Daily weather types (WTs) over the Southeast United States have been analyzed using 850 hPa winds from reanalysis data from March to October of 1979–2019. Six WTs were obtained. WTs 1–3 represent mid-latitude synoptic systems propagating eastward. WT4 is a summer-type pattern predominantly occurring in June–August, with the center of the North Atlantic Subtropical High (NASH) along the Gulf coast in the southern United States. WT5 is most frequent from August to middle October, with the NASH pushed further north and southerly winds over the northern Great Plains. An anticyclone centered at the Carolina coast characterizes WT6, which occurs in all months but is slightly more frequent in the spring and fall, especially in October, corresponding to fair weather in the region. WTs 1, 2 and 3 can persist for only a few days. WTs 4, 5 and 6 can have long spells of persistence. Besides self-persistence, the most observed progression loop is WT1 to WT2, to WT3, and then back to WT1, corresponding to eastward-propagating waves. WTs 4 and 5 are likely to show persistence, with long periods of consecutive days. WT6 usually persists but can also transfer to WT3, i.e., a change from fair weather in the Southeast U.S. to rainy weather in the Mississippi River Valley. A diurnal cycle of precipitation is apparent for each WT, especially over coastal plains. The nocturnal precipitation in central U.S. is associated with WT3. WTs 1–3 are more frequent in El Niño years, corresponding to stronger westerly wave activities and above normal rainfall in the Southeast U.S. in the spring. The positive rainfall anomaly in the Mississippi and Ohio River valley in El Niño years is also associated with more frequent WT3.

Model and algorithm of stochastic dynamic traffic assignment based on dynamic rainfall intensity

2021 ◽  
pp. 1-11
Author(s):  
Xun Ji ◽  
Chunfu Shao
Keyword(s):  
Cost Function ◽  
Traffic Flow ◽  
Rainfall Intensity ◽  
Traffic Assignment ◽  
Dynamic Traffic Assignment ◽  
Dynamic Network ◽  
Travel Cost ◽  
Stochastic Dynamic ◽  
Dynamic Traffic ◽  
Rainy Weather

Frequent occurrence of urban rainy weather, especially rainstorm weather, affects transportation operation and safety, so it is essential that effective intervention measures to recover disordered traffic be adopted and then analyzed for their influence on the dynamic network. Therefore, models and algorithm to show dynamic traffic flow of traffic network in rainy weather are a fundamental need and have drawn great interest from governments and scholars. In this paper, innovative content contains a travel cost function considering rainfall intensity; considering the travel cost function, a dynamic traffic assignment model based on dynamic rainfall intensity is built. Then a corresponding algorithm is designed. Moreover, this study designs three scenarios under rainfall and analyzes the influence of the rainfall on an example network. The results show that rainfall has a significant effect on traffic flow. The finding proved the proposed models and algorithm can express the development trend of path flow rate on a dynamic network under rainfall.

Fungi Associated with Garlic During the Cropping Season, with Focus on Fusarium proliferatum and F. oxysporum

2021 ◽  
Author(s):  
Letizia Mondani ◽  
Giorgio Chiusa ◽  
Paola Battilani
Keyword(s):  
Seed Transmission ◽  
Fusarium Proliferatum ◽  
Growth Stages ◽  
Sowing Time ◽  
Dry Rot ◽  
Cropping Season ◽  
Rainy Weather ◽  
Crop Growth Stage ◽  
Growing Conditions ◽  
The Impact

Fusarium proliferatum has been reported as the main causal agent of garlic dry rot during the postharvest stage, but information on this fungus during the crop growth stage is lacking. We focused on the cropping season of garlic (Allium sativum L.) in the field, until its harvest, with the aim of clarifying the role of F. proliferatum in bulb infection as well as the impact of crop growing conditions on pathogen-plant interaction. Studies were conducted in Piacenza (northern Italy) for three seasons from 2016 to 2019. Six garlic farms were sampled. A different field was sampled every year. Soil samples were recovered at sowing time for the counting of fungal colony forming units (CFU). Plant samples were collected at three growth stages, from BBCH 15 (fifth leaf visible) to BBCH 49 (ripening), for which disease severity assessment and fungi isolations were performed. Fusarium was the most frequently isolated genus, of which F. proliferatum and F. oxysporum were the dominant species. F. proliferatum registered the highest incidence in all the farms tested, but F. oxysporum was dominant in the first year of the study. F. oxysporum incidence was correlated with dry weather, whereas F. proliferatum was correlated with rainy weather. In conclusion, our result confirms the association of F. proliferatum with garlic bulbs from the crop’s early growth stages, suggesting potential seed transmission as a source of this fungal pathogen. Further studies should investigate the link between fusaria occurrence in the field and dry rot outbreaks occurring postharvest and during storage of garlic.

Seasonal Dynamics of Internode Length of Salix triandra L. (Salicaceae) Against the Background of Short-Term Atmospheric Drought

2021 ◽  
pp. 104-112
Author(s):  
Alexey A. Afonin
Keyword(s):  
Seasonal Dynamics ◽  
Internode Length ◽  
Summer Drought ◽  
Sharp Change ◽  
Regression Equations ◽  
Endogenous Rhythms ◽  
Seasonal Trends ◽  
Rainy Weather ◽  
Short Period ◽  
Salix Triandra

Almond willow (Salix triandra L.) is a valuable basket species that is used to create plantings for various purposes. He occupies a special place in the system of the genus Salix. He can be used as a model object to identify patterns of morphogenesis of shoots. Object of research: model inbred population of almond willow in culture. Subject of research: seasonal dynamics of internode length on annual shoots of three-year-old seedlings willow of almond willow. The purpose of the research: to identify the seasonal dynamics of the length of internodes on annual shoots of almond willow against the background of a sharp change in early summer drought by cold rainy weather. Empirical methods for obtaining initial data: comparative-morphological. The obtained data were processed using the methods of analysis of dynamics series. It is found that seasonal trends in the dynamics of internode length are described by second-order regression equations with varying reliability. The configuration and topology of nonlinear seasonal trends are determined by individual differences between seedlings. The dynamics of deviations of internode length from seasonal trends correlates with the dynamics of hydrothermic conditions. Deviations in the length of internodes from seasonal trends are cyclical. The empirical series of deviations of the internode length from seasonal trends with high reliability are approximated by the sums of harmonic oscillations. The maximum contribution to the cyclical deviations of the internode length from seasonal trends is made by the rhythm with a period of fluctuations of 54 days. On most shoots, the influence of rhythms with a period of fluctuations of 36 and 27 days can be traced. Short-period rhythms detected on different shoots are irregular. In most observations, the specific rhythms of seasonal dynamics of internode length are determined by differences between shoots. The identified rhythms do not depend on hydrothermic conditions, on the length of shoots, on the length of internodes, or on seasonal trends in the dynamics of internode length. The hypothesis that the relationship between the dynamics of deviations in the length of internodes from seasonal trends and the dynamics of hydrothermic conditions is random is substantiated. Cyclicity deviations of internode length from seasonal trends are determined by endogenous rhythms of development.

scholarly journals Hubungan Shalat Fardu Berjamaah Dengan Kecerdasan Emosional Pada Jamaah Mesjid Al Jihad Banjarmasin

2017 ◽  
Vol 5 (1) ◽  
pp. 25
Author(s):  
Ahmad Jauhari ◽  
Asmaran AS ◽  
Siti Faridah
Keyword(s):  
Emotional Intelligence ◽  
Weather Conditions ◽  
Technical Data ◽  
Rainy Weather ◽  
The Face ◽  
Qualitative Descriptive ◽  
Distance Difference ◽  
Stress Burden ◽  
Heart And Mind ◽  
Relationship Of

Al Jihad  Mosque Banjarmasin is a mosque that is identical with Muhammadiyah, this mosque is followed by many pilgrims and loyal at the time of the implementation of prayers fardu congregation. Jamaah consists of various groups regardless of background, both in terms of age, economy, organization and even the sick pilgrims (post-stroke) are actively involved in congregation. Active Jamaat prayers in congregation do not only come from residents around the mosque complex, but also many pilgrims who come from outside the mosque complex, even the distance difference between their residence with the mosque a few kilometers. In heavy rainy weather conditions, they still enthusiastically follow the prayers in congregation fardu mosque. In addition, there are things that are felt by pilgrims such as comfort, tranquility of heart and mind, emotional stability, silaturrahim which all is related to emotional intelligence.In this study, the main problem is how is the relationship of prayer in congregation with emotional intelligence in the congregation of Al Jihad Mosque Banjarmasin ?. The method used is quantitative and qualitative descriptive method with methodological arrangement such as approach and type of research, research location, population and sample, data and data source, procedure and data collection, quantitative and qualitative technical data analysis.The result of the study found that there is a correlation between salat fardu congregation with emotional intelligence, this is proved by the data from questionnaires from 30 pilgrims (respondents) that is: able to control the impulse of worldly lusts with the highest opinion is 60% said yes and 40% stated sometimes .Motivating yourself with the highest opinion is 90% states yes and 10% states sometimes. Able to survive in the face of trials with the highest opinion is 86.67 states yes and 13, 33 states sometimes. No exaggeration with the highest opinion is 90% states yes and 10% states sometimes. Being able to set the mood with the highest opinion is 86.33% and 13.33 states sometimes. Keeping the stress burden does not cripple the thinking ability with the highest opinion is 90% states yes and 10% states sometimes. The ability to empathize and pray with the highest opinion is 90% say yes and 10% say sometimes.

scholarly journals Analysis of wind power potential as an electricity source for safety light and sign on limestone mining hauling road

2021 ◽  
Vol 331 ◽  
pp. 02016
Author(s):  
Ikhsan Purnama ◽  
Muhammad Imran Hamid
Keyword(s):  
Wind Power ◽  
Average Wind Speed ◽  
Mining Areas ◽  
Heavy Equipment ◽  
Rainy Weather ◽  
Wind Potential ◽  
Steep Terrain ◽  
Unsafe Condition ◽  
The Right ◽  
Parameter Values

A work accident can occur anytime and anywhere to the worker if they take unsafe action and are in an unsafe condition. Mining areas located in the hills have unsafe conditions for operating heavy equipment, such as steep terrain conditions, slippery roads, and foggy weather, and lack of lighting. Installation of light assign is the right step in reducing work accidents at night, foggy and rainy weather. Measurement of wind data and calculation of wind potential statistically using Weibull distribution. The parameter values of scale and shape are 1.67 and 1,71 respectively, with an average wind speed of 1,49 m/s and the wind power potential of 3.14 W/m2. Based on measurement and analysis results, this quarry always gets wind gusts both day and night, so it has the potential to take advantage of wind energy either on a small turbine scale or in small and medium electric power.

scholarly journals Improving the transfer learning performances in the classification of the automotive traffic roads signs

2021 ◽  
Vol 234 ◽  
pp. 00064
Author(s):  
Anass Barodi ◽  
Abderrahim Bajit ◽  
Mohammed Benbrahim ◽  
Ahmed Tamtaoui
Keyword(s):  
Transfer Learning ◽  
Intelligent System ◽  
Confusion Matrix ◽  
Weather Conditions ◽  
Classification Model ◽  
Road Signs ◽  
Road Sign ◽  
Rainy Weather ◽  
Depth Analysis ◽  
Driving Assistance

This paper represents a study for the realization of a system based on Artificial Intelligence, which allows the recognition of traffic road signs in an intelligent way, and also demonstrates the performance of Transfer Learning for object classification in general. When systems are trained on the aspects of human visualization (HVS), which helps or generates the same decisions, the construct robust and efficient systems. This allows us to avoid many environmental risks, both for weather conditions, such as cloudy or rainy weather that causes obscured vision of signs, but the main objective is to avoid all road risks that are dangerous to achieve road safety, such as accidents due to non-compliance with traffic rules, both for vehicles and passengers. However, simply collecting road signs in different places does not solve the problem, an intelligent system for classifying road signs is needed to improve the safety of people in its environment. This study proposed a traffic road sign classification system that extracts visual characteristics from a Convolution Neural Network (CNN) classification model. This model aims to assign a class to the image of the road sign through the classifier with the most efficient optimized. Then the evaluation of its effectiveness according to several criteria, using the Confusion Matrix and the classification report, with an in-depth analysis of the results obtained by the images that are taken from the urban world. The results obtained by the system are encouraging in comparison with the systems developed in the scientific literature, for example, the Advanced Driving Assistance Systems (ADAS) of the sector automobile.

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