Search results for: multivariate road index
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5192

Search results for: multivariate road index

4892 Formulation and Test of a Model to explain the Complexity of Road Accident Events in South Africa

Authors: Dimakatso Machetele, Kowiyou Yessoufou

Abstract:

Whilst several studies indicated that road accident events might be more complex than thought, we have a limited scientific understanding of this complexity in South Africa. The present project proposes and tests a more comprehensive metamodel that integrates multiple causality relationships among variables previously linked to road accidents. This was done by fitting a structural equation model (SEM) to the data collected from various sources. The study also fitted the GARCH Model (Generalized Auto-Regressive Conditional Heteroskedasticity) to predict the future of road accidents in the country. The analysis shows that the number of road accidents has been increasing since 1935. The road fatality rate follows a polynomial shape following the equation: y = -0.0114x²+1.2378x-2.2627 (R²=0.76) with y = death rate and x = year. This trend results in an average death rate of 23.14 deaths per 100,000 people. Furthermore, the analysis shows that the number of crashes could be significantly explained by the total number of vehicles (P < 0.001), number of registered vehicles (P < 0.001), number of unregistered vehicles (P = 0.003) and the population of the country (P < 0.001). As opposed to expectation, the number of driver licenses issued and total distance traveled by vehicles do not correlate significantly with the number of crashes (P > 0.05). Furthermore, the analysis reveals that the number of casualties could be linked significantly to the number of registered vehicles (P < 0.001) and total distance traveled by vehicles (P = 0.03). As for the number of fatal crashes, the analysis reveals that the total number of vehicles (P < 0.001), number of registered (P < 0.001) and unregistered vehicles (P < 0.001), the population of the country (P < 0.001) and the total distance traveled by vehicles (P < 0.001) correlate significantly with the number of fatal crashes. However, the number of casualties and again the number of driver licenses do not seem to determine the number of fatal crashes (P > 0.05). Finally, the number of crashes is predicted to be roughly constant overtime at 617,253 accidents for the next 10 years, with the worse scenario suggesting that this number may reach 1 896 667. The number of casualties was also predicted to be roughly constant at 93 531 overtime, although this number may reach 661 531 in the worst-case scenario. However, although the number of fatal crashes may decrease over time, it is forecasted to reach 11 241 fatal crashes within the next 10 years, with the worse scenario estimated at 19 034 within the same period. Finally, the number of fatalities is also predicted to be roughly constant at 14 739 but may also reach 172 784 in the worse scenario. Overall, the present study reveals the complexity of road accidents and allows us to propose several recommendations aimed to reduce the trend of road accidents, casualties, fatal crashes, and death in South Africa.

Keywords: road accidents, South Africa, statistical modelling, trends

Procedia PDF Downloads 139
4891 Sliding Mode Controller for Active Suspension System on a Passenger Car Model

Authors: Nouby M. Ghazaly, Ahmed O. Moaaz, Mostafa Makrahy

Abstract:

The main purpose of a car suspension system is to reduce the vibrations resulting from road roughness. The main objective of this research paper is to decrease vibration and improve passenger comfort through controlling car suspension system using sliding mode control techniques. The mathematical model for passive and active suspensions systems for quarter car model which subject to excitation from different road profiles is obtained. The active suspension system is synthesized based on sliding mode control for a quarter car model. The performance of the sliding mode control is determined through computer simulations using MATLAB and SIMULINK toolbox. The simulated results plotted in time domain, and root mean square values. It is found that active suspension system using sliding mode control improves the ride comfort and decrease vibration.

Keywords: quarter car model, active suspension system, sliding mode control, road profile

Procedia PDF Downloads 282
4890 Health Risk Assessment According to Exposure with Heavy Metals and Physicochemical Parameters; Water Quality Index and Contamination Degree Evaluation in Bottled Water

Authors: Samaneh Abolli, Mahmood Alimohammadi

Abstract:

The survey analyzed 71 bottled water brands in Tehran, Iran, examining 10 physicochemical parameters and 16 heavy metals. The water quality index (WQI) approach was used to assess water quality, and methods such as carcinogen risk (CR) and hazard index (HI) were employed to evaluate health risks. The results indicated that the bottled water had good quality overall, but some brands were of poor or very poor quality. The study also revealed significant human health risks, especially for children, due to the presence of minerals and heavy metals in bottled water. Correlation analyses and risk assessments for various substances were conducted, providing valuable insights into the potential health impacts of the analyzed bottled water.

Keywords: bottled wate, rwater quality index, health risk assessment, contamination degree, heavy metal evaluation index

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4889 EWMA and MEWMA Control Charts for Monitoring Mean and Variance in Industrial Processes

Authors: L. A. Toro, N. Prieto, J. J. Vargas

Abstract:

There are many control charts for monitoring mean and variance. Among these, the X y R, X y S, S2 Hotteling and Shewhart control charts, for mentioning some, are widely used for monitoring mean a variance in industrial processes. In particular, the Shewhart charts are based on the information about the process contained in the current observation only and ignore any information given by the entire sequence of points. Moreover, that the Shewhart chart is a control chart without memory. Consequently, Shewhart control charts are found to be less sensitive in detecting smaller shifts, particularly smaller than 1.5 times of the standard deviation. These kind of small shifts are important in many industrial applications. In this study and effective alternative to Shewhart control chart was implemented. In case of univariate process an Exponentially Moving Average (EWMA) control chart was developed and Multivariate Exponentially Moving Average (MEWMA) control chart in case of multivariate process. Both of these charts were based on memory and perform better that Shewhart chart while detecting smaller shifts. In these charts, information the past sample is cumulated up the current sample and then the decision about the process control is taken. The mentioned characteristic of EWMA and MEWMA charts, are of the paramount importance when it is necessary to control industrial process, because it is possible to correct or predict problems in the processes before they come to a dangerous limit.

Keywords: control charts, multivariate exponentially moving average (MEWMA), exponentially moving average (EWMA), industrial control process

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4888 Single Fly Over as a Solution to Congestion of Intersection Junction: Case Study of Jalan Jatingaleh Semarang

Authors: Rachmat Mudiyono, Siti Sumiati

Abstract:

In the next few years, traffic will happen most of the time. This was triggered by the growing rate of vehicles againts the road capacity which is not balance. All the time the congestion in the city of Semarang has been occured at peak hours. Congestion also occured in between Teuku Umar and Setia Budi road Jatingaleh because of a plot intersection (Kesatrian intersection, PLN intersection and Jatingaleh intersection) with the Toll Road. Jatingaleh is located in the southern city of Semarang which is a central meeting point between the upper and lower Semarang where the vehicle flows in through a combination of local current and regional traffic, and the flow of vehicles coming in and out from highway. The main cause of the problems that occurred in the area of Jatingaleh is due to the numbers of vehicles movement that occurs at the intersections. With the above issues, it is necessary to analyse the existing conditions and look into some solutions. Before carrying out an analysis of field surveys at peak hours for example morning (06:00 to 08:00 am) and for the afternoon (04:00 to 06:00 pm)should be conducted, then the number of vehicles is counted manually with “short-breakcounting” according to types of vehicles. From the analysis we found that the degree of saturation (DS) is 1.61 between Teuku Umar and Setia Budi road during the morning peak hours and 1.56 during the afternoon peak hours. This means that the capacity of the existing road is no longer able to accommodate the traffic flow. One of the solutions for the congestion that occurs at the intersection of Jatingaleh is to apply the efficiency of the intersection that is not in a plot with a Fly over, Underpass and the combination of Fly Over-Underpass. Base on the flow reduction calculation with 3 comparative modeling it shows that the Fly Over is the most technically efficient to be applied in this research.

Keywords: single fly over, congestion, intersection, interchange

Procedia PDF Downloads 370
4887 Clustering of Extremes in Financial Returns: A Comparison between Developed and Emerging Markets

Authors: Sara Ali Alokley, Mansour Saleh Albarrak

Abstract:

This paper investigates the dependency or clustering of extremes in the financial returns data by estimating the extremal index value θ∈[0,1]. The smaller the value of θ the more clustering we have. Here we apply the method of Ferro and Segers (2003) to estimate the extremal index for a range of threshold values. We compare the dependency structure of extremes in the developed and emerging markets. We use the financial returns of the stock market index in the developed markets of US, UK, France, Germany and Japan and the emerging markets of Brazil, Russia, India, China and Saudi Arabia. We expect that more clustering occurs in the emerging markets. This study will help to understand the dependency structure of the financial returns data.

Keywords: clustring, extremes, returns, dependency, extermal index

Procedia PDF Downloads 379
4886 Road Accidents to School Children’s in Dar Es Salaam, Tanzania

Authors: Kabuga Daniel

Abstract:

Road accidents resulting to deaths and injuries have become a new public health challenge especially in developing countries including Tanzania. Reports from Tanzania Traffic Police Force shows that last year 2016 accidents increased compare to previous year 2015, accident happened from 3710 up to 5219, accidents and safety data indicate that children are the most vulnerable to road crashes where 78 pupils died and 182 others were seriously injured in separate roads accident last year. A survey done by Amend indicates that Pupil mode of transport in Dar es salaam schools are by walk 87%, bus 9.21%, car 1.32%, motorcycle 0.88%, 3-wheeler 0.24%, train 0.14%, bicycle 0.10%, ferry 0.07%, and combined mode 0.44%. According to this study, majority of school children’s uses walking mode, most of school children’s agreed to continue using walking mode and request to have signs for traffic control during crossing road like STOP sign and CHILD CROSSING sign for safe crossing. Because children not only sit inside this buses (Daladala) but also they walk in a group to/from school, and few (33.2%) parents or adults are willing to supervise their children’s during working to school while 50% of parents agree to let their children walking alone to school if the public transport started from nearby street. The study used both qualitative and quantitative methods of research by conducting physical surveying on sample districts. The main objectives of this research are to carries out all factors affecting school children’s when they use public road, to promote and encourage the safe use of public road by all classes especially pupil or student through the circulation of advice, information and knowledge gain from research and to recommends future direction for the developments for road design or plan to vulnerable users. The research also critically analyze the problems causing death and injuries to school children’s in Dar es Salaam Region. This study determines the relationship between road traffic accidents and factors, such as socio-economic, status, and distance from school, number of sibling, behavioral problems, knowledge and attitudes of public and their parents towards road safety and parent educational study traffic. The study comes up with some of recommendations including Infrastructure Improvements like, safe footpaths, Safe crossings, Speed humps, Speed limits, Road signs. However, Planners and policymakers wishing to increase walking and cycling among children need to consider options that address distance constraints, the land use planners and transport professionals use better understanding of the various factors that affect children’s choices of school travel mode, results suggest that all school travel attributes should be considered during school location.

Keywords: accidents, childrens, school, Tanzania

Procedia PDF Downloads 218
4885 Life Cycle Carbon Dioxide Emissions from the Construction Phase of Highway Sector in China

Authors: Yuanyuan Liu, Yuanqing Wang, Di Li

Abstract:

Carbon dioxide (CO2) emissions mitigation from road construction activities is one of the potential pathways to deal with climate change due to its higher use of materials, machinery energy consumption, and high quantity of vehicle and equipment fuels for transportation and on-site construction activities. Aiming to assess the environmental impact of the road infrastructure construction activities and to identify hotspots of emissions sources, this study developed a life-cycle CO2 emissions assessment framework covering three stages of material production, to-site and on-site transportation under the guidance of the principle of LCA ISO14040. Then streamlined inventory analysis on sub-processes of each stage was conducted based on the budget files from cases of highway projects in China. The calculation results were normalized into functional unit represented as ton per km per lane. Then a comparison between the amount of emissions from each stage, and sub-process was made to identify the major contributor in the whole highway lifecycle. In addition, the calculating results were used to be compared with results in other countries for understanding the level of CO2 emissions associated with Chinese road infrastructure in the world. The results showed that materials production stage produces the most of the CO2 emissions (for more than 80%), and the production of cement and steel accounts for large quantities of carbon emissions. Life cycle CO2 emissions of fuel and electric energy associated with to-site and on-site transportation vehicle and equipment are a minor component of total life cycle CO2 emissions from highway project construction activities. Bridges and tunnels are dominant large carbon contributor compared to the road segments. The life cycle CO2 emissions of road segment in highway project in China are slightly higher than the estimation results of highways in European countries and USA, about 1500 ton per km per lane. In particularly, the life cycle CO2 emissions of road pavement in majority cities all over the world are about 500 ton per km per lane. However, there is obvious difference between the cities when the estimation on life cycle CO2 emissions of highway projects included bridge and tunnel. The findings of the study could offer decision makers a more comprehensive reference to understand the contribution of road infrastructure to climate change, especially understand the contribution from road infrastructure construction activities in China. In addition, the identified hotspots of emissions sources provide the insights of how to reduce road carbon emissions for development of sustainable transportation.

Keywords: carbon dioxide emissions, construction activities, highway, life cycle assessment

Procedia PDF Downloads 239
4884 Numerical Analysis of Rainfall-Induced Roadside Slope Failures and Their Stabilizing Solution

Authors: Muhammad Suradi, Sugiarto, Abdullah Latip

Abstract:

Many roadside slope failures occur during the rainy season, particularly in the period of extreme rainfall along Connecting National Road of Salubatu-Mambi, West Sulawesi, Indonesia. These occurrences cause traffic obstacles and endanger people along and around the road. Research collaboration between P2JN (National Road Construction Board) West Sulawesi Province, who authorize to supervise the road condition, and Ujung Pandang State Polytechnic (Applied University) was established to cope with the landslide problem. This research aims to determine factors triggering roadside slope failures and their optimum stabilizing solution. To achieve this objective, site observation and soil investigation were carried out to obtain parameters for analyses of rainfall-induced slope instability and reinforcement design using the SV Flux and SV Slope software. The result of this analysis will be taken into account for the next analysis to get an optimum design of the slope reinforcement. The result indicates some factors such as steep slopes, sandy soils, and unvegetated slope surface mainly contribute to the slope failures during intense rainfall. With respect to the contributing factors as well as construction material and technology, cantilever/butressing retaining wall becomes the optimum solution for the roadside slope reinforcement.

Keywords: roadside slope, failure, rainfall, slope reinforcement, optimum solution

Procedia PDF Downloads 80
4883 Sustainable Development, China’s Emerging Role via One Belt, One Road

Authors: Saeid Rabiei Majd, Motahareh Alvandi, Mehrad Rabiei

Abstract:

The rapid economic and technological development of any country depends on access to cheap sources of energy. Competition for access to petroleum resources is always accompanied by numerous environmental risks. These factors have caused more attention to environmental issues and sustainable development in petroleum contracts and activities. Nowadays, a sign of developed countries is adhering to the principles and rules of international environmental law and sustainable development of commercial contracts. China has entered into play through the massive project plan, One Belt, One Road. China is becoming a new emerging power in the world. China's bilateral investment treaties have an impact on environmental rights and sustainable development through regional and international foreign direct investment. The aim of this research is to examine China's key position to promote and improve environmental principles and international law and sustainable development in the energy sector in the world through the initiative, One Belt, One Road. Based on this hypothesis, it seems that in the near future, China's investment bilateral investment treaties will become popular investment model used in global trade, especially in the field of energy and sustainable development. They will replace the European and American models. The research method is including literature review, analytical and descriptive methods.

Keywords: principles of sustainable development, oil and gas law, Chinas BITs, One Belt One Road, environmental rights

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4882 Environmental Impact Assessment Methodology of the Tirana–Elbasan Road Project

Authors: Aurora Cerri, Niko Pollojani

Abstract:

The Tirana – Elbasan Road project is the most important highway project in Albania, constructed in the period May 2011 - ongoing. This project included construction of 38 km highway category road including 2.6 km of tunnel. It serves as a corridor connecting the Tirana, Capital of Albania and South-East area, and in the near future it is expected to continue in the direction of Macedonian border. Environmental Impact Assesment procedure for this project is provided by the Albanian Environmental Law No. 10431. This law establishes the regulation of procedures for identifying, assessment and reporting on the effects of certain projects on the environment, and the associated administrative procedures, during the decision-making process by the Ministry of Environment and Tourism for issuing environmental permit, and ensures that all relevant information concerning the environment are provided and considered. Due to the nature and size of the project, during the environmental impact assessment process, the European Union legislation, namely the EIA Directive 85/337 / EEC is considered. Moreover, in some cases, due to the lack of national standards and practical guidelines, when necessary those of EU member countries are considered. This paper presents an analysis of the EIA procedure followed on ‘Tirana – Elbasan’ Road project, with a focus on the application of the main stages of the procedure such as: screening, scoping, review, the EIA report; and consideration of alternatives, measures for impact prevention and reduction, and the public hearing T/discussion.

Keywords: highway, environmental impact assesment, Tirana, prevention

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4881 A Posteriori Trading-Inspired Model-Free Time Series Segmentation

Authors: Plessen Mogens Graf

Abstract:

Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

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4880 Characterization of CuO Incorporated CMOS Dielectric for Fast Switching System

Authors: Nissar Mohammad Karim, Norhayati Soin

Abstract:

To ensure fast switching in high-K incorporated Complementary Metal Oxide Semiconductor (CMOS) transistors, the results on the basis of d (NBTI) by incorporating SiO2 dielectric with aged samples of CuO sol-gels have been reported. Precursor ageing has been carried out for 4 days. The minimum obtained refractive index is 1.0099 which was found after 3 hours of adhesive UV curing. Obtaining a low refractive index exhibits a low dielectric constant and hence a faster system.

Keywords: refractive index, Sol-Gel, precursor aging, aging

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4879 Phytoplankton Community and Saprobic Pollution Index of Warm Water Fishes Ponds at East of Golestan Province: Case Study: Gonbade Kavous City

Authors: Mehrdad Kamali-Sanzighi, Maziar Kamali-Sanzighi

Abstract:

The aim of this investigation is to study the phytoplankton and saprobic index at warm water fish ponds in the East of Golestan province, Gonbade Kavous city. Phytoplankton and ciliate sampling were done monthly during one season of culture. Finally, 39 genera from 7 classes of phytoplankton and 4 genera from the ciliate group were identified. Although, among different classes, Chlorophyceae, Cyanophyceae, Bacillariophyceae, Charophyceae, Chrysophyceae, Dinophyceae, and Euglenophyceae had the highest and lowest frequency percent of phytoplankton community with 23, 21, 20, 14, 11, 6 and 5 percent respectively. The results show that there are no significant differences between the saprobic index of different ponds (P > 0.05). But there are significant differences between the saprobic index value of different months and seasons during season culture (P < 0.05). Also, in current research, the saprobic index indicated the ß-mesosaprob water quality level. There was a general tends of decrease in the saprobic index value from the beginning to the end of the culture season. Parameters such as biomass increase of grower fishes, an increase of introduced chemical fertilizer and manure sedimentation, uneaten fish feed, fish fecal, and no regular exchangeable water resources are some of these changes' reasons.

Keywords: fish pond, Golestan Province, saprobi index, phytoplankton, water quality

Procedia PDF Downloads 108
4878 Public-Private Partnership for Critical Infrastructure Resilience

Authors: Anjula Negi, D. T. V. Raghu Ramaswamy, Rajneesh Sareen

Abstract:

Road infrastructure is emphatically one of the top most critical infrastructure to the Indian economy. Road network in the country of around 3.3 million km is the second largest in the world. Nationwide statistics released by Ministry of Road, Transport and Highways reveal that every minute an accident happens and one death every 3.7 minutes. This reported scale in terms of safety is a matter of grave concern, and economically represents a national loss of 3% to the GDP. Union Budget 2016-17 has allocated USD 12 billion annually for development and strengthening of roads, an increase of 56% from last year. Thus, highlighting the importance of roads as critical infrastructure. National highway alone represent only 1.7% of the total road linkages, however, carry over 40% of traffic. Further, trends analysed from 2002 -2011 on national highways, indicate that in less than a decade, a 22 % increase in accidents have been reported, but, 68% increase in death fatalities. Paramount inference is that accident severity has increased with time. Over these years many measures to increase road safety, lessening damage to physical assets, reducing vulnerabilities leading to a build-up for resilient road infrastructure have been taken. In the context of national highway development program, policy makers proposed implementation of around 20 % of such road length on PPP mode. These roads were taken up on high-density traffic considerations and for qualitative implementation. In order to understand resilience impacts and safety parameters, enshrined in various PPP concession agreements executed with the private sector partners, such highway specific projects would be appraised. This research paper would attempt to assess such safety measures taken and the possible reasons behind an increase in accident severity through these PPP case study projects. Delving further on safety features to understand policy measures adopted in these cases and an introspection on reasons of severity, whether an outcome of increased speeds, faulty road design and geometrics, driver negligence, or due to lack of discipline in following lane traffic with increased speed. Assessment exercise would study these aspects hitherto to PPP and post PPP project structures, based on literature review and opinion surveys with sectoral experts. On the way forward, it is understood that the Ministry of Road, Transport and Highway’s estimate for strengthening the national highway network is USD 77 billion within next five years. The outcome of this paper would provide an understanding of resilience measures adopted, possible options for accessible and safe road network and its expansion to policy makers for possible policy initiatives and funding allocation in securing critical infrastructure.

Keywords: national highways, policy, PPP, safety

Procedia PDF Downloads 233
4877 Application of Multivariate Statistics and Hydro-Chemical Approach for Groundwater Quality Assessment: A Study on Birbhum District, West Bengal, India

Authors: N. C. Ghosh, Niladri Das, Prolay Mondal, Ranajit Ghosh

Abstract:

Groundwater quality deterioration due to human activities has become a prime factor of modern life. The major concern of the study is to access spatial variation of groundwater quality and to identify the sources of groundwater chemicals and its impact on human health of the concerned area. Multivariate statistical techniques, cluster, principal component analysis, and hydrochemical fancies are been applied to measure groundwater quality data on 14 parameters from 107 sites distributed randomly throughout the Birbhum district. Five factors have been extracted using Varimax rotation with Kaiser Normalization. The first factor explains 27.61% of the total variance where high positive loading have been concentrated in TH, Ca, Mg, Cl and F (Fluoride). In the studied region, due to the presence of basaltic Rajmahal trap fluoride contamination is highly concentrated and that has an adverse impact on human health such as fluorosis. The second factor explains 24.41% of the total variance which includes Na, HCO₃, EC, and SO₄. The last factor or the fifth factor explains 8.85% of the total variance, and it includes pH which maintains the acidic and alkaline character of the groundwater. Hierarchical cluster analysis (HCA) grouped the 107 sampling station into two clusters. One cluster having high pollution and another cluster having less pollution. Moreover hydromorphological facies viz. Wilcox diagram, Doneen’s chart, and USSL diagram reveal the quality of the groundwater like the suitability of the groundwater for irrigation or water used for drinking purpose like permeability index of the groundwater, quality assessment of groundwater for irrigation. Gibb’s diagram depicts that the major portion of the groundwater of this region is rock dominated origin, as the western part of the region characterized by the Jharkhand plateau fringe comprises basalt, gneiss, granite rocks.

Keywords: correlation, factor analysis, hydrological facies, hydrochemistry

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4876 Life Cycle Analysis of Using Brick Waste in Road Technology

Authors: Mezhoud Samy, Toumi Youcef, Boukendekdji Otmane

Abstract:

Nowadays, industrial by-products and waste are increasing along with public needs increase. The engineering sector has turned to sustainable development by emphasizing the aspects of environmental and life cycle assessment as an important objective. Among this waste, the remains of the red bricks (DBR) may be an alternative worth checking out, given their availability and abundance at the construction sites. In this context, this work aims to valorize DBR in the concrete road (BR). The incorporation of DBR is carried out by the substitution of the granular fractions of mixtures from noble quarry materials. The experimental plan aims to determine the physico-mechanical performance and environmental performance of manufactured BRs from DBR with a cement content (6.5%) and compared with a control BR without DBR. The studied characteristics are proctor, resistance to compression, resistance to flexural tensile at 7 and 28 days, modulus of elasticity, and total shrinkage. The results of this experimental study showed that the characteristics of recycled aggregates (DBR) are lower than those of natural aggregates but remain acceptable with respect to regulations. Results demonstrate the mechanical performance of BR made from less DBR than the control BR without DBR but remains appreciable and encourage their jobs in the road sector. Recycled aggregates can constitute an interesting economic and ecological alternative but require elementary precautions before any use.

Keywords: life cycle assessment, brick waste, road concrete, performance

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4875 Maximizing Bidirectional Green Waves for Major Road Axes

Authors: Christian Liebchen

Abstract:

Both from an environmental perspective and with respect to road traffic flow quality, planning so-called green waves along major road axes is a well-established target for traffic engineers. For one-way road axes (e.g. the Avenues in Manhattan), this is a trivial downstream task. For bidirectional arterials, the well-known necessary condition for establishing a green wave in both directions is that the driving times between two subsequent crossings must be an integer multiple of half of the cycle time of the signal programs at the nodes. In this paper, we propose an integer linear optimization model to establish fixed-time green waves in both directions that are as long and as wide as possible, even in the situation where the driving time condition is not fulfilled. In particular, we are considering an arterial along whose nodes separate left-turn signal groups are realized. In our computational results, we show that scheduling left-turn phases before or after the straight phases can reduce waiting times along the arterial. Moreover, we show that there is always a solution with green waves in both directions that are as long and as wide as possible, where absolute priority is put on just one direction. Compared to optimizing both directions together, establishing an ideal green wave into one direction can only provide suboptimal quality when considering prioritized parts of a green band (e.g., first few seconds).

Keywords: traffic light coordination, synchronization, phase sequencing, green waves, integer programming

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4874 Remote Assessment and Change Detection of GreenLAI of Cotton Crop Using Different Vegetation Indices

Authors: Ganesh B. Shinde, Vijaya B. Musande

Abstract:

Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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4873 Multivariate Rainfall Disaggregation Using MuDRain Model: Malaysia Experience

Authors: Ibrahim Suliman Hanaish

Abstract:

Disaggregation daily rainfall using stochastic models formulated based on multivariate approach (MuDRain) is discussed in this paper. Seven rain gauge stations are considered in this study for different distances from the referred station starting from 4 km to 160 km in Peninsular Malaysia. The hourly rainfall data used are covered the period from 1973 to 2008 and July and November months are considered as an example of dry and wet periods. The cross-correlation among the rain gauges is considered for the available hourly rainfall information at the neighboring stations or not. This paper discussed the applicability of the MuDRain model for disaggregation daily rainfall to hourly rainfall for both sources of cross-correlation. The goodness of fit of the model was based on the reproduction of fitting statistics like the means, variances, coefficients of skewness, lag zero cross-correlation of coefficients and the lag one auto correlation of coefficients. It is found the correlation coefficients based on extracted correlations that was based on daily are slightly higher than correlations based on available hourly rainfall especially for neighboring stations not more than 28 km. The results showed also the MuDRain model did not reproduce statistics very well. In addition, a bad reproduction of the actual hyetographs comparing to the synthetic hourly rainfall data. Mean while, it is showed a good fit between the distribution function of the historical and synthetic hourly rainfall. These discrepancies are unavoidable because of the lowest cross correlation of hourly rainfall. The overall performance indicated that the MuDRain model would not be appropriate choice for disaggregation daily rainfall.

Keywords: rainfall disaggregation, multivariate disaggregation rainfall model, correlation, stochastic model

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4872 Dissimilarity-Based Coloring for Symbolic and Multivariate Data Visualization

Authors: K. Umbleja, M. Ichino, H. Yaguchi

Abstract:

In this paper, we propose a coloring method for multivariate data visualization by using parallel coordinates based on dissimilarity and tree structure information gathered during hierarchical clustering. The proposed method is an extension for proximity-based coloring that suffers from a few undesired side effects if hierarchical tree structure is not balanced tree. We describe the algorithm by assigning colors based on dissimilarity information, show the application of proposed method on three commonly used datasets, and compare the results with proximity-based coloring. We found our proposed method to be especially beneficial for symbolic data visualization where many individual objects have already been aggregated into a single symbolic object.

Keywords: data visualization, dissimilarity-based coloring, proximity-based coloring, symbolic data

Procedia PDF Downloads 141
4871 Using Support Vector Machines for Measuring Democracy

Authors: Tommy Krieger, Klaus Gruendler

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We present a novel approach for measuring democracy, which enables a very detailed and sensitive index. This method is based on Support Vector Machines, a mathematical algorithm for pattern recognition. Our implementation evaluates 188 countries in the period between 1981 and 2011. The Support Vector Machines Democracy Index (SVMDI) is continuously on the 0-1-Interval and robust to variations in the numerical process parameters. The algorithm introduced here can be used for every concept of democracy without additional adjustments, and due to its flexibility it is also a valuable tool for comparison studies.

Keywords: democracy, democracy index, machine learning, support vector machines

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4870 Observation of Critical Sliding Velocity

Authors: Visar Baxhuku, Halil Demolli, Alishukri Shkodra

Abstract:

This paper presents the monitoring of vehicle movement, namely the developing of speed of vehicles during movement in a certain twist. The basic geometry data of twist are measured with the purpose of calculating the slide in border speed. During the research, measuring developed speed of passenger vehicles for the real conditions of the road surface, dry road with average damage, was realised. After setting values, the analysis was done in function security of movement in twist.

Keywords: critical sliding velocity, moving velocity, curve, passenger vehicles

Procedia PDF Downloads 390
4869 Automated Pothole Detection Using Convolution Neural Networks and 3D Reconstruction Using Stereovision

Authors: Eshta Ranyal, Kamal Jain, Vikrant Ranyal

Abstract:

Potholes are a severe threat to road safety and a major contributing factor towards road distress. In the Indian context, they are a major road hazard. Timely detection of potholes and subsequent repair can prevent the roads from deteriorating. To facilitate the roadway authorities in the timely detection and repair of potholes, we propose a pothole detection methodology using convolutional neural networks. The YOLOv3 model is used as it is fast and accurate in comparison to other state-of-the-art models. You only look once v3 (YOLOv3) is a state-of-the-art, real-time object detection system that features multi-scale detection. A mean average precision(mAP) of 73% was obtained on a training dataset of 200 images. The dataset was then increased to 500 images, resulting in an increase in mAP. We further calculated the depth of the potholes using stereoscopic vision by reconstruction of 3D potholes. This enables calculating pothole volume, its extent, which can then be used to evaluate the pothole severity as low, moderate, high.

Keywords: CNN, pothole detection, pothole severity, YOLO, stereovision

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4868 Characterizing of CuO Incorporated CMOS Dielectric for Fast Switching System

Authors: Nissar Mohammad Karim, Norhayati Soin

Abstract:

To ensure fast switching in high-K incorporated Complementary Metal Oxide Semiconductor (CMOS) transistors, the results on the basis of d (NBTI) by incorporating SiO2 dielectric with aged samples of CuO sol-gels have been reported. Precursor ageing has been carried out for 4 days. The minimum obtained refractive index is 1.0099 which was found after 3 hours of adhesive UV curing. Obtaining a low refractive index exhibits a low dielectric constant and hence a faster system.

Keywords: refractive index, sol-gel, precursor ageing, metallurgical and materials engineering

Procedia PDF Downloads 354
4867 Development of Map of Gridded Basin Flash Flood Potential Index: GBFFPI Map of QuangNam, QuangNgai, DaNang, Hue Provinces

Authors: Le Xuan Cau

Abstract:

Flash flood is occurred in short time rainfall interval: from 1 hour to 12 hours in small and medium basins. Flash floods typically have two characteristics: large water flow and big flow velocity. Flash flood is occurred at hill valley site (strip of lowland of terrain) in a catchment with large enough distribution area, steep basin slope, and heavy rainfall. The risk of flash floods is determined through Gridded Basin Flash Flood Potential Index (GBFFPI). Flash Flood Potential Index (FFPI) is determined through terrain slope flash flood index, soil erosion flash flood index, land cover flash floods index, land use flash flood index, rainfall flash flood index. Determining GBFFPI, each cell in a map can be considered as outlet of a water accumulation basin. GBFFPI of the cell is determined as basin average value of FFPI of the corresponding water accumulation basin. Based on GIS, a tool is developed to compute GBFFPI using ArcObjects SDK for .NET. The maps of GBFFPI are built in two types: GBFFPI including rainfall flash flood index (real time flash flood warning) or GBFFPI excluding rainfall flash flood index. GBFFPI Tool can be used to determine a high flash flood potential site in a large region as quick as possible. The GBFFPI is improved from conventional FFPI. The advantage of GBFFPI is that GBFFPI is taking into account the basin response (interaction of cells) and determines more true flash flood site (strip of lowland of terrain) while conventional FFPI is taking into account single cell and does not consider the interaction between cells. The GBFFPI Map of QuangNam, QuangNgai, DaNang, Hue is built and exported to Google Earth. The obtained map proves scientific basis of GBFFPI.

Keywords: ArcObjects SDK for NET, basin average value of FFPI, gridded basin flash flood potential index, GBFFPI map

Procedia PDF Downloads 350
4866 Effects of China's Urban Form on Urban Carbon Emission

Authors: Lu Lin

Abstract:

Urbanization has reshaped physical environment, energy consumption and carbon emission of the urban area. China is a typical developing country under a rapid urbanization process and is the world largest carbon emission country. This study aims to explore the correlation between urban form and carbon emission caused by urban energy consumption in China. 287 provincial-level and prefecture-level cities are studied in 2000, 2005, and 2010. Compact ratio index, shape index, and fractal dimension index are used to quantify urban form. Geographically weighted regression (GWR) model is employed to explore the relationship between urban form, energy consumption, and related carbon emission. The results show the average compact ratio index decreased from 2000 to 2010 which indicates urban in China sprawled. The average fractal dimension index increases by 3%, indicating the spatial layouts of China's cities were more complicated. The results by the GWR model show that shape index and fractal dimension index had a non-significant relationship with carbon emission by urban energy consumption. However, compact urban form reduced carbon emission. The findings of this study will help policy-makers make sustainable urban planning and reduce urban carbon emission.

Keywords: carbon emission, GWR model, urban energy consumption, urban form

Procedia PDF Downloads 318
4865 Study and Analysis of the Factors Affecting Road Safety Using Decision Tree Algorithms

Authors: Naina Mahajan, Bikram Pal Kaur

Abstract:

The purpose of traffic accident analysis is to find the possible causes of an accident. Road accidents cannot be totally prevented but by suitable traffic engineering and management the accident rate can be reduced to a certain extent. This paper discusses the classification techniques C4.5 and ID3 using the WEKA Data mining tool. These techniques use on the NH (National highway) dataset. With the C4.5 and ID3 technique it gives best results and high accuracy with less computation time and error rate.

Keywords: C4.5, ID3, NH(National highway), WEKA data mining tool

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4864 Predicting Returns Volatilities and Correlations of Stock Indices Using Multivariate Conditional Autoregressive Range and Return Models

Authors: Shay Kee Tan, Kok Haur Ng, Jennifer So-Kuen Chan

Abstract:

This paper extends the conditional autoregressive range (CARR) model to multivariate CARR (MCARR) model and further to the two-stage MCARR-return model to model and forecast volatilities, correlations and returns of multiple financial assets. The first stage model fits the scaled realised Parkinson volatility measures using individual series and their pairwise sums of indices to the MCARR model to obtain in-sample estimates and forecasts of volatilities for these individual and pairwise sum series. Then covariances are calculated to construct the fitted variance-covariance matrix of returns which are imputed into the stage-two return model to capture the heteroskedasticity of assets’ returns. We investigate different choices of mean functions to describe the volatility dynamics. Empirical applications are based on the Standard and Poor 500, Dow Jones Industrial Average and Dow Jones United States Financial Service Indices. Results show that the stage-one MCARR models using asymmetric mean functions give better in-sample model fits than those based on symmetric mean functions. They also provide better out-of-sample volatility forecasts than those using CARR models based on two robust loss functions with the scaled realised open-to-close volatility measure as the proxy for the unobserved true volatility. We also find that the stage-two return models with constant means and multivariate Student-t errors give better in-sample fits than the Baba, Engle, Kraft, and Kroner type of generalized autoregressive conditional heteroskedasticity (BEKK-GARCH) models. The estimates and forecasts of value-at-risk (VaR) and conditional VaR based on the best MCARR-return models for each asset are provided and tested using Kupiec test to confirm the accuracy of the VaR forecasts.

Keywords: range-based volatility, correlation, multivariate CARR-return model, value-at-risk, conditional value-at-risk

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4863 Probabilistic Crash Prediction and Prevention of Vehicle Crash

Authors: Lavanya Annadi, Fahimeh Jafari

Abstract:

Transportation brings immense benefits to society, but it also has its costs. Costs include such as the cost of infrastructure, personnel and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion and various indirect costs in terms of air transport. More research has been done to identify the various factors that affect road accidents, such as road infrastructure, traffic, sociodemographic characteristics, land use, and the environment. The aim of this research is to predict the probabilistic crash prediction of vehicles using machine learning due to natural and structural reasons by excluding spontaneous reasons like overspeeding etc., in the United States. These factors range from weather factors, like weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity to human made structures like road structure factors like bump, roundabout, no exit, turning loop, give away, etc. Probabilities are dissected into ten different classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes that happened in all states collected by the US government. To calculate the probability, multinomial expected value was used and assigned a classification label as the crash probability. We applied three different classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-deep insights through exploratory data analysis.

Keywords: road safety, crash prediction, exploratory analysis, machine learning

Procedia PDF Downloads 87