Search results for: generalized assignment problem
5696 Rd-PLS Regression: From the Analysis of Two Blocks of Variables to Path Modeling
Authors: E. Tchandao Mangamana, V. Cariou, E. Vigneau, R. Glele Kakai, E. M. Qannari
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A new definition of a latent variable associated with a dataset makes it possible to propose variants of the PLS2 regression and the multi-block PLS (MB-PLS). We shall refer to these variants as Rd-PLS regression and Rd-MB-PLS respectively because they are inspired by both Redundancy analysis and PLS regression. Usually, a latent variable t associated with a dataset Z is defined as a linear combination of the variables of Z with the constraint that the length of the loading weights vector equals 1. Formally, t=Zw with ‖w‖=1. Denoting by Z' the transpose of Z, we define herein, a latent variable by t=ZZ’q with the constraint that the auxiliary variable q has a norm equal to 1. This new definition of a latent variable entails that, as previously, t is a linear combination of the variables in Z and, in addition, the loading vector w=Z’q is constrained to be a linear combination of the rows of Z. More importantly, t could be interpreted as a kind of projection of the auxiliary variable q onto the space generated by the variables in Z, since it is collinear to the first PLS1 component of q onto Z. Consider the situation in which we aim to predict a dataset Y from another dataset X. These two datasets relate to the same individuals and are assumed to be centered. Let us consider a latent variable u=YY’q to which we associate the variable t= XX’YY’q. Rd-PLS consists in seeking q (and therefore u and t) so that the covariance between t and u is maximum. The solution to this problem is straightforward and consists in setting q to the eigenvector of YY’XX’YY’ associated with the largest eigenvalue. For the determination of higher order components, we deflate X and Y with respect to the latent variable t. Extending Rd-PLS to the context of multi-block data is relatively easy. Starting from a latent variable u=YY’q, we consider its ‘projection’ on the space generated by the variables of each block Xk (k=1, ..., K) namely, tk= XkXk'YY’q. Thereafter, Rd-MB-PLS seeks q in order to maximize the average of the covariances of u with tk (k=1, ..., K). The solution to this problem is given by q, eigenvector of YY’XX’YY’, where X is the dataset obtained by horizontally merging datasets Xk (k=1, ..., K). For the determination of latent variables of order higher than 1, we use a deflation of Y and Xk with respect to the variable t= XX’YY’q. In the same vein, extending Rd-MB-PLS to the path modeling setting is straightforward. Methods are illustrated on the basis of case studies and performance of Rd-PLS and Rd-MB-PLS in terms of prediction is compared to that of PLS2 and MB-PLS.Keywords: multiblock data analysis, partial least squares regression, path modeling, redundancy analysis
Procedia PDF Downloads 1535695 Implementing Equitable Learning Experiences to Increase Environmental Awareness and Science Proficiency in Alabama’s Schools and Communities
Authors: Carly Cummings, Maria Soledad Peresin
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Alabama has a long history of racial injustice and unsatisfactory educational performance. In the 1870s Jim Crow laws segregated public schools and disproportionally allocated funding and resources to white institutions across the South. Despite the Supreme Court ruling to integrate schools following Brown vs. the Board of Education in 1954, Alabama’s school system continued to exhibit signs of segregation, compounded by “white flight” and the establishment of exclusive private schools, which still exist today. This discriminatory history has had a lasting impact of the state’s education system, reflected in modern school demographics and achievement data. It is well known that Alabama struggles with education performance, especially in science education. On average, minority groups scored the lowest in science proficiency. In Alabama, minority populations are concentrated in a region known as the Black Belt, which was once home to countless slave plantations and was the epicenter of the Civil Rights Movement. Today the Black Belt is characterized by a high density of woodlands and plays a significant role in Alabama’s leading economic industry-forest products. Given the economic importance of forestry and agriculture to the state, environmental science proficiency is essential to its stability; however, it is neglected in areas where it is needed most. To better understand the inequity of science education within Alabama, our study first investigates how geographic location, demographics and school funding relate to science achievement scores using ArcGIS and Pearson’s correlation coefficient. Additionally, our study explores the implementation of a relevant, problem-based, active learning lesson in schools. Relevant learning engages students by connecting material to their personal experiences. Problem-based active learning involves real-world problem-solving through hands-on experiences. Given Alabama’s significant woodland coverage, educational materials on forest products were developed with consideration of its relevance to students, especially those located in the Black Belt. Furthermore, to incorporate problem solving and active learning, the lesson centered around students using forest products to solve environmental challenges, such as water pollution- an increasing challenge within the state due to climate change. Pre and post assessment surveys were provided to teachers to measure the effectiveness of the lesson. In addition to pedagogical practices, community and mentorship programs are known to positively impact educational achievements. To this end, our work examines the results of surveys measuring educational professionals’ attitudes toward a local mentorship group within the Black Belt and its potential to address environmental and science literacy. Additionally, our study presents survey results from participants who attended an educational community event, gauging its effectiveness in increasing environmental and science proficiency. Our results demonstrate positive improvements in environmental awareness and science literacy with relevant pedagogy, mentorship, and community involvement. Implementing these practices can help provide equitable and inclusive learning environments and can better equip students with the skills and knowledge needed to bridge this historic educational gap within Alabama.Keywords: equitable education, environmental science, environmental education, science education, racial injustice, sustainability, rural education
Procedia PDF Downloads 705694 Evaluation of the Impact of Reducing the Traffic Light Cycle for Cars to Improve Non-Vehicular Transportation: A Case of Study in Lima
Authors: Gheyder Concha Bendezu, Rodrigo Lescano Loli, Aldo Bravo Lizano
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In big urbanized cities of Latin America, motor vehicles have priority over non-motor vehicles and pedestrians. There is an important problem that affects people's health and quality of life; lack of inclusion towards pedestrians makes it difficult for them to move smoothly and safely since the city has been planned for the transit of motor vehicles. Faced with the new trend for sustainable and economical transport, the city is forced to develop infrastructure in order to incorporate pedestrians and users with non-motorized vehicles in the transport system. The present research aims to study the influence of non-motorized vehicles on an avenue, the optimization of a cycle using traffic lights based on simulation in Synchro software, to improve the flow of non-motor vehicles. The evaluation is of the microscopic type; for this reason, field data was collected, such as vehicular, pedestrian, and non-motor vehicle user demand. With the values of speed and travel time, it is represented in the current scenario that contains the existing problem. These data allow to create a microsimulation model in Vissim software, later to be calibrated and validated so that it has a behavior similar to reality. The results of this model are compared with the efficiency parameters of the proposed model; these parameters are the queue length, the travel speed, and mainly the travel times of the users at this intersection. The results reflect a reduction of 27% in travel time, that is, an improvement between the proposed model and the current one for this great avenue. The tail length of motor vehicles is also reduced by 12.5%, a considerable improvement. All this represents an improvement in the level of service and in the quality of life of users.Keywords: bikeway, microsimulation, pedestrians, queue length, traffic light cycle, travel time
Procedia PDF Downloads 1795693 Prediction of Ionic Liquid Densities Using a Corresponding State Correlation
Authors: Khashayar Nasrifar
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Ionic liquids (ILs) exhibit particular properties exemplified by extremely low vapor pressure and high thermal stability. The properties of ILs can be tailored by proper selection of cations and anions. As such, ILs are appealing as potential solvents to substitute traditional solvents with high vapor pressure. One of the IL properties required in chemical and process design is density. In developing corresponding state liquid density correlations, scaling hypothesis is often used. The hypothesis expresses the temperature dependence of saturated liquid densities near the vapor-liquid critical point as a function of reduced temperature. Extending the temperature dependence, several successful correlations were developed to accurately correlate the densities of normal liquids from the triple point to a critical point. Applying mixing rules, the liquid density correlations are extended to liquid mixtures as well. ILs are not molecular liquids, and they are not classified among normal liquids either. Also, ILs are often used where the condition is far from equilibrium. Nevertheless, in calculating the properties of ILs, the use of corresponding state correlations would be useful if no experimental data were available. With well-known generalized saturated liquid density correlations, the accuracy in predicting the density of ILs is not that good. An average error of 4-5% should be expected. In this work, a data bank was compiled. A simplified and concise corresponding state saturated liquid density correlation is proposed by phenomena-logically modifying reduced temperature using the temperature-dependence for an interacting parameter of the Soave-Redlich-Kwong equation of state. This modification improves the temperature dependence of the developed correlation. Parametrization was next performed to optimize the three global parameters of the correlation. The correlation was then applied to the ILs in our data bank with satisfactory predictions. The correlation of IL density applied at 0.1 MPa and was tested with an average uncertainty of around 2%. No adjustable parameter was used. The critical temperature, critical volume, and acentric factor were all required. Methods to extend the predictions to higher pressures (200 MPa) were also devised. Compared to other methods, this correlation was found more accurate. This work also presents the chronological order of developing such correlations dealing with ILs. The pros and cons are also expressed.Keywords: correlation, corresponding state principle, ionic liquid, density
Procedia PDF Downloads 1315692 Collective Problem Solving: Tackling Obstacles and Unlocking Opportunities for Young People Not in Education, Employment, or Training
Authors: Kalimah Ibrahiim, Israa Elmousa
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This study employed the world café method alongside semi-structured interviews within a 'conversation café' setting to engage stakeholders from the public health and primary care sectors. The objective was to collaboratively explore strategies to improve outcomes for young people not in education, employment, or training (NEET). The discussions were aimed at identifying the underlying causes of disparities faced by NEET individuals, exchanging experiences, and formulating community-driven solutions to bolster preventive efforts and shape policy initiatives. A thematic analysis of the qualitative data gathered emphasized the importance of community problem-solving through the exchange of ideas and reflective discussions. Healthcare professionals reflected on their potential roles, pinpointing a significant gap in understanding the specific needs of the NEET population and the unclear distribution of responsibilities among stakeholders. The results underscore the necessity for a unified approach in primary care and the fostering of multi-agency collaborations that focus on addressing social determinants of health. Such strategies are critical not only for the immediate improvement of health outcomes for NEET individuals but also for informing broader policy decisions that can have long-term benefits. Further research is ongoing, delving deeper into the unique challenges faced by this demographic and striving to develop more effective interventions. The study advocates for continued efforts to integrate insights from various sectors to create a more holistic and effective response to the needs of the NEET population, ensuring that future strategies are informed by a comprehensive understanding of their circumstances and challenges.Keywords: multi-agency working, primary care, public health, social inequalities
Procedia PDF Downloads 435691 Intrusion Detection Techniques in NaaS in the Cloud: A Review
Authors: Rashid Mahmood
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The network as a service (NaaS) usage has been well-known from the last few years in the many applications, like mission critical applications. In the NaaS, prevention method is not adequate as the security concerned, so the detection method should be added to the security issues in NaaS. The authentication and encryption are considered the first solution of the NaaS problem whereas now these are not sufficient as NaaS use is increasing. In this paper, we are going to present the concept of intrusion detection and then survey some of major intrusion detection techniques in NaaS and aim to compare in some important fields.Keywords: IDS, cloud, naas, detection
Procedia PDF Downloads 3265690 Capacity Oversizing for Infrastructure Sharing Synergies: A Game Theoretic Analysis
Authors: Robin Molinier
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Industrial symbiosis (I.S) rely on two basic modes of cooperation between organizations that are infrastructure/service sharing and resource substitution (the use of waste materials, fatal energy and recirculated utilities for production). The former consists in the intensification of use of an asset and thus requires to compare the incremental investment cost to be incurred and the stand-alone cost faced by each potential participant to satisfy its own requirements. In order to investigate the way such a cooperation mode can be implemented we formulate a game theoretic model integrating the grassroot investment decision and the ex-post access pricing problem. In the first period two actors set cooperatively (resp. non-cooperatively) a level of common (resp. individual) infrastructure capacity oversizing to attract ex-post a potential entrant with a plug-and-play offer (available capacity, tariff). The entrant’s requirement is randomly distributed and known only after investments took place. Capacity cost exhibits sub-additive property so that there is room for profitable overcapacity setting in the first period under some conditions that we derive. The entrant willingness-to-pay for the access to the infrastructure is driven by both her standalone cost and the complement cost to be incurred in case she chooses to access an infrastructure whose the available capacity is lower than her requirement level. The expected complement cost function is thus derived, and we show that it is decreasing, convex and shaped by the entrant’s requirements distribution function. For both uniform and triangular distributions optimal capacity level is obtained in the cooperative setting and equilibrium levels are determined in the non-cooperative case. Regarding the latter, we show that competition is deterred by the first period investor with the highest requirement level. Using the non-cooperative game outcomes which gives lower bounds for the profit sharing problem in the cooperative one we solve the whole game and describe situations supporting sharing agreements.Keywords: capacity, cooperation, industrial symbiosis, pricing
Procedia PDF Downloads 4435689 Beyond Personal Evidence: Using Learning Analytics and Student Feedback to Improve Learning Experiences
Authors: Shawndra Bowers, Allie Brandriet, Betsy Gilbertson
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This paper will highlight how Auburn Online’s instructional designers leveraged student and faculty data to update and improve online course design and instructional materials. When designing and revising online courses, it can be difficult for faculty to know what strategies are most likely to engage learners and improve educational outcomes in a specific discipline. It can also be difficult to identify which metrics are most useful for understanding and improving teaching, learning, and course design. At Auburn Online, the instructional designers use a suite of data based student’s performance, participation, satisfaction, and engagement, as well as faculty perceptions, to inform sound learning and design principles that guide growth-mindset consultations with faculty. The consultations allow the instructional designer, along with the faculty member, to co-create an actionable course improvement plan. Auburn Online gathers learning analytics from a variety of sources that any instructor or instructional design team may have access to at their own institutions. Participation and performance data, such as page: views, assignment submissions, and aggregate grade distributions, are collected from the learning management system. Engagement data is pulled from the video hosting platform, which includes unique viewers, views and downloads, the minutes delivered, and the average duration each video is viewed. Student satisfaction is also obtained through a short survey that is embedded at the end of each instructional module. This survey is included in each course every time it is taught. The survey data is then analyzed by an instructional designer for trends and pain points in order to identify areas that can be modified, such as course content and instructional strategies, to better support student learning. This analysis, along with the instructional designer’s recommendations, is presented in a comprehensive report to instructors in an hour-long consultation where instructional designers collaborate with the faculty member on how and when to implement improvements. Auburn Online has developed a triage strategy of priority 1 or 2 level changes that will be implemented in future course iterations. This data-informed decision-making process helps instructors focus on what will best work in their teaching environment while addressing which areas need additional attention. As a student-centered process, it has created improved learning environments for students and has been well received by faculty. It has also shown to be effective in addressing the need for improvement while removing the feeling the faculty’s teaching is being personally attacked. The process that Auburn Online uses is laid out, along with the three-tier maintenance and revision guide that will be used over a three-year implementation plan. This information can help others determine what components of the maintenance and revision plan they want to utilize, as well as guide them on how to create a similar approach. The data will be used to analyze, revise, and improve courses by providing recommendations and models of good practices through determining and disseminating best practices that demonstrate an impact on student success.Keywords: data-driven, improvement, online courses, faculty development, analytics, course design
Procedia PDF Downloads 635688 Remote Sensing and GIS Based Methodology for Identification of Low Crop Productivity in Gautam Buddha Nagar District
Authors: Shivangi Somvanshi
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Poor crop productivity in salt-affected environment in the country is due to insufficient and untimely canal supply to agricultural land and inefficient field water management practices. This could further degrade due to inadequate maintenance of canal network, ongoing secondary soil salinization and waterlogging, worsening of groundwater quality. Large patches of low productivity in irrigation commands are occurring due to waterlogging and salt-affected soil, particularly in the scarcity rainfall year. Satellite remote sensing has been used for mapping of areas of low crop productivity, waterlogging and salt in irrigation commands. The spatial results obtained for these problems so far are less reliable for further use due to rapid change in soil quality parameters over the years. The existing spatial databases of canal network and flow data, groundwater quality and salt-affected soil were obtained from the central and state line departments/agencies and were integrated with GIS. Therefore, an integrated methodology based on remote sensing and GIS has been developed in ArcGIS environment on the basis of canal supply status, groundwater quality, salt-affected soils, and satellite-derived vegetation index (NDVI), salinity index (NDSI) and waterlogging index (NSWI). This methodology was tested for identification and delineation of area of low productivity in the Gautam Buddha Nagar district (Uttar Pradesh). It was found that the area affected by this problem lies mainly in Dankaur and Jewar blocks of the district. The problem area was verified with ground data and was found to be approximately 78% accurate. The methodology has potential to be used in other irrigation commands in the country to obtain reliable spatial data on low crop productivity.Keywords: remote sensing, GIS, salt affected soil, crop productivity, Gautam Buddha Nagar
Procedia PDF Downloads 2885687 Multimedia Container for Autonomous Car
Authors: Janusz Bobulski, Mariusz Kubanek
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The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.Keywords: an autonomous car, image processing, lidar, obstacle detection
Procedia PDF Downloads 2295686 Joint Probability Distribution of Extreme Water Level with Rainfall and Temperature: Trend Analysis of Potential Impacts of Climate Change
Authors: Ali Razmi, Saeed Golian
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Climate change is known to have the potential to impact adversely hydrologic patterns for variables such as rainfall, maximum and minimum temperature and sea level rise. Long-term average of these climate variables could possibly change over time due to climate change impacts. In this study, trend analysis was performed on rainfall, maximum and minimum temperature and water level data of a coastal area in Manhattan, New York City, Central Park and Battery Park stations to investigate if there is a significant change in the data mean. Partial Man-Kendall test was used for trend analysis. Frequency analysis was then performed on data using common probability distribution functions such as Generalized Extreme Value (GEV), normal, log-normal and log-Pearson. Goodness of fit tests such as Kolmogorov-Smirnov are used to determine the most appropriate distributions. In flood frequency analysis, rainfall and water level data are often separately investigated. However, in determining flood zones, simultaneous consideration of rainfall and water level in frequency analysis could have considerable effect on floodplain delineation (flood extent and depth). The present study aims to perform flood frequency analysis considering joint probability distribution for rainfall and storm surge. First, correlation between the considered variables was investigated. Joint probability distribution of extreme water level and temperature was also investigated to examine how global warming could affect sea level flooding impacts. Copula functions were fitted to data and joint probability of water level with rainfall and temperature for different recurrence intervals of 2, 5, 25, 50, 100, 200, 500, 600 and 1000 was determined and compared with the severity of individual events. Results for trend analysis showed increase in long-term average of data that could be attributed to climate change impacts. GEV distribution was found as the most appropriate function to be fitted to the extreme climate variables. The results for joint probability distribution analysis confirmed the necessity for incorporation of both rainfall and water level data in flood frequency analysis.Keywords: climate change, climate variables, copula, joint probability
Procedia PDF Downloads 3675685 Telogen Effluvium: A Modern Hair Loss Concern and the Interventional Strategies
Authors: Chettyparambil Lalchand Thejalakshmi, Sonal Sabu Edattukaran
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Hair loss is one of the main issues that contemporary society is dealing with. It can be attributable to a wide range of factors, listing from one's genetic composition and the anxiety we experience on a daily basis. Telogen effluvium [TE] is a condition that causes temporary hair loss after a stressor that might shock the body and cause the hair follicles to temporarily rest, leading to hair loss. Most frequently, women are the ones who bring up these difficulties. Extreme illness or trauma, an emotional or important life event, rapid weight loss and crash dieting, a severe scalp skin problem, a new medication, or ceasing hormone therapy are examples of potential causes. Men frequently do not notice hair thinning with time, but women with long hair may be easily identified when shedding, which can occasionally result in bias because women tend to be more concerned with aesthetics and beauty standards of the society, and approach frequently with the concerns .The woman, who formerly possessed a full head of hair, is worried about the hair loss from her scalp . There are several cases of hair loss reported every day, and Telogen effluvium is said to be the most prevalent one of them all without any hereditary risk factors. While the patient has loss in hair volume, baldness is not the result of this problem . The exponentially growing Dermatology and Aesthetic medical division has discovered that this problem is the most common and also the easiest to cure since it is feasible for these people to regrow their hair, unlike those who have scarring alopecia, in which the follicle itself is damaged and non-viable. Telogen effluvium comes in two different forms: acute and chronic. Acute TE occurs in all the age groups with a hair loss of less than three months, while chronic TE is more common in those between the ages of 30 and 60 with a hair loss of more than six months . Both kinds are prevalent throughout all age groups, regardless of the predominance. It takes between three and six months for the lost hair to come back, although this condition is readily reversed by eliminating stresses. After shedding their hair, patients frequently describe having noticeable fringes on their forehead. The current medical treatments for this condition include topical corticosteroids, systemic corticosteroids, minoxidil and finasteride, CNDPA (caffeine, niacinamide, panthenol, dimethicone, and an acrylate polymer) .Individual terminal hair growth was increased by 10% as a result of the innovative intervention CNDPA. Botulinum Toxin A, Scalp Micro Needling, Platelet Rich Plasma Therapy [PRP], and sessions with Multivitamin Mesotherapy Injections are some recently enhanced techniques with partially or completely reversible hair loss. Also, it has been shown that supplements like Nutrafol and Biotin are producing effective outcomes. There is virtually little evidence to support the claim that applying sulfur-rich ingredients to the scalp, such as onion juice, can help TE patients' hair regenerate.Keywords: dermatology, telogen effluvium, hair loss, modern hair loass treatments
Procedia PDF Downloads 935684 Methodological Issues of Teaching Vocabulary in a Technical University
Authors: Elza Salakhova
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The purpose of this article is to consider some common difficulties encountered in teaching vocabulary in technical higher educational institutions. It deals with the problem of teaching special vocabulary in the process of teaching a foreign language. There have been analyzed some problems in teaching a foreign language to learners of a technical higher establishment. There are some recommendations for teachers to motivate their students to learn and master a foreign language through learning terminology.Keywords: professionally-oriented study, motivation, technical university, foreign language
Procedia PDF Downloads 1605683 Decreasing Non-Compliance with the Garbage Collection Fee Payment: A Case Study from the Intervention in a Municipality in the Slovak Republic
Authors: Anetta Caplanova, Eva Sirakovova, Estera Szakadatova
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Non-payment of taxes and fees represents a problem, which occurs at national and local government levels in many countries. An effective tax collection is key for generating government and local government budget revenues to finance public services and infrastructure; thus, there is the need to address this problem. The standard approach considers as a solution raising taxes/fees to boost public revenues, which may be politically challenging and time-consuming to implement. An alternative approach is related to using behavioral interventions. These can be usually implemented relatively quickly, and in most cases, they are associated with low cost. In the paper, we present the results of the behavioral experiment focused on raising the level of compliance with the payment of garbage collection fees in a selected municipality in the Slovak Republic. The experiment was implemented using the leaflets sent to residential households together with the invoice for the garbage collection in the municipality Hlohovec, Western Slovakia, in Spring 2021. The sample of about 10000 households was divided into three random groups, a control group and two intervention groups. Households in intervention group 1 were sent a leaflet using the social norm nudge, while households in intervention group 2 were sent a leaflet using the deterrence nudge. The social norm framing leaflet pointed out that in the municipality, the prevailing majority of people paid the garbage collection fee and encouraged recipients to join this majority. The deterrent leaflet reminded the recipients that if they did not pay the fee on time, enforcement proceedings would follow. This was aimed to increase the subjective perception of citizens of the enforcement proceedings in case of noncompliance. In the paper, we present and discuss the results from the experiment and formulate relevant generalizations for other municipalities.Keywords: municipal governments, garbage fee collection, behavioural intervention, social norm, deterrence nudge
Procedia PDF Downloads 1945682 Achieving Process Stability through Automation and Process Optimization at H Blast Furnace Tata Steel, Jamshedpur
Authors: Krishnendu Mukhopadhyay, Subhashis Kundu, Mayank Tiwari, Sameeran Pani, Padmapal, Uttam Singh
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Blast Furnace is a counter current process where burden descends from top and hot gases ascend from bottom and chemically reduce iron oxides into liquid hot metal. One of the major problems of blast furnace operation is the erratic burden descent inside furnace. Sometimes this problem is so acute that burden descent stops resulting in Hanging and instability of the furnace. This problem is very frequent in blast furnaces worldwide and results in huge production losses. This situation becomes more adverse when blast furnaces are operated at low coke rate and high coal injection rate with adverse raw materials like high alumina ore and high coke ash. For last three years, H-Blast Furnace Tata Steel was able to reduce coke rate from 450 kg/thm to 350 kg/thm with an increase in coal injection to 200 kg/thm which are close to world benchmarks and expand profitability. To sustain this regime, elimination of irregularities of blast furnace like hanging, channeling, and scaffolding is very essential. In this paper, sustaining of zero hanging spell for consecutive three years with low coke rate operation by improvement in burden characteristics, burden distribution, changes in slag regime, casting practices and adequate automation of the furnace operation has been illustrated. Models have been created to comprehend and upgrade the blast furnace process understanding. A model has been developed to predict the process of maintaining slag viscosity in desired range to attain proper burden permeability. A channeling prediction model has also been developed to understand channeling symptoms so that early actions can be initiated. The models have helped to a great extent in standardizing the control decisions of operators at H-Blast Furnace of Tata Steel, Jamshedpur and thus achieving process stability for last three years.Keywords: hanging, channelling, blast furnace, coke
Procedia PDF Downloads 1975681 Description of the Non-Iterative Learning Algorithm of Artificial Neuron
Authors: B. S. Akhmetov, S. T. Akhmetova, A. I. Ivanov, T. S. Kartbayev, A. Y. Malygin
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The problem of training of a network of artificial neurons in biometric appendices is that this process has to be completely automatic, i.e. the person operator should not participate in it. Therefore, this article discusses the issues of training the network of artificial neurons and the description of the non-iterative learning algorithm of artificial neuron.Keywords: artificial neuron, biometrics, biometrical applications, learning of neuron, non-iterative algorithm
Procedia PDF Downloads 4985680 Random Vertical Seismic Vibrations of the Long Span Cantilever Beams
Authors: Sergo Esadze
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Seismic resistance norms require calculation of cantilevers on vertical components of the base seismic acceleration. Long span cantilevers, as a rule, must be calculated as a separate construction element. According to the architectural-planning solution, functional purposes and environmental condition of a designing buildings/structures, long span cantilever construction may be of very different types: both by main bearing element (beam, truss, slab), and by material (reinforced concrete, steel). A choice from these is always linked with bearing construction system of the building. Research of vertical seismic vibration of these constructions requires individual approach for each (which is not specified in the norms) in correlation with model of seismic load. The latest may be given both as deterministic load and as a random process. Loading model as a random process is more adequate to this problem. In presented paper, two types of long span (from 6m – up to 12m) reinforcement concrete cantilever beams have been considered: a) bearing elements of cantilevers, i.e., elements in which they fixed, have cross-sections with large sizes and cantilevers are made with haunch; b) cantilever beam with load-bearing rod element. Calculation models are suggested, separately for a) and b) types. They are presented as systems with finite quantity degree (concentrated masses) of freedom. Conditions for fixing ends are corresponding with its types. Vertical acceleration and vertical component of the angular acceleration affect masses. Model is based on assumption translator-rotational motion of the building in the vertical plane, caused by vertical seismic acceleration. Seismic accelerations are considered as random processes and presented by multiplication of the deterministic envelope function on stationary random process. Problem is solved within the framework of the correlation theory of random process. Solved numerical examples are given. The method is effective for solving the specific problems.Keywords: cantilever, random process, seismic load, vertical acceleration
Procedia PDF Downloads 1935679 Structural Design of a Relief Valve Considering Strength
Authors: Nam-Hee Kim, Jang-Hoon Ko, Kwon-Hee Lee
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A relief valve is a mechanical element to keep safety by controlling high pressure. Usually, the high pressure is relieved by using the spring force and letting the fluid to flow from another way out of system. When its normal pressure is reached, the relief valve can return to initial state. The relief valve in this study has been applied for pressure vessel, evaporator, piping line, etc. The relief valve should be designed for smooth operation and should satisfy the structural safety requirement under operating condition. In general, the structural analysis is performed by following fluid flow analysis. In this process, the FSI (Fluid-Structure Interaction) is required to input the force obtained from the output of the flow analysis. Firstly, this study predicts the velocity profile and the pressure distribution in the given system. In this study, the assumptions for flow analysis are as follows: • The flow is steady-state and three-dimensional. • The fluid is Newtonian and incompressible. • The walls of the pipe and valve are smooth. The flow characteristics in this relief valve does not induce any problem. The commercial software ANSYS/CFX is utilized for flow analysis. On the contrary, very high pressure may cause structural problem due to severe stress. The relief valve is made of body, bonnet, guide, piston and nozzle, and its material is stainless steel. To investigate its structural safety, the worst case loading is considered as the pressure of 700 bar. The load is applied to inside the valve, which is greater than the load obtained from FSI. The maximum stress is calculated as 378 MPa by performing the finite element analysis. However, the value is greater than its allowable value. Thus, an alternative design is suggested to improve the structural performance through case study. We found that the sensitive design variable to the strength is the shape of the nozzle. The case study is to vary the size of the nozzle. Finally, it can be seen that the suggested design satisfy the structural design requirement. The FE analysis is performed by using the commercial software ANSYS/Workbench.Keywords: relief valve, structural analysis, structural design, strength, safety factor
Procedia PDF Downloads 3095678 The Motivation System Development: Case-Study of the Trade Metal Company in Russian Federation
Authors: Elena V. Lysenko
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Motivating as the leading function of a modern Human Resources Management involves issues of increasing the effectiveness of the organization in a broader context. During the formation of motivational systems, the top-management of organization should pay equal attention to both external motivation (incentive system) and internal (self-motivation). The balance of internal and external motivation harmonizes the relations between employers and employees, increases the level of job satisfaction by the organization staff, which in turn leads the organization to success and ensures the organization`s profitability and competitiveness in the market environment. The article is devoted to the study of personnel motivation system in the small metal trade company, which is located in Yekaterinburg, Russian Federation. The study took place during November-December, 2016 ordered by the Company Director to analyze the motivational potential of work (managerial aspect of motivation) and motivation of personnel (personnel aspect of motivation) with the purpose to construct a system of employees’ motivation. The research tools included 6 specially selected tests of motivation, which are: “Motivation profile of your job”, “Constructive motivational attitudes”, Tests about Motivation of achievements (1st variant: Test by А.Mehrabian by the theory of D.С.McClelland and 2nd variant: Test about leading needs according with the theory of D.С.MacClelland), Tests by T.Elers (1st variant: “Determination of the motivation towards success or to avoid failure” and 2nd variant: “Trends to achieve results or to avoid failure”). The results of the study showed only one, but fundamental problem of the whole organization: high level of both motivational potential in work and self-motivation, especially in terms of achievement motivation, but serious lack of productivity. According the results which study showed this problem is derived from insufficient staff competence. The research suggests basic guidelines in order to build the new personnel motivation system for this Company, which is planned to be developed in the nearest future.Keywords: incentive system, motivation of achievements, motivation system, self-motivation
Procedia PDF Downloads 3155677 An Approach for Ensuring Data Flow in Freight Delivery and Management Systems
Authors: Aurelija Burinskienė, Dalė Dzemydienė, Arūnas Miliauskas
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This research aims at developing the approach for more effective freight delivery and transportation process management. The road congestions and the identification of causes are important, as well as the context information recognition and management. The measure of many parameters during the transportation period and proper control of driver work became the problem. The number of vehicles per time unit passing at a given time and point for drivers can be evaluated in some situations. The collection of data is mainly used to establish new trips. The flow of the data is more complex in urban areas. Herein, the movement of freight is reported in detail, including the information on street level. When traffic density is extremely high in congestion cases, and the traffic speed is incredibly low, data transmission reaches the peak. Different data sets are generated, which depend on the type of freight delivery network. There are three types of networks: long-distance delivery networks, last-mile delivery networks and mode-based delivery networks; the last one includes different modes, in particular, railways and other networks. When freight delivery is switched from one type of the above-stated network to another, more data could be included for reporting purposes and vice versa. In this case, a significant amount of these data is used for control operations, and the problem requires an integrated methodological approach. The paper presents an approach for providing e-services for drivers by including the assessment of the multi-component infrastructure needed for delivery of freights following the network type. The construction of such a methodology is required to evaluate data flow conditions and overloads, and to minimize the time gaps in data reporting. The results obtained show the possibilities of the proposing methodological approach to support the management and decision-making processes with functionality of incorporating networking specifics, by helping to minimize the overloads in data reporting.Keywords: transportation networks, freight delivery, data flow, monitoring, e-services
Procedia PDF Downloads 1305676 Elastoplastic Modified Stillinger Weber-Potential Based Discretized Virtual Internal Bond and Its Application to the Dynamic Fracture Propagation
Authors: Dina Kon Mushid, Kabutakapua Kakanda, Dibu Dave Mbako
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The failure of material usually involves elastoplastic deformation and fracturing. Continuum mechanics can effectively deal with plastic deformation by using a yield function and the flow rule. At the same time, it has some limitations in dealing with the fracture problem since it is a theory based on the continuous field hypothesis. The lattice model can simulate the fracture problem very well, but it is inadequate for dealing with plastic deformation. Based on the discretized virtual internal bond model (DVIB), this paper proposes a lattice model that can account for plasticity. DVIB is a lattice method that considers material to comprise bond cells. Each bond cell may have any geometry with a finite number of bonds. The two-body or multi-body potential can characterize the strain energy of a bond cell. The two-body potential leads to the fixed Poisson ratio, while the multi-body potential can overcome the limitation of the fixed Poisson ratio. In the present paper, the modified Stillinger-Weber (SW), a multi-body potential, is employed to characterize the bond cell energy. The SW potential is composed of two parts. One part is the two-body potential that describes the interatomic interactions between particles. Another is the three-body potential that represents the bond angle interactions between particles. Because the SW interaction can represent the bond stretch and bond angle contribution, the SW potential-based DVIB (SW-DVIB) can represent the various Poisson ratios. To embed the plasticity in the SW-DVIB, the plasticity is considered in the two-body part of the SW potential. It is done by reducing the bond stiffness to a lower level once the bond reaches the yielding point. While before the bond reaches the yielding point, the bond is elastic. When the bond deformation exceeds the yielding point, the bond stiffness is softened to a lower value. When unloaded, irreversible deformation occurs. With the bond length increasing to a critical value, termed the failure bond length, the bond fails. The critical failure bond length is related to the cell size and the macro fracture energy. By this means, the fracture energy is conserved so that the cell size sensitivity problem is relieved to a great extent. In addition, the plasticity and the fracture are also unified at the bond level. To make the DVIB able to simulate different Poisson ratios, the three-body part of the SW potential is kept elasto-brittle. The bond angle can bear the moment before the bond angle increment is smaller than a critical value. By this method, the SW-DVIB can simulate the plastic deformation and the fracturing process of material with various Poisson ratios. The elastoplastic SW-DVIB is used to simulate the plastic deformation of a material, the plastic fracturing process, and the tunnel plastic deformation. It has been shown that the current SW-DVIB method is straightforward in simulating both elastoplastic deformation and plastic fracture.Keywords: lattice model, discretized virtual internal bond, elastoplastic deformation, fracture, modified stillinger-weber potential
Procedia PDF Downloads 1035675 Winners and Losers of Severe Drought and Grazing on a Dryland Grassland in Limpopo Province
Authors: Vincent Mokoka, Kai Behn, Edwin Mudongo, Jan Ruppert, Kingsley Ayisi, Anja Linstädter
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Severe drought may trigger a transition of vegetation composition in dryland grasslands, with productive perennial grasses often being replaced by annual grasses. Grazing pressure is thought to exacerbate drought effects, but little is known on the joint effects of grazing and drought on the functional and taxonomic composition of the herbaceous vegetation in African savannas. This study thus aimed to elucidate which herbaceous species and plant functional types (PFTs) are most resistant to prolonged drought and grazing and whether resting plays a role in this context. Thus, we performed a six-year field experiment in South Africa’s Limpopo province, combining drought and grazing treatments. Aboveground herbaceous biomass was harvested annually and separated into species. We grouped species into five PFTs, i.e. very broad-leaved perennial grasses, broad-leaved perennial grasses, narrow-leaved perennial grasses, annual grasses, and forbs. For all species, we also recorded three-leaf traits (leaf area - LA, specific leaf area – SLA, and leaf dry matter content – LDM) to describe their resource acquisition strategies. We used generalized linear models to test for treatment effects and their interaction. Association indices were used to detect the relationship between species and treatments. We found that there were no absolute winner species or PFTs, as the six-year severe drought had a pronounced negative impact on the biomass production of all species and PFTs. However, we detected relative winners with increases in relative abundances, mainly forbs and less palatable narrow-leafed grasses with comparatively low LA and high LDMC, such as Aristida stipidata Hack. These species and PFTs also tended to be favored by grazing. Although few species profited from resting, for most species, the combination of drought and resting proved to be particularly unfavorable. Winners and losers can indicate ecological transition and may be used to guide management decisions.Keywords: aboveground net primary production, drought, functional diversity, winner and loser species
Procedia PDF Downloads 1785674 A Study on ZnO Nanoparticles Properties: An Integration of Rietveld Method and First-Principles Calculation
Authors: Kausar Harun, Ahmad Azmin Mohamad
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Zinc oxide (ZnO) has been extensively used in optoelectronic devices, with recent interest as photoanode material in dye-sensitize solar cell. Numerous methods employed to experimentally synthesized ZnO, while some are theoretically-modeled. Both approaches provide information on ZnO properties, but theoretical calculation proved to be more accurate and timely effective. Thus, integration between these two methods is essential to intimately resemble the properties of synthesized ZnO. In this study, experimentally-grown ZnO nanoparticles were prepared by sol-gel storage method with zinc acetate dihydrate and methanol as precursor and solvent. A 1 M sodium hydroxide (NaOH) solution was used as stabilizer. The optimum time to produce ZnO nanoparticles were recorded as 12 hours. Phase and structural analysis showed that single phase ZnO produced with wurtzite hexagonal structure. Further work on quantitative analysis was done via Rietveld-refinement method to obtain structural and crystallite parameter such as lattice dimensions, space group, and atomic coordination. The lattice dimensions were a=b=3.2498Å and c=5.2068Å which were later used as main input in first-principles calculations. By applying density-functional theory (DFT) embedded in CASTEP computer code, the structure of synthesized ZnO was built and optimized using several exchange-correlation functionals. The generalized-gradient approximation functional with Perdew-Burke-Ernzerhof and Hubbard U corrections (GGA-PBE+U) showed the structure with lowest energy and lattice deviations. In this study, emphasize also given to the modification of valence electron energy level to overcome the underestimation in DFT calculation. Both Zn and O valance energy were fixed at Ud=8.3 eV and Up=7.3 eV, respectively. Hence, the following electronic and optical properties of synthesized ZnO were calculated based on GGA-PBE+U functional within ultrasoft-pseudopotential method. In conclusion, the incorporation of Rietveld analysis into first-principles calculation was valid as the resulting properties were comparable with those reported in literature. The time taken to evaluate certain properties via physical testing was then eliminated as the simulation could be done through computational method.Keywords: density functional theory, first-principles, Rietveld-refinement, ZnO nanoparticles
Procedia PDF Downloads 3095673 Arabic Lexicon Learning to Analyze Sentiment in Microblogs
Authors: Mahmoud B. Rokaya
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The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation
Procedia PDF Downloads 1915672 Environmental Radioactivity Analysis by a Sequential Approach
Authors: G. Medkour Ishak-Boushaki, A. Taibi, M. Allab
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Quantitative environmental radioactivity measurements are needed to determine the level of exposure of a population to ionizing radiations and for the assessment of the associated risks. Gamma spectrometry remains a very powerful tool for the analysis of radionuclides present in an environmental sample but the basic problem in such measurements is the low rate of detected events. Using large environmental samples could help to get around this difficulty but, unfortunately, new issues are raised by gamma rays attenuation and self-absorption. Recently, a new method has been suggested, to detect and identify without quantification, in a short time, a gamma ray of a low count source. This method does not require, as usually adopted in gamma spectrometry measurements, a pulse height spectrum acquisition. It is based on a chronological record of each detected photon by simultaneous measurements of its energy ε and its arrival time τ on the detector, the pair parameters [ε,τ] defining an event mode sequence (EMS). The EMS serials are analyzed sequentially by a Bayesian approach to detect the presence of a given radioactive source. The main object of the present work is to test the applicability of this sequential approach in radioactive environmental materials detection. Moreover, for an appropriate health oversight of the public and of the concerned workers, the analysis has been extended to get a reliable quantification of the radionuclides present in environmental samples. For illustration, we consider as an example, the problem of detection and quantification of 238U. Monte Carlo simulated experience is carried out consisting in the detection, by a Ge(Hp) semiconductor junction, of gamma rays of 63 keV emitted by 234Th (progeny of 238U). The generated EMS serials are analyzed by a Bayesian inference. The application of the sequential Bayesian approach, in environmental radioactivity analysis, offers the possibility of reducing the measurements time without requiring large environmental samples and consequently avoids the attached inconvenient. The work is still in progress.Keywords: Bayesian approach, event mode sequence, gamma spectrometry, Monte Carlo method
Procedia PDF Downloads 4985671 Self-Reported Health Status and Its Consistency: Evidence from India
Authors: Dona Ghosh, Zakir Husain
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In India, the increase in share of aged has generated many social and economic issues, of which health concerns is a major challenge that society must confront in coming years. Self-reported health (SRH) is a popular health measure in this regard but has been questioned in recent years due to its heavy dependence on the socioeconomic status. So, the validity of SRH, as a measure of health status during old age, is needed to be verified. This paper emphasizes on the self-reported health and related inconsistent responses among elderly in India. The objective of the study is bifurcated into two parts: firstly, to identify the socioeconomic determinants of subjective health status and its change over time; and secondly, to analyse the role of the socioeconomic components in providing inconsistent responses regarding the health status of elderly. Inconsistency in response can rise in two ways: positive response bias (if an individual has a health problem but reports his/her health as good) and negative response bias (if bad health is reported even if there is no health problem). However, in the present study, we focus only on the negative response bias of elderly individuals. To measure the inconsistencies in responses, self-reported health is compared with two types of physical health conditions – existence of chronicle ailment and physical immobility. Using NSS dataset of 60th and 71st rounds, the study found that subjective health has worsened over time in both rural and urban areas. Findings suggest that inconsistency in responses, related to chronic ailment, vary across social classes, living environments, geographical regions, age groups and education levels. On the contrary, variation in inconsistent responses regarding physical mobility is quite rare and difficult to explain by socioeconomic characteristics because most of the indicators are found to be insignificant in this regard. The findings indicate that in case of chronicle ailment, inconsistency between objective and subjective health status largely depends on socioeconomic conditions but the importance of such factors disappears for physical immobility.Keywords: India, aging, self-reported health, inconsistent responses
Procedia PDF Downloads 2965670 Flexible Communication Platform for Crisis Management
Authors: Jiří Barta, Tomáš Ludík, Jiří Urbánek
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The topics of disaster and emergency management are highly debated among experts. Fast communication will help to deal with emergencies. Problem is with the network connection and data exchange. The paper suggests a solution, which allows possibilities and perspectives of new flexible communication platform to the protection of communication systems for crisis management. This platform is used for everyday communication and communication in crisis situations too.Keywords: crisis management, information systems, interoperability, crisis communication, security environment, communication platform
Procedia PDF Downloads 4795669 Addressing Housing Issue at Regional Level Planning: A Case Study of Mumbai Metropolitan Region
Authors: Bhakti Chitale
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Mumbai city, which is the business capital of India and one of the most crowded cities in the world, holds the biggest slum in Asia. The Mumbai Metropolitan Region (MMR) occupies an area of 4035 sq.km. with a population of 22.8 million people. This population is mostly urban with 91% of this population living in areas of Municipal Corporations and Councils. Another 3% live in Census Towns. The region has 9 Municipal Corporations, 8 Municipal councils, and around 1000 villages. On the one hand MMR reflects the highest contribution to the Nations overall economy and on the other hand it shows the horrible and intolerable picture of about 2 million people, who are living in slums/without even slum with totally unhygienic conditions and with total loss of hope. The generations are about to get affected adversely if the solution is not worked out. This study is an attempt towards working out the solution. Mumbai Metropolitan Region Development Authority (MMRDA) is state government's authority, specially formed to govern the development of MMR. MMRDA is engaged in long term planning, promotion of new growth centres, implementation of strategic projects and financing infrastructure development. While preparing the master plan for MMR for next 20 years MMRDA conducted a detail study regarding Housing scenario in MMR and possible options for improvement. The author was the in charge officer for the said assignment. This paper puts light on the interesting outcomes of the research study, which ranges from the adverse effects of government policies, automatic responses of housing market, effects on planning processes, and overall changing needs of housing patterns in the world due to changes in the social mechanism. It alarms the urban planners who usually focus on smart infrastructure development, about allied future dangers. This housing study will explain the complexities, realities and needs of innovations in the housing policies all over the world. The paper will explain further few success stories and failure stories of government initiatives with reasons. It gives the clear idea about the differences in needs of housing for people from different economic groups and direct and indirect market pressures on low cost housing. Magical phenomenon came in front like a large percentage of vacant houses is present in spite of the huge need. Housing market gets affected by the developments or any other physical and financial changes taking place in the nearby areas or cities, also by changes in cities which are located far from the region and also by the international investments or policy changes. Instead of just depending on governments actions in case of generation of affordable housing, it becomes equally important to make the housing markets automatically generate such stock and still make them sustainable is the aim of all the movement. In summary, we may say that the paper will sequentially elaborate the complete dynamics of housing in one of the most crowded urban area in the world that is Mumbai Metropolitan Region, with a lot of data, analysis, case studies, and recommendations.Keywords: Mumbai India, slum housing, region planning, market recommendations
Procedia PDF Downloads 2825668 Advanced Technologies and Algorithms for Efficient Portfolio Selection
Authors: Konstantinos Liagkouras, Konstantinos Metaxiotis
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In this paper we present a classification of the various technologies applied for the solution of the portfolio selection problem according to the discipline and the methodological framework followed. We provide a concise presentation of the emerged categories and we are trying to identify which methods considered obsolete and which lie at the heart of the debate. On top of that, we provide a comparative study of the different technologies applied for efficient portfolio construction and we suggest potential paths for future work that lie at the intersection of the presented techniques.Keywords: portfolio selection, optimization techniques, financial models, stochastic, heuristics
Procedia PDF Downloads 4385667 The Effects of Billboard Content and Visible Distance on Driver Behavior
Authors: Arsalan Hassan Pour, Mansoureh Jeihani, Samira Ahangari
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Distracted driving has been one of the most integral concerns surrounding our daily use of vehicles since the invention of the automobile. While much attention has been recently given to cell phones related distraction, commercial billboards along roads are also candidates for drivers' visual and cognitive distractions, as they may take drivers’ eyes from the road and their minds off the driving task to see, perceive and think about the billboard’s content. Using a driving simulator and a head-mounted eye-tracking system, speed change, acceleration, deceleration, throttle response, collision, lane changing, and offset from the center of the lane data along with gaze fixation duration and frequency data were collected in this study. Some 92 participants from a fairly diverse sociodemographic background drove on a simulated freeway in Baltimore, Maryland area and were exposed to three different billboards to investigate the effects of billboards on drivers’ behavior. Participants glanced at the billboards several times with different frequencies, the maximum of which occurred on the billboard with the highest cognitive load. About 74% of the participants didn’t look at billboards for more than two seconds at each glance except for the billboard with a short visible area. Analysis of variance (ANOVA) was performed to find the variations in driving behavior when they are invisible, readable, and post billboards area. The results show a slight difference in speed, throttle, brake, steering velocity, and lane changing, among different areas. Brake force and deviation from the center of the lane increased in the readable area in comparison with the visible area, and speed increased right after each billboard. The results indicated that billboards have a significant effect on driving performance and visual attention based on their content and visibility status. Generalized linear model (GLM) analysis showed no connection between participants’ age and driving experience with gaze duration. However, the visible distance of the billboard, gender, and billboard content had a significant effect on gaze duration.Keywords: ANOVA, billboards, distracted driving, drivers' behavior, driving simulator, eye-Tracking system, GLM
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