Search results for: train passenger

Authors: Shadab Bahreini

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Public transportation is one of the most important aspects of cities, which impacts various factors of the Quality of Life (QoL) of citizens. A passenger's experience is influenced by a variety of indicators in addition to the cost and safety of the trip. This article intends to investigate how QoL is affected by public transport in an urban environment by introducing a literature review of QoL and Quality of Urban Life (QoUL), investigating the intersection of QoL and public transport, and reviewing the background theory for Transport Quality of Life (TQoL). The article proposes a Public Transport Quality of Life (PTQoL) framework comprised of a set of indicators that measure how public transport impacts QoL across personal (physical and mental), socioeconomic, and environmental dimensions. The study proposes using the framework to evaluate objective or subjective factors affecting a person's QoL regarding public transport. Finally, it concludes that public transport is a key component in shaping QoL in urban environments and that policymakers and urban planners should use the PTQoL framework to make evidence-based decisions to improve public transport systems and their impact on QoL.

Keywords: public transport, quality of life, subjective and objective indicators, urban environment

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Authors: Adel A. Ghobbar, Varun Raman

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The Corrective maintenance of components and systems is a problem plaguing almost every industry in the world today. Train operators’ and the maintenance repair and overhaul subsidiary of the Dutch railway company is also facing this problem. A considerable portion of the maintenance activities carried out by the company are unscheduled. This, in turn, severely stresses and stretches the workforce and resources available. One possible solution is to have a robust preventive maintenance plan. The other possible solution is to plan maintenance based on real-time data obtained from sensor-based ‘Health and Usage Monitoring Systems.’ The former has been investigated in this paper. The preventive maintenance model developed for train operator will subsequently be extended, to tackle the unscheduled maintenance problem also affecting the aerospace industry. The extension of the model to the aerospace sector will be dealt with in the second part of the research, and it would, in turn, validate the soundness of the model developed. Thus, there are distinct areas that will be addressed in this paper, including the mathematical modelling of preventive maintenance and optimization based on cost and system availability. The results of this research will help an organization to choose the right maintenance strategy, allowing it to save considerable sums of money as opposed to overspending under the guise of maintaining high asset availability. The concept of delay time modelling was used to address the practical problem of unscheduled maintenance in this paper. The delay time modelling can be used to help with support planning for a given asset. The model was run using MATLAB, and the results are shown that the ideal inspection intervals computed using the extended from a minimal cost perspective were 29 days, and from a minimum downtime, perspective was 14 days. Risk matrix integration was constructed to represent the risk in terms of the probability of a fault leading to breakdown maintenance and its consequences in terms of maintenance cost. Thus, the choice of an optimal inspection interval of 29 days, resulted in a cost of approximately 50 Euros and the corresponding value of b(T) was 0.011. These values ensure that the risk associated with component X being maintained at an inspection interval of 29 days is more than acceptable. Thus, a switch in maintenance frequency from 90 days to 29 days would be optimal from the point of view of cost, downtime and risk.

Keywords: delay time modelling, unscheduled maintenance, reliability, maintainability, availability

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Authors: Yao Cheng, Weihua Zhang

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Although the measured vibration signal contains rich information on machine health conditions, the white noise interferences and the discrete harmonic coming from blade, shaft and mash make the fault diagnosis of rolling element bearings difficult. In order to overcome the interferences of useless signals, a new fault diagnosis method combining Complete Ensemble Empirical Mode Decomposition with adaptive noise (CEEMDAN) and Multipoint Optimal Minimum Entropy Deconvolution (MOMED) is proposed for the fault diagnosis of high-speed train bearings. Firstly, the CEEMDAN technique is applied to adaptively decompose the raw vibration signal into a series of finite intrinsic mode functions (IMFs) and a residue. Compared with Ensemble Empirical Mode Decomposition (EEMD), the CEEMDAN can provide an exact reconstruction of the original signal and a better spectral separation of the modes, which improves the accuracy of fault diagnosis. An effective sensitivity index based on the Pearson's correlation coefficients between IMFs and raw signal is adopted to select sensitive IMFs that contain bearing fault information. The composite signal of the sensitive IMFs is applied to further analysis of fault identification. Next, for propose of identifying the fault information precisely, the MOMED is utilized to enhance the periodic impulses in composite signal. As a non-iterative method, the MOMED has better deconvolution performance than the classical deconvolution methods such Minimum Entropy Deconvolution (MED) and Maximum Correlated Kurtosis Deconvolution (MCKD). Third, the envelope spectrum analysis is applied to detect the existence of bearing fault. The simulated bearing fault signals with white noise and discrete harmonic interferences are used to validate the effectiveness of the proposed method. Finally, the superiorities of the proposed method are further demonstrated by high-speed train bearing fault datasets measured from test rig. The analysis results indicate that the proposed method has strong practicability.

Keywords: bearing, complete ensemble empirical mode decomposition with adaptive noise, fault diagnosis, multipoint optimal minimum entropy deconvolution

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Authors: Tawanda Mushiri, Charles Mbohwa

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The performance of door assembly is very significant for the vehicle design. In the present paper, the finite element method is used in the development processes of the door assembly. The stiffness, strength, modal characteristic, and anti-extrusion of a newly developed passenger vehicle door assembly are calculated and evaluated by several finite element analysis commercial software. The structural problems discovered by FE analysis have been modified and finally achieved the expected door structure performance target of this new vehicle. The issue in focus is to predict the performance of the door assembly by powerful finite element analysis software, and optimize the structure to meet the design targets. It is observed that this method can be used to forecast the performance of vehicle door efficiently when it’s designed. In order to reduce lead time and cost in the product development of vehicles more development will be made virtually.

Keywords: vehicle door, structure, strength, stiffness, modal characteristic, anti-extrusion, Finite Element Method

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Authors: Pedro Pablo Ramírez Sánchez, Alassane Ballé Ndiaye, Roberto Rendeiro Martín-Cejas

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The aim of this paper is to analyse the different environmental policies adopted in Europe for car emissions, to comment on some of the possible perverse effects generated and point out these policies which are considered more efficient under the environmental perspective. This paper is focused on passenger cars as this category is the most significant in road transport. The utility of this research lies in this being the first step or basis to improve and optimise actual policies. The methodology applied in this paper refers to a comparative analysis from a practical and theoretical point of view of European environmental policies in road transport. This work describes an overview of the road transport industry in Europe pointing out some relevant aspects such as the contribution of road transport to total emissions and the vehicle fleet in Europe. Additionally, we propose a brief practice guide with the combined policies in order to optimise their aim.

Keywords: air quality, climate change, emission, environment, perverse effect, road transport, tax policy

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Authors: A. Alharbi, R. Boukhanouf, T. Habeebullah, H. Ibrahim

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This paper presents a detailed description of evaporative cooling systems used for space cooling in Mina Valley, Saudi Arabia. The thermal performance and environmental impact of the evaporative coolers were evaluated. It was found that the evaporative cooling systems used for space cooling in pilgrims’ accommodations and in the train stations could reduce energy consumption by as much as 75% and cut carbon dioxide emission by 78% compared to traditional vapour compression systems.

Keywords: evaporative cooling, vapor compression, electricity consumption, CO2 emission

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Authors: Badr A. Al-Harbi, Fahd T. Abdullah, Mazen T. Wali, Mohammed W. Al-Obaidi, Reda M. Bakhdlg

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Over the past few years, the aviation society had demonstrated a huge concern for securing the sustainability of commercial aviation. Future aerospace engineers in Saudi Arabia are expected to play a major role in dealing with these aspects, taking into consideration the expected growth in both traffic, passenger mileage, and fleet expansions in the region. In the present work, the authors investigate the perception of engineering students in the two undergraduate aerospace engineering programs in the Kingdom. A questionnaire was distributed using google forms and targeted approximately 300 students in both programs on several WhatsApp groups. Data collection was stopped after one week when a response rate above 35% was reached. The questionnaire aimed at assessing the students’ awareness of sustainable aviation and associated obstacles. The results obtained from the study indicate the necessity of introducing curricular modifications to address the subject with more targeted extracurricular activities and better use of social media, which is becoming a main source of students’ awareness.

Keywords: aviation, engineering education, students’ perception, sustainable aviation

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Authors: S. K. Subah, R. Tasnim, M. I. Jahan, M. R. Islam

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While talking about how comfortable and convenient Dhaka's bus service is, the minimum emphasis is placed on the female commuters of the Dhaka city. Recognizing the contemporary situation, the supreme focus is to develop experimental model based on statistical methods. SEM has been adopted to quantify passenger satisfaction, which is affected by the perceived service quality. The study deals with 16 observed variables and three latent variables, which were correlated to identify their significance on the regulation of perceived SQ (Service Quality). To calibrate the model, a dataset of 250 responses from female users of local buses has been utilized through survey. A questionnaire structured with SQ variables was prepared in consultation with prevailing literature, practitioners, academicians, and users. The result concludes that the attributes of safe and secured environment have the most significant impact on the overall bus service quality according to the insight of female respondents. The study outcome might be a great help for the policymakers, women's organizations, and NGOs to formulate transport policy that will ensure a women-friendly public bus service.

Keywords: bus service quality, female perception, structural equation modelling, safety-security, women friendly bus

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Authors: Vishwa Joshi

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The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

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Authors: J. K. Alhassan, C. S. Actsu

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This study is on the prediction of feature performance of undergraduate students with Artificial Neural Networks (ANN). With the growing decline in the quality academic performance of undergraduate students, it has become essential to predict the students’ feature academic performance early in their courses of first and second years and to take the necessary precautions using such prediction-based information. The feed forward multilayer neural network model was used to train and develop a network and the test carried out with some of the input variables. A result of 80% accuracy was obtained from the test which was carried out, with an average error of 0.009781.

Keywords: academic performance, artificial neural network, prediction, students

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Authors: Hussein Altartouri

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The purpose of this paper is to present a modeling and control of the active suspension system using robust state feedback controller implemented for a half car model. This system represents a mechatronic system which contains all the essential components to be considered a complete mechatronic system. This system must adapt different conditions which are difficult to compromise, such as disturbances, slippage, and motion on rough road (that contains rocks, stones, and other miscellanies). Some current automobile suspension systems use passive components only by utilizing spring and damping coefficient with fixed rates. Vehicle suspensions systems are used to provide good road handling and improve passenger comfort. Passive suspensions only offer compromise between these two conflicting criteria. Active suspension poses the ability to reduce the traditional design as a compromise between handling and comfort by directly controlling the suspensions force actuators. In this study, the robust state feedback controller implemented to the active suspensions system for half car model.

Keywords: half-car model, active suspension system, state feedback, road profile

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Authors: Arfanara Najnin, Michael W. Roach, Jr., Dr. Jianhong Cecilia Xia

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The SkyCar Rapid Transit System (SRT) is an innovative intelligent transport system for the sustainable urban transport system. This system will increase the urban area network connectivity and decrease urban area traffic congestion. The SRT system is designed as a suspended Personal Rapid Transit (PRT) system that travels under a guideway 5m above the ground. A driver-less passenger is via pod-cars that hang from slender beams supported by columns that replace existing lamp posts. The beams are setup in a series of interconnecting loops providing non-stop travel from beginning to end to assure journey time. The SRT forward movement is effected by magnetic motors built into the guideway. Passenger stops are at either at line level 5m above the ground or ground level via a spur guideway that curves off the main thoroughfare. The main objective of this paper is to propose an integrated Automated Transit Network (ATN) technology for the future intelligent transport system in the urban built environment. To fulfil the objective a 4D simulated model in the urban built environment has been proposed by using the concept of SRT-ATN system. The methodology for the design, construction and testing parameters of a Technology Demonstrator (TD) for proof of concept and a Simulator (S) has been demonstrated. The completed TD and S will provide an excellent proving ground for the next development stage, the SRT Prototype (PT) and Pilot System (PS). This paper covered by a 4D simulated model in the virtual built environment is to effectively show how the SRT-ATN system works. OpenSim software has been used to develop the model in a virtual environment, and the scenario has been simulated to understand and visualize the proposed SkyCar Rapid Transit Network model. The SkyCar system will be fabricated in a modular form which is easily transported. The system would be installed in increasingly congested city centers throughout the world, as well as in airports, tourist resorts, race tracks and other special purpose for the urban community. This paper shares the lessons learnt from the proposed innovation and provides recommendations on how to improve the future transport system in urban built environment. Safety and security of passengers are prime factors to be considered for this transit system. Design requirements to meet the safety needs to be part of the research and development phase of the project. Operational safety aspects would also be developed during this period. The vehicles, the track and beam systems and stations are the main components that need to be examined in detail for safety and security of patrons. Measures will also be required to protect columns adjoining intersections from errant vehicles in vehicular traffic collisions. The SkyCar Rapid Transit takes advantage of all current disruptive technologies; batteries, sensors and 4G/5G communication and solar energy technologies which will continue to reduce the costs and make the systems more profitable. SkyCar's energy consumption is extremely low compared to other transport systems.

Keywords: SkyCar, rapid transit, Intelligent Transport System (ITS), Automated Transit Network (ATN), urban built environment, 4D Visualization, smart city

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Authors: Seyedmirsajad Mokhtarimousavi, Danial Talebi, Hamidreza Asgari

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Gate Assignment Problem (GAP) is one of the most substantial issues in airport operation. In principle, GAP intends to maintain the maximum capacity of the airport through the best possible allocation of the resources (gates) in order to reach the optimum outcome. The problem involves a wide range of dependent and independent resources and their limitations, which add to the complexity of GAP from both theoretical and practical perspective. In this study, GAP was mathematically formulated as a three-objective problem. The preliminary goal of multi-objective formulation was to address a higher number of objectives that can be simultaneously optimized and therefore increase the practical efficiency of the final solution. The problem is solved by applying the second version of Non-dominated Sorting Genetic Algorithm (NSGA-II). Results showed that the proposed mathematical model could address most of major criteria in the decision-making process in airport management in terms of minimizing both airport/airline cost and passenger walking distance time. Moreover, the proposed approach could properly find acceptable possible answers.

Keywords: airport management, gate assignment problem, mathematical modeling, genetic algorithm, NSGA-II

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Authors: Eusebio Odiari, Mark Birkin, Susan Grant-Muller, Nicolas Malleson

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Big data typically refers to consumer datasets revealing some detailed heterogeneity in human behavior, which if harnessed appropriately, could potentially revolutionize our understanding of the collective phenomena of the physical world. Inadvertent missing values skew these datasets and compromise the validity of the thesis. Here we discuss a conceptually consistent strategy for identifying other relevant datasets to combine with available big data, to plug the gaps and to create a rich requisite comprehensive dataset for subsequent analysis. Specifically, emphasis is on how these methodologies can for the first time enable the construction of more detailed pictures of passenger demand and drivers of mobility on the railways. These methodologies can predict the influence of changes within the network (like a change in time-table or impact of a new station), explain local phenomena outside the network (like rail-heading) and the other impacts of urban morphology. Our analysis also reveals that our new imputation data model provides for more equitable revenue sharing amongst network operators who manage different parts of the integrated UK railways.

Keywords: big-data, micro-simulation, mobility, ticketing-data, commuters, transport, synthetic, population

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Authors: Paola Quintana, Angélica Vaca, Sebastián Villacres, Henry Acurio

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Ecuador through the Organic Law of Energy Efficiency establishes that "Starting in the year 2025, all vehicles that are incorporated into the urban and inter-parroquial public transport service must only be electric”, this marks a foundation for the introduction of electric mobility in the country. The present investigation is based on developing an analysis and projection of the Energy Required for the incorporation of electric buses for public passenger transport in the city of Ambato-Ecuador, taking into account the useful life of the vehicle fleet, number of existing vehicles and analysis of transport routes in the study city. The energy demand based on the vehicular dynamics is analyzed, determination of equations for the calculation of force in the wheel since it is considered a variable of slope due to the fact that this has a great incidence in the autonomy when speaking of electric mobility, later the energy analysis applied to public transport routes, finally a projection of the energy requirement is made based on the change of public transport units according to their useful life.

Keywords: public transport, electric mobility, energy, ecuador

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Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: Jure Galović, Peter Hofmann

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Thermochemical energy storage (TCES), as a long-term and lossless energy storage principle, provides a contribution for the reduction of greenhouse emissions of mobile applications, such as passenger vehicles with an internal combustion engine. A prototype of a TCES system, based on reversible sorption reactions of LiBr composite and methanol has been designed at Vienna University of Technology. In this paper, the selection of reactive and inert carrier materials as well as the design of heat exchangers (reactor vessel and evapo-condenser) was reviewed and the cycle stability under real operating conditions was investigated. The performance of the developed system strongly depends on the environmental temperatures, to which the reactor vessel and evapo-condenser are exposed during the phases of thermal conversion. For an integration of the system into mobile applications, the functionality of the designed prototype was proved in numerous conducted cycles whereby no adverse reactions were observed.

Keywords: dynamic applications, LiBr composite, methanol, performance of TCES system, sorption process, thermochemical energy storage

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Authors: Malathi Iyer, Jayesh Vaidya

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The demographic dividend of India will last for thirty years from now. However, reduction in birth rate, an increase in working population, improvements in medicine and better health practices lead to an ever-expanding elderly population, bringing additional burden to the economy and putting an end to the demographic dividend. To reap the dividend India needs to train the youth for employability. The need of the hour is to improve their life skills which lead the youth to become industrious and have continuous employment. The study will be conducted in perceiving the skill gaps that exist in commerce students for employability. The analysis results indicate the relation between the core study and the right skills for the workforce, with the steps that are taken to open the window for the demographic dividend.

Keywords: demographic dividend, life skills, employability, workforce

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Authors: Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

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Current state-of-the-art classification and detection algorithms rely on supervised training. In this work we study unsupervised feature learning in the context of temporally coherent video data. We focus on feature learning from unlabeled video data, using the assumption that adjacent video frames contain semantically similar information. This assumption is exploited to train a convolutional pooling auto-encoder regularized by slowness and sparsity. We establish a connection between slow feature learning to metric learning and show that the trained encoder can be used to define a more temporally and semantically coherent metric.

Keywords: machine learning, pattern clustering, pooling, classification

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Authors: Watchareeporn Chaimongkol

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In this paper, we compare the statistical measures accuracy of composite forecasting model to estimate automobile customer demand in Thailand. A modified simple exponential smoothing and autoregressive integrate moving average (ARIMA) forecasting model is built to estimate customer demand of passenger cars, instead of using information of historical sales data. Our model takes into account special characteristic of the Thai automobile market such as sales promotion, advertising and publicity, petrol price, and interest rate for loan. We evaluate our forecasting model by comparing forecasts with actual data using six accuracy measurements, mean absolute percentage error (MAPE), geometric mean absolute error (GMAE), symmetric mean absolute percentage error (sMAPE), mean absolute scaled error (MASE), median relative absolute error (MdRAE), and geometric mean relative absolute error (GMRAE).

Keywords: composite forecasting, simple exponential smoothing model, autoregressive integrate moving average model selection, accuracy measurements

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Authors: Mohammadamin Abbasnejad

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The analysis of expression and facial Action Units (AUs) detection are very important tasks in fields of computer vision and Human Computer Interaction (HCI) due to the wide range of applications in human life. Many works have been done during the past few years which has their own advantages and disadvantages. In this work, we present a new model based on Gaussian Conditional Random Field. We solve our objective problem using ADMM and we show how well the proposed model works. We train and test our work on two facial expression datasets, CK+, and RU-FACS. Experimental evaluation shows that our proposed approach outperform state of the art expression recognition.

Keywords: Gaussian Conditional Random Field, ADMM, convergence, gradient descent

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Authors: Toan Vo

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Electronic attacks, illegal drones, interference, and jamming are no longer capabilities reserved for a state-sponsored, near-peer adversary. The proliferation of jammers on auction websites has lowered the price of entry for electronics hobbyists and nefarious actors. To enable local authorities and enforcement bodies to keep up with these challenges, this paper proposes a training as a service model to quickly and economically train and equip police departments and local law enforcement agencies. Using the U.S Department of Defense’s investment in Electronic Warfare as a guideline, a large number of personnel can be trained on effective spectrum monitoring techniques using commercial equipment readily available on the market. Finally, this paper will examine the economic benefits to the test and measurement industry if the TaaS model is applied.

Keywords: training, electronic warfare, economics, law enforcement

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Authors: Kemal Polat

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In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

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Authors: Sowntharya L.

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Aerodynamics is the most important factor when it comes to resistive forces such as lift, drag and side forces acting on the vehicle. In passenger vehicles, reducing the drag will not only unlock the door for higher achievable speed but will also reduce the fuel consumption of the vehicle. Generally, tyre contributes significantly to the overall aerodynamics of the vehicle. Hence, understanding the air-flow behaviour around the tyre is vital to optimize the aerodynamic performance in the early stage of design process. Nowadays, aerodynamic simulation employing Computational Fluid Dynamics (CFD) is gaining more importance as it reduces the number of physical wind-tunnel experiments during vehicle development process. This research develops a methodology to predict aerodynamic drag of a standalone tyre using Numerical CFD Solver and to validate the same using a wind tunnel experiment. A parametric study was carried out on different tread pattern tyres such as slick, circumferential groove & patterned tyre in stationary and rotating boundary conditions. In order to represent wheel rotation contact with the ground, moving reference frame (MRF) approach was used in this study. Aerodynamic parameters such as drag lift & air flow behaviour around the tire were simulated and compared with experimental results.

Keywords: aerodynamics, CFD, drag, MRF, wind-tunnel

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Authors: Seyed Abbas Tabatabaei, Marjan Naderan Tahan, Arman Kadkhodai

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An efficient optimization approach, called feasible gate (FG), is developed to enhance the computation efficiency and solution quality of the previously developed highway alignment optimization (HAO) model. This approach seeks to realistically represent various user preferences and environmentally sensitive areas and consider them along with geometric design constraints in the optimization process. This is done by avoiding the generation of infeasible solutions that violate various constraints and thus focusing the search on the feasible solutions. The proposed method is simple, but improves significantly the model’s computation time and solution quality. On the other, highway alignment optimization through Feasible Gates, eventuates only economic model by considering minimum design constrains includes minimum reduce of circular curves, minimum length of vertical curves and road maximum gradient. This modelling can reduce passenger comfort and road safety. In most of highway optimization models, by adding penalty function for each constraint, final result handles to satisfy minimum constraint. In this paper, we want to propose a safety-function solution by introducing gift function.

Keywords: safety, highway geometry, optimization, alignment

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Authors: Sharon Garyn-Tal, Shoshana Shahrabani

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Military service in general, and in combat units in particular, can be physically and psychologically stressful. Therefore, type of service may have significant implications for soldiers during and after their military service including emotions, judgments and risk perceptions. Previous studies have focused on risk propensity and risky behavior among soldiers, however there is still lack of knowledge on the impact of type of army service on risk perceptions. The current study examines the effect of type of army service (combat versus non-combat service) and negative incidental emotions on risk perceptions. In 2014 a survey was conducted among 153 combat and non-combat Israeli soldiers. The survey was distributed in train stations and central bus stations in various places in Israel among soldiers waiting for the train/bus. Participants answered questions related to the levels of incidental negative emotions they felt, to their risk perceptions (chances to be hurt by terror attack, by violent crime and by car accident), and personal details including type of army service. The data in this research is unique because military service in Israel is compulsory, so that the Israeli population serving in the army is wide and diversified. The results indicate that currently serving combat participants were more pessimistic in their risk perceptions (for all type of risks) compared to the currently serving non-combat participants. Since combat participants probably experienced severe and distressing situations during their service, they became more pessimistic regarding their probabilities of being hurt in different situations in life. This result supports the availability heuristic theory and the findings of previous studies indicating that those who directly experience distressing events tend to overestimate danger. The findings also indicate that soldiers who feel higher levels of incidental fear and anger have pessimistic risk perceptions. In addition, respondents who experienced combat army service also have pessimistic risk perceptions if they feel higher levels of fear. In addition, the findings suggest that higher levels of the incidental emotions of fear and anger are related to more pessimistic risk perceptions. These results can be explained by the compulsory army service in Israel that constitutes a focused threat to soldiers' safety during their period of service. Thus, in this stressful environment, negative incidental emotions even during routine times correlate with higher risk perceptions. In conclusion, the current study results suggest that combat army service shapes risk perceptions and the way young people control their negative incidental emotions in everyday life. Recognizing the factors affecting risk perceptions among soldiers is important for better understanding the impact of army service on young people.

Keywords: army service, combat soldiers, incidental emotions, risk perceptions

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Authors: Chang Su Woo, Hyun Sung Park

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Air spring system is widely accepted for railway vehicle secondary suspension to reduce and absorb the vibration and noise. The low natural frequency ensures a comfortable ride and an invariably good stiffness. In this paper, the characteristic and durability test was conducted in laboratory by using servo-hydraulic fatigue testing system to reliability evaluation of air spring for electric railway vehicle. The experimental results show that the characteristics and durability of domestically developed products are excellent. Moreover, to guarantee the adaption of air spring, the ride comfort and air pressure variation were measured in train test on subway line. Air spring developed by this study for railway vehicles can guarantee the reliability of average usage of 1 million times at 90% confidence level.

Keywords: air spring, reliability, railway, service lifetime

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Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

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A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

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Authors: Hatem Mrad, Mohamed Bouazara, Fouad Erchiqui

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Fatigue, is considered as one of the main cause of mechanical properties degradation of mechanical parts. Probability and reliability methods are appropriate for fatigue analysis using uncertainties that exist in fatigue material or process parameters. Current work deals with the study of the effect of the number and counting Rainflow cycle on fatigue lifetime (cumulative damage) of an upper arm of the vehicle suspension system. The major part of the fatigue damage induced in suspension arm is caused by two main classes of parameters. The first is related to the materials properties and the second is the road excitation or the applied force of the passenger’s number. Therefore, Young's modulus and road excitation are selected as input parameters to conduct repetitive simulations by Monte Carlo (MC) algorithm. Latin hypercube sampling method is used to generate these parameters. Response surface method is established according to fatigue lifetime of each combination of input parameters according to strain-life method. A PYTHON script was developed to automatize finite element simulations of the upper arm according to a design of experiments.

Keywords: fatigue, monte carlo, rainflow cycle, response surface, suspension system

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Authors: Ioanna Pagoni, Annitsa Koumoutsidi

Abstract:

The aim of this paper is to estimate the efficiency of airports that are located in touristic regions. It focuses on the regional airports of Greece, which are located at the mainland and the islands that constitute touristic destinations. Most of these airports share the following characteristics. They operate at levels below capacity with a high level of seasonality to their traffic. In addition, in such airports, the operation of charter and low-cost airlines is significant. The efficiency of the study airports is calculated by using the non-parametric data envelopment analysis during the period of 2010-2016. The selected inputs include several airport infrastructure measures such as passenger terminal size, aircraft parking area, runway length, and the number of check-in counters, while the number of employees in each airport is also used. The number of passengers and aircraft movements are selected as outputs. The effect of seasonality, as well as the operation of charter airlines and low-cost carriers on airport efficiency, is estimated by running proper regression models. Preliminary findings indicate that low-cost and charter airlines contribute to increasing airport efficiency for most of the study airports. The results of this research could be useful for airlines, airport operators, hotel businesses, and other tourism-related operators.

Keywords: airport efficiency, data envelopment analysis, low-cost carriers, charter airlines, seasonality

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