Search results for: Plug-in Hybrid Vehicles

Authors: Jinghao Sun, Guozhen Tan, Guangjian Hou

Abstract:

The Chinese Postman Problem (CPP) is one of the classical problems in graph theory and is applicable in a wide range of fields. With the rapid development of hybrid systems and model based testing, Chinese Postman Problem with Time Dependent Travel Times (CPPTDT) becomes more realistic than the classical problems. In the literature, we have proposed the first integer programming formulation for the CPPTDT problem, namely, circuit formulation, based on which some polyhedral results are investigated and a cutting plane algorithm is also designed. However, there exists a main drawback: the circuit formulation is only available for solving the special instances with all circuits passing through the origin. Therefore, this paper proposes a new integer programming formulation for solving all the general instances of CPPTDT. Moreover, the size of the circuit formulation is too large, which is reduced dramatically here. Thus, it is possible to design more efficient algorithm for solving the CPPTDT in the future research.

Keywords: Chinese Postman Problem, Time Dependent, Integer Programming, Upper Bound Analysis.

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Authors: Alicia Y. C. Tang, Rukaini Abdullah, Sharifuddin M. Zain, Noorsaadah A. Rahman

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This paper discusses the causal explanation capability of QRIOM, a tool aimed at supporting learning of organic chemistry reactions. The development of the tool is based on the hybrid use of Qualitative Reasoning (QR) technique and Qualitative Process Theory (QPT) ontology. Our simulation combines symbolic, qualitative description of relations with quantity analysis to generate causal graphs. The pedagogy embedded in the simulator is to both simulate and explain organic reactions. Qualitative reasoning through a causal chain will be presented to explain the overall changes made on the substrate; from initial substrate until the production of final outputs. Several uses of the QPT modeling constructs in supporting behavioral and causal explanation during run-time will also be demonstrated. Explaining organic reactions through causal graph trace can help improve the reasoning ability of learners in that their conceptual understanding of the subject is nurtured.

Keywords: Qualitative reasoning, causal graph, organicreactions, explanation, QPT, modeling constructs.

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Authors: Yassamina Berkane, Leïla Kloul, Yoann Demoli

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Quality of life, environmental impact, congestion of mobility means, and infrastructures remain significant challenges for urban mobility. Solutions like car sharing, spatial redesign, eCommerce, and autonomous vehicles will likely increase the unit veh-km and the density of cars in urban traffic, thus reducing congestion. However, the impact of such solutions is not clear for researchers. Congestion arises from growing populations that must travel greater distances to arrive at similar locations (e.g., workplaces, schools) during the same time frame (e.g., rush hours). This paper first reviews the research and application cases of urban congestion methods through recent years. Rethinking the question of time, it then investigates people’s willingness and flexibility to adapt their arrival and departure times from workplaces. We use neural networks and methods of supervised learning to apply a methodology for predicting peoples’ intentions from their responses in a questionnaire. We created and distributed a questionnaire to more than 50 companies in the Paris suburb. Obtained results illustrate that our methodology can predict peoples’ intentions to reschedule their activities (work, study, commerce, etc.).

Keywords: Urban mobility, decongestion, machine learning, neural network.

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Authors: W. Hasan, H. Farhat

Abstract:

A hybrid quasi-steady thermal lattice Boltzmann model was used to study the combined effects of temperature and contact angle on the movement of slugs and droplets of oil in water (O/W) system flowing between two parallel plates. The model static contact angle due to the deposition of the O/W droplet on a flat surface with simulated hydrophilic characteristic at different fluid temperatures, matched very well the proposed theoretical calculation. Furthermore, the model was used to simulate the dynamic behavior of droplets and slugs deposited on the domain’s upper and lower surfaces, while subjected to parabolic flow conditions. The model accurately simulated the contact angle hysteresis for the dynamic droplets cases. It was also shown that at elevated temperatures the required power to transport the mixture diminished remarkably.

Keywords: Lattice Boltzmann method, Gunstensen model, thermal, contact angle, high viscosity ratio.

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Authors: Mozhgan Aliakbari, Sara Moridpour

Abstract:

In recent years, much attention has been given to truck drivers’ fatigue management. Long working hours negatively influence truck drivers’ physiology, health, and safety. However, there is little empirical research in the heavy vehicle transport sector in Australia to identify the influence of working hours’ management on drivers’ fatigue and consequently, on the risk of crashes and injuries. There is no national legislation regulating the number of hours or kilometres travelled by truck drivers. Consequently, it is almost impossible to define a standard number of hours or kilometres for truck drivers in a safety management system. This paper reviews the existing studies concerning safe system interventions such as tachographs in relation to fatigue caused by long working hours. This paper also reviews the literature to identify the influence of frequency of rest breaks on the reduction of work-related road transport accidents involving trucks. A framework is presented to manage truck drivers’ fatigue, which may result in the reduction of injuries and fatalities involving heavy vehicles.

Keywords: Fatigue, time management, trucks, traffic safety.

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Authors: Suneel M. Agerwala, Ashley Votta, Briana Hogan, John Yannocone, Steven Samuels, SheilaChiffriller

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Road rage is an increasingly prevalent expression of aggression in our society. Its dangers are apparent and understanding its causes may shed light on preventative measures. This study involved a fifteen-minute survey administered to 147 undergraduate students at a North Eastern suburban university. The survey consisted of a demographics section, questions regarding financial investment in respondents- vehicles, experience driving, habits of driving, experiences witnessing role models driving, and an evaluation of road rage behavior using the Driving Vengeance Questionnaire. The study found no significant differences in driving aggression between respondents who were financially invested in their vehicle compared to those who were not, or between respondents who drove in heavy traffic hours compared to those who did not, suggesting internal factors correlate with aggressive driving habits. The study also found significant differences in driving aggression between males versus females, those with more points on their license versus fewer points, and those who witnessed parents driving aggressively very often versus rarely or never. Additional studies can investigate how witnessing parents driving aggressively is related to future driving behaviors.

Keywords: Aggression, college, driving, road rage.

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Authors: Tomas Duranik, Juraj Ruzbarsky, Markus Stopper

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CONWIP (constant work-in-process) as a pull production system have been widely studied by researchers to date. The CONWIP pull production system is an alternative to pure push and pure pull production systems. It lowers and controls inventory levels which make the throughput better, reduces production lead time, delivery reliability and utilization of work. In this article a CONWIP pull production system was simulated. It was simulated push and pull planning system. To compare these systems via a production planning system (PPS) game were adjusted parameters of each production planning system. The main target was to reduce the total WIP and achieve throughput and delivery reliability to minimum values. Data was recorded and evaluated. A future state was made for real production of plastic components and the setup of the two indicators with CONWIP pull production system which can greatly help the company to be more competitive on the market.

Keywords: CONWIP, constant work in process, delivery reliability, hybrid production planning, PPS.

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Authors: Tor Kindsbekken Kjeldby, Ruud Henkes, Ole Jørgen Nydal

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Experimental data from an atmospheric air/water terrain slugging case has been made available by the Shell Amsterdam research center, and has been subject to numerical simulation and comparison with a one-dimensional two-phase slug tracking simulator under development at the Norwegian University of Science and Technology. The code is based on tracking of liquid slugs in pipelines by use of a Lagrangian grid formulation implemented in Cµ by use of object oriented techniques. An existing hybrid spatial discretization scheme is tested, in which the stratified regions are modelled by the two-fluid model. The slug regions are treated incompressible, thus requiring a single momentum balance over the whole slug. Upon comparison with the experimental data, the period of the simulated severe slugging cycle is observed to be sensitive to slug generation in the horizontal parts of the system. Two different slug initiation methods have been tested with the slug tracking code, and grid dependency has been investigated.

Keywords: Hydrodynamic initiation, slug tracking, terrain slugging, two-fluid model, two-phase flow.

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Authors: Benjamin Gorry, Zezhi Chen, Kevin Hammond, Andy Wallace, Greg Michaelson

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This paper describes new computer vision algorithms that have been developed to track moving objects as part of a long-term study into the design of (semi-)autonomous vehicles. We present the results of a study to exploit variable kernels for tracking in video sequences. The basis of our work is the mean shift object-tracking algorithm; for a moving target, it is usual to define a rectangular target window in an initial frame, and then process the data within that window to separate the tracked object from the background by the mean shift segmentation algorithm. Rather than use the standard, Epanechnikov kernel, we have used a kernel weighted by the Chamfer distance transform to improve the accuracy of target representation and localization, minimising the distance between the two distributions in RGB color space using the Bhattacharyya coefficient. Experimental results show the improved tracking capability and versatility of the algorithm in comparison with results using the standard kernel. These algorithms are incorporated as part of a robot test-bed architecture which has been used to demonstrate their effectiveness.

Keywords: Hume, functional programming, autonomous vehicle, pioneer robot, vision.

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Authors: Sanjay Kumar Srivastava, Anu Rani Sharma, Kamna Sachdeva

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The aim of the paper is to analyze the characteristics of winter fog in terms of its trend and spatial-temporal variability over Indo-Gangetic plains. The study reveals that during last four and half decades (1971-2015), an alarming increasing trend in fog frequency has been observed during the winter months of December and January over the study area. The frequency of fog has increased by 118.4% during the peak winter months of December and January. It has also been observed that on an average central part of IGP has 66.29% fog days followed by west IGP with 41.94% fog days. Further, Empirical Orthogonal Function (EOF) decomposition and Mann-Kendall variation analysis are used to analyze the spatial and temporal patterns of winter fog. The findings have significant implications for the further research of fog over IGP and formulate robust strategies to adapt the fog variability and mitigate its effects. The decision by Delhi Government to implement odd-even scheme to restrict the use of private vehicles in order to reduce pollution and improve quality of air may result in increasing the alarming increasing trend of fog over Delhi and its surrounding areas regions of IGP.

Keywords: Fog, climatology, spatial variability, temporal variability, empirical orthogonal function, visibility, Mann-Kendall test, variation point.

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Authors: Bruno Vilić Belina, Ivan Župan

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Smart industry concepts and digital transformation are very popular in many industries. They develop their own digital platforms, which have an important role in innovations and transactions. The main idea of smart industry digital platforms is central data collection, industrial data integration and data usage for smart applications and services. This paper presents the development of a digital platform for building critical infrastructure protection systems in smart industries. Different service contraction modalities in Service Level Agreements (SLAs), Customer Relationship Management (CRM) relations, trends and changes in business architectures (especially process business architecture) for the purpose of developing infrastructural production and distribution networks, information infrastructure meta-models and generic processes by critical infrastructure owner demanded by critical infrastructure law, satisfying cybersecurity requirements and taking into account hybrid threats are researched.

Keywords: Cybersecurity, critical infrastructure, smart industries, digital platform.

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Authors: Jafar Abbaszadeh Chekan, Kaveh Merat, Hassan Zohoor

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In this study the regional stability of a rotor system which is supported on rolling bearings with radial clearance is studied. The rotor is assumed to be rigid. Due to radial clearance of bearings and dynamic configuration of system, each rolling elements of bearings has the possibility to be in contact with both of the races (under compression) or lose its contact. As a result, this change in dynamic of the system makes it to be known as switching system which is a type of Hybrid systems. In this investigation by adopting Multiple Lyapunov Function theorem and using Hamiltonian function as a candidate Lyapunov function, the stability of the system is studied. The purpose of this study is to inspect the regional stability of rotor-roller bearing and rotor-ball bearing systems.

Keywords: Stability analysis, Rotor-rolling bearing systems, Switching systems, Multiple Lyapunov Function Method

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Authors: Sungho Kim, Chaehoon Park, Yukyung Choi, Soon Kwon, In So Kweon

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In this paper, a novel corner detection method is presented to stably extract geometrically important corners. Intensity-based corner detectors such as the Harris corner can detect corners in noisy environments but has inaccurate corner position and misses the corners of obtuse angles. Edge-based corner detectors such as Curvature Scale Space can detect structural corners but show unstable corner detection due to incomplete edge detection in noisy environments. The proposed image-based direct curvature estimation can overcome limitations in both inaccurate structural corner detection of the Harris corner detector (intensity-based) and the unstable corner detection of Curvature Scale Space caused by incomplete edge detection. Various experimental results validate the robustness of the proposed method.

Keywords: Feature, intensity, contour, hybrid.

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Authors: Orestis Κ. Efthymiou, Stavros T. Ponis

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In the last decade, a new industrial revolution seems to be emerging, supported -once again- by the rapid advancements of Information Technology in the areas of Machine-to-Machine (M2M) communication permitting large numbers of intelligent devices, e.g. sensors to communicate with each other and take decisions without any or minimum indirect human intervention. The advent of these technologies have triggered the emergence of a new category of hybrid (cyber-physical) manufacturing systems, combining advanced manufacturing techniques with innovative M2M applications based on the Internet of Things (IoT), under the umbrella term Industry 4.0. Even though the topic of Industry 4.0 has attracted much attention during the last few years, the attempts of providing a systematic literature review of the subject are scarce. In this paper, we present the authors’ initial study of the field with a special focus on the use and applications of Industry 4.0 principles in material handling automations and in-house logistics. Research shows that despite the vivid discussion and attractiveness of the subject, there are still many challenges and issues that have to be addressed before Industry 4.0 becomes standardized and widely applicable.

Keywords: Industry 4.0, internet of things, manufacturing systems, material handling, logistics.

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Authors: Tijani Delleji, Mourad Zribi, Ahmed Ben Hamida

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This paper discusses EM algorithm and Bootstrap approach combination applied for the improvement of the satellite image fusion process. This novel satellite image fusion method based on estimation theory EM algorithm and reinforced by Bootstrap approach was successfully implemented and tested. The sensor images are firstly split by a Bayesian segmentation method to determine a joint region map for the fused image. Then, we use the EM algorithm in conjunction with the Bootstrap approach to develop the bootstrap EM fusion algorithm, hence producing the fused targeted image. We proposed in this research to estimate the statistical parameters from some iterative equations of the EM algorithm relying on a reference of representative Bootstrap samples of images. Sizes of those samples are determined from a new criterion called 'hybrid criterion'. Consequently, the obtained results of our work show that using the Bootstrap EM (BEM) in image fusion improve performances of estimated parameters which involve amelioration of the fused image quality; and reduce the computing time during the fusion process.

Keywords: Satellite image fusion, Bayesian segmentation, Bootstrap approach, EM algorithm.

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Authors: Cristina Vatamanu, Doina Cosovan, Dragoş Gavriluţ, Henri Luchian

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In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through (semi)-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability.

Keywords: Detection Rate, False Positives, Perceptron, One Side Class, Ensembles, Decision Tree, Hybrid methods, Feature Selection.

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Authors: Abdelouahab Moussaoui, Nabila Ferahta, Victor Chen

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The development of aid's systems for the medical diagnosis is not easy thing because of presence of inhomogeneities in the MRI, the variability of the data from a sequence to the other as well as of other different source distortions that accentuate this difficulty. A new automatic, contextual, adaptive and robust segmentation procedure by MRI brain tissue classification is described in this article. A first phase consists in estimating the density of probability of the data by the Parzen-Rozenblatt method. The classification procedure is completely automatic and doesn't make any assumptions nor on the clusters number nor on the prototypes of these clusters since these last are detected in an automatic manner by an operator of mathematical morphology called skeleton by influence zones detection (SKIZ). The problem of initialization of the prototypes as well as their number is transformed in an optimization problem; in more the procedure is adaptive since it takes in consideration the contextual information presents in every voxel by an adaptive and robust non parametric model by the Markov fields (MF). The number of bad classifications is reduced by the use of the criteria of MPM minimization (Maximum Posterior Marginal).

Keywords: Clustering, Automatic Classification, SKIZ, MarkovFields, Image segmentation, Maximum Posterior Marginal (MPM).

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Authors: Reza Ghasemi, Negin Amiri Hazaveh

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In this paper, control methodology based on the selection of the type of traffic light and the period of the green phase to accomplish an optimum balance at intersections is proposed. This balance should be flexible to the static behavior of time, and randomness in a traffic situation; the goal of the proposed method is to reduce traffic volume in transportation, the average delay for each vehicle, and control over the crash of cars. The proposed method was specifically investigated at the intersection through an appropriate timing of traffic lights by sampling a multi-agent system. It consists of a large number of intersections, each of which is considered as an independent agent that exchanges information with each other, and the stability of each agent is provided separately. The robustness against uncertainties, scalability, and stability of the closed-loop overall system are the main merits of the proposed methodology. The simulation results show that the fuzzy intelligent controller in this multi-factor system which is a Takagi-Sugeno (TS) fuzzy is more useful than scheduling in the fixed-time method and it reduces the lengths of vehicles queuing.

Keywords: Fuzzy intelligent controller, traffic-light control, multi-agent systems, state space equations, stability.

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Authors: Hans R. Márquez, Cesar Hernández, Ingrid Páez

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This paper develops a multiple channel assignment model, which allows to take advantage of spectrum opportunities in cognitive radio networks in the most efficient way. The developed scheme allows making several assignments of available and frequency adjacent channel, which require a bigger bandwidth, under an equality environment. The hybrid assignment model it is made by two algorithms, one that makes the ranking and selects available frequency channels and the other one in charge of establishing the Max-Min Fairness for not restrict the spectrum opportunities for all the other secondary users, who also claim to make transmissions. Measurements made were done for average bandwidth, average delay, as well as fairness computation for several channel assignments. Reached results were evaluated with experimental spectrum occupational data from captured GSM frequency band. The developed model shows evidence of improvement in spectrum opportunity use and a wider average transmission bandwidth for each secondary user, maintaining equality criteria in channel assignment.

Keywords: Bandwidth, fairness, multichannel, secondary users.

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Authors: Tahar Ezzedine, Mohamed Miladi, Ridha Bouallegue

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Because nodes are usually battery-powered, the energy presents a very scarce resource in wireless sensor networks. For this reason, the design of medium access control had to take energy efficiency as one of its hottest concerns. Accordingly, in order to improve the energy performance of MAC schemes in wireless sensor networks, several ways can be followed. In fact, some researchers try to limit idle listening while others focus on mitigating overhearing (i.e. a node can hear a packet which is destined to another node) or reducing the number of the used control packets. We, in this paper, propose a new hybrid MAC protocol termed ELE-MAC (i.e. Energy Latency Efficient MAC). The ELE-MAC major design goals are energy and latency efficiencies. It adopts less control packets than SMAC in order to preserve energy. We carried out ns- 2 simulations to evaluate the performance of the proposed protocol. Thus, our simulation-s results prove the ELE-MAC energy efficiency. Additionally, our solution performs statistically the same or better latency characteristic compared to adaptive SMAC.

Keywords: Control packet, energy efficiency, medium access control, wireless sensor networks.

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Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

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Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: Equivalent circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square.

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Authors: Lina Galinskaitė, Gytautas Ignatavičius

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Animal vehicle collisions (AVCs) affect human safety, cause property damage and wildlife welfare. The number of AVCs are increasing and creating serious implications for the animal conservation and management. Roe deer (Capreolus capreolus) and other large ungulates (moose, wild boar, red deer) are the most frequently collided ungulate with vehicles in Europe. Therefore, we analyzed temporal patterns of roe deer vehicle collisions (RDVC) occurring in Lithuania. Using a comprehensive dataset, consisting of 15,891 data points, we examined the influence of different time units (i.e. time of the day, day of week, month, and season) on RDVC. We identified accident periods within the analyzed time units. Highest frequencies of RDVC occurred on Fridays. Highest frequencies of roe deer-vehicle accidents occurred in May, November and December. Regarding diurnal patterns, most of RDVC occur after sunset and before sunset (during dark hours). Since vehicle collisions with animals showed temporal variation, these should be taken into consideration in developing statistical models of spatial AVC patterns, and also in planning strategies to reduce accident risk.

Keywords: Animal vehicle collision, diurnal patterns, road safety, roe deer, statistical analysis.

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Authors: Souhir Ben Amor, Heni Boubaker, Lotfi Belkacem

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This aims of this paper is to forecast the electricity spot prices. First, we focus on modeling the conditional mean of the series so we adopt a generalized fractional -factor Gegenbauer process (k-factor GARMA). Secondly, the residual from the -factor GARMA model has used as a proxy for the conditional variance; these residuals were predicted using two different approaches. In the first approach, a local linear wavelet neural network model (LLWNN) has developed to predict the conditional variance using the Back Propagation learning algorithms. In the second approach, the Gegenbauer generalized autoregressive conditional heteroscedasticity process (G-GARCH) has adopted, and the parameters of the k-factor GARMA-G-GARCH model has estimated using the wavelet methodology based on the discrete wavelet packet transform (DWPT) approach. The empirical results have shown that the k-factor GARMA-G-GARCH model outperform the hybrid k-factor GARMA-LLWNN model, and find it is more appropriate for forecasts.

Keywords: k-factor, GARMA, LLWNN, G-GARCH, electricity price, forecasting.

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Authors: Mert Bal, Hayri Sever, Oya Kalıpsız

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Medical Decision Support Systems (MDSSs) are sophisticated, intelligent systems that can provide inference due to lack of information and uncertainty. In such systems, to model the uncertainty various soft computing methods such as Bayesian networks, rough sets, artificial neural networks, fuzzy logic, inductive logic programming and genetic algorithms and hybrid methods that formed from the combination of the few mentioned methods are used. In this study, symptom-disease relationships are presented by a framework which is modeled with a formal concept analysis and theory, as diseases, objects and attributes of symptoms. After a concept lattice is formed, Bayes theorem can be used to determine the relationships between attributes and objects. A discernibility relation that forms the base of the rough sets can be applied to attribute data sets in order to reduce attributes and decrease the complexity of computation.

Keywords: Formal Concept Analysis, Rough Set Theory, Granular Computing, Medical Decision Support System.

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Authors: Gyo Woo Lee, Man Young Kim

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Emission regulations for diesel engines are being strengthened and it is impossible to meet the standards without exhaust after-treatment systems. Lack of the space in many diesel vehicles, however, make it difficult to design and install stand-alone catalytic converters such as DOC, DPF, and SCR in the vehicle exhaust systems. Accordingly, those have been installed inside the muffler to save the space, and referred to the catalytic muffler. However, that has complex internal structure with perforated plate and pipe for noise and monolithic catalyst for emission reduction. For this reason, flow uniformity and pressure drop, which affect efficiency of catalyst and engine performance, respectively, should be examined when the catalytic muffler is designed. In this work, therefore, the flow uniformity and pressure drop to improve the performance of the catalytic converter and the engine have been numerically investigated by changing various design parameters such as inlet shape, porosity, and outlet shape of the muffler using the three-dimensional turbulent flow of the incompressible, non-reacting, and steady state inside the catalytic muffler. Finally, it can be found that the shape, in which the muffler has perforated pipe inside the inlet part, has higher uniformity index and lower pressure drop than others considered in this work.

Keywords: Catalytic muffler, Perforated inlet cone, Catalysts, Perforated pipe, Flow uniformity, Pressure drop.

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Authors: Kh.Farhangdoust, H.Kamankesh

Abstract:

Undoubtedly, chassis is one of the most important parts of a vehicle. Chassis that today are produced for vehicles are made up of four parts. These parts are jointed together by screwing. Transverse parts are called cross member. This study reviews the stress generated by cyclic laboratory loads in front cross member of Peugeot 405. In this paper the finite element method is used to simulate the welding process and to determine the physical response of the spot-welded joints. Analysis is done by the Abaqus software. The Stresses generated in cross member structure are generally classified into two groups: The stresses remained in form of residual stresses after welding process and the mechanical stress generated by cyclic load. Accordingly the total stress must be obtained by determining residual stress and mechanical stress separately and then sum them according to the superposition principle. In order to improve accuracy, material properties including physical, thermal and mechanical properties were supposed to be temperature-dependent. Simulation shows that maximum Von Misses stresses are located at special points. The model results are then compared to the experimental results which are reported by producing factory and good agreement is observed.

Keywords: Chassis, cross member, residual stress, resistancespot weld.

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Authors: P.Varzakas

Abstract:

In this paper, an accurate theoretical analysis for the achievable average channel capacity (in the Shannon sense) per user of a hybrid cellular direct-sequence/fast frequency hopping code-division multiple-access (DS/FFH-CDMA) system operating in a Rayleigh fading environment is presented. The analysis covers the downlink operation and leads to the derivation of an exact mathematical expression between the normalized average channel capacity available to each system-s user, under simultaneous optimal power and rate adaptation and the system-s parameters, as the number of hops per bit, the processing gain applied, the number of users per cell and the received signal-tonoise power ratio over the signal bandwidth. Finally, numerical results are presented to illustrate the proposed mathematical analysis.

Keywords: Shannon capacity, adaptive systems, code-division multiple access, fading channels.

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Authors: Basharat Ali Haider, Naveed Durrani, Nadeem Aizud, Salimuddin Zahir

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The aerodynamic stall control of a baseline 13-percent thick NASA GA(W)-2 airfoil using a synthetic jet actuator (SJA) is presented in this paper. Unsteady Reynolds-averaged Navier-Stokes equations are solved on a hybrid grid using a commercial software to simulate the effects of a synthetic jet actuator located at 13% of the chord from the leading edge at a Reynolds number Re = 2.1x106 and incidence angles from 16 to 22 degrees. The experimental data for the pressure distribution at Re = 3x106 and aerodynamic coefficients at Re = 2.1x106 (angle of attack varied from -16 to 22 degrees) without SJA is compared with the computational fluid dynamic (CFD) simulation as a baseline validation. A good agreement of the CFD simulations is obtained for aerodynamic coefficients and pressure distribution. A working SJA has been integrated with the baseline airfoil and initial focus is on the aerodynamic stall control at angles of attack from 16 to 22 degrees. The results show a noticeable improvement in the aerodynamic performance with increase in lift and decrease in drag at these post stall regimes.

Keywords: Active flow control, Aerodynamic stall, Airfoilperformance, Synthetic jet actuator.

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Authors: Guo Yan

Abstract:

Clothing recycling bin is a traditional way to collect textile waste in many areas. In the clothing recycling business, the transportation cost normally takes over 50% of total costs. This case gives a good way to reduce transportation cost by reverse logistics system. In this reverse logistics system, there are offline strategic alliance partners, such as transport firms, convenience stores, laundries, and post office which are integrated onto the mobile APP. Offline strategic alliance partners provide the service of textile waste collection, and transportation by their vacant vehicles return journey from convenience stores, laundries and post offices to sorting centers. The results of the case study provide the strategic alliance with a valuable and light - asset business model by using the logistics of offline memberships. The company in this case just focuses on textile waste sorting, reuse, recycling etc. The research method of this paper is a case study of a clothing recycling company in Chengdu by field research and interview; the analysis is based on the theory of the reverse logistics system.

Keywords: Closed-loop recycles system, clothing recycling, end-of-life clothing, sharing economy, strategic alliance, reverse logistics.

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Authors: Anita Khadka, Gregory Epiphaniou, Carsten Maple

Abstract:

There is a dramatic surge in the adoption of Machine Learning (ML) techniques in many areas, including the nuclear industry (such as fault diagnosis and fuel management in nuclear power plants), autonomous systems (including self-driving vehicles), space systems (space debris recovery, for example), medical surgery, network intrusion detection, malware detection, to name a few. Artificial Intelligence (AI) has become a part of everyday modern human life. To date, the predominant focus has been developing underpinning ML algorithms that can improve accuracy, while factors such as resiliency and robustness of algorithms have been largely overlooked. If an adversarial attack is able to compromise the learning method or data, the consequences can be fatal, especially but not exclusively in safety-critical applications. In this paper, we present an in-depth analysis of five adversarial attacks and two defence methods on a crack detection ML model. Our analysis shows that it can be dangerous to adopt ML techniques without rigorous testing, since they may be vulnerable to adversarial attacks, especially in security-critical areas such as the nuclear industry. We observed that while the adopted defence methods can effectively defend against different attacks, none of them could protect against all five adversarial attacks entirely.

Keywords: Resilient Machine Learning, attacks, defences, nuclear industry, crack detection.

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