Search results for: traffic field

Authors: Manas Tripathi, Arunabha Mukhopadhyay

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In Cloud computing environment, cloud servers, sometimes may crash after receiving huge amount of request and cloud services may stop which can create huge loss to users of that cloud services. This situation is called Denial of Service (DoS) attack. In Distributed Denial of Service (DDoS) attack, an attacker targets multiple network paths by compromising various vulnerable systems (zombies) and floods the victim with huge amount of request through these zombies. There are many solutions to mitigate this challenge but most of the methods allows the attack traffic to arrive at Cloud Service Provider (CSP) and then only takes actions against mitigation. Here in this paper we are rather focusing on preventive mechanism to deal with these attacks. We analyze network topology and find most vulnerable paths beforehand without waiting for the traffic to arrive at CSP. We have used Dijkstra's and Yen’s algorithm. Finally, risk assessment of these paths can be done by multiplying the probabilities of attack for these paths with the potential loss.

Keywords: cloud computing, DDoS, Dijkstra, Yen’s k-shortest path, network security

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Authors: Bijay Kumar Sahoo

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An important feature of InₓGa₁-ₓN/GaN heterostructures is strong built-in polarization (BIP) electric field at the hetero-interface due to spontaneous (sp) and piezoelectric (pz) polarizations. The intensity of this electric field reaches several MV/cm. This field has profound impact on optical, electrical and thermal properties. In this work, the effect of BIP field on thermal conductivity of InₓGa₁-ₓN/GaN heterostructure has been investigated theoretically. The interaction between the elastic strain and built in electric field induces additional electric polarization. This additional polarization contributes to the elastic constant of InₓGa₁-ₓN alloy. This in turn modifies material parameters of InₓGa₁-ₓN. The BIP mechanism enhances elastic constant, phonon velocity and Debye temperature and their bowing constants in InₓGa₁-ₓN alloy. These enhanced thermal parameters increase phonon mean free path which boost thermal conduction process. The thermal conductivity (k) of InxGa1-xN alloy has been estimated for x=0, 0.1, 0.3 and 0.9. Computation finds that irrespective of In content, the room temperature k of InₓGa₁-ₓN/GaN heterostructure is enhanced by BIP mechanism. Our analysis shows that at a certain temperature both k with and without BIP show crossover. Below this temperature k with BIP field is lower than k without BIP; however, above this temperature k with BIP field is significantly contributed by BIP mechanism leading to k with BIP field become higher than k without BIP field. The crossover temperature is primary pyroelectric transition temperature. The pyroelectric transition temperature of InₓGa₁-ₓN alloy has been predicted for different x. This signature of pyroelectric nature suggests that thermal conductivity can reveal pyroelectricity in InₓGa₁-ₓN alloy. The composition dependent room temperature k for x=0.1 and 0.3 are in line with prior experimental studies. The result can be used to minimize the self-heating effect in InₓGa₁-ₓN/GaN heterostructures.

Keywords: built-in polarization, phonon relaxation time, thermal properties of InₓGa₁-ₓN /GaN heterostructure, self-heating

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Authors: Farzad Tofigh, Saeideh Najafi, Reza Heidari, Rashid Jamei

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In order to study the effects of magnetic field on the root system and growth of Phaseolus vulgaris, an experiment was conducted in 2012. The possible involvement of magnetic field (MF) pretreatment in physiological factors of Phaseolus vulgaris was investigated. Seeds were subjected to 10 days with 1.8 mT of magnetic field for 1h per day. MF pretreatment decreased the plant height, fresh and dry weight, length of root and length of shoot, Chlorophyll a, Chlorophyll b and carotenoid in 10 days old seedling. In addition, activity of enzymes such as Catalase and Guaiacol peroxidase was decreased due to MF exposure. Also, the total Protein and DPPH content of the treated by magnetic field was not significantly changed in compare to control groups, while the flavonoid, Phenol and prolin content of the treated of the treated by magnetic field was significantly changed in compare to control groups. Lateral branches of roots and secondary roots increased with MF. The results suggest that pretreatment of this MF plays important roles in changes in crop productivity. In all cases there was observed a slight stimulating effect of the factors examined. The growth dynamics were weakened. The plants were shorter. Moreover, the effect of a magnetic field on the crop of Phaseolus vulgaris and its structure was small.

Keywords: carotenoid, chlorophyll a, chlorophyll b, DPPH, enzymes, flavonoid, germination, growth, phenol, proline, protein, magnetic field

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Authors: Henok Girma Abebe

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The Vision Zero is a long-term goal of preventing all road traffic fatalities and serious injuries which was first adopted in Sweden in 1997. It is based on the assumption that death and serious injury in the road system is morally unacceptable. In order to approach this end, vision zero has put in place strategies that are radically different from the traditional safety work. The vision zero, for instance, promoted the adoption of the best available technology to promote safety, and placed the ultimate responsibility for traffic safety on system designers. Despite Vision Zero’s moral appeal and its expansion to different safety areas and also parts of the world, important philosophical concerns related to the adoption and implementation of the vision zero remain to be addressed. Moreover, the vision zero goal has been criticized on different grounds. The aim of this paper is to identify and systematically categorize criticisms that have been put forward against vision zero. The findings of the paper are solely based on a critical analysis of secondary sources and snowball method is employed to identify the relevant philosophical and empirical literatures. Two general categories of criticisms on the vision zero goal are identified. The first category consists of criticisms that target the setting of vision zero as a ‘goal’ and some of the basic assumptions upon which the goal is based. Among others, the goal of achieving zero fatalities and serious injuries, together with vision zero’s lexicographical prioritization of safety has been criticized as unrealistic. The second category consists of criticisms that target the strategies put in place to achieve the goal of zero fatalities and serious injuries. For instance, Vision zero’s responsibility ascription for road safety and its rejection of cost-benefit analysis in the formulation and adoption of safety measures has both been criticized as counterproductive. In this category also falls the criticism that Vision Zero safety measures tend to be too paternalistic. Significant improvements have been recorded in road safety work since the adoption of vision zero, however, for the vision zero to even succeed more, it is important that issues and criticisms of philosophical nature associated with it are identified and critically dealt with.

Keywords: criticisms, systems approach, traffic safety, vision zero

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Authors: Amin Hamrahi

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Near Field Communication (NFC) is one of the latest wireless communication technologies. NFC enables electronic devices to communicate in short range using the radio waves. NFC offers safe yet simple communication between electronic devices. This technology provides the fastest way to communicate two device with in a fraction of second. With NFC technology, communication occurs when an NFC-compatible device is brought within a few centimeters of another NFC device. NFC is an open-platform technology that is being standardized in the NFC Forum. NFC is based on and extends on RFID. It operates on 13.56 MHz frequency.

Keywords: near field communication, NFC technology, wireless communication technologies, NFC-compatible device, NFC, communication

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Authors: Mohammad Ahmad, Dayalan Kasilingam

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In this paper, a spectral domain implementation of the fast multipole method is presented. It is shown that the aggregation, translation, and disaggregation stages of the fast multipole method (FMM) can be performed using the spectral domain (SD) analysis. The spectral domain fast multipole method (SD-FMM) has the advantage of eliminating the near field/far field classification used in conventional FMM formulation. The study focuses on the application of SD-FMM to one-dimensional (1D) and two-dimensional (2D) electric field integral equation (EFIE). The case of perfectly conducting strip, circular and square cylinders are numerically analyzed and compared with the results from the standard method of moments (MoM).

Keywords: electric field integral equation, fast multipole method, method of moments, wave scattering, spectral domain

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Authors: Sabiha Chouchane, Azzedine Hani, Jean-Paul Chopart, Alexandra Levesque

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The electrodeposition of Zn-Ni alloy is mostly studied for its high degree of corrosion and mechanical properties. In this work, the zinc–nickel alloy coatings elaborated from sulfate bath have been carried out under low and high applied magnetic field. The effect of alloy stuctural parameters upon corrosion behavior is studied. It has been found that the magnetically induced convection changes the phase composition, promoting the zinc phase in spite of the γ-Ni₅Zn₂₁. Low magnetic field acts also on the morphology of the deposits as a levelling agent and a refiner by lowering the deposit roughness Ra and the spot size. For alloy obtained with low magnetic field (up to 1T) superimposition, surface morphology modification has no significant influence on corrosion behavior whereas for low nickel content alloy, the modification of phase composition, induced by applied magnetic field, favours higher polarization resistance. When high magnetic field amplitude is involved (up to12T), the phase composition modifications are the same that for low applied B and the morphology is not largely modified. In this case, the hydrogen reduction current dramatically decreases that leads to a large shift of the corrosion potential. It is suggested that the surface reactivity of electrodeposited alloys depends on the magnetically induced convection that is efficient during the codeposition process.

Keywords: magnetic field, Zn-Ni alloy, corrosion, corrosive medium

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Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: decision tree, feature selection, intrusion detection system, support vector machine

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Authors: Xiao Yihong, Yu Kexin, Burra Venkata Durga Kumar

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With the accelerating process of urbanization, the problem of urban road congestion is becoming more and more serious. Intelligent transportation system combining distributed and artificial intelligence has become a research hotspot. As the core development direction of the intelligent transportation system, Cooperative Intelligent Transportation System (C-ITS) integrates advanced information technology and communication methods and realizes the integration of humans, vehicle, roadside infrastructure, and other elements through the multi-agent distributed system. By analyzing the system architecture and technical characteristics of C-ITS, the report proposes a distributed multi-agent C-ITS. The system consists of Roadside Sub-system, Vehicle Sub-system, and Personal Sub-system. At the same time, we explore the scalability of the C-ITS and put forward incorporating local rewards in the centralized training decentralized execution paradigm, hoping to add a scalable value decomposition method. In addition, we also suggest introducing blockchain to improve the safety of the traffic information transmission process. The system is expected to improve vehicle capacity and traffic safety.

Keywords: distributed system, artificial intelligence, multi-agent, cooperative intelligent transportation system

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Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

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As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%).

Keywords: intrusion detection, supervised learning, traffic classification, computer networks

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Authors: Peter Baji

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In recent years, a growing body of literature emphasizes the increasingly negative impacts of urban road congestion in the everyday life of citizens. Although there are different responses from the public sector to decrease traffic congestion in urban regions, the most effective public intervention is using congestion charges. Because travel is an economic asset, its consumption can be controlled by extra taxes or prices effectively, but this demand-side intervention is often unpopular. Measuring traffic flows with the help of different methods has a long history in transport sciences, but until recently, there was not enough sufficient data for evaluating road traffic flow patterns on the scale of an entire road system of a larger urban area. European cities (e.g., London, Stockholm, Milan), in which congestion charges have already been introduced, designated a particular zone in their downtown for paying, but it protects only the users and inhabitants of the CBD (Central Business District) area. Through the use of Google Maps data as a resource for revealing urban road traffic flow patterns, this paper aims to provide a solution for a fairer and smarter congestion pricing method in cities. The case study area of the research contains three bordering districts of Budapest which are linked by one main road. The first district (5th) is the original downtown that is affected by the congestion charge plans of the city. The second district (13th) lies in the transition zone, and it has recently been transformed into a new CBD containing the biggest office zone in Budapest. The third district (4th) is a mainly residential type of area on the outskirts of the city. The raw data of the research was collected with the help of Google’s Distance Matrix API (Application Programming Interface) which provides future estimated traffic data via travel times between freely fixed coordinate pairs. From the difference of free flow and congested travel time data, the daily congestion patterns and hot spots are detectable in all measured roads within the area. The results suggest that the distribution of congestion peak times and hot spots are uneven in the examined area; however, there are frequently congested areas which lie outside the downtown and their inhabitants also need some protection. The conclusion of this case study is that cities can develop a real-time and place-based congestion charge system that forces car users to avoid frequently congested roads by changing their routes or travel modes. This would be a fairer solution for decreasing the negative environmental effects of the urban road transportation instead of protecting a very limited downtown area.

Keywords: Budapest, congestion charge, distance matrix API, application programming interface, pilot study

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Authors: Yuan Zheng

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3D model-based vehicle matching provides a new way for vehicle recognition, localization and tracking. Its key is to construct an evaluation function, also called fitness function, to measure the degree of vehicle matching. The existing fitness functions often poorly perform when the clutter and occlusion exist in traffic scenarios. In this paper, we present a practical and efficient fitness function. Unlike the existing evaluation functions, the proposed fitness function is to study the vehicle matching problem from both local and global perspectives, which exploits the pixel gradient information as well as the silhouette information. In view of the discrepancy between 3D vehicle model and real vehicle, a weighting strategy is introduced to differently treat the fitting of the model’s wireframes. Additionally, a normalization operation for the model’s projection is performed to improve the accuracy of the matching. Experimental results on real traffic videos reveal that the proposed fitness function is efficient and robust to the cluttered background and partial occlusion.

Keywords: 3D-2D matching, fitness function, 3D vehicle model, local image gradient, silhouette information

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Authors: E. Azizi Asiyabar

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The phenomenon of migration to larger cities has brought about a range of consequences, including increased travel demand and the necessity for smooth traffic flow to expedite transportation. Regrettably, insufficient urban transportation infrastructure has given rise to various issues, including air pollution, heightened fuel consumption, and wasted time. To address traffic-related problems and the economic, social, and environmental challenges that ensue, a well-equipped, efficient, fast, cost-effective, and high-capacity transportation system is imperative, with a focus on reliability. This study undertakes a comprehensive examination of rail transportation systems and subsequently compares their advantages and limitations. The findings of this investigation reveal that hybrid monorails exhibit lower maintenance requirements and associated costs when compared to other types of monorails, standard trains, and urban light rail systems. Given their favorable attributes in terms of pollution reduction, increased transportation speed, and enhanced quality of service, hybrid monorails emerge as a highly recommended and suitable option.

Keywords: comparing, most efficient, selecting, urban transportation

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Authors: Shun-Qi Zhang, Shu-Yang Zhang, Min Chen

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Applying strong electric field on piezoelectric actuators, on one hand very significant electroelastic material nonlinear effects will occur, on the other hand piezo plates and shells may undergo large displacements and rotations. In order to give a precise prediction of piezolaminated smart structures under large electric field, this paper develops a finite element (FE) model accounting for both electroelastic material nonlinearity and geometric nonlinearity with large rotations based on the first order shear deformation (FSOD) hypothesis. The proposed FE model is applied to analyze a piezolaminated semicircular shell structure.

Keywords: smart structures, piezolamintes, material nonlinearity, strong electric field

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Authors: Fatemeh Yazdanmehr, Iulian Nistor

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The scope of the current study is the evaluation of the electric field effect on electrostatic desalting mathematical modeling with laboratory data. This research study was focused on developing a model for an existing operation desalting unit of one of the Iranian heavy oil field with a 75 MBPD production capacity. The high temperature of inlet oil to dehydration unit reduces the oil recovery, so the mathematical modeling of desalter operation parameters is very significant. The existing production unit operating data has been used for the accuracy of the mathematical desalting plant model. The inlet oil temperature to desalter was decreased from 110 to 80°C, and the desalted electrical field was increased from 0.75 to 2.5 Kv/cm. The model result shows that the desalter parameter changes meet the water-oil specification and also the oil production and consequently annual income is increased. In addition to that, changing desalter operation conditions reduces environmental footprint because of flare gas reduction. Following to specify the accuracy of selected electrostatic desalter electrical field, laboratory data has been used. Experimental data are used to ensure the effect of electrical field change on desalter. Therefore, the lab test is done on a crude oil sample. The results include the dehydration efficiency in the presence of a demulsifier and under electrical field (0.75 Kv) conditions at various temperatures. Comparing lab experimental and electrostatic desalter mathematical model results shows 1-3 percent acceptable error which confirms the validity of desalter specification and operation conditions changes.

Keywords: desalter, electrical field, demulsification, mathematical modeling, water-oil separation

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Authors: Yue Yan, Chang Nyung Kim

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The numerical investigation of the three-dimensional liquid-metal (LM) magnetohydrodynamic (MHD) flows in a curved duct with flow channel insert (FCI) is presented in this paper, based on the computational fluid dynamics (CFD) method. A uniform magnetic field is applied perpendicular to the duct. The interdependency of the flow variables is examined in terms of the flow velocity, current density, electric potential and pressure. The electromagnetic characteristics of the LM MHD flows are reviewed with an introduction of the electric-field component and electro-motive component of the current. The influence of the existence of the FCI on the fluid flow is investigated in detail. The case with FCI slit located near the side layer yields smaller pressure gradient with stable flow field.

Keywords: curved duct, flow channel insert, liquid-metal, magnetohydrodynamic

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Authors: Zyad Elkhadir, Khalid Chougdali, Mohammed Benattou

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Most of the existing intrusion detection systems works on quantitative network traffic data with many irrelevant and redundant features, which makes detection process more time’s consuming and inaccurate. A several feature extraction methods, such as linear discriminant analysis (LDA), have been proposed. However, LDA suffers from the small sample size (SSS) problem which occurs when the number of the training samples is small compared with the samples dimension. Hence, classical LDA cannot be applied directly for high dimensional data such as network traffic data. In this paper, we propose two solutions to solve SSS problem for LDA and apply them to a network IDS. The first method, reduce the original dimension data using principal component analysis (PCA) and then apply LDA. In the second solution, we propose to use the pseudo inverse to avoid singularity of within-class scatter matrix due to SSS problem. After that, the KNN algorithm is used for classification process. We have chosen two known datasets KDDcup99 and NSLKDD for testing the proposed approaches. Results showed that the classification accuracy of (PCA+LDA) method outperforms clearly the pseudo inverse LDA method when we have large training data.

Keywords: LDA, Pseudoinverse, PCA, IDS, NSL-KDD, KDDcup99

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Authors: Neeti Nayak, Khalid Duri

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Despite the many advances made in transportation planning, the number of injuries and fatalities in the United States which involve motorized vehicles near intersections remain largely unchanged year over year. Data from the National Highway Traffic Safety Administration for 2018 indicates accidents involving motorized vehicles at traffic intersections accounted for 8,245 deaths and 914,811 injuries. Furthermore, collisions involving pedal cyclists killed 861 people (38% at intersections) and injured 46,295 (68% at intersections), while accidents involving pedestrians claimed 6,247 lives (25% at intersections) and injured 71,887 (56% at intersections)- the highest tallies registered in nearly 20 years. Some of the causes attributed to the rising number of accidents relate to increasing populations and the associated changes in land and traffic usage patterns, insufficient visibility conditions, and inadequate applications of traffic controls. Intersections that were initially designed with a particular land use pattern in mind may be rendered obsolete by subsequent developments. Many accidents involving pedestrians are accounted for by locations which should have been designed for safe crosswalks. Conventional solutions for evaluating intersection safety often require costly deployment of engineering surveys and analysis, which limit the capacity of resource-constrained administrations to satisfy their community’s needs for safe roadways adequately, effectively relegating mitigation efforts for high-risk areas to post-incident responses. This paper demonstrates how geospatial technology can identify high-risk locations and evaluate the viability of specific intersection management techniques. GIS is used to simulate relevant real-world conditions- the presence of traffic controls, zoning records, locations of interest for human activity, design speed of roadways, topographic details and immovable structures. The proposed methodology provides a low-cost mechanism for empowering urban planners to reduce the risks of accidents using 2-dimensional data representing multi-modal street networks, parcels, crosswalks and demographic information alongside 3-dimensional models of buildings, elevation, slope and aspect surfaces to evaluate visibility and lighting conditions and estimate probabilities for jaywalking and risks posed by blind or uncontrolled intersections. The proposed tools were developed using sample areas of Southern California, but the model will scale to other cities which conform to similar transportation standards given the availability of relevant GIS data.

Keywords: crosswalks, cyclist safety, geotechnology, GIS, intersection safety, pedestrian safety, roadway safety, transportation planning, urban design

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Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

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Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

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Authors: Jeryes Danial, Yosi Ben Asher

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Algorithms for controlling a swarm of robots is an active research field, out of which cattle herding is one of the most complex problems to solve. In this paper, we derive an independent herding algorithm that is specifically designed for a swarm of quadcopters. The algorithm works by devising flight trajectories that cause the cows to run-away in the desired direction and hence herd cows that are distributed in a given field towards a common gathering point. Unlike previously proposed swarm herding algorithms, this algorithm does not use a flocking model but rather stars each cow separately. The effectiveness of this algorithm is verified experimentally using a simulator. We use a special set of experiments attempting to demonstrate that the herding times of this algorithm correspond to field diameter small constant regardless of the number of cows in the field. This is an optimal result indicating that the algorithm groups the cows into intermediate groups and herd them as one forming ever closing bigger groups.

Keywords: swarm, independent, distributed, algorithm

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Authors: Naima Jannat, Ariful Islam, Sharafat Hossain

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Due to the involvement of the large target volume, Craniospinal Irradiation makes it challenging to achieve a uniform dose, and it requires different isocenters. This isocentric junction needs to shift after every five fractions to overcome the possibility of hot and cold spots. This study aims to evaluate the Planning Target Volume coverage & sparing Organ at Risk between two techniques and shows that the Field Alignment Technique does not need replanning and resetting. Planning method for Craniospinal Irradiation by Eclipse treatment planning system Field Alignment and Extended Source to Surface Distance technique was developed where 36 Gy in 20 Fraction at the rate of 1.8 Gy was prescribed. The patient was immobilized in the prone position. In the Field Alignment technique, the plan consists of half beam blocked parallel opposed cranium and a single posterior cervicospine field was developed by sharing the same isocenter, which obviates divergence matching. Further, a single field was created to treat the remaining lumbosacral spine. Matching between the inferior diverging edge of the cervicospine field and the superior diverging edge of a lumbosacral field, the field alignment option was used, which automatically matches the field edge divergence as per the field alignment rule in Eclipse Treatment Planning System where the couch was set to 2700. In the Extended Source to Surface Distance technique, two parallel opposed fields were created for the cranium, and a single posterior cervicospine field was created where the Source to Surface Distance was from 120-140 cm. Dose Volume Histograms were obtained for each organ contoured and for each technique used. In all, the patient’s maximum dose to Planning Target Volume is higher for the Extended Source to Surface Distance technique to Field Alignment technique. The dose to all surrounding structures was increased with the use of a single Extended Source to Surface Distance when compared to the Field Alignment technique. The average mean dose to Eye, Brain Steam, Kidney, Oesophagus, Heart, Liver, Lung, and Ovaries were respectively (58% & 60 %), (103% & 98%), (13% & 15%), (10% & 63%), (12% & 16%), (33% & 30%), (14% & 18%), (69% & 61%) for Field Alignment and Extended Source to Surface Distance technique. However, the clinical target volume at the spine junction site received a less homogeneous dose with the Field Alignment technique as compared to Extended Source to Surface Distance. We conclude that, although the use of a single field Extended Source to Surface Distance delivered a more homogenous, but its maximum dose is higher than the Field Alignment technique. Also, a huge advantage of the Field Alignment technique for Craniospinal Irradiation is that it doesn’t need replanning and resetting up of patients after every five fractions and 95% prescribed dose was received by more than 95% of the Planning Target Volume in all the plane with the acceptable hot spot.

Keywords: craniospinalirradiation, cranium, cervicospine, immobilize, lumbosacral spine

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Authors: Muhammad Ahsan

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The effective decommissioning of oil and gas fields and related assets is one of the most important challenges facing the oil and gas industry today and in the future. Decommissioning decisions can no longer be avoided by the operators and the industry as a whole. Decommissioning yields no return on investment and carries significant regulatory liabilities. The main objective of this paper is to provide an approach and mechanism for the estimation of emissions associated with decommissioning of Oil and Gas fields. The model uses gate to gate approach and considers field life from development phase up to asset end life. The model incorporates decommissioning processes which includes; well plugging, plant dismantling, wellhead, and pipeline dismantling, cutting and temporary fabrication, new manufacturing from raw material and recycling of metals. The results of the GHG emissions during decommissioning phase are 2.31x10-2 Kg CO2 Eq. per Mcf of the produced natural gas. Well plug and abandonment evolved to be the most GHG emitting activity with 84.7% of total field decommissioning operational emissions.

Keywords: LCA (life cycle analysis), gas field, decommissioning, emissions

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Authors: Hassan Ali, Abdulrahman Hamid

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This paper discusses using of instruments to monitor deformation and settlement. Specifically, it concentrates on field instruments such as inclinometer and plate load test and their applications in the field. Inclinometer has been used effectively to monitor lateral earth movements and settlement in landslide areas, embankments and foundations. They are also used to monitor the deflection of retaining walls and piles under load. This paper is reviewing types of inclinometer systems, comparison between systems, applications, field accuracy and correction. The paper also will present a case study of using inclinometer to monitor the creep movements within the ancient landslide on The Washington Park Station. Furthermore, the application of deformation and settlement instruments in Saudi Arabia will be discussed in this manuscript.

Keywords: inclinometer, plate load test, backfills, sand, deformation and settlement

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Authors: Victor Bloch, Eerikki Kaila, Reetta Palva

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Field robots are an important tool for enhancing efficiency and decreasing the climatic impact of food production. There exists a number of commercial field robots; however, since this technology is still new, the robot advantages and limitations, as well as methods for optimal using of robots, are still unclear. In this study, the performance of a commercial field robot for seeding and weeding was assessed. A research 2-ha sugar beet field with 0.5m row width was used for testing, which included robotic sowing of sugar beet and weeding five times during the first two months of the growing. About three and five percent of the field were used as untreated and chemically weeded control areas, respectively. The plant detection was based on the exact plant location without image processing. The robot was equipped with six seeding and weeding tools, including passive between-rows harrow hoes and active hoes cutting inside rows between the plants, and it moved with a maximal speed of 0.9 km/h. The robot's performance was assessed by image processing. The field images were collected by an action camera with a height of 2 m and a resolution 27M pixels installed on the robot and by a drone with a 16M pixel camera flying at 4 m height. To detect plants and weeds, the YOLO model was trained with transfer learning from two available datasets. A preliminary analysis of the entire field showed that in the areas treated by the robot, the weed average density varied across the field from 6.8 to 9.1 weeds/m² (compared with 0.8 in the chemically treated area and 24.3 in the untreated area), the weed average density inside rows was 2.0-2.9 weeds / m (compared with 0 on the chemically treated area), and the emergence rate was 90-95%. The information about the robot's performance has high importance for the application of robotics for field tasks. With the help of the developed method, the performance can be assessed several times during the growth according to the robotic weeding frequency. When it’s used by farmers, they can know the field condition and efficiency of the robotic treatment all over the field. Farmers and researchers could develop optimal strategies for using the robot, such as seeding and weeding timing, robot settings, and plant and field parameters and geometry. The robot producers can have quantitative information from an actual working environment and improve the robots accordingly.

Keywords: agricultural robot, field robot, plant detection, robot performance

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Authors: Hongda Guo, Wenxia Sima

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Transformer oil is widely used in power systems because of its excellent insulation properties. The accurate measurement of electric field and space charge distribution in transformer oil under high voltage impulse has important theoretical and practical significance, but still remains challenging to date because of its low Kerr constant. In this study, the continuous electric field and space charge distribution over time between parallel-plate electrodes in high-voltage pulsed transformer oil based on the Kerr effect is directly measured using a linear array photoelectrical detector. Experimental results demonstrate the applicability and reliability of this method. This study provides a feasible approach to further study the space charge effects and breakdown mechanisms in transformer oil.

Keywords: electric field, Kerr, space charge, transformer oil

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Authors: Mahmoud T. Alwidyan, Ahmad Alrawashdeh, Alaa O. Oteir

Abstract:

Background: Emergency medical service (EMS) providers, oftentimes, use the lights and sirens (L&S) of their ambulances to warn road users, navigate through traffic, and expedite transport to save lives of ill and injured patients. Despite the contribution of road users in the effectiveness of reducing transport time of EMS ambulances using L&S, there is a lack of empirical assessments exploring the road user’s attitude and behavior in such situations. This study, therefore, aimed to assess the attitude and behavior of road users in response to EMS ambulances with warning L&S in use. Methods: This was a cross-sectional survey developed and distributed to adult road users in Northern Jordan. The questionnaire included 20 items addressing demographics, attitudes, and behavior toward emergency ambulances. We described the participants’ responses and assessed the association between demographics and attitude statements using logistic regression. Results: A total of 1302 questionnaires were complete and appropriate for analysis. The mean age was 34.2 (SD± 11.4) years, and the majority were males (72.6%). About half of road users (47.9%) in our sample would perform inappropriate action in response to EMS ambulances with L&S in use. The multivariate logistic regression model show that being female (OR, 0.63; 95% CI = 0.48-0.81), more educated (OR, 0.68; 95% CI = 0.53-0.86), or public transport driver (OR, 0.55; 95% CI = 0.34-0.90) is significantly associated with inappropriate response to EMS ambulances. Additionally, a significant proportion of road users may perform inappropriate and lawless driving practices such as crossing red traffic lights or following the passing by EMS ambulances, which would, in turn, increase the risk on ambulances and other road users. Conclusions: A large proportion of road users in Jordan may respond inappropriately to the EMS ambulances, and many engage in risky driving behaviors due perhaps to the lack of procedural knowledge. Policy-related interventions and educational programs are crucially needed to increase public awareness of the traffic law concerning EMS ambulances and to enhance appropriate driving behavior, which, in turn, improves the efficiency of ambulance services.

Keywords: EMS ambulances, lights and sirens, road users, attitude and behavior

Procedia PDF Downloads 88

Authors: Syed M. Jawwad Riaz

Abstract:

There has been a lot of interest in exploring the thermodynamic properties at the horizon of a black hole geometry. Earlier, it has been shown, for different spacetimes, that the Einstein field equations at the horizon can be expressed as a first law of black hole thermodynamics. In this paper, considering r = constant slices, for the Kerr-Newman black hole, shown that the Einstein field equations for the induced 3-metric of the hypersurface is expressed in thermodynamic quantities under the virtual displacements of the hypersurfaces. As expected, it is found that the field equations of the induced metric corresponding to the horizon can only be written as a first law of black hole thermodynamics. It is to be mentioned here that the procedure adopted is much easier, to obtain such results, as here one has to essentially deal with (n - 1)-dimensional induced metric for an n-dimensional spacetime.

Keywords: black hole space-times, Einstein's field equation, foliation, hyper-surfaces

Procedia PDF Downloads 344

Authors: Arindam Roy, Madhushree Das, Apurba Manna, Samir Maity

Abstract:

In this research paper, an algorithmic approach is developed to solve a novel multi-objective four-dimensional traveling salesman problem (MO4DTSP) where different paths with various numbers of conveyances are available to travel between two cities. NSGA-II and Decomposition algorithms are modified to solve MO4DTSP in an IoT-based transport system. This IoT-based transport system can be widely observed, analyzed, and controlled by an extensive distribution of traffic networks consisting of various types of sensors and actuators. Due to urbanization, most of the cities are connected using an intelligent traffic management system. Practically, for a traveler, multiple routes and vehicles are available to travel between any two cities. Thus, the classical TSP is reformulated as multi-route and multi-vehicle i.e., 4DTSP. The proposed MO4DTSP is designed with traveling cost, time, and customer satisfaction as objectives. In reality, customer satisfaction is an important parameter that depends on travel costs and time reflects in the present model.

Keywords: multi-objective four-dimensional traveling salesman problem (MO4DTSP), decomposition, NSGA-II, IoT-based transport system, customer satisfaction

Procedia PDF Downloads 109

Authors: Gordon Newlove Asamoah, Wendy Ama Oti

Abstract:

This study focused on evaluating access to finance for local oil field companies in Ghana. The study adopted a census survey design in evaluating access to finance for local oil field companies in Ghana. The respondents of this study were 30 management members of three oil field companies in Ghana. The data collected was analysed using Statistical Package for Social Scientists (SPSS) to generate tables and graphs for interpretation. The results show that most companies use equity financing in combination with other forms of financing to finance their business activities. This research has shown the various challenges bordering on the financing of local oil and gas projects, with emphasis on the challenges of raising funds by indigenous oil companies. Financing of the projects by indigenous oil field companies in Ghana is preferably achieved through equity finance mainly because it is the easiest to get compared to all the other forms of financing available. Other sources of financing available are debt financing, joint venture, and retained earnings from the profits generated from their operations. The study made recommendations to local oil field companies as to how they can make good use of the capital market to raise financing.

Keywords: access, financing, oil fields, Ghana

Procedia PDF Downloads 105

Authors: Bernabeo R. Alberto

Abstract:

With the tremendous improvements in the processing power of computers, the possibilities of artificial intelligence will increasingly be used in aviation and make autonomous flights, preventive maintenance, ATM (Air Traffic Management) optimization, pilots, cabin crew, ground staff, and airport staff training possible in a cost-saving, less time-consuming and less polluting way. Through the use of artificial intelligence, we foresee an interviewing scenario where the interviewee will interact with the artificial intelligence tool to contextualize the character and the necessary information in a way that aligns reasonably with the character and the scenario. We are creating simulated scenarios connected with either an aviation incident or accident to enhance also the training of future accident/incident investigators integrating artificial intelligence and augmented reality tools. The project's goal is to improve the learning and teaching scenario through academic and professional expertise in aviation and in the artificial intelligence field. Thus, we intend to contribute to the needed high innovation capacity, skills, and training development and management of artificial intelligence, supported by appropriate regulations and attention to ethical problems.

Keywords: artificial intelligence, aviation accident, aviation incident, risk, safety

Procedia PDF Downloads 20