Search results for: analysis vehicles

Authors: I. Paeglite, A. Paeglitis

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The paper presents a study of dynamic effects obtained from the dynamic load testing of the city highway bridges in Latvia carried out from 2005 to 2012. 9 pre-stressed concrete bridges and 4 composite bridges were considered. 11 of 13 bridges were designed according to the Eurocodes but two according to the previous structural codes used in Latvia (SNIP 2.05.03-84). The dynamic properties of the bridges were obtained by heavy vehicles passing the bridge roadway with different driving speeds and with or without even pavement. The obtained values of the Dynamic amplification factor (DAF) and bridge natural frequency were analyzed and compared to the values of built-in traffic load models provided in Eurocode 1. The actual DAF values for even bridge deck in the most cases are smaller than the value adopted in Eurocode 1. Vehicle speed for uneven pavements significantly influence Dynamic amplification factor values.

Keywords: bridge, dynamic effects, load testing, dynamic amplification factor

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Authors: Ya-Li Tsai

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Nitrogen is a vital element crucial for crop growth, significantly influencing crop yield. In rice cultivation, farmers often apply substantial nitrogen fertilizer to maximize yields. However, excessive nitrogen application increases the risk of lodging and pest infestation, leading to yield losses. Additionally, conventional flooded irrigation methods consume significant water resources, necessitating precise agricultural and intelligent water management systems. In this study, it leveraged physiological data and field images captured by unmanned aerial vehicles, considering fertilizer treatment and irrigation as key factors. Statistical models incorporating rice physiological data, yield, and vegetation indices from image data were developed. Missing physiological data were addressed using multiple imputation and regression methods, and regression models were established using principal component analysis and stepwise regression. Target nitrogen accumulation at key growth stages was identified to optimize fertilizer application, with the difference between actual and target nitrogen accumulation guiding recommendations for ear dressing dosage. Field experiments conducted in 2022 validated the recommended ear dressing dosage, demonstrating no significant difference in final yield compared to traditional fertilizer levels under alternate wetting and drying irrigation. These findings highlight the efficacy of applying recommended dosages based on fertilizer decision models, offering the potential for reduced fertilizer use while maintaining yield in rice cultivation.

Keywords: intelligent fertilizer management, nitrogen top and ear dressing fertilizer, rice, yield optimization

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Authors: Pallavi Roe

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Violent crime is a significant public safety concern in urban areas across the United States, and Washington, DC, is no exception. This research discusses the prevalence and types of crime, particularly violent crime, in Washington, DC, along with the factors contributing to the high rate of violent crime in the city, including poverty, inequality, access to guns, and racial disparities. The organizations working towards ensuring safety in neighborhoods are also listed. The proposal to perform spatial and temporal analysis on violent crime and the use of guns in crime analysis is presented to identify patterns and trends to inform evidence-based interventions to reduce violent crime and improve public safety in Washington, DC. The stakeholders for crime analysis are also discussed, including law enforcement agencies, prosecutors, judges, policymakers, and the public. The anticipated result of the spatial and temporal analysis is to provide stakeholders with valuable information to make informed decisions about preventing and responding to violent crimes.

Keywords: crime analysis, spatial analysis, temporal analysis, violent crime

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Authors: Aly Elshafei, Daniela Romano

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With the development of autonomous vehicles, a human-machine interaction (HMI) system is needed for a safe transition of control when a takeover request (TOR) is required. An important part of the HMI system is the ability to monitor the level of situational awareness (SA) of any driver in real-time, in different scenarios, and without any pre-calibration. Presenting state-of-the-art machine learning models used to measure SA is the purpose of this systematic review. Investigating the limitations of each type of sensor, the gaps, and the most suited sensor and computational model that can be used in driving applications. To the author’s best knowledge this is the first literature review identifying online and offline classification methods used to measure SA, explaining which measurements are subject or session-specific, and how many classifications can be done with each classification model. This information can be very useful for researchers measuring SA to identify the most suited model to measure SA for different applications.

Keywords: situational awareness, autonomous driving, gaze metrics, EEG, ECG

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Authors: Sandro Bartolini, Alessandro Mecocci, Alessio Medaglini

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The growing popularity of systems based on unmanned aerial vehicles (UAVs) is highlighting their vulnerability, particularly in relation to the positioning system used. Typically, UAV architectures use the civilian GPS, which is exposed to a number of different attacks, such as jamming or spoofing. This is why it is important to develop alternative methodologies to accurately estimate the actual UAV position without relying on GPS measurements only. In this paper, we propose a position estimate method for UAVs based on monocular visual odometry. We have developed a flight control system capable of keeping track of the entire trajectory travelled, with a reduced dependency on the availability of GPS signals. Moreover, the simplicity of the developed solution makes it applicable to a wide range of commercial drones. The final goal is to allow for safer flights in all conditions, even under cyber-attacks trying to deceive the drone.

Keywords: visual odometry, autonomous uav, position measurement, autonomous outdoor flight

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Authors: Jie Liu, Xudong Luo, Pingping Lin, Yifan Fan

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Facebook, Twitter, Weibo, and other social media and significant e-commerce sites generate a massive amount of online texts, which can be used to analyse people’s opinions or sentiments for better decision-making. So, sentiment analysis, especially fine-grained sentiment analysis, is a very active research topic. In this paper, we survey various methods for fine-grained sentiment analysis, including traditional sentiment lexicon-based methods, machine learning-based methods, and deep learning-based methods in aspect/target/attribute-based sentiment analysis tasks. Besides, we discuss their advantages and problems worthy of careful studies in the future.

Keywords: sentiment analysis, fine-grained, machine learning, deep learning

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Authors: Adrien Marque, Daniel Delahaye, Pierre Maréchal, Isabelle Berry

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Wind direction and uncertainty are crucial in aircraft or unmanned aerial vehicle trajectories. By computing wind covariance matrices on each spatial grid point, these spatial grids can be defined as images with symmetric positive definite matrix elements. A data pre-processing step, a specific convolution, a specific max-pooling, and a specific flatten layers are implemented to process such images. Then, the neural network is applied to spatial grids, whose elements are wind covariance matrices, to solve classification problems related to the feasibility of unmanned aerial vehicles based on wind direction and wind uncertainty.

Keywords: wind direction, uncertainty level, unmanned aerial vehicle, convolution neural network, SPD matrices

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Authors: Farideh Gheitasi, Amir Hossain Jaberansari, Payam Abedini

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The World Health Organization (WHO) Manifesto for Safe Communities states that "All human beings have an equal right to health and safety". The purpose of a safe Community is to minimize the damages threatening people. It seems that not sufficient attention has been given to relate environment and objectives of the safe Community. The reason for that can be assigned to the lack of enough information about environmental parameters and their relation with indices of the safe community like type and effect time of damages resulting from air pollution. Air pollution can be characterized as one of main environmental problems of Tehran. This problem is mostly due to the special geographic and climate situation, high population density and irregular growth in the number of vehicles. This paper is aimed at investigating the necessity of considering environmental factors to obtain a safe community through determining the effects of environmental pollution, particularly air pollution, on 490000 elders (+65) of Tehran. The methodology used in this study was on the basis of Random sampling and social surveying. The number of questionnaires was determined to be 321 through using Cochran method and the questionnaires were filled out by elders during personal interviews. The analysis of obtained results indicated that elders believe the major effects of air pollution include heart and respiratory diseases, obligation to stay at home on polluted days and its associated mental problems. Moreover, it was found that there is direct link between the number of polluted days and mortality frequency of elders. Having an environmental view may have an appreciable influence on the qualitative and quantitative development of activities and also facilitate obtaining the goals of the Safe Communities. In addition to reduce damages caused by pollutions, this view will encourage friends of the environment to cooperate with authorities of the safe community.

Keywords: air pollution, elderly people, environment, waste management

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Authors: A. B. Robert, Adam Pramadia, Calvin Andika

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The main purpose of this study is to explore consumer loyalty characteristic of mobile phone category in Indonesia. Second, this research attempts to identify consumer segment and to explore their profile in each segment as the basis of marketing strategy formulation. This study used some tools of multivariate analysis such as discriminant analysis and cluster analysis. Discriminate analysis used to discriminate consumer loyal and not loyal by using particular variables. Cluster analysis used to reveal various segment in mobile phone category. In addition to having better customer understanding in each segment, this study used descriptive analysis and cross tab analysis in each segment defined by cluster analysis. This study expected several findings. First, consumer can be divided into two large group of loyal versus not loyal by set of variables. Second, this study identifies customer segment in mobile phone category. Third, exploring customer profile in each segment that has been identified. This study answer a call for additional empirical research into different product categories. Therefore, a replication research is advisable. By knowing the customer loyalty characteristic, and deep analysis of their consumption behavior and profile for each segment, this study is very advisable for high impact marketing strategy development. This study contributes body of knowledge by adding empirical study of consumer loyalty, segmentation analysis in mobile phone category by multiple brand analysis.

Keywords: customer loyalty, segmentation, marketing strategy, discriminant analysis, cluster analysis, mobile phone

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Authors: Joaquin Ticzon, Christian Demition, Jaime Honra

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Additive manufacturing (AM) or 3D printing has been one of the emerging trends present in various industries, particularly in prototyping. This review focuses on the impact of additive manufacturing on a motor vehicle's performance aiming to investigate potential advancements to further revolutionize the way parts are manufactured. One of the most common problems faced in the automotive industry is carbon footprint emissions from motor vehicles, which was stated to be remedied by lightweight; additively manufactured parts helped reduce these emissions due to weight reduction provided by additively manufactured parts. Composed of various techniques for AM as well as materials utilized during the manufacturing process, which differ in terms of the quality and performance it provides during its application on the final product. Given this, the generative design will not be discussed in such a detailed manner because the focus will revolve around the effects on the performance of a vehicle due to additively manufactured parts.

Keywords: additive manufacturing (AM), automotive, computer aided design (CAD), generative design

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Authors: Krzysztof Skiba, Zbigniew Czyz, Ksenia Siadkowska, Piotr Borowiec

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The article presents selected concepts of technologies that use intelligent materials in aircraft in order to improve their performance. Most of the research focuses on solutions that improve the performance of fixed wing aircraft due to related to their previously dominant market share. Recently, the development of the rotorcraft has been intensive, so there are not only helicopters but also gyroplanes and unmanned aerial vehicles using rotors and vertical take-off and landing. There are many different technologies to change a shape of the aircraft or its elements. Piezoelectric, deformable actuator systems can be applied in the system of an active control of vibration dampening in the aircraft tail structure. Wires made of shape memory alloys (SMA) could be used instead of hydraulic cylinders in the rear part of the aircraft flap. The aircraft made of intelligent materials (piezoelectrics and SMA) is one of the NASA projects which provide the possibility of changing a wing shape coefficient by 200%, a wing surface by 50%, and wing deflections by 20 degrees. Active surfaces made of shape memory alloys could be used to control swirls in the flowing stream. An intelligent control system for helicopter blades is a method for the active adaptation of blades to flight conditions and the reduction of vibrations caused by the rotor. Shape memory alloys are capable of recovering their pre-programmed shapes. They are divided into three groups: nickel-titanium-based, copper-based, and ferromagnetic. Due to the strongest shape memory effect and the best vibration damping ability, a Ni-Ti alloy is the most commercially important. The subject of this work was to prepare a conceptual design of a rotor blade with SMA actuators. The scope of work included 3D design of the supporting rotor blade, 3D design of beams enabling to change the geometry by changing the angle of rotation and FEM (Finite Element Method) analysis. The FEM analysis was performed using NX 12 software in the Pre/Post module, which includes extended finite element modeling tools and visualizations of the obtained results. Calculations are presented for two versions of the blade girders. For FEM analysis, three types of materials were used for comparison purposes (ABS, aluminium alloy 7057, steel C45). The analysis of internal stresses and extreme displacements of crossbars edges was carried out. The internal stresses in all materials were close to the yield point in the solution of girder no. 1. For girder no. 2 solution, the value of stresses decreased by about 45%. As a result of the displacement analysis, it was found that the best solution was the ABS girder no. 1. The displacement of about 0.5 mm was obtained, which resulted in turning the crossbars (upper and lower) by an angle equal to 3.59 degrees. This is the largest deviation of all the tests. The smallest deviation was obtained for beam no. 2 made of steel. The displacement value of the second girder solution was approximately 30% lower than the first solution. Acknowledgement: This work has been financed by the Polish National Centre for Research and Development under the LIDER program, Grant Agreement No. LIDER/45/0177/L-9/17/NCBR/2018.

Keywords: aircraft, helicopters, shape memory alloy, SMA, smart material, unmanned aerial vehicle, UAV

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Authors: Chothmal, Basant Agarwal

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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: feature selection methods, machine learning, NB, one-class SVM, sentiment analysis, support vector machine

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Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

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This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: neural network, self-organizing map, rule extraction, rule insertion

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Authors: Abeer K. Jameel, Harry Evdorides

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Iraq is a middle income country where the road safety issue is considered one of the leading causes of deaths. To control the road risk issue, the Iraqi Ministry of Planning, General Statistical Organization started to organise a collection system of traffic accidents data with details related to their causes and severity. These data are published as an annual report. In this paper, a review of the available crash data in Iraq will be presented. The available data represent the rate of accidents in aggregated level and classified according to their types, road users’ details, and crash severity, type of vehicles, causes and number of causalities. The review is according to the types of models used in road safety studies and research, and according to the required road safety data in the road constructions tasks. The available data are also compared with the road safety dataset published in the United Kingdom as an example of developed country. It is concluded that the data in Iraq are suitable for descriptive and exploratory models, aggregated level comparison analysis, and evaluation and monitoring the progress of the overall traffic safety performance. However, important traffic safety studies require disaggregated level of data and details related to the factors of the likelihood of traffic crashes. Some studies require spatial geographic details such as the location of the accidents which is essential in ranking the roads according to their level of safety, and name the most dangerous roads in Iraq which requires tactic plan to control this issue. Global Road safety agencies interested in solve this problem in low and middle-income countries have designed road safety assessment methodologies which are basing on the road attributes data only. Therefore, in this research it is recommended to use one of these methodologies.

Keywords: road safety, Iraq, crash data, road risk assessment, The International Road Assessment Program (iRAP)

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Authors: Bashir Abdu Muzakkari, Aisha Umar Sulaiman, Mohamed Afendee Muhamad, Sanah Abdullahi Muaz

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The field of the Internet of Things (IoT) is rapidly expanding and has the potential to completely change how we work, live, and interact with the world. The Internet of Things (IoT) is the term used to describe a network of networked physical objects, including machinery, vehicles, and buildings, which are equipped with electronics, software, sensors, and network connectivity. This review paper aims to provide a comprehensive overview of the current state of IoT, including its definition, key components, development history, and current applications. The paper will also discuss the challenges and opportunities presented by IoT, as well as its potential impact on various industries, such as healthcare, agriculture, and transportation. In addition, this paper will highlight the ethical and security concerns associated with IoT and the need for effective solutions to address these challenges. The paper concludes by highlighting the prospects of IoT and the directions for future research in this field.

Keywords: internet of things, IoT, sensors, network

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Authors: Francisco Duarte, Adelino Ferreira, Paulo Fael

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With the growing need for alternative energy sources, research into energy harvesting technologies has increased considerably in recent years. The particular case of energy harvesting on road pavements is a very recent area of research, with different technologies having been developed in recent years. However, none of them have presented high conversion efficiencies nor technical or economic viability. This paper deals with the development of a mechanical system to implement on a road pavement energy harvesting electromechanical device, to transmit energy from the device surface to an electrical generator. The main goal is to quantify the energy harvesting, transmission and conversion efficiency of the proposed system and compare it with existing systems. Conclusions about the system’s efficiency are presented.

Keywords: road pavement, energy harvesting, energy conversion, system modelling

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Authors: Lucas Bublitz, Michael Herdrich

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By achieving the first commercialization approval in San Francisco the Autonomous Driving (AD) industry proves the technology maturity of the SAE L4 AD systems and the corresponding software and hardware stack. This milestone reflects the upcoming phase in the industry, where the focus is now about scaling and supervising larger autonomous vehicle (AV) fleets in different operation areas. This requires an operation framework, which organizes and assigns responsibilities to the relevant AV technology and operation stakeholders from the AV system provider, the Remote Intervention Operator, the MaaS provider and regulatory & approval authority. This holistic operation framework consists of technological, processual, and organizational activities to ensure safe operation for fully automated vehicles. Regarding the supervision of large autonomous vehicle fleets, a major focus is on the continuous field monitoring. The field monitoring approach must reflect the safety and security criticality of incidents in the field during driving operation. This includes an automatic containment approach, with the overall goal to avoid safety critical incidents and reduce downtime by a malfunction of the AD software stack. An End-to-end (E2E) field monitoring approach detects critical faults in the field, uses a knowledge-based approach for evaluating the safety criticality and supports the automatic containment of these E/E faults. Applying such an approach will ensure the scalability of AV fleets, which is determined by the handling of incidents in the field and the continuous regulatory compliance of the technology after enhancing the Operational Design Domain (ODD) or the function scope by Functions on Demand (FoD) over the entire digital product lifecycle.

Keywords: field monitoring, incident management, multicompliance management for AI in AD, root cause analysis, database approach

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Authors: Loganathan Kumaresan, Velusamy Chidambaram, Arumugam Velayutham Karthikeyani, Alex Cheru Pulikottil, Madhusudan Sau, Gurpreet Singh Kapur, Sankara Sri Venkata Ramakumar

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Environmentally driven regulations throughout the world stipulate dramatic improvements in the quality of transportation fuels and refining operations. The exhaust gases like CO, NOx, and SOx from stationary sources (e.g., refinery) and motor vehicles contribute to a large extent for air pollution. The refining industry is under constant environmental pressure to achieve more rigorous standards on sulphur content in the fuel used in the transportation sector and other off-gas emissions. Fluid catalytic cracking unit (FCCU) is a major secondary process in refinery for gasoline and diesel production. CO-combustion promoter additive and gasoline sulphur reduction (GSR) additive are catalytic systems used in FCCU to assist the combustion of CO to CO₂ in the regenerator and regulate sulphur in gasoline faction respectively along with main FCC catalyst. Effectiveness of these catalysts is governed by the active metal used, its dispersion, the type of base material employed, and retention characteristics of additive in FCCU such as attrition resistance and density. The challenge is to have a high-density microsphere catalyst support for its retention and high activity of the active metals as these catalyst additives are used in low concentration compare to the main FCC catalyst. The present paper discusses in the first part development of high dense microsphere of nanocrystalline alumina by hydro-thermal method for CO combustion promoter application. Performance evaluation of additive was conducted under simulated regenerator conditions and shows CO combustion efficiency above 90%. The second part discusses the efficacy of a co-precipitation method for the generation of the active crystalline spinels of Zn, Mg, and Cu with aluminium oxides as an additive. The characterization and micro activity test using heavy combined hydrocarbon feedstock at FCC unit conditions for evaluating gasoline sulphur reduction activity are studied. These additives were characterized by X-Ray Diffraction, NH₃-TPD & N₂ sorption analysis, TPR analysis to establish structure-activity relationship. The reaction of sulphur removal mechanisms involving hydrogen transfer reaction, aromatization and alkylation functionalities are established to rank GSR additives for their activity, selectivity, and gasoline sulphur removal efficiency. The sulphur shifting in other liquid products such as heavy naphtha, light cycle oil, and clarified oil were also studied. PIONA analysis of liquid product reveals 20-40% reduction of sulphur in gasoline without compromising research octane number (RON) of gasoline and olefins content.

Keywords: hydrothermal, nanocrystalline, spinel, sulphur reduction

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Authors: Yogita Patil-Sen

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Magnetic nanoparticles such as those made of iron oxide have been widely explored as biocatalysts, contrast agents, and drug delivery systems. However, some of the challenges associated with these particles are agglomeration and biocompatibility, which lead to concern of toxicity of the particles, especially for drug delivery applications. Coating the particles with biocompatible materials such as lipids and peptides have shown to improve the mentioned issues. Thus, these core-shell type nanoparticles are emerging as the new class of nanomaterials for targeted drug delivery applications. In this study, various types of core-shell magnetic nanoparticles are prepared and characterized using techniques, such as Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Vibrating Sample Magnetometer (VSM) and Thermogravimetric Analysis (TGA). The heating ability of nanoparticles is tested under oscillating magnetic field. The efficacy of the nanoparticles as drug carrier is also investigated. The loading of an anticancer drug, Doxorubicin at 18 °C is measured up to 48 hours using UV-visible spectrophotometer. The drug release profile is obtained under thermal incubation condition at 37 °C and compared with that under the influence of oscillating field. The results suggest that the core-shell nanoparticles exhibit superparamagnetic behaviour, although, coating reduces the magnetic properties of the particles. Both the uncoated and coated particles show good heating ability, again it is observed that coating decreases the heating behaviour of the particles. However, coated particles show higher drug loading efficiency than the uncoated particles and the drug release is much more controlled under the oscillating magnetic field. Thus, the results strongly indicate the suitability of the prepared core-shell type nanoparticles as drug delivery vehicles and their potential in magnetic hyperthermia applications and for hyperthermia cancer therapy.

Keywords: core-shell, hyperthermia, magnetic nanoparticles, targeted drug delivery

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Authors: Hasan Fatih Ertuğrul, Beytullah Okur, Huseyin Üvet, Kadir Erkan

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The objective of this paper is to analyze a 4-pole hybrid magnetic levitation system by using 3D finite element and analytical methods. The magnetostatic analysis of the system is carried out by using ANSYS MAXWELL-3D package. An analytical model is derived by magnetic equivalent circuit (MEC) method. The purpose of magnetostatic analysis is to determine the characteristics of attractive force and rotational torques by the change of air gap clearances, inclination angles and current excitations. The comparison between 3D finite element analysis and analytical results are presented at the rest of the paper.

Keywords: yoke hybrid electromagnet, 3D finite element analysis, magnetic levitation system, magnetostatic analysis

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Authors: Paulo Fernando Silva Filho, Elcio Hideiti Shiguemori

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The selection of specific landmarks for an Unmanned Aerial Vehicles’ Visual Navigation systems based on Automatic Landmark Recognition has significant influence on the precision of the system’s estimated position. At the same time, manual selection of the landmarks does not guarantee a high recognition rate, which would also result on a poor precision. This work aims to develop an automatic landmark selection that will take the image of the flight area and identify the best landmarks to be recognized by the Visual Navigation Landmark Recognition System. The criterion to select a landmark is based on features detected by ORB or AKAZE and edges information on each possible landmark. Results have shown that disposition of possible landmarks is quite different from the human perception.

Keywords: clustering, edges, feature points, landmark selection, X-means

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Authors: M. Jathaveda, Joben Leons, G. Vidya

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Reentry from orbit is a critical phase in the entry trajectory. For a non-propulsive ballistic entry, static and dynamic stability play an important role in the trajectory, especially for the safe deployment of parachutes, typically at subsonic Mach numbers. Static stability of flight vehicles are being estimated through CFD techniques routinely. Advances in CFD software as well as computational facilities have enabled the estimation of the dynamic stability derivatives also through CFD techniques. Longitudinal static and dynamic stability of a typical reentry body for subsonic Mach number of 0.6 is predicted using commercial software CFD++ and presented here. Steady state simulations are carried out for α = 2° on an unstructured grid using SST k-ω model. Transient simulation using forced oscillation method is used to compute pitch damping derivatives.

Keywords: stability, typical reentry body, subsonic, static and dynamic

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Authors: Ju-Young Hwang, Hyo-Gyoung Kwak

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This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical nonlinearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC, high temperature, after-cooling analysis, nonlinear analysis

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Authors: Syed Ahzam Tariq, Atharva Modi

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This paper presents a probabilistic analysis of the safety of water tube boilers using fault tree analysis (FTA). A fault tree has been constructed by considering all possible areas where a malfunction could lead to a boiler accident. Boiler accidents are relatively rare, causing a scarcity of data. The fuzzy approach is employed to perform a quantitative analysis, wherein theories of fuzzy logic are employed in conjunction with expert elicitation to calculate failure probabilities. The Fuzzy Fault Tree Analysis (FFTA) provides a scientific and contingent method to forecast and prevent accidents.

Keywords: fault tree analysis water tube boiler, fuzzy probability score, failure probability

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Authors: Emad Khorshid, Habib Awada

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Newly developed Ergonomic speed control hump/Dip designs are conducted. The numerical simulation for the driver-vehicle-hump dynamic system will be performed using computer software. The design problem for which the speed hump or dip should provide: (1) discomfort feeling to the driver if speed is over the specified limit, and (2) normal/good comfort level to the driver (and or other passengers) if the speed is within the limit. For comparison reasons, different vehicles suspension systems (active, semi-active and non-active suspension) are used in the simulation. The measuring of the acceptable range of vibration will be referenced to the British standard BS6841, ISO 2631/1 and the new ISO 2631/5. All these standards are related to human health and comfort level in terms of acceptable range of whole body vibration exposure.

Keywords: speed hump, speed dip, ergonomic design, human health, vehicle modeling

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Authors: Masahiro Suzuki, Nobuyuki Okura

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The crosswind effect on ground transportations has been extensively investigated for decades. The effect of tornado, however, has been hardly studied in spite of the fact that even heavy ground vehicles, namely, trains were overturned by tornadoes with casualties in the past. Therefore, aerodynamic effects of the tornado on the train were studied by several approaches in this study. First, an experimental facility was developed to clarify aerodynamic forces acting on a vehicle running through a tornado. Our experimental set-up consists of two apparatus. One is a tornado simulator, and the other is a moving model rig. PIV measurements showed that the tornado simulator can generate a swirling-flow field similar to those of the natural tornadoes. The flow field has the maximum tangential velocity of 7.4 m/s and the vortex core radius of 96 mm. The moving model rig makes a 1/40 scale model train of single-car/three-car unit run thorough the swirling flow with the maximum speed of 4.3 m/s. The model car has 72 pressure ports on its surface to estimate the aerodynamic forces. The experimental results show that the aerodynamic forces vary its magnitude and direction depends on the location of the vehicle in the flow field. Second, the aerodynamic forces on the train were estimated by using Rankin vortex model. The Rankin vortex model is a simple tornado model which widely used in the field of civil engineering. The estimated aerodynamic forces on the middle car were fairly good agreement with the experimental results. Effects of the vortex core radius and the path of the train on the aerodynamic forces were investigated using the Rankin vortex model. The results shows that the side and lift forces increases as the vortex core radius increases, while the yawing moment is maximum when the core radius is 0.3875 times of the car length. Third, a computational simulation was conducted to clarify the flow field around the train. The simulated results qualitatively agreed with the experimental ones.

Keywords: aerodynamic force, experimental method, tornado, train

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Authors: Khalil Ahmad Kakar

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In developing countries increasing the automobile and low capacity public transport (para-transit) which are creating congestion, pollution, noise, and traffic accident are the most critical quandary. These issues are under the analysis of assessors to break down the puzzle and propose sustainable urban public transport system. Kabul city is one of those urban areas that the inhabitants are suffering from lack of tolerable and friendly public transport system. The city is the most-populous and overcrowded with around 4.5 million population. The para-transit is the only dominant public transit system with a very poor level of services and low capacity vehicles (6-20 passengers). Therefore, this study after detailed investigations suggests bus rapid transit (BRT) system in Kabul City. It is aimed to mitigate the role of informal transport and decreases congestion. The research covers three parts. In the first part, aggregated travel demand modelling (four-step) is applied to determine the number of users for para-transit and assesses BRT network based on higher passenger demand for public transport mode. In the second part, state preference (SP) survey and binary logit model are exerted to figure out the utility of existing para-transit mode and planned BRT system. Finally, the impact of predicted BRT system on para-transit is evaluated. The extracted outcome based on high travel demand suggests 10 km network for the proposed BRT system, which is originated from the district tenth and it is ended at Kabul International Airport. As well as, the result from the disaggregate travel mode-choice model, based on SP and logit model indicates that the predicted mass rapid transit system has higher utility with the significant impact regarding the reduction of para-transit.

Keywords: BRT, para-transit, travel demand modelling, Kabul City, logit model

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Authors: Ksenia Siadkowska, Łukasz Grabowski, Michał Gęca

Abstract:

The dynamic development of photovoltaics in the 21st century has resulted in more possibilities for using photovoltaic systems. In order to reduce emissions, a retrofitting of vehicles with photovoltaic modules has recently become increasingly popular. Preparing such an installation, however, requires professional knowledge and compliance with safety rules. The paper discusses the advantages and disadvantages of some types of flexible photovoltaic modules that can be applied to mobile installations, types and causes of damage to photovoltaic modules as well as the most frequent types of misinstallation. Our attention has been drawn to the risk of fire caused by misintallation or defective insulation and the need to closely monitor mobile installations, for example by a non-destructive testing with a thermal imaging camera. The paper also presents certain selected results of the research conducted at the Lublin University of Technology. This work has been financed by the Polish National Centre for Research and Development, under Grant Agreement No. PBS2/A6/16/2013.

Keywords: flexible PV module, mobile PV module, photovoltaic module, photovoltaic

Procedia PDF Downloads 247

Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

Abstract:

Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

Procedia PDF Downloads 476

Authors: Ujjal Chattaraj, P. C. Dasbebartta, S. Bhuyan

Abstract:

This paper aims to propose a method to detect the action of the driver’s eyes, using the concept of face detection. There are three major key contributing methods which can rapidly process the framework of the facial image and hence produce results which further can program the reactions of the vehicles as pre-programmed for the traffic safety. This paper compares and analyses the methods on the basis of their reaction time and their ability to deal with fluctuating images of the driver. The program used in this study is simple and efficient, built using the AdaBoost learning algorithm. Through this program, the system would be able to discard background regions and focus on the face-like regions. The results are analyzed on a common computer which makes it feasible for the end users. The application domain of this experiment is quite wide, such as detection of drowsiness or influence of alcohols in drivers or detection for the case of identification.

Keywords: AdaBoost learning algorithm, face detection, framework, traffic safety

Procedia PDF Downloads 155