Search results for: electric hybrid vehicles

Authors: Hamza A. Ali, Adnan H. M. Al-Helali

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Generally, a watermark is information that identifies the ownership of multimedia (text, image, audio or video files). It is achieved by introducing modifications into these files that are imperceptible to the human senses but easily recoverable by a computer program. These modifications are done according to a secret key in a descriptive model that would be either in the time domain or frequency domain or both. This paper presents a procedure for watermarking by mixing amplitude modulation with frequency transformation histogram; namely a specific value is used to modulate the intensity component Y of the YIQ components of the carrier image. This scheme is referred to as histogram embedding technique (HET). Results comparison with those of other techniques such as discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) have shown an enhance efficiency in terms of ease and performance. It has manifested a good degree of robustness against various environment effects such as resizing, rotation and different kinds of noise. This method would prove very useful technique for copyright protection and ownership judgment.

Keywords: watermarking, ownership, copyright protection, steganography, information hiding, authentication

Procedia PDF Downloads 363

Authors: Erika Tatiana Paredes Prada, Diana Marina Camargo Lemos

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Introduction: Recreovía as a public health strategy contributes to encourage the practice and adherence to physical activity (PA) recommendations, by temporarily closing the roads to motorized vehicles. The determination of the PA requires the evaluation of the reliability of the measurement instruments, in order to sustain the continuity and relevance of Recreovía as a community intervention. Objective: Establish the inter-rater reliability of the App for the System for Observing Play and Recreation in Communities (iSOPARC®) in the Recreovía of Bucaramanga, Colombia. Methods: Five trained observers at two observation points on the 2.3 km of the Recreovía (14th Street and 32nd Street) used the App (iSOPARC®), between 08:00 a.m. and 12:00 m. in periods of 20 minutes during a regular Sunday. Reliability analysis was performed using the Intraclass Correlation Coefficient (ICC 2.1). Results: A total of 2682 users were observed (43.6 % women) in 7 observations. ICC showed a range between 0.96 and 0.99 for the PA level and ICC between 0.95 and 0.99 for age group for the two observation points. Conclusion: The reliability found for the iSOPARC® guarantees the consecutive measurement of the PA level at the Recreovía, which will allow measuring it is effectiveness in the medium and long term, as a community intervention strategy.

Keywords: environment, observation, physical activity, recreation, reliability

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Authors: Deepak Kumar, Debasish Deb, Reena Mamgain

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Radar signal processing requires high number crunching capability. Most often this is achieved using multiprocessor platform. Though multiprocessor platform provides the capability of meeting the real time computational challenges, the architecture of the same along with mapping of the algorithm on the architecture plays a vital role in efficiently using the platform. Towards this, along with standard performance metrics, few additional metrics are defined which helps in evaluating the multiprocessor platform along with the algorithm mapping. A generic multiprocessor architecture can not suit all the processing requirements. Depending on the system requirement and type of algorithms used, the most suitable architecture for the given problem is decided. In the paper, we study different architectures and quantify the different performance metrics which enables comparison of different architectures for their merit. We also carried out case study of different architectures and their efficiency depending on parallelism exploited on algorithm or data or both.

Keywords: radar signal processing, multiprocessor architecture, efficiency, load imbalance, buffer requirement, pipeline, parallel, hybrid, cluster of processors (COPs)

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Authors: Chandan Pramanik, Bikramjit Chanda

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Large metal mines operated with open-cast mining methods must transition to underground mining at the conclusion of the operation; however, this requires a period of a difficult time when production convergence due to interference between the two mining methods. A transition model with collaborative mining operations is presented and established in this work, based on the case of the South Kaliapani Underground Project, to address these technical issues of inadequate production security and other mining challenges during the transition phase and beyond. By integrating the technology of the small-scale Drift and Fill method and Highly productive Sub Level Open Stoping at deep section, this hybrid mining concept tries to eliminate major bottlenecks and offers an optimized production profile with the safe and sustainable operation. Considering every geo-mining aspect, this study offers a genuine and precise technical deliberation for the transition from open pit to underground mining.

Keywords: drift and fill, geo-mining aspect, sublevel open stoping, underground mining method

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Authors: Qaiser uz Zaman Khan

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This research article provides a comprehensive study of combining steel fiber and polypropylene fibers in concrete at different mix ratios. This blending of various fibers has led to the development of hybrid fiber-reinforced concrete (HFRC), which offers notable improvements in mechanical properties and increased resistance to cracking. Steel fibers are known for their high tensile strength and excellent crack control abilities, while polypropylene fibers offer increased toughness and impact resistance. The synergistic use of these two fiber types in concrete has yielded promising outcomes, effectively enhancing its overall performance. This article explores the key aspects of hybridization, including fiber types, proportions, mixing methods, and the resulting properties of the concrete. Additionally, challenges, potential applications, and future research directions in the field are discussed.

Keywords: FRC, fiber-reinforced concrete, split tensile testing, HFRC, mechanical properties, steel fibers, reinforced concrete, polypropylene fibers

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Authors: Echo Wang, Andrew Li

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Transparency could be defined as the voluntary release of information by institutions that is relevant to their own evaluation. Transparency based on information disclosure is recognised to be vital for the Third Sector, as civil society organisations are under pressure to become more transparent to answer the call for accountability. The growing importance of social enterprises as hybrid organisations emerging from the nexus of the public, the private and the Third Sector makes their transparency a topic worth exploring. However, transparency for social enterprises has not yet been studied: as a new form of organisation that combines non-profit missions with commercial means, it is unclear to both the practical and the academic world if the shift in operational logics from non-profit motives to for-profit pursuits has significantly altered their transparency. This is especially so in China, where informational governance and practices of information disclosure by local governments, industries and civil society are notably different from other countries. This study investigates the transparency-seeking behaviour of social enterprises in Greater China to understand what factors at the organisational level may affect their transparency, measured by their willingness to disclose financial information. We make use of the Survey on the Models and Development Status of Social Enterprises in the Greater China Region (MDSSGCR) conducted in 2015-2016. The sample consists of more than 300 social enterprises from the Mainland, Hong Kong and Taiwan. While most respondents have provided complete answers to most of the questions, there is tremendous variation in the respondents’ demonstrated level of transparency in answering those questions related to the financial aspects of their organisations, such as total revenue, net profit, source of revenue and expense. This has led to a lot of missing data on such variables. In this study, we take missing data as data. Specifically, we use missing values as a proxy for an organisation’s level of transparency. Our dependent variables are constructed from missing data on total revenue, net profit, source of revenue and cost breakdown. In addition, we also take into consideration the quality of answers in coding the dependent variables. For example, to be coded as being transparent, an organization must report the sources of at least 50% of its revenue. We have four groups of predictors of transparency, namely nature of organization, decision making body, funding channel and field of concentration. Furthermore, we control for an organisation’s stage of development, self-identity and region. The results show that social enterprises that are at their later stages of organisational development and are funded by financial means are significantly more transparent than others. There is also some evidence that social enterprises located in the Northeast region in China are less transparent than those located in other regions probably because of local political economy features. On the other hand, the nature of the organisation, the decision-making body and field of concentration do not systematically affect the level of transparency. This study provides in-depth empirical insights into the information disclosure behaviour of social enterprises under specific social context. It does not only reveal important characteristics of Third Sector development in China, but also contributes to the general understanding of hybrid institutions.

Keywords: China, information transparency, organisational behaviour, social enterprise

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Authors: S. Guruprasad, M. Z. Kurian, H. N. Suma

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Medical imaging modalities are becoming life saving components. These modalities are very much essential to doctors for proper diagnosis, treatment planning and follow up. Some modalities provide anatomical information such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), X-rays and some provides only functional information such as Positron Emission Tomography (PET). Therefore, single modality image does not give complete information. This paper presents the fusion of structural information in CT and functional information present in PET image. This fused image is very much essential in detecting the stages and location of abnormalities and in particular very much needed in oncology for improved diagnosis and treatment. We have implemented and compared image fusion techniques like pyramid, wavelet, and principal components fusion methods along with hybrid method of DWT and PCA. The performances of the algorithms are evaluated quantitatively and qualitatively. The system is implemented and tested by using MATLAB software. Based on the MSE, PSNR and ENTROPY analysis, PCA and DWT-PCA methods showed best results over all experiments.

Keywords: image fusion, pyramid, wavelets, principal component analysis

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Authors: Kun-Ting Song, Christian Schott, Peter Schneider, Sebastian Watzele, Regina Kluge, Elena Gubanova, Aliaksandr S. Bandarenka

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The combination of electrochemical impedance spectroscopy (EIS) and the hydrodynamic technique like rotation disc electrode (RDE) provides a critical method for quantitively investigating mechanisms of hydrogen evolution reaction (HER) in acidic and alkaline media. Pt5Gd represented higher HER activities than polycrystalline Pt (Pt(pc)) by means of the surface strain effects. The model of the equivalent electric circuit to fit the impedance data under the RDE configurations is developed. To investigate the relative reaction contribution, the ratio of the charge transfer reactions of the Volmer-Heyrovsky and Volmer-Tafel pathways on Pt and Pt5Gd electrodes is determined. The ratio remains comparably similar in acidic media, but it changes in alkaline media with Volmer–Heyrovsky pathway dominating. This combined approach of EIS and RDE can help to study the electrolyte effects and other essential reactions for electrocatalysis in future work.

Keywords: hydrogen evolution reaction, electrochemical impedance spectroscopy, hydrodynamic methods, electrocatalysis, electrochemical interface

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Authors: Pham Ngoc Thang, Le Thai Hung, Nguyen Quang Bau

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The influence of confined acoustic phonons on the Shubnikov – de Haas magnetoresistance oscillations in a doped semiconductor superlattice (DSSL), subjected in a magnetic field, DC electric field, and a laser radiation, has been theoretically studied based on quantum kinetic equation method. The analytical expression for the magnetoresistance in a DSSL has been obtained as a function of external fields, DSSL parameters, and especially the quantum number m characterizing the effect of confined acoustic phonons. When m goes to zero, the results for bulk phonons in a DSSL could be achieved. Numerical calculations are also achieved for the GaAs:Si/GaAs:Be DSSL and compared with other studies. Results show that the Shubnikov – de Haas magnetoresistance oscillations amplitude decrease as the increasing of phonon confinement effect.

Keywords: Shubnikov–de Haas magnetoresistance oscillations, quantum kinetic equation, confined acoustic phonons, laser radiation, doped semiconductor superlattices

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Authors: Soheib Fergani

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This paper concerns with the formal asymptotic stability guarantees, analysis and evaluation of a nonlinear controlled unmanned aerial vehicles (uav) for trajectory tracking purpose. As the system has been recognised as an under-actuated non linear system, the control strategy has been oriented towards a hierarchical control. The dynamics of the system and the mission purpose make it mandatory to provide an absolute proof of the vehicle stability during the maneuvers. For this sake, this work establishes the complete theoretical proof for an implementable control oriented strategy that asymptotically stabilizes (GAS and LISS) the system and has never been provided in previous works. The considered model is reorganized into two partly decoupled sub-systems. The concidered control strategy is presented into two stages: the first sub-system is controlled by a nonlinear backstepping controller that generates the desired control inputs to stabilize the second sub-system. This methodology is then applied to a harware in the loop uav simulator (SiMoDrones) that reproduces the realistic behaviour of the uav in an indoor environment has been performed to show the efficiency of the proposed strategy.

Keywords: UAV application, trajectory tracking, backstepping, sliding mode control, input to state stability, stability evaluation

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Authors: Usama Mohamed Ahamed

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This research deals with the bond behavior of carbon FRP composite wraps adhered/bonded to the surface of the concrete. Four concrete mixes were designed to achieve a concrete compressive strength of 18, 22.5,25 and 30 MP after 28 days of curing. The focus of the study is on bond degradation when the hybrid structure is exposed to hot weather conditions. Specimens were exposed to 50 0C temperature duration 6 months and other specimens were sustained in laboratory temperature ( 20-24) 0C. Upon removing the specimens from their conditioning environment, tension tests were performed in the machine using a specially manufactured concrete cube holder. A lightweight mortar layer is used to protect the bonded carbon FRP layer on the concrete surface. The results show that the higher the concrete's compressive, the higher the bond strength. The high temperature decreases the bond strength between concrete and carbon fiber-reinforced polymer. The use of a protection layer is essential for concrete exposed to hot weather.

Keywords: concrete, bond, hot weather and carbon fiber, carbon fiber reinforced polymers

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Authors: Muhammad Abid

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In this study, we performed the comparative exergetic and exergoeconomic analyses of a wind turbine over a period of twelve months from 1st January to 30th December 2011. The turbine is part of a wind-PV hybrid system with hydrogen storage, located on the roof of Mechanical Engineering Department, King Saud University, Riyadh, Saudi Arabia. The rated power output from this turbine is 1.7 W with a rated wind speed of 12 m/s and cut-in/cut-out wind speeds of 3/14 m/s. We utilize a wide range of experimental data in the analysis and assessment. We determine exergy efficiencies and their relation with meteorological variables, such as temperature and density. We also calculate exergoeconomic parameter R ̇_ex and its dependence on the temperature, using the average values for twelve months of the year considered for comparison purposes. The exergy efficiency changes from 0.12 to 0.31 while the density varies between 1.31 and 1.2 kg/m3 for different temperature values. The R ̇_ex has minimum and maximum values of 0.02 and 0.81, respectively, while the temperature is in the range of 8-24°C for various wind velocity values.

Keywords: exergy, efficiency, renewable energy, wind energy, meteorological variables

Procedia PDF Downloads 237

Authors: Farshad Zeinali, Sajedeh Norouzi, Nader Mokari, Eduard Jorswieck

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The capacity of fifth-generation (5G) vehicle-to-everything (V2X) networks poses significant challenges. To ad- dress this challenge, this paper utilizes New Radio (NR) and New Radio Unlicensed (NR-U) networks to develop a heterogeneous vehicular network (HetNet). We propose a new framework, named joint BS assignment and resource allocation (JBSRA) for mobile V2X users and also consider coexistence schemes based on flexible duty cycle (DC) mechanism for unlicensed bands. Our objective is to maximize the average throughput of vehicles while guaranteeing the WiFi users' throughput. In simulations based on deep reinforcement learning (DRL) algorithms such as deep deterministic policy gradient (DDPG) and deep Q network (DQN), our proposed framework outperforms existing solutions that rely on fixed DC or schemes without consideration of unlicensed bands.

Keywords: vehicle-to-everything (V2X), resource allocation, BS assignment, new radio (NR), new radio unlicensed (NR-U), coexistence NR-U and WiFi, deep deterministic policy gradient (DDPG), deep Q-network (DQN), joint BS assignment and resource allocation (JBSRA), duty cycle mechanism

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Authors: Gerson E. Cornejo, Luis A. Gamarra, David S. Mauricio

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The Enterprise Resource Planning Systems (ERP) allows the integration of all the business processes of the functional areas of the companies, in order to automate and standardize the processes, obtain accurate information and improve decision making in time real. In Peru, 79% of medium and small companies (SMEs) do not use any management software, this is because it is believed that ERPs are expensive, complex and difficult to implement. However, for more than 20 years there have been Open Source ERPs, which are more accessible and have the same benefit as proprietary ERPs, but there is little information on the implementation process. In this work is made a case of study, in order to show the implementation process of an Open Source ERP, Odoo, based on the ASAP methodology (Accelerated SAP) and applied to a company of corrective and preventive maintenance services of vehicles. The ERP allowed the SME to standardize its business processes, increase its productivity, reducing up to 40% certain processes. The study of this case shows that it is feasible and profitable to implement an Open Source ERP in SMEs in the Automotive Sector of Peru. In addition, it is shown that the ASAP methodology is adequate to carry out Open Source ERPs implementation projects.

Keywords: ASAP, automotive sector, ERP implementation, open source

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Authors: Alsaidi M. Altaher, Mohd Tahir Ismail

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Wavelet thresholding has been a power tool in curve estimation and data analysis. In the presence of outliers this non parametric estimator can not suppress the outliers involved. This study proposes a new two-stage combined method based on the use of the median filter as primary step before applying wavelet thresholding. After suppressing the outliers in a signal through the median filter, the classical wavelet thresholding is then applied for removing the remaining noise. We use automatic boundary corrections; using a low order polynomial model or local polynomial model as a more realistic rule to correct the bias at the boundary region; instead of using the classical assumptions such periodic or symmetric. A simulation experiment has been conducted to evaluate the numerical performance of the proposed method. Results show strong evidences that the proposed method is extremely effective in terms of correcting the boundary bias and eliminating outlier’s sensitivity.

Keywords: boundary correction, median filter, simulation, wavelet thresholding

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Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: Erdinç Vural, Bülent Özdalyan, Serkan Özel

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The four-stroke single cylinder diesel engine has been used in this study, the pistons and valves of the engine have been stabilized, the aluminum oxide (Al₂O₃) in different ratios has been added in the power of zirconium (ZrO₂) magnesium oxide (MgO), and has been coated with the plasma spray method. The pistons and valves of the combustion chamber of the engine are coated with 5 different (ZrO₂ + MgO), (ZrO₂ + MgO + 25% Al₂O₃), (ZrO₂ + MgO + 50% Al₂O₃), (ZrO₂ + MgO + 75% Al₂O₃), (Al₂O₃) sample. The material tests have been made for each of the coated engine parts with the scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and X-ray diffraction (XRD) using Cu Kα radiation surface analysis methods. The engine tests have been repeated for each sample in any electric dynamometer in full power 1600 rpm, 2000 rpm, 2400 rpm and 2800 rpm engine speeds. The material analysis and engine tests have shown that the best performance has been performed with (ZrO₂ + MgO + 50% Al₂O₃). Thus, there is no significant change in HC and Smoke emissions, but NOx emission is increased, as the engine improves power, torque, specific fuel consumption and CO emissions in the tests made with sample A3.

Keywords: ceramic coating, material characterization, engine performance, exhaust emissions

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Authors: Cornelius Femi Popoola

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This study investigated logistics information systems in the distribution of flour in Nigeria. A case study design was used and 50 staff of Honeywell Flour Mill was sampled for the study. Data generated through a questionnaire were analysed using correlation and regression analysis. The findings of the study revealed that logistic information systems such as e-commerce, interactive telephone systems and electronic data interchange positively correlated with the distribution of flour in Honeywell Flour Mill. Finding also deduced that e-commerce, interactive telephone systems and electronic data interchange jointly and positively contribute to the distribution of flour in Honeywell Flour Mill in Nigeria (R = .935; Adj. R2 = .642; F (3,47) = 14.739; p < .05). The study therefore recommended that Honeywell Flour Mill should upgrade their logistic information systems to computer-to-computer communication of business transactions and documents, as well adopt new technology such as, tracking-and-tracing systems (barcode scanning for packages and palettes), tracking vehicles with Global Positioning System (GPS), measuring vehicle performance with ‘black boxes’ (containing logistic data), and Automatic Equipment Identification (AEI) into their systems.

Keywords: e-commerce, electronic data interchange, flour distribution, information system, interactive telephone systems

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Authors: Lin-Lin Liu, Song-Qi Hu, Yin Wang

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Paraffin-based fuels are regarded to be a promising fuel of hybrid rocked motor because of the high regression rate, low price, and environmental friendliness. Graphene Oxide (GO) is an attractive energetic material which is expected to be widely used in propellants, explosives, and some high energy fuels. Paraffin-based fuels with paraffin and GO as raw materials were prepared, and the oxidation process of the samples was investigated by thermogravimetric analysis differential scanning calorimetry (TG/DSC) under oxygen (O₂) and nitrous oxide (N₂O) atmospheres. The oxidation reaction kinetics of the fuels was estimated through the non-isothermal measurements and model-free isoconversional methods based on the experimental results of TGA. The results show that paraffin-based fuels are easier oxidized under O₂ rather than N₂O with atmospheres due to the lower activation energy; GO plays a catalytic role for the oxidation of paraffin-based fuels under the both atmospheres, and the activation energy of the oxidation process decreases with the increase of GO; catalytic effect of GO on the oxidation of paraffin-based fuels are more obvious under O₂ atmospheres than under N₂O atmospheres.

Keywords: graphene oxide, paraffin-based fuels, oxidation, activation energy, TGA

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Authors: Alan S. Hoback

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Most people see human faces in car front and back ends because of the process of pareidolia. 96 people were surveyed to see how many of them saw a face in the vehicle styling. Participants were aged 18 to 72 years. 94% of the participants saw faces in the front-end design of production models. All participants that recognized faces indicated that most styles showed some degree of an angry expression. It was found that women were more likely to see faces in inanimate objects. However, with respect to whether women were more likely to perceive anger in the vehicle design, the results need further clarification. Survey responses were correlated to the design features of vehicles to determine what cues the respondents were likely looking at when responding. Whether the features looked anthropomorphic was key to anger perception. Features such as the headlights which could represent eyes and the air intake that could represent a mouth had high correlations to trends in scores. Results are compared among models, makers, by groupings of body styles classifications for the top 12 brands sold in the US, and by year for the top 20 models sold in the US in 2016. All of the top models sold increased in perception of an angry expression over the last 20 years or since the model was introduced, but the relative change varied by body style grouping.

Keywords: aggressive driving, face recognition, road rage, vehicle styling

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Authors: Faraji Sepideh

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Nowadays, purchase rate of the smart device is increasing and user authentication is one of the important issues in information security. Alphanumeric strong passwords are difficult to memorize and also owners write them down on papers or save them in a computer file. In addition, text password has its own flaws and is vulnerable to attacks. Graphical password can be used as an alternative to alphanumeric password that users choose images as a password. This type of password is easier to use and memorize and also more secure from pervious password types. In this paper we have designed a more secure graphical password system to prevent shoulder surfing, smudge and brute force attack. This scheme is a combination of two types of graphical passwords recognition based and Cued recall based. Evaluation the usability and security of our proposed scheme have been explained in conclusion part.

Keywords: brute force attack, graphical password, shoulder surfing attack, smudge attack

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Authors: Nunziata Ivana Guarneri, Arcangelo Bruna, Giuseppe Spampinato, Antonio Buemi

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In the last decade, automotive companies have invested a lot in terms of innovation about many aspects regarding the automatic driver assistance systems. One innovation regards the usage of a smart camera placed on the car’s side mirror for monitoring the back and lateral road situation. A common road scenario is the overtaking of the preceding car and, in this case, a brief distraction or a loss of concentration can lead the driver to undertake this action, even if there is an already overtaking vehicle, leading to serious accidents. A valid support for a secure drive can be a smart camera system, which is able to automatically analyze the road scenario and consequentially to warn the driver when another vehicle is overtaking. This paper describes a method for monitoring the side view of a vehicle by using camera optical flow motion vectors. The proposed solution detects the presence of incoming vehicles, assesses their distance from the host car, and warns the driver through different levels of alert according to the estimated distance. Due to the low complexity and computational cost, the proposed system ensures real time performances.

Keywords: camera calibration, ego-motion, Kalman filters, object tracking, real time systems

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Authors: Safayat Ali Shaikh

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Software has been developed for optimal cropping pattern in an irrigation project considering land constraint, water availability constraint and pick up flow constraint using modified Simplex Algorithm. Artificial Neural Network Models (ANN) have been developed to predict rainfall. AR (1) model used to generate 1000 years rainfall data to train the ANN. Simulation has been done with expected rainfall data. Eight number crops and three types of soil class have been considered for optimization model. Area under each crop and each soil class have been quantified using Modified Simplex Algorithm to get optimum net return. Efficacy of the software has been tested using data of large irrigation project in India.

Keywords: artificial neural network, large irrigation project, modified simplex algorithm, optimal cropping pattern

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Authors: Xiaoyun Zhao, Rami Darwish, Anna Pernestål

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Automated vehicles (AVs) have the potential to enhance road capacity, improving road safety and traffic efficiency. Research and development on AVs have been going on for many years. However, when the complicated traffic rules and real situations interacted, AVs fail to make decisions on contradicting situations, and are not able to have control in all conditions due to highly dynamic driving scenarios. This limits AVs’ usage and restricts the full potential benefits that they can bring. Furthermore, regulations, infrastructure development, and public acceptance cannot keep up at the same pace as technology breakthroughs. Facing these challenges, this paper proposes automated vehicle traffic control tower (AVTCT) acting as a safe, efficient and integrated solution for AV control. It introduces a concept of AVTCT for control, management, decision-making, communication and interaction with various aspects in transportation. With the prototype demonstrations and simulations, AVTCT has the potential to overcome the control challenges with AVs and can facilitate AV reaching their full potential. Possible functionalities, benefits as well as challenges of AVTCT are discussed, which set the foundation for the conceptual model, simulation and real application of AVTCT.

Keywords: automated vehicle, connectivity and automation, intelligent transport system, traffic control, traffic safety

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Authors: Nawaf Alotaibi, Andy Evans, Alison Heppenstall, Nick Malleson

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Throughout the last two decades, motor vehicle theft (MVT) has accounted for the largest proportion of property crime incidents in Saudi Arabia (SA). However, to date, few studies have investigated SA’s MVT problem. Those that have are primarily focused on the characteristics of car thieves, and most have overlooked any spatial-temporal distribution of MVT incidents and the characteristics of victims. This paper represents the first step in understanding this problem by reviewing the existing MVT studies contextualised within the theoretical frameworks developed in environmental criminology theories – originating in the West – and exploring to what extent they are relevant to the SA context. To achieve this, the paper has identified a range of key features in SA that are different from typical Western contexts, that could limit the appropriateness and capability of applying existing environmental criminology theories. Furthermore, despite these Western studies reviewed so far having introduced a number of explanatory variables for MVT rates, a range of significant elements are apparently absent in the current literature and this requires further analysis. For example, almost no attempts have been made to quantify the associations between the locations of vehicle theft, recovery of stolen vehicles, joyriding and traffic volume.

Keywords: environmental criminology theories, motor vehicle theft, Saudi Arabia, spatial analysis

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Authors: Debesh R. Roy

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The fundamental issue in understanding the origin and growth mechanism of nanomaterials, from a fundamental unit is a big challenging problem to the scientists. Recently, an immense attention is generated to the researchers for prediction of exceptionally stable atomic cluster units as the building units for future smart materials. The present study is a systematic investigation on the stability and electronic properties of a series of bimetallic (semiconductor-alkaline earth) clusters, viz., BxMg3 (x=1-5) is performed, in search for exceptional and/ or unusual stable motifs. A very popular hybrid exchange-correlation functional, B3LYP as proposed by A. D. Becke along with a higher basis set, viz., 6-31+G[d,p] is employed for this purpose under the density functional formalism. The magic stability among the concerned clusters is explained using the jellium model. It is evident from the present study that the magic stability of B4Mg3 cluster arises due to the jellium shell closure.

Keywords: atomic clusters, density functional theory, jellium model, magic clusters, smart nanomaterials

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Authors: Surita Maini, Sanjay Dhanka

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Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

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Authors: Nur Ashida Salim, Muhammad Murtadha Othman, Ismail Musirin, Mohd Salleh Serwan

Abstract:

Uncertainty of system operating conditions is one of the causative reasons which may render to the instability of a transmission system. This will encumber the performance of transmission system to efficiently transmit the electrical power between areas. For that reason, accurate assessment of Transmission Reliability Margin (TRM) is essential in order to ensure effective power transfer between areas during the occurrence of system uncertainties. The power transfer is also called as the Available Transfer Capability (ATC) in which it is the information required by the utilities and marketers to instigate selling and buying the electric energy. This paper proposes a computationally effective approach to estimate TRM and ATC by considering the uncertainties of system cascading collapse and transmission line outages which is identified as the main reasons in power system instability. In accordance to the results that have been obtained, the proposed method is essential for the transmission providers which could help the power marketers and planning sectors in the operation and reserving transmission services based on the ATC calculated.

Keywords: system cascading collapse, transmission line outages, transmission reliability margin, available transfer capability

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Authors: Yassamina Berkane, Leila Kloul, Yoann Demoli

Abstract:

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

Keywords: urban mobility, decongestion, machine learning, neural network

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Authors: Jorge Urrutia-Mosquera, Luz Flórez-Calderón, Yasna Cortés

Abstract:

We assessed the state of progress in terms of urban sustainability indicators and studied the impact of current land use conditions and the level of spatial accessibility to basic urban amenities on travel patterns and sustainable mobility in Santiago de Chile. We determined the spatial impact of urban facilities on sustainable travel patterns through the statistical analysis, data visualisation, and weighted regression models. The results show a need to diversify land use in more than 60% of the communes, although in 85% of the communes, accessibility to public spaces is guaranteed. The findings also suggest improving access to early education facilities, as only 26% of the communes meet the sustainability standard, negatively impacting travel in sustainable modes. It is also observed that the level of access to urban facilities generates spatial heterogeneity in the city, which negatively affects travel patterns in terms of time over 60 minutes and modes of travel in private vehicles. The results obtained allow us to identify opportunities for public policy intervention to promote and adopt sustainable mobility.

Keywords: land use, urban sustainability, travel patterns, spatial heterogeneity, GWR model, sustainable mobility

Procedia PDF Downloads 71