Search results for: unmanned aerobic vehicles

Authors: Ersan Aktas, Eren Turanoğuz

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In this study, the quad-electrical rotor driven unmanned aerial vehicle system is designed and modeled using fundamental dynamic equations. After that, mechanical, electronical and control system of the air vehicle are designed and implemented. Brushless motor speeds are altered via electronic speed controllers in order to achieve desired controllability. The vehicle's fundamental Euler angles (i.e., roll angle, pitch angle, and yaw angle) are obtained via AHRS sensor. These angles are provided as an input to the control algorithm that run on soft the processor on the electronic card. The vehicle control algorithm is implemented in the electronic card. Controller is designed and improved for each Euler angles. Finally, flight tests have been performed to observe and improve the flight characteristics.

Keywords: quadrotor, UAS applications, control architectures, PID

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Authors: M. Caramihai, Irina Severin

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This paper deals with the design of an intelligent control structure for a bioprocess of Hansenula polymorpha yeast cultivation. The objective of the process control is to produce biomass in a desired physiological state. The work demonstrates that the designed Hybrid Control Techniques (HCT) are able to recognize specific evolution bioprocess trajectories using neural networks trained specifically for this purpose, in order to estimate the model parameters and to adjust the overall bioprocess evolution through an expert system and a fuzzy structure. The design of the control algorithm as well as its tuning through realistic simulations is presented. Taking into consideration the synergism of different paradigms like fuzzy logic, neural network, and symbolic artificial intelligence (AI), in this paper we present a real and fulfilled intelligent control architecture with application in bioprocess control.

Keywords: bioprocess, intelligent control, neural nets, fuzzy structure, hybrid techniques

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Authors: Asim Cengiz, Dede Basturk, Hakan Ozalp

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Practicing recurring resistance workout such as may cause changes in human muscle. These changes may be because combination if several factors determining physical fitness. Thus, it is important to identify these changes. Several studies were reviewed to investigate these changes. As a result, the changes included positive modifications in amplified citrate synthase (CS) maximal activity, increased capacity for pyruvate oxidation, improvement on molecular signaling on human performance, amplified resting muscle glycogen and whole GLUT4 protein content, better health outcomes such as enhancement in cardiorespiratory fitness. Sprint training also have numerous long long-term changes inhuman body such as better enzyme action, changes in muscle fiber and oxidative ability. This is important because SV is the critical factor influencing maximal cardiac output and therefore oxygen delivery and maximal aerobic power.

Keywords: sprint, training, performance, exercise

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Authors: William Li

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Lane-change path planning is a crucial and yet complex task in autonomous driving. The traditional path planning approach based on a system of carefully-crafted rules to cover various driving scenarios becomes unwieldy as more and more rules are added to deal with exceptions and corner cases. This paper proposes to divide the entire path planning to two stages. In the first stage the ego vehicle travels longitudinally in the source lane to reach a safe state. In the second stage the ego vehicle makes lateral lane-change maneuver to the target lane. The paper derives the safe state conditions based on lateral lane-change maneuver calculation to ensure collision free in the second stage. To determine the acceleration sequence that minimizes the time to reach a safe state in the first stage, the paper proposes three schemes, namely, kinetic model based optimization, deep reinforcement learning, and 5G vehicle-to-vehicle (V2V) communications. The paper investigates these schemes via simulation. The model-based optimization is sensitive to the model assumptions. The deep reinforcement learning is more flexible in handling scenarios beyond the model assumed by the optimization. The 5G V2V eliminates uncertainty in predicting future behaviors of surrounding vehicles by sharing driving intents and enabling cooperative driving.

Keywords: lane change, path planning, autonomous driving, deep reinforcement learning, 5G, V2V communications, connected vehicles

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Authors: Raffaello Furlan

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In the 21st century, the sustainable urban development of GCC-cities is challenged by inhabitants’ over-dependency on private-use vehicles. In turn, this habit has generated problems of urban inefficiency, contributing to traffic congestion, pollution, urban sprawling, fragmentation of the urban fabric, and various environmental and social challenges. In the context of Doha, the capital city of the State of Qatar, the over-dependency on private-use vehicles is justified by the lack of alternative public modes of transportation that support the need to connect fragmented urban districts and provide an effective solution to urban sprawl. Therefore, the current construction of the Qatar Metro Rail is offering the potential for investigating and defining a strategy for the sustainable urban development and/or urban regeneration of transit villages (TODs) in Qatar. Namely, the aim of this research study is (i) to investigate the development of transit villages (TODs) in the cultural-heritage district of Msheireb, Downtown Doha, (ii) to explore how the introduction of the new public transport system of Doha Metro can be effectively utilized as means of urban regeneration of the cultural core of the city, (iii) to propose a masterplan for TOD suitable for the district, suiting and responding to regional cultural and societal values. The findings reveal that the strategies for the sustainable urban regeneration of Msheireb are based on (i) the integration of land-use and multimodal transportation systems, (ii) the implementation of the public realm, and (iii) conservation of culture and urban identity.

Keywords: sustainable urbanism, smart growth, TODs, cultural district, Msheireb Downtown Doha

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Authors: Ahlyum Mun, Ji-Young Moon, Moon-Seok Yoon, Dong-Jin Baek, Doo-Seok Seo, Oun-Kyong Moon

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There is a growing public concern over the standards of farm animal welfare, with higher standards of food safety. In addition, the recent low incidence of Avian Influenza in laying hens among certificated farms is receiving attention. In this study, we introduce animal welfare systems covering the rearing, transport and slaughter of farm animals in South Korea. The concepts of animal welfare farm certification are based on ensuring the five freedoms of animal. The animal welfare is also achieved by observing the condition of environment including shelter and resting area, feeding and water and the care for the animal health. The certification of farm animal welfare is handled by the Animal Protection & Welfare Division of Animal and Plant Quarantine Agency (APQA). Following the full amendment of Animal Protection Law in 2011, animal welfare farm certification program has been implemented since 2012. The certification system has expanded to cover laying hen, swine, broiler, beef cattle and dairy cow, goat and duck farms. Livestock farmers who want to be certified must apply for certification at the APQA. Upon receipt of the application, the APQA notifies the applicant of the detailed schedule of the on-site examination after reviewing the document and conducts the on-site inspection according to the evaluation criteria of the welfare standard. If the on-site audit results meet the certification criteria, APQA issues a certificate. The production process of certified farms is inspected at least once a year for follow-up management. As of 2017, a total of 145 farms have been certified (95 laying hen farms, 12 swine farms, 30 broiler farms and 8 dairy cow farms). In addition, animal welfare transportation vehicles and slaughterhouses have been designated since 2013 and currently 6 slaughterhouses have been certified. Animal Protection Law has been amended so that animal welfare certification marks can be affixed only to livestock products produced by animal welfare farms, transported through animal welfare vehicles and slaughtered at animal welfare slaughterhouses. The whole process including rearing–transportation- slaughtering completes the farm animal welfare system. APQA established its second 5-year animal welfare plan (2014-2019) that includes setting a minimum standard of animal welfare applicable to all livestock farms, transportation vehicles and slaughterhouses. In accordance with this plan, we will promote the farm animal welfare policy in order to truly advance the Korean livestock industry.

Keywords: animal welfare, farm animal, certification system, South Korea

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Authors: Frederick Kobe O. Obar, Preity B. Quinzon, Trisha B. Tumbokon, Mario Joshua D. Marron, Kenichi Katsuo Kichiro A. Rimorin

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The Public Utility Vehicle Modernization Program (PUVMP) is a program meant to reform the current state of the Philippines’ public transportation sector. This study determined the impact of the Public Utility Vehicle Modernization Program on San Fernando City, La Union's jeepney drivers, interviewing six individuals, three with traditional vehicles and three with modernized units. This study used a descriptive qualitative research design and employed purposive sampling to select the six participants suited for the study, who were then subjected to a semi-structured face-to-face interview. The gathered data was then analyzed through thematic analysis. The findings highlighted evidence that the jeepney drivers experienced abrupt and prevailing changes in their routine and in their everyday work. This study concludes that while the sentiment of the program was appreciated, it has changed the environment for jeepney drivers drastically, provoking many reactions. These changes have, of course, shifted the daily lives of the jeepney drivers significantly, but through adaptability, they found ways. Recommendations include flexible compliance policies, educational initiatives, and support for drivers, providing valuable insights for informed decision-making in the ongoing transportation modernization discussion. This study concluded that while the drivers are not opposed to reform, they are not entirely in approval of the current effects of the program as it is being implemented in their local area.

Keywords: transport reform, transport modernization, public transport, jeepney drivers, PUVMP, urban planning, public utility vehicles

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Authors: Ali Mashayekh, Mahdiye Khorasani, Thomas Weyh

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The tendency to use the Battery-Electric vehicle (BEV) for the low and medium driving range or even high driving range has been growing more and more. As a result, higher safety, reliability, and durability of the battery pack as a component of electric vehicles, which has a great share of cost and weight of the final product, are the topics to be considered and investigated. Battery aging can be considered as the predominant factor regarding the reliability and durability of BEV. To better understand the aging process, offline battery characterization has been widely used, which is time-consuming and needs very expensive infrastructures. This paper presents the substitute method for the conventional battery characterization methods, which is based on battery Modular Multilevel Management (BM3). According to this Topology, the battery cells can be drained and charged concerning their capacity, which allows varying battery pack structures. Due to the integration of the power electronics, the output voltage of the battery pack is no longer fixed but can be dynamically adjusted in small steps. In other words, each cell can have three different states, namely series, parallel, and bypass in connection with the neighbor cells. With the help of MATLAB/Simulink and by using the BM3 modules, the battery string model is created. This model allows us to switch two cells with the different SoC as parallel, which results in the internal balancing of the cells. But if the parallel switching lasts just for a couple of ms, we can have a perturbation pulse which can stimulate the cells out of the relaxation phase. With the help of modeling the voltage response pulse of the battery, it would be possible to characterize the cell. The Online EIS method, which is discussed in this paper, can be a robust substitute for the conventional battery characterization methods.

Keywords: battery characterization, SoH estimation, RLS, BEV

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Authors: Salman Naseer

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One of the main challenges of operating a smart city (SC) is collecting the massive data generated from multiple data sources (DS) and to transmit them to the control units (CU) for further data processing and analysis. These ever-increasing data demands require not only more and more capacity of the transmission channels but also results in resource over-provision to meet the resilience requirements, thus the unavoidable waste because of the data fluctuations throughout the day. In addition, the high energy consumption (EC) and carbon discharges from these data transmissions posing serious issues to the environment we live in. Therefore, to overcome the issues of intensive EC and carbon emissions (CE) of massive data dissemination in Smart Cities, we propose an energy efficient and carbon reduction approach by utilizing the daily mobility of the existing vehicles as an alternative communications channel to accommodate the data dissemination in smart cities. To illustrate the effectiveness and efficiency of our approach, we take the Auckland City in New Zealand as an example, assuming massive data generated by various sources geographically scattered throughout the Auckland region to the control centres located in city centre. The numerical results show that our proposed approach can provide up to 5 times lower delay as transferring the large volume of data by utilizing the existing daily vehicles’ mobility than the conventional transmission network. Moreover, our proposed approach offers about 30% less EC and CE than that of conventional network transmission approach.

Keywords: smart city, delay tolerant network, infrastructure offloading, opportunistic network, vehicular mobility, energy consumption, carbon emission

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Authors: Abdurrahman Arslanyilmaz, Salman Al Matouq, Durmus V. Doner

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Level 3 autonomous vehicles are able to take full responsibility over the control of the vehicle unless a system boundary is reached or a system failure occurs, in which case, the driver is expected to take-over the control of the vehicle. While this happens, the driver is often not aware of the traffic situation or is engaged in a secondary task. Factors affecting the duration and quality of take-overs in these situations have included secondary task type and nature, traffic density, take-over request (TOR) time, and TOR warning type and modality. However, to the best of the authors’ knowledge, no prior study examined time buffer for TORs when a system failure occurs immediately before intersections. The first objective of this study is to investigate the effect of time buffer (3 and 7 seconds) on the duration and quality of take-overs when a system failure occurs just prior to intersections. In addition, eye-tracking has become one of the most popular methods to report what individuals view, in what order, for how long, and how often, and it has been utilized in driving simulations with various objectives. However, to the extent of authors’ knowledge, none has compared drivers’ eye gaze behavior in the two different time buffers in order to examine drivers’ attention and comprehension of salient information. The second objective is to understand the driver’s attentional focus on comprehension of salient traffic-related information presented on different parts of the dashboard and on the roads.

Keywords: autonomous vehicles, driving simulation, eye gaze, attention, comprehension, take-over duration, take-over quality, time buffer

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Authors: Nicolas Plamondon, Stuart Atkinson, Shuzi Zhou

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The insurance industry is usually not the first topic one has in mind when thinking about applications of data science. However, the use of data science in the finance and insurance industry is growing quickly for several reasons, including an abundance of reliable customer data, ferocious competition requiring more accurate pricing, etc. Among the top use cases of data science, we find pricing optimization, customer segmentation, customer risk assessment, fraud detection, marketing, and triage analytics. The objective of this paper is to present an application of the generalized additive model (GAM) on a commercial automobile insurance product: an individually rated commercial automobile. These are vehicles used for commercial purposes, but for which there is not enough volume to apply pricing to several vehicles at the same time. The GAM model was selected as an improvement over GLM for its ease of use and its wide range of applications. The model was trained using the largest split of the data to determine model parameters. The remaining part of the data was used as testing data to verify the quality of the modeling activity. We used the Gini coefficient to evaluate the performance of the model. For long-term monitoring, commonly used metrics such as RMSE and MAE will be used. Another topic of interest in the insurance industry is to process of producing the model. We will discuss at a high level the interactions between the different teams with an insurance company that needs to work together to produce a model and then monitor the performance of the model over time. Moreover, we will discuss the regulations in place in the insurance industry. Finally, we will discuss the maintenance of the model and the fact that new data does not come constantly and that some metrics can take a long time to become meaningful.

Keywords: insurance, data science, modeling, monitoring, regulation, processes

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Authors: H. M. Liman, Y. M. Suleiman A. A. David

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Poor air quality often considered one of the greatest environmental threats facing the world today is caused majorly by the emission of carbon monoxide into the atmosphere. The principal air pollutant is carbon monoxide. One prominent source of carbon monoxide emission is the transportation sector. Not much was known about the emission levels of carbon monoxide, the primary pollutant from the road transportation in the study area. Therefore, this study assessed the levels of carbon monoxide emission from road transportation in the Minna, Niger State. The database shows the carbon monoxide data collected. MSA Altair gas alert detector was used to take the carbon monoxide emission readings in Parts per Million for the peak and off-peak periods of vehicular movement at the road intersections. Their Global Positioning System (GPS) coordinates were recorded in the Universal Transverse Mercator (UTM). Bar chart graphs were plotted by using the emissions level of carbon dioxide as recorded on the field against the scientifically established internationally accepted safe limit of 8.7 Parts per Million of carbon monoxide in the atmosphere. Further statistical analysis was also carried out on the data recorded from the field using the Statistical Package for Social Sciences (SPSS) software and Microsoft excel to show the variance of the emission levels of each of the parameters in the study area. The results established that emissions’ level of atmospheric carbon monoxide from the road transportation in the study area exceeded the internationally accepted safe limits of 8.7 parts per million. In addition, the variations in the average emission levels of CO between the four parameters showed that morning peak is having the highest average emission level of 24.5PPM followed by evening peak with 22.84PPM while morning off peak is having 15.33 and the least is evening off peak 12.94PPM. Based on these results, recommendations made for poor air quality mitigation via carbon monoxide emissions reduction from transportation include Introduction of the urban mass transit would definitely reduce the number of traffic on the roads, hence the emissions from several vehicles that would have been on the road. This would also be a cheaper means of transportation for the masses and Encouraging the use of vehicles using alternative sources of energy like solar, electric and biofuel will also result in less emission levels as the these alternative energy sources other than fossil fuel originated diesel and petrol vehicles do not emit especially carbon monoxide.

Keywords: carbon monoxide, climate change emissions, road transportation, vehicular

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Authors: Michael C. Barbecho, Romeo B. Morcilla

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This study focused on the development of a solar powered front wheel drive electric trike for personal use and short distance travel, utilizing solar power and a variable speed transmission to adapt in places where varying road grades and unavailability of plug-in charging stations are of great problems. The actual performance of the vehicle was measured in terms of duration of charging using solar power, distance travel and battery power duration, top speed developed at full power, and load capacity. This project followed the research and development process which involved planning, designing, construction, and testing. Solar charging tests revealed that the vehicle requires 6 to 8 hours sunlight exposure to fully charge the batteries. At full charge, the vehicle can travel 35 km utilizing battery power down to 42%. Vehicle showed top speed of 25 kph at 0 to 3% road grade carrying a maximum load of 122 kg. The maximum climbing grade was 23% with the vehicle carrying a maximum load of 122 kg. Technically the project was feasible and can be a potential model for possible conversion of traditional Philippine made “pedicabs” and gasoline engine powered tricycle into modern electric vehicles. Moreover, it has several technical features and advantages over a commercialized electric vehicle such as the use solar charging system and variable speed power transmission and front drive power train for adaptability in any road gradient.

Keywords: electric vehicle, solar vehicles, front drive, solar, solar power

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Authors: Farhad Salek, Shahaboddin Resalati

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The production of electric vehicles (EVs) featuring lithium-ion battery technology has substantially escalated over the past decade, demonstrating a steady and persistent upward trajectory. The imminent retirement of electric vehicle (EV) batteries after approximately eight years underscores the critical need for their redirection towards recycling, a task complicated by the current inadequacy of recycling infrastructures globally. A potential solution for such concerns involves extending the operational lifespan of electric vehicle (EV) batteries through their utilization in stationary energy storage systems during secondary applications. Such adoptions, however, require addressing the safety concerns associated with batteries’ knee points and thermal runaways. This paper develops an accurate mathematical model representative of the second-life battery packs from a cell-to-pack scale using an equivalent circuit model (ECM) methodology. Neural network algorithms are employed to forecast the degradation parameters based on the EV batteries' aging history to develop a degradation model. The degradation model is integrated with the ECM to reflect the impacts of the cycle aging mechanism on battery parameters during operation. The developed model is tested under real-life load profiles to evaluate the life span of the batteries in various operating conditions. The methodology and the algorithms introduced in this paper can be considered the basis for Battery Management System (BMS) design and techno-economic analysis of such technologies.

Keywords: second life battery, electric vehicles, degradation, neural network

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Authors: Qiaosi Li, Frankie Kwan Kit Wong, Tung Fung

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Lightweight unmanned aerial vehicle (UAV) loading with novel sensors offers a low cost approach for data acquisition in complex environment. This study established a framework for applying UAV system in complex environment quick mapping and assessed the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area Mai Po Inner Deep Bay Ramsar Site, Hong Kong. The study area was part of shallow bay with flat terrain and the major species including reedbed and four mangroves: Kandelia obovata, Aegiceras corniculatum, Acrostichum auerum and Acanthus ilicifolius. Other species involved in various graminaceous plants, tarbor, shrub and invasive species Mikania micrantha. In particular, invasive species climbed up to the mangrove canopy caused damage and morphology change which might increase species distinguishing difficulty. Hyperspectral images were acquired by Headwall Nano sensor with spectral range from 400nm to 1000nm and 0.06m spatial resolution image. A sequence of multi-view RGB images was captured with 0.02m spatial resolution and 75% overlap. Hyperspectral image was corrected for radiative and geometric distortion while high resolution RGB images were matched to generate maximum dense point clouds. Furtherly, a 5 cm grid digital surface model (DSM) was derived from dense point clouds. Multiple feature reduction methods were compared to identify the efficient method and to explore the significant spectral bands in distinguishing different species. Examined methods including stepwise discriminant analysis (DA), support vector machine (SVM) and minimum noise fraction (MNF) transformation. Subsequently, spectral subsets composed of the first 20 most importance bands extracted by SVM, DA and MNF, and multi-source subsets adding extra DSM to 20 spectrum bands were served as input in maximum likelihood classifier (MLC) and SVM classifier to compare the classification result. Classification results showed that feature reduction methods from best to worst are MNF transformation, DA and SVM. MNF transformation accuracy was even higher than all bands input result. Selected bands frequently laid along the green peak, red edge and near infrared. Additionally, DA found that chlorophyll absorption red band and yellow band were also important for species classification. In terms of 3D data, DSM enhanced the discriminant capacity among low plants, arbor and mangrove. Meanwhile, DSM largely reduced misclassification due to the shadow effect and morphological variation of inter-species. In respect to classifier, nonparametric SVM outperformed than MLC for high dimension and multi-source data in this study. SVM classifier tended to produce higher overall accuracy and reduce scattered patches although it costs more time than MLC. The best result was obtained by combining MNF components and DSM in SVM classifier. This study offered a precision species distribution survey solution for inaccessible wetland area with low cost of time and labour. In addition, findings relevant to the positive effect of DSM as well as spectral feature identification indicated that the utility of UAV-borne hyperspectral and photogrammetry deriving 3D data is promising in further research on wetland species such as bio-parameters modelling and biological invasion monitoring.

Keywords: digital surface model (DSM), feature reduction, hyperspectral, photogrammetric point cloud, species mapping, unmanned aerial vehicle (UAV)

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Authors: Koichi Yonemoto, Hiroshi Yamasaki, Masatomo Ichige, Yusuke Ura, Guna S. Gossamsetti, Takumi Ohki, Kento Shirakata, Ahsan R. Choudhuri, Shinji Ishimoto, Takashi Mugitani, Hiroya Asakawa, Hideaki Nanri

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This paper presents the strategic development plan of winged rockets WIRES (WInged REusable Sounding rocket) aiming at unmanned suborbital winged rocket for demonstrating future fully reusable space transportation technologies, such as aerodynamics, Navigation, Guidance and Control (NGC), composite structure, propulsion system, and cryogenic tanks etc., by universities in collaboration with government and industries, as well as the past and current flight test results.

Keywords: autonomous guidance and control, reusable rocket, space transportation system, suborbital vehicle, winged rocket

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Authors: Rossana Roila, Raffaella Branciari, Lorenzo Cardinali, David Ranucci

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The wild boar (Sus scrofa) population has strongly increased across Europe in the last decades, also causing severe fauna management issues. In central Italy, wild boar is the main hunted wild game species, with approximately 40,000 animals killed per year only in the Umbria region. The meat of the game is characterized by high-quality nutritional value as well as peculiar taste and aroma, largely appreciated by consumers. This type of meat and products thereof can meet the current consumers’ demand for higher quality foodstuff, not only from a nutritional and sensory point of view but also in relation to environmental sustainability, the non-use of chemicals, and animal welfare. The game meat production chain is characterized by some gaps from a hygienic point of view: the harvest process is usually conducted in a wild environment where animals can be more easily contaminated during hunting and subsequent practices. The definition and implementation of a certified and controlled supply chain could ensure quality, traceability and safety for the final consumer and therefore promote game meat products. According to European legislation in some animal species, such as bovine, the use of weak acid solutions for carcass decontamination is envisaged in order to ensure the maintenance of optimal hygienic characteristics. A preliminary study was carried out to evaluate the applicability of similar strategies to control the hygienic level of wild boar carcasses. The carcasses, harvested according to the selective method and processed into the game-handling establishment, were treated by nebulization with two different solutions: a 2% food-grade lactic acid solution and aromatic vinegar. Swab samples were performed before treatment and in different moments after-treatment of the carcasses surfaces and subsequently tested for Total Aerobic Mesophilic Load, Total Aerobic Psychrophilic Load, Enterobacteriaceae, Staphylococcus spp. and lactic acid bacteria. The results obtained for the targeted microbial populations showed a positive effect of the application of the lactic acid solution on all the populations investigated, while aromatic vinegar showed a lower effect on bacterial growth. This study could lay the foundations for the optimization of the use of a lactic acid solution to treat wild boar carcasses aiming to guarantee good hygienic level and safety of meat.

Keywords: game meat, food safety, process hygiene criteria, microbial population, microbial growth, food control

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Authors: Karima Kharroub, Mohamed Amine Gomri, Mercedes Monteoliva-Sanchez

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Sabkhas and chotts are examples of hypersaline environments inhabited by halophilic microorganisms. In the present study, a culture-dependent methodology was used to determine the archaeal diversity present within Ezzemoul sabkha located in the north-eastern of Algeria. It was assessed using different media with different substrates in attempt to initiate the growth of wide spectrum of halophiles. Several strains were isolated and subjected to a polyphasic taxonomic characterization. The isolates tested placed within the family Halobacteriaceae, a group of extremely halophilic, aerobic archaea that have a salinity tolerance of 3 to 4M and associated with six genera Halorubrum, Halobacterium, Haloterrigena, Haloferax, Halomicrobium and Haloarcula. Halorubrum species were found to be the dominant archaea community as indicated by the presence of different strains recovered from this sabkha. In the other hand, two new species within Halobacteriaceae family; Halorubrum ezzemolulense sp. nov. and Halomicrobium katesii sp. nov. were described.

Keywords: sabkha, archaea, halophilic, hypersaline environments

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Authors: Onabajo Paul

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The testing and assessment of physical fitness of school-aged adolescents in Nigeria has been going on for several decades. Originally, these tests strictly focused on identifying health and physical fitness status and comparing the results of adolescents with others. There is a considerable interest in health and performance fitness of adolescents in which results attained are compared with criteria representing positive health rather than simply on score comparisons with others. Despite the fact that physical education program is being studied in secondary schools and physical activities are encouraged, it is observed that regular assessment of students’ fitness level and health status seems to be scarce or not being done in these schools. The purpose of the study was to assess the heath and performance fitness of adolescents in middle-income schools in Lagos State. A total number of 150 students were selected using the simple random sampling technique. Participants were measured on hand grip strength, sit-up, pacer 20 meter shuttle run, standing long jump, weight and height. The data collected were analyzed with descriptive statistics of means, standard deviations, and range and compared with fitness norms. It was concluded that majority 111(74.0%) of the adolescents achieved the healthy fitness zone, 33(22.0%) were very lean, and 6(4.0%) needed improvement according to the normative standard of Body Mass Index test. For muscular strength, majority 78(52.0%) were weak, 66(44.0%) were normal, and 6(4.0%) were strong according to the normative standard of hand-grip strength test. For aerobic capacity fitness, majority 93(62.0%) needed improvement and were at health risk, 36(24.0%) achieved healthy fitness zone, and 21(14.0%) needed improvement according to the normative standard of PACER test. Majority 48(32.0%) of the participants had good hip flexibility, 38(25.3%) had fair status, 27(18.0%) needed improvement, 24(16.0%) had very good hip flexibility status, and 13(8.7%) of the participants had excellent status. Majority 61(40.7%) had average muscular endurance status, 30(20.0%) had poor status, 29(18.3%) had good status, 28(18.7%) had fair muscular endurance status, and 2(1.3%) of the participants had excellent status according to the normative standard of sit-up test. Majority 52(34.7%) had low jump ability fitness, 47(31.3%) had marginal fitness, 31(20.7%) had good fitness, and 20(13.3%) had high performance fitness according to the normative standard of standing long jump test. Based on the findings, it was concluded that majority of the adolescents had better Body Mass Index status, and performed well in both hip flexibility and muscular endurance tests. Whereas majority of the adolescents performed poorly in aerobic capacity test, muscular strength and jump ability test. It was recommended that to enhance wellness, adolescents should be involved in physical activities and recreation lasting 30 minutes three times a week. Schools should engage in fitness program for students on regular basis at both senior and junior classes so as to develop good cardio-respiratory, muscular fitness and improve overall health of the students.

Keywords: adolescents, health-related fitness, performance-related fitness, physical fitness

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Authors: Mujahid Muhammad, Paul Kearney, Adel Aneiba

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The ability for vehicles to communicate with other vehicles (V2V), the physical (V2I) and network (V2N) infrastructures, pedestrians (V2P), etc. – collectively known as V2X (Vehicle to Everything) – will enable a broad and growing set of applications and services within the intelligent transport domain for improving road safety, alleviate traffic congestion and support autonomous driving. The telecommunication research and industry communities and standardization bodies (notably 3GPP) has finally approved in Release 14, cellular communications connectivity to support V2X communication (known as LTE – V2X). LTE – V2X system will combine simultaneous connectivity across existing LTE network infrastructures via LTE-Uu interface and direct device-to-device (D2D) communications. In order for V2X services to function effectively, a robust security mechanism is needed to ensure legal and safe interaction among authenticated V2X entities in the LTE-based V2X architecture. The characteristics of vehicular networks, and the nature of most V2X applications, which involve human safety makes it significant to protect V2X messages from attacks that can result in catastrophically wrong decisions/actions include ones affecting road safety. Attack vectors include impersonation attacks, modification, masquerading, replay, MiM attacks, and Sybil attacks. In this paper, we focus our attention on LTE-based V2X security and access control mechanisms. The current LTE-A security framework provides its own access authentication scheme, the AKA protocol for mutual authentication and other essential cryptographic operations between UEs and the network. V2N systems can leverage this protocol to achieve mutual authentication between vehicles and the mobile core network. However, this protocol experiences technical challenges, such as high signaling overhead, lack of synchronization, handover delay and potential control plane signaling overloads, as well as privacy preservation issues, which cannot satisfy the adequate security requirements for majority of LTE-based V2X services. This paper examines these challenges and points to possible ways by which they can be addressed. One possible solution, is the implementation of the distributed peer-to-peer LTE security mechanism based on the Bitcoin/Namecoin framework, to allow for security operations with minimal overhead cost, which is desirable for V2X services. The proposed architecture can ensure fast, secure and robust V2X services under LTE network while meeting V2X security requirements.

Keywords: authentication, long term evolution, security, vehicle-to-everything

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Authors: Ashish Pathak, Dong-Jin Kim, Haragobinda Srichandan, Byoung-Gon Kim

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Microbial depyritization of coal using chemoautotrophic bacteria is gaining acceptance as an efficient and eco-friendly technique. The process uses the metabolic activity of chemoautotrophic bacteria in removing sulfur and pyrite from the coal. The aim of the present study was to investigate the potential of Acidithiobacillus ferrooxidans in removing the pyritic sulfur and iron from high iron and sulfur containing US coal. The experiment was undertaken in 8 L bench scale stirred tank reactor having 1% (w/v) pulp density of coal. The reactor was operated at 35ºC and aerobic conditions were maintained by sparging the air into the reactor. It was found that at the end of bio-depyritization process, about 90% of pyrite and 67% of pyritic sulfur was removed from the coal. The results indicate that the bio-depyritization process is an efficient process in treating the high pyrite and sulfur containing coal.

Keywords: At.ferrooxidans, batch reactor, coal desulfurization, pyrite

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Authors: Zhihao Peng, Qiong Zhang, Xiyao Li, Yongzhen Peng

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Nowadays, conventional nitrogen removal process (nitrification and denitrification) was adopted in most wastewater treatment plants, but many problems have occurred, such as: high aeration energy consumption, extra carbon sources dosage and high sludge treatment costs. The emergence of anammox has bring about the great revolution to the nitrogen removal technology, and only the ammonia and nitrite were required to remove nitrogen autotrophically, no demand for aeration and sludge treatment. However, there existed many challenges in anammox applications: difficulty of biomass retention, insufficiency of nitrite substrate, damage from complex organic etc. Much effort was put into the research in overcoming the above challenges, and the payment was rewarded. It was also imperative to establish an innovative process that can settle the above problems synchronously, after all any obstacle above mentioned can cause the collapse of anammox system. Therefore, in this study, a two-stage process was established that the sequencing batch reactor (SBR) and upflow anaerobic sludge blanket (UASB) were used in the pre-stage and post-stage, respectively. The domestic wastewater entered into the SBR first and went through anaerobic/aerobic/anoxic (An/O/A) mode, and the draining at the aerobic end of SBR was mixed with domestic wastewater, the mixture then entering to the UASB. In the long term, organic and nitrogen removal performance was evaluated. All along the operation, most COD was removed in pre-stage (COD removal efficiency > 64.1%), including some macromolecular organic matter, like: tryptophan, tyrosinase and fulvic acid, which could weaken the damage of organic matter to anammox. And the An/O/A operating mode of SBR was beneficial to the achievement and maintenance of partial nitrification (PN). Hence, sufficient and steady nitrite supply was another favorable condition to anammox enhancement. Besides, the flexible mixing ratio helped to gain a substrate ratio appropriate to anammox (1.32-1.46), which further enhance the anammox. Further, the UASB was used and gas recirculation strategy was adopted in the post-stage, aiming to achieve granulation by the selection pressure. As expected, the granules formed rapidly during 38 days, which increased from 153.3 to 354.3 μm. Based on bioactivity and gene measurement, the anammox metabolism and abundance level rose evidently, by 2.35 mgN/gVss·h and 5.3 x109. The anammox bacteria mainly distributed in the large granules (>1000 μm), while the biomass in the flocs (<200 μm) and microgranules (200-500 μm) barely displayed anammox bioactivity. Enhanced anammox promoted the advanced autotrophic nitrogen removal, which increased from 71.9% to 93.4%, even when the temperature was only 12.9 ℃. Therefore, it was feasible to enhance anammox in the multiple favorable conditions created, and the strategy extended the application of anammox to the full-scale mainstream, enhanced the understanding of anammox in the aspects of culturing conditions.

Keywords: anammox, granules, nitrite accumulation, nitrogen removal efficiency

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

Abstract:

This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

Procedia PDF Downloads 168

Authors: Loha Hashimy, Isabella Castillo

Abstract:

In today's rapidly evolving technological landscape, the importance of precise navigation and mapping systems cannot be understated. As various sectors undergo transformative changes, the market potential for Advanced Mapping and Management Systems (AMMS) emerges as a critical focus area. The Galileo/GNSS-Based Autonomous Mobile Mapping System (GAMMS) project, specifically targeted toward high-definition mapping (HDM), endeavours to provide insights into this market within the broader context of the geomatics and navigation fields. With the growing integration of Autonomous Vehicles (AVs) into our transportation systems, the relevance and demand for sophisticated mapping solutions like HDM have become increasingly pertinent. The research employed a meticulous, lean, stepwise, and interconnected methodology to ensure a comprehensive assessment. Beginning with the identification of pivotal project results, the study progressed into a systematic market screening. This was complemented by an exhaustive desk research phase that delved into existing literature, data, and trends. To ensure the holistic validity of the findings, extensive consultations were conducted. Academia and industry experts provided invaluable insights through interviews, questionnaires, and surveys. This multi-faceted approach facilitated a layered analysis, juxtaposing secondary data with primary inputs, ensuring that the conclusions were both accurate and actionable. Our investigation unearthed a plethora of drivers steering the HD maps landscape. These ranged from technological leaps, nuanced market demands, and influential economic factors to overarching socio-political shifts. The meteoric rise of Autonomous Vehicles (AVs) and the shift towards app-based transportation solutions, such as Uber, stood out as significant market pull factors. A nuanced PESTEL analysis further enriched our understanding, shedding light on political, economic, social, technological, environmental, and legal facets influencing the HD maps market trajectory. Simultaneously, potential roadblocks were identified. Notable among these were barriers related to high initial costs, concerns around data quality, and the challenges posed by a fragmented and evolving regulatory landscape. The GAMMS project serves as a beacon, illuminating the vast opportunities that lie ahead for the HD mapping sector. It underscores the indispensable role of HDM in enhancing navigation, ensuring safety, and providing pinpoint, accurate location services. As our world becomes more interconnected and reliant on technology, HD maps emerge as a linchpin, bridging gaps and enabling seamless experiences. The research findings accentuate the imperative for stakeholders across industries to recognize and harness the potential of HD mapping, especially as we stand on the cusp of a transportation revolution heralded by Autonomous Vehicles and advanced geomatic solutions.

Keywords: high-definition mapping (HDM), autonomous vehicles, PESTEL analysis, market drivers

Procedia PDF Downloads 74

Authors: Ali Moradiamani, Samaneh Sadat Sajjadi, Mahdi Jalili

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Power system analysis has been a major research topic in the generation and distribution sections, in both industry and academia, for a long time. Several load flow and fault analysis scenarios have been normally performed to study the performance of different parts of the grid in the context of, for example, voltage and frequency control. Software tools, such as PSCAD, PSSE, and PowerFactory DIgSILENT, have been developed to perform these analyses accurately. Distribution grid had been the passive part of the grid and had been known as the grid of consumers. However, a significant paradigm shift has happened with the emergence of Distributed Energy Resources (DERs) in the distribution level. It means that the concept of power system analysis needs to be extended to the distribution grid, especially considering self sufficient technologies such as microgrids. Compared to the generation and transmission levels, the distribution level includes significantly more generation/consumption nodes thanks to PV rooftop solar generation and battery energy storage systems. In addition, different consumption profile is expected from household residents resulting in a diverse set of scenarios. Emergence of electric vehicles will absolutely make the environment more complicated considering their charging (and possibly discharging) requirements. These complexities, as well as the large size of distribution grids, create challenges for the available power system analysis software. In this paper, we study the requirements of simulation tools in the distribution grid and how data-driven algorithms are required to increase the accuracy of the simulation results.

Keywords: smart grids, distributed energy resources, electric vehicles, battery storage systsms, simulation tools

Procedia PDF Downloads 97

Authors: Mohammed Hmimou, Khalid Amediaz, Imane Sebari, Nabil Bounajma

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Annual crop production is one of the most important macroeconomic indicators for the majority of countries around the world. This information is valuable, especially for exporting countries which need a yield estimation before harvest in order to correctly plan the supply chain. When it comes to estimating agricultural yield, especially for arboriculture, conventional methods are mostly applied. In the case of the citrus industry, the sale before harvest is largely practiced, which requires an estimation of the production when the fruit is on the tree. However, conventional method based on the sampling surveys of some trees within the field is always used to perform yield estimation, and the success of this process mainly depends on the expertise of the ‘estimator agent’. The present study aims to propose a methodology based on the combination of unmanned aerial vehicle (UAV) images and terrestrial laser scanner (TLS) point cloud to estimate citrus production. During data acquisition, a fixed wing and rotatory drones, as well as a terrestrial laser scanner, were tested. After that, a pre-processing step was performed in order to generate point cloud and digital surface model. At the processing stage, a machine vision workflow was implemented to extract points corresponding to fruits from the whole tree point cloud, cluster them into fruits, and model them geometrically in a 3D space. By linking the resulting geometric properties to the fruit weight, the yield can be estimated, and the statistical distribution of fruits size can be generated. This later property, which is information required by importing countries of citrus, cannot be estimated before harvest using the conventional method. Since terrestrial laser scanner is static, data gathering using this technology can be performed over only some trees. So, integration of drone data was thought in order to estimate the yield over a whole orchard. To achieve that, features derived from drone digital surface model were linked to yield estimation by laser scanner of some trees to build a regression model that predicts the yield of a tree given its features. Several missions were carried out to collect drone and laser scanner data within citrus orchards of different varieties by testing several data acquisition parameters (fly height, images overlap, fly mission plan). The accuracy of the obtained results by the proposed methodology in comparison to the yield estimation results by the conventional method varies from 65% to 94% depending mainly on the phenological stage of the studied citrus variety during the data acquisition mission. The proposed approach demonstrates its strong potential for early estimation of citrus production and the possibility of its extension to other fruit trees.

Keywords: citrus, digital surface model, point cloud, terrestrial laser scanner, UAV, yield estimation, 3D modeling

Procedia PDF Downloads 137

Authors: T. Ahilan, V. Aswin Adityan, S. Kailash

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UAV’s are small remote operated or automated aerial surveillance systems without a human pilot aboard. UAV’s generally finds its use in military and special operation application, a recent growing trend in UAV’s finds its application in several civil and non military works such as inspection of power or pipelines. The objective of this paper is the augmentation of a UAV in order to replace the existing expensive sonar (sound navigation and ranging) based equipment amongst small scale fisherman, for whom access to sonar equipment are restricted due to limited economic resources. The surveillance equipment’s present in the UAV will relay data and GPS location onto a receiver on the fishing boat using RF signals, using which the location of the schools of fishes can be found. In addition to this, an emergency beacon system is present for rescue operations and drone recovery.

Keywords: UAV, Surveillance, RF signals, fishing, sonar, GPS, video stream, school of fish

Procedia PDF Downloads 451

Authors: Anna-Caroline Lavergne-Bril, Jean-François Colin, David Peralta, Pascale Maldivi

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Cobalt is a critical material, widely used in Li-ion batteries. Due to the planned electrification of European vehicles, cobalt needs are expending – and resources are limited. To meet the needs in cobalt to come, it is necessary to develop new efficient ways to recycle cobalt. One of the biggest sources comes from old electrical vehicles batteries (batteries sold in 2019: 500 000 tons of waste to be). A closed loop process of cobalt recycling has been developed and this presentation aims to present the selectivity mechanism of cobalt over manganese and nickel in solution. Cobalt precipitation as a ZIF material (Zeolitic Imidazolate framework) from a starting solution composed of equimolar nickel, manganese and cobalt is studied. A 2-MeIm (2-methylimidazole) linker is introduced in a multimetallic Ni, Mn, Co solution and the resulting ZIF-67 is 100% pure Co among its metallic centers. Selectivity of Co over Ni is experimentally studied and DFT modelisation calculation are conducted to understand the geometry of ligand-metal-solvent complexes in solution. Selectivity of Co over Mn is experimentally studied, and DFT modelisation calcucation are conducted to understand the link between pKa of the ligand and precipitration of Mn impurities within the final material. Those calculation open the way to other ligand being used in the same process, with more efficiency. Experimental material are synthetized from bimetallic (Ni²⁺/Co²⁺, Mn²⁺/Co²⁺, Mn²⁺/Ni²⁺) solutions. Their crystallographic structure is analysed by XRD diffraction (Brüker AXS D8 diffractometer, Cu anticathode). Morphology is studied by scanning electron microscopy, using a LEO 1530 FE-SEM microscope. The chemical analysis is performed by using ICP-OES (Agilent Technologies 700 series ICP-OES). Modelisation calculation are DFT calculation (density functional theory), using B3LYP, conducted with Orca 4.2.

Keywords: MOFs, ZIFs, recycling, closed-loop, cobalt, li-ion batteries

Procedia PDF Downloads 129

Authors: Weeradej Cheewapattananuwong, Keeree Srivichian, Godchamon Somchai, Wasin Phusanong, Nontawat Yoddamnern

Abstract:

Natural rubber used for traffic devices in Thailand has been developed and researched for several years. When compared with Dry Rubber Content (DRC), the quality of Rib Smoked Sheet (RSS) is better. However, the cost of admixtures, especially CaCO₃ and sulphur, is higher than the cost of RSS itself. In this research, Flexible Guideposts and Rubber Fender Barriers (RFB) are taken into consideration. In case of flexible guideposts, the materials used are both RSS and DRC60%, but for RFB, only RSS is used due to the controlled performance tests. The objective of flexible guideposts and RFB is to decrease a number of accidents, fatal rates, and serious injuries. Functions of both devices are to save road users and vehicles as well as to absorb impact forces from vehicles so as to decrease of serious road accidents. This leads to the mitigation methods to remedy the injury of motorists, form severity to moderate one. The solution is to find the best practice of traffic devices using natural rubber under the engineering concepts. In addition, the performances of materials, such as tensile strength and durability, are calculated for the modulus of elasticity and properties. In the laboratory, the simulation of crashes, finite element of materials, LRFD, and concrete technology methods are taken into account. After calculation, the trials' compositions of materials are mixed and tested in the laboratory. The tensile test, compressive test, and weathering or durability test are followed and based on ASTM. Furthermore, the Cycle-Repetition Test of Flexible Guideposts will be taken into consideration. The final decision is to fabricate all materials and have a real test section in the field. In RFB test, there will be 13 crash tests, 7 Pickup Truck tests, and 6 Motorcycle Tests. The test of vehicular crashes happens for the first time in Thailand, applying the trial and error methods; for example, the road crash test under the standard of NCHRP-TL3 (100 kph) is changed to the MASH 2016. This is owing to the fact that MASH 2016 is better than NCHRP in terms of speed, types, and weight of vehicles and the angle of crash. In the processes of MASH, Test Level 6 (TL-6), which is composed of 2,270 kg Pickup Truck, 100 kph, and 25 degree of crash-angle is selected. The final test for real crash will be done, and the whole system will be evaluated again in Korea. The researchers hope that the number of road accidents will decrease, and Thailand will be no more in the top tenth ranking of road accidents in the world.

Keywords: LRFD, load and resistance factor design, ASTM, american society for testing and materials, NCHRP, national cooperation highway research program, MASH, manual for assessing safety hardware

Procedia PDF Downloads 121

Authors: Rahman Ali, Muhammad Sajjad, Farkhund Iqbal, Muhammad Sadiq Hassan Zada, Mohammed Hussain

Abstract:

Emission of Carbon Dioxide (CO₂) has adversely affected the environment. One of the major sources of CO₂ emission is transportation. In the last few decades, the increase in mobility of people using vehicles has enormously increased the emission of CO₂ in the environment. To reduce CO₂ emission, sustainable transportation system is required in which smart parking is one of the important measures that need to be established. To contribute to the issue of reducing the amount of CO₂ emission, this research proposes a smart parking system. A cloud-based solution is provided to the drivers which automatically searches and recommends the most preferred parking slots. To determine preferences of the parking areas, this methodology exploits a number of unique parking features which ultimately results in the selection of a parking that leads to minimum level of CO₂ emission from the current position of the vehicle. To realize the methodology, a scenario-based implementation is considered. During the implementation, a mobile application with GPS signals, vehicles with a number of vehicle features and a list of parking areas with parking features are used by sorting, multi-level filtering, exploratory data analysis (EDA, Analytical Hierarchy Process (AHP)) and weighted sum model (WSM) to rank the parking areas and recommend the drivers with top-k most preferred parking areas. In the EDA process, “2020testcar-2020-03-03”, a freely available dataset is used to estimate CO₂ emission of a particular vehicle. To evaluate the system, results of the proposed system are compared with the conventional approach, which reveal that the proposed methodology supersedes the conventional one in reducing the emission of CO₂ into the atmosphere.

Keywords: car parking, Co2, Co2 reduction, IoT, merge sort, number plate recognition, smart car parking

Procedia PDF Downloads 141