Search results for: satellite launch vehicle

Authors: Ali Babaei

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There is a worldwide growing tendency toward construction of infrastructures with the possibility of private sector participation instead of free exploitation of public infrastructures. The construction and development of roads through private sector participation is performed by different countries because of appropriate results and benefits such as compensation of public budget deficit in road construction and maintenance and responding to traffic growth (demand). Toll is the most definite form of budget provision in road development. There are two issues in the toll rate assignment: A. costing of transport, B. Cost allocation and distribution of cost between different types of vehicles as each vehicle pay its own share. There can be different goals in toll collection and its extent is variable according to the strategy of toll collection. Costing principles in different countries are based on inclusion of the whole transport and not peculiar to the toll roads. For example, fuel tax policy functions where the road network users pay transportation cost (not just users of toll road). Whereas transportation infrastructures in Iran are free, these methods are not applicable. In Iran, different toll freeways have built by public investment and government provides participation in the road construction through encouragement of financial institutions. In this paper, the existing policies about the toll roads are studied and then the appropriate method of costing and cost allocation to different vehicles is introduced.

Keywords: toll allocation, road pricing, transportation, financial and industrial systems

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Authors: Saad Algharib, Jay Lee

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Urbanization is a complex phenomenon that occurs during the city’s development from one form to another. In other words, it is the process when the activities in the land use/land cover change from rural to urban. Since the oil exploration, Kuwait City has been growing rapidly due to its urbanization and population growth by both natural growth and inward immigration. The main objective of this study is to detect changes in urban land use/land cover and to examine the changing spatial patterns of urban growth in and around Kuwait City between 1989 and 2001. In addition, this study also evaluates the spatial patterns of the changes detected and how they can be related to the spatial configuration of the city. Recently, the use of remote sensing and geographic information systems became very useful and important tools in urban studies because of the integration of them can allow and provide the analysts and planners to detect, monitor and analyze the urban growth in a region effectively. Moreover, both planners and users can predict the trends of the growth in urban areas in the future with remotely sensed and GIS data because they can be effectively updated with required precision levels. In order to identify the new urban areas between 1989 and 2001, the study uses satellite images of the study area and remote sensing technology for classifying these images. Unsupervised classification method was applied to classify images to land use and land cover data layers. After finishing the unsupervised classification method, GIS overlay function was applied to the classified images for detecting the locations and patterns of the new urban areas that developed during the study period. GIS was also utilized to evaluate the distribution of the spatial patterns. For example, Moran’s index was applied for all data inputs to examine the urban growth distribution. Furthermore, this study assesses if the spatial patterns and process of these changes take place in a random fashion or with certain identifiable trends. During the study period, the result of this study indicates that the urban growth has occurred and expanded 10% from 32.4% in 1989 to 42.4% in 2001. Also, the results revealed that the largest increase of the urban area occurred between the major highways after the forth ring road from the center of Kuwait City. Moreover, the spatial distribution of urban growth occurred in cluster manners.

Keywords: geographic information systems, remote sensing, urbanization, urban growth

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Authors: Mohammed Al Sulaimani, Hamad Al Manhi

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With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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Authors: Magdy Torab

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Ancient Egyptians built their temples purposefully close to the River Nile to use it for transporting construction stones from far away quarries to building sites in river-boats. Most temples, therefore, have river-harbors associated with their geometric designs. The paleoriver channel remapped by using this idea, besides other geomorphological and geoarchaeological indicators/evidence located between Aswan and Luxor cities. In this sense, this paper defines the characteristics of this ancient course and its associated landforms using paleochannel morphology, paleomeandering, and ancient river dynamics during historic and prehistoric times. Both geomorphological and geoarchaeological approaches used to reconstruct the paleomorphology of the river course. It helps to investigate the ancient river morphology by using the following techniques: comparison and interpretation of multi dates satellite images and historical maps between 1943 and 2004. The results illustrated on maps using GIS (ARC GIS V.10 software) and the field data collected from the western bank of The Nile River at Luxor area and Karnak, Edfu, Esna and Kom Ombo temples. Created both current and paleogeomorphological maps depending upon the results of geoarchaeological surveying and soil analysis and dating, for surface and subsurface soil sampling by handle auger, laser diffraction analysis for 7 soil samples collected from some mounds and Malkata channel in the western bank of The Nile River near Luxor. Paleo-current directions were determined by using standard Brunton compass to use it as an indicator is evidence for the direction of flow of The Nile River during deposition of some accumulated mounds on the western part of the floodplain near Luxor city. C-14 dating was used for two samples collected from these mounds as well as geographical information system (GIS) technique for mapping. The geomorphological and geoarchaeological evidence shows that the Nile River course in Luxor area was around 4.5 km wide and contained many islands and sandbars which separated inside the river channel, now appearing as scattered mounds inside the floodplain. Upper Egypt has migrated during the historic times to the east up to five kilometers and become far away from the ancient temples, quarries, and harbors. It has also become as well as become more meandering and narrower than before.

Keywords: Nile River, ancient harbours, Luxor, paleogeomorphology, geoarchaeology

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Authors: Mitchell Browe, Oriehi Destiny Anyaiwe, Zahraddeen Gwarzo

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The Internet of Things (IoT) is a major evolution of technology and of the internet, which has the power to revolutionize the way people live. IoT has the power to change the way people interact with each other and with their homes; It has the ability to give people new ways to interact with and monitor their health; It can alter socioeconomic landscapes by providing new and efficient methods of resource management, saving time and money for both individuals and society as a whole; It even has the potential to save lives through autonomous vehicle technology and smart security measures. Unfortunately, nearly every revolution bears challenges which must be addressed to minimize harm by the new technology upon its adopters. IoT represents an internet technology revolution which has the potential to risk privacy, safety, and security of its users, should devices be developed, implemented, or utilized improperly. This article examines past and current examples of these ethical faults in an attempt to highlight the importance of consumer awareness of potential dangers of these technologies in making informed purchasing and utilization decisions, as well as to reveal how deficiencies and limitations of IoT devices should be better addressed by both companies and by regulatory bodies. Aspects such as consumer trust, corporate transparency, and misuse of individual data are all factors in the implementation of proper ethical boundaries in the IoT.

Keywords: IoT, ethical concerns, privacy, safety, security, smart devices

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Authors: Jessica C. Bannon, Cleso M. Jordao Jr., Mohammad Melebari, Carlos Leon-Velarde, Roger Johnson, Keith Warriner

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There has been an increased incidence of non-O157 Shiga Toxin Escherichia coli (STEC) with six serotypes (Top 6) being implicated in causing haemolytic uremic syndrome (HUS). Beef has been suggested to be a significant vehicle for non-O157 STEC although conclusive evidence has yet to be obtained. The following aimed to determine the prevalence of the Top 6 non-O157 STEC in beef processing using three different diagnostic platforms then characterize the recovered isolates. Hide, carcass and environmental swab samples (n = 60) were collected from a beef processing facility over a 12 month period. Enriched samples were screened using Biocontrol GDS, BAX or PALLgene molecular diagnostic tests. Presumptive non-O157 STEC positive samples were confirmed using conventional PCR and serology. STEC was detected by GDS (55% positive), BAX (85% positive), and PALLgene (93%). However, during confirmation testing only 8 of the 60 samples (13%) were found to harbour STEC. Interestingly, the presence of virulence factors in the recovered isolates was unstable and readily lost during subsequent sub-culturing. There is a low prevalence of Top 6 non-O157 STEC associated with beef although other serotypes are encountered. Yet, the instability of the virulence factors in recovered strains would question their clinical relevance.

Keywords: beef, food microbiology, shiga toxin, STEC

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Authors: Yun Chen, Qihang Liu, Catherine Ticehurst, Chandrama Sarker, Fazlul Karim, Dave Penton, Ashmita Sengupta

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The application of ICESAT-2 altimetry data in river hydrology critically depends on the accuracy of the mean water surface elevation (WSE) at a virtual station (VS) where satellite observations intersect with water. The ICESAT-2 track generates multiple VSs as it crosses the different water bodies. The difficulties are particularly pronounced in large river basins where there are many tributaries and meanders often adjacent to each other. One challenge is to split photon segments along a beam to accurately partition them to extract only the true representative water height for individual elements. As far as we can establish, there is no automated procedure to make this distinction. Earlier studies have relied on human intervention or river masks. Both approaches are unsatisfactory solutions where the number of intersections is large, and river width/extent changes over time. We describe here an automated approach called “auto-segmentation”. The accuracy of our method was assessed by comparison with river water level observations at 10 different stations on 37 different dates along the Lower Murray River, Australia. The congruence is very high and without detectable bias. In addition, we compared different outlier removal methods on the mean WSE calculation at VSs post the auto-segmentation process. All four outlier removal methods perform almost equally well with the same R2 value (0.998) and only subtle variations in RMSE (0.181–0.189m) and MAE (0.130–0.142m). Overall, the auto-segmentation method developed here is an effective and efficient approach to deriving accurate mean WSE at river VSs. It provides a much better way of facilitating the application of ICESAT-2 ATL13 altimetry to rivers compared to previously reported studies. Therefore, the findings of our study will make a significant contribution towards the retrieval of hydraulic parameters, such as water surface slope along the river, water depth at cross sections, and river channel bathymetry for calculating flow velocity and discharge from remotely sensed imagery at large spatial scales.

Keywords: lidar sensor, virtual station, cross section, mean water surface elevation, beam/track segmentation

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Authors: Zhixiang Li, Shuguang Yao, Wen Ma

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Coupler rubber buffer has been widely applied on the high-speed trains and the main function of the rubber buffer is dissipating the impact energy between vehicles. The rubber buffer consists of two groups of rubbers, which are both pre-compressed and then installed into the frame body. This paper focuses on the energy absorption characteristics of the rubber buffers particularly. Firstly, the quasi-static compression tests were carried out for 1 and 3 pairs of rubber sheets and some energy absorption responses relationship, i.e. Eabn = n×Eab1, Edissn = n×Ediss1, and Ean = Ea1, were obtained. Next, a series of quasi-static tests were performed for 1 pair of rubber sheet to investigate the energy absorption performance with different compression ratio of the rubber buffers. Then the impact tests with five impact velocities were conducted and the coupler knuckle was destroyed when the impact velocity was 10.807 km/h. The impact tests results showed that with the increase of impact velocity, the Eab, Ediss and Ea of rear buffer increased a lot, but the three responses of front buffer had not much increase. Finally, the results of impact tests and quasi-static tests were contrastively analysed and the results showed that with the increase of the stroke, the values of Eab, Ediss, and Ea were all increase. However, the increasing rates of impact tests were all larger than that of quasi-static tests. The maximum value of Ea was 68.76% in impact tests, it was a relatively high value for vehicle coupler buffer. The energy capacity of the rear buffer was determined for dynamic loading, it was 22.98 kJ.

Keywords: rubber buffer, coupler, energy absorption, impact tests

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Authors: Dihia Sidi Ahmed, Hiba Mili

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In the current context of European and global energy transition and the accelerated integration of renewable energies, the transition to electric vehicles with V2X (Vehicle-to-anything) charging options is favored to enhance the power grid and to serve as an energy supply in peak demand periods. Regarding the fast development of EV charging infrastructures, a cost-effective and efficient solution is required to meet OEM's (Original Equipment Manufacturers) needs. In this context, a single-phase 7.4 kW bidirectional on-board charger with G2V, V2G and V2L capabilities has been developed to support faster charging. The proposed architecture consists of two power stages. A Totem Pole PFC stage works as a rectifier in G2V with a unity power factor and as an inverter in V2G and V2L. The second stage is a CLLLC resonant converter selected to achieve higher energy efficiency, ZVS and ZCS and cost-effectiveness. SiC technology is used for switching devices to maximize power efficiency by lowering switching losses and to improve power density by minimizing the size of filters and passive components. Pulse frequency modulation (PWM) control is used for the Totem Pole PFC and pulse frequency modulation (PFM) control is used for the CLLC stage to control the stage gain in both energy transfer directions. In the context of validating the topology, this paper elaborates the simulation and the performance evaluation of the first power stage in the Matlab/Simulink environment.

Keywords: V2G, V2X, OBC, CLLC.

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Authors: Atef Alaaeddine Sarraj, Brendan Jackman, Frank Walsh

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Tomorrow’s car will be more automated and increasingly connected. Innovative and intuitive interfaces are essential to accompany this functional enrichment. For that, today the automotive companies are competing to offer an advanced driver assistance system (ADAS) which will be able to provide enhanced navigation, collision avoidance, intersection support and lane keeping. These vision-based functions require an accurately calibrated camera. To achieve such differentiation in ADAS requires sophisticated sensors and efficient algorithms. This paper explores the different calibration methods applicable to vehicle-mounted fish-eye cameras with arbitrary fields of view and defines the first steps towards a self-calibration method that adequately addresses ADAS requirements. In particular, we present a self-calibration method after comparing different camera calibration algorithms in the context of ADAS requirements. Our method gathers data from unknown scenes while the car is moving, estimates the camera intrinsic and extrinsic parameters and corrects the wide-angle distortion. Our solution enables continuous and real-time detection of objects, pedestrians, road markings and other cars. In contrast, other camera calibration algorithms for ADAS need pre-calibration, while the presented method calibrates the camera without prior knowledge of the scene and in real-time.

Keywords: advanced driver assistance system (ADAS), fish-eye, real-time, self-calibration

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Authors: Tayyaba Hussain, Sobia Jangsher, Saqib Ali, Saqib Ejaz

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Unmanned Aerial vehicles (UAV’s) have gained great popularity due to their remoteness, ease of deployment and high maneuverability in different applications like real-time surveillance, image capturing, weather atmospheric studies, disaster site monitoring and mapping. These applications can involve a real-time communication with the ground station. However, altitude and mobility possess a few challenges for the communication. UAV’s at high altitude usually require more transmit power. One possible solution can be with the use of multi hops (UAV’s acting as relays) and exploiting the mobility pattern of the UAV’s. In this paper, we studied a relay (UAV’s acting as relays) selection for a reliable transmission to a destination UAV. We exploit the mobility information of the UAV’s to propose a Mobility-Aware Relay Selection (MARS) algorithm with the objective of giving improved data rates. The results are compared with Non Mobility-Aware relay selection scheme and optimal values. Numerical results show that our proposed MARS algorithm gives 6% better achievable data rates for the mobile UAV’s as compared with Non MobilityAware relay selection scheme. On average a decrease of 20.2% in data rate is achieved with MARS as compared with SDP solver in Yalmip.

Keywords: mobility aware, relay selection, time division multiple acess, unmanned aerial vehicle

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Authors: Muhammad Ganda Wiratama

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XYZ company is one of the upstream chemical companies that produce chemical products such as NaOH, HCl, NaClO, VCM, EDC, and PVC for downstream companies. The products are shipped by land using trucks and sea lanes using ship mode. Especially for solid products such as flake caustic soda (F-NaOH) and PVC resin, the products are sold in loose bag packing and palletize packing (packed in pallet). The focus of this study is to increase the number of items that can be loaded in pallet packaging on the company's logistics vehicle. This is very difficult because on this packaging, the dimensions or size of the material to be loaded become larger and certainly much heavier than the loose bag packing. This factor causes the arrangement and handling of materials in the mode of transportation more difficult. In this case, it is difficult to load a different type of volume packing pallet dimension in one truck or container. By using the Cube-IQ software, it is hoped that the planning of stuffing activity material by pallet can become easier in optimizing the existing space with various possible combinations of possibilities. In addition, the output of this software can also be used as a reference for operators in the material handling include the order and orientation of materials contained in the truck or container. The more optimal contents of logistics cargo, then transportation costs can also be minimized.

Keywords: loading activity, container loading, palletize product, simulation

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Authors: Y. Alrubyli

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Unmanned Arial Vehicles (UAVs), and more specifically, quadcopters need to be stable during their flights. Altitude stability is usually achieved by using a PID controller that is built into the flight controller software. Furthermore, the PID controller has gains that need to be tuned to reach optimal altitude stabilization during the quadcopter’s flight. For that, control system engineers need to tune those gains by using extensive modeling of the environment, which might change from one environment and condition to another. As quadcopters penetrate more sectors, from the military to the consumer sectors, they have been put into complex and challenging environments more than ever before. Hence, intelligent self-stabilizing quadcopters are needed to maneuver through those complex environments and situations. Here we show that by using online reinforcement learning with minimal background knowledge, the altitude stability of the quadcopter can be achieved using a model-free approach. We found that by using background knowledge instead of letting the online reinforcement learning algorithm wander for a while to tune the PID gains, altitude stabilization can be achieved faster. In addition, using this approach will accelerate development by avoiding extensive simulations before applying the PID gains to the real-world quadcopter. Our results demonstrate the possibility of using the trial and error approach of reinforcement learning combined with background knowledge to achieve faster quadcopter altitude stabilization in different environments and conditions.

Keywords: reinforcement learning, Q-leanring, online learning, PID tuning, unmanned aerial vehicle, quadcopter

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Authors: Barenten Suciu

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An electrical generator able to harness energy from the water waves and designed as a double-cone geared motor-generator (DCGMG), is proposed and theoretically investigated. Similar to a differential gear mechanism, used in the transmission system of the auto vehicle wheels, an angular speed differential is created between the cones rolling on two concentric circular rails. Water wave acting on the floating DCGMG produces and a gear-box amplifies the speed differential to gain sufficient torque for power generation. A model that allows computation of the speed differential, torque, and power of the DCGMG is suggested. Influence of various parameters, regarding the construction of the DCGMG, as well as the contact between the double-cone and rails, on the electro-mechanical output, is emphasized. Results obtained indicate that the generated electrical power can be increased by augmenting the mass of the double-cone, the span of the rails, the apex angle of the cones, the friction between cones and rails, the amplification factor of the gear-box, and the efficiency of the motor-generator. Such findings are useful to formulate a design methodology for the proposed wave-powered generator.

Keywords: amplification of angular speed differential, circular concentric rails, double-cone, wave-powered electrical generator

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Authors: Zhiwen Yang, Jingyuan Li, Zhenkai Xie, Jian Ling, Jiguang Wang, Mengliang Li

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To reflect the effects of different emission control strategies, such as retrofitting after-treatment system and replacing with natural gas-fueled vehicles, on particle number (PN), particle mass (PM) and nitrogen oxides (NOx) emissions emitted by urban bus, a portable emission measurement system (PEMS) was employed herein to conduct real-world driving emission measurements on a diesel oxidation catalytic converter (DOC) and catalyzed diesel particulate filter (CDPF) retrofitting China IV diesel bus, a China IV diesel bus, and a China V natural gas bus. The results show that both tested diesel buses possess markedly advantages in NOx emission control when compared to the lean-burn natural gas bus equipped without any NOx after-treatment system. As to PN and PM, only the DOC+CDPF retrofitting diesel bus exhibits enormous benefits on emission control relate to the natural gas bus, especially the normal diesel bus. Meanwhile, the differences in PM and PN emissions between retrofitted and normal diesel buses generally increase with the increase in vehicle-specific power (VSP). Furthermore, the differences in PM emissions, especially those in the higher VSP ranges, are more significant than those in PN. In addition, the maximum peak PN particle size (32 nm) of the retrofitted diesel bus was significantly lower than that of the normal diesel bus (100 nm). These phenomena indicate that the CDPF retrofitting can effectively reduce diesel bus exhaust particle emissions, especially those with large particle sizes.

Keywords: CDPF, diesel, natural gas, real-world emissions

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Authors: Sara Tokhi Arab, Rozo Noguchi, Tofeal Ahamed

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Drought is a natural disaster that occurs in a region due to a lack of precipitation and high temperatures over a continuous period or in a single season as a consequence of climate change. Precipitation deficits and prolonged high temperatures mostly affect the agricultural sector, water resources, socioeconomics, and the environment. Consequently, it causes agricultural product loss, food shortage, famines, migration, and natural resources degradation in a region. Agriculture is the first sector affected by drought. Therefore, it is important to develop an agricultural drought risk and loss assessment to mitigate the drought impact in the agriculture sector. In this context, the main purpose of this study was to assess yield loss using composite drought indices in the drought-affected vineyards. In this study, the CDI was developed for the years 2016 to 2020 by comprising five indices: the vegetation condition index (VCI), temperature condition index (TCI), deviation of NDVI from the long-term mean (NDVI DEV), normalized difference moisture index (NDMI) and precipitation condition index (PCI). Moreover, the quantitative principal component analysis (PCA) approach was used to assign a weight for each input parameter, and then the weights of all the indices were combined into one composite drought index. Finally, Bayesian regularized artificial neural networks (BRANNs) were used to evaluate the yield variation in each affected vineyard. The composite drought index result indicated the moderate to severe droughts were observed across the Kabul Province during 2016 and 2018. Moreover, the results showed that there was no vineyard in extreme drought conditions. Therefore, we only considered the severe and moderated condition. According to the BRANNs results R=0.87 and R=0.94 in severe drought conditions for the years of 2016 and 2018 and the R= 0.85 and R=0.91 in moderate drought conditions for the years of 2016 and 2018, respectively. In the Kabul Province within the two years drought periods, there was a significate deficit in the vineyards. According to the findings, 2018 had the highest rate of loss almost -7 ton/ha. However, in 2016 the loss rates were about – 1.2 ton/ha. This research will support stakeholders to identify drought affect vineyards and support farmers during severe drought.

Keywords: grapes, composite drought index, yield loss, satellite remote sensing

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Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: Alexandra Monteiro, K. Bousson, Fernando J. O. Moreira, Ricardo Reis

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Fixed-wing flying vehicles are usually controlled by means of control surfaces such as elevators, ailerons, and rudders. The failure of these systems may lead to severe or even fatal crashes. These failures resulted in increased popularity for research activities on propulsion control in the last decades. The present work deals with a hybrid control architecture in which the propulsion-controlled vehicle maintains its traditional control surfaces, addressing the issue of robust lateral-directional dynamics control. The challenges stem from the parameter uncertainties in the stability and control derivatives and some unknown terms in the flight dynamics model. Two approaches are implemented and tested: linear quadratic regulation with robustness characteristics and H∞ control. The problem is centered on roll-yaw controller design with full state-feedback, which is able to deal with a standalone propulsion control mode as well as a hybrid mode combining both propulsion control and conventional control surface concepts while maintaining the original flight maneuverability characteristics. The results for both controllers emphasized very good control performances; however, the H∞ controller showed higher stabilization rates and robustness albeit with a slightly higher control magnitude than using the linear quadratic regulator.

Keywords: robust propulsion control, h-infinity control, lateral-directional flight dynamics, parameter uncertainties

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Authors: Rudolph Carl Barrientos, Juwaln Diego Descallar, Rainer James Palmiano

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Household Appliance Scheduling Systems (HASS) coupled with a Time-of-Use (TOU) pricing scheme, a form of Demand Side Management (DSM), is not widely utilized in the Philippines’ residential electricity sector. This paper’s goal is to encourage distribution utilities (DUs) to adopt HASS and TOU by analyzing the effect of household schedulers on the electricity price and load profile in a residential environment. To establish this, a city based on an implemented survey is generated using Monte Carlo Analysis (MCA). Then, a Binary Particle Swarm Optimization (BPSO) algorithm-based HASS is developed considering user satisfaction, electricity budget, appliance prioritization, energy storage systems, solar power, and electric vehicles. The simulations were assessed under varying levels of user compliance. Results showed that the average electricity cost, peak demand, and peak-to-average ratio (PAR) of the city load profile were all reduced. Therefore, the deployment of the HASS and TOU pricing scheme is beneficial for both stakeholders.

Keywords: appliance scheduling, DSM, TOU, BPSO, city-wide simulation, electric vehicle, appliance prioritization, energy storage system, solar power

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Authors: Zehai Yu, Hui Zhu, Linglong Lin, Huawei Liang, Biao Yu, Weixin Huang

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With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm.

Keywords: curve fitting, lane-level road map, line recognition, multi-thresholding, two-stage clustering

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Authors: Aneesh Babu, S. P. Anusha

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A dynamic signal control system combines traditional traffic lights with an array of sensors to intelligently control vehicle and pedestrian traffic. The present study focus on evaluating the performance of dynamic signal control systems for mixed traffic conditions. Data collected from four different approaches to a typical four-legged signalized intersection at Trivandrum city in the Kerala state of India is used for the study. Performance of three other dynamic signal control methods, namely (i) Non-sequential method (ii) Webster design for consecutive signal cycle using flow as input, and (iii) dynamic signal control using RFID delay as input, were evaluated. The evaluation of the dynamic signal control systems was carried out using a calibrated VISSIM microsimulation model. Python programming was used to integrate the dynamic signal control algorithm through the COM interface in VISSIM. The intersection delay obtained from different dynamic signal control methods was compared with the delay obtained from fixed signal control. Based on the study results, it was observed that the intersection delay was reduced significantly by using dynamic signal control methods. The dynamic signal control method using delay from RFID sensors resulted in a higher percentage reduction in delay and hence is a suitable choice for implementation under mixed traffic conditions. The developed dynamic signal control strategies can be implemented in ITS applications under mixed traffic conditions.

Keywords: dynamic signal control, intersection delay, mixed traffic conditions, RFID sensors

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Authors: Bhavesh Dadhich, Fenil Bamnoliya, Akshita Swaminathan

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This project aims to design a system to generate energy from flowing wind due to the motion of a vehicle on the road or from the flow of wind in compact areas to utilize the wasteful energy into a useful one. It is envisaged through a design and aerodynamic performance improvement of a Savonius vertical axis wind turbine rotor and used in an integrated system with a Triboelectric Nanogenerator (TENG) that can generate a good amount of electrical energy. Aerodynamic calculations are performed numerically using Computational Fluid Dynamics software, and TENG's performance is evaluated analytically. The Turbine's coefficient of power is validated with published results for an inlet velocity of 7 m/s with a Tip Speed Ratio of 0.75 and found to reasonably agree with that of experiment results. The baseline design is modified with a new blade arc angle and rotor position angle based on the recommended parameter ranges suggested by previous researchers. Simulations have been performed for different T.S.R. values ranging from 0.25 to 1.5 with an interval of 0.25 with two applicable free stream velocities of 5 m/s and 7m/s. Finally, the newly designed VAWT CFD performance results are used as input for the analytical performance prediction of the triboelectric nanogenerator. The results show that this approach could be feasible and useful for small power source applications.

Keywords: savonius turbine, power, overlap ratio, tip speed ratio, TENG

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Authors: Alie Wube Dametew, Frank Ebinger

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This study investigated the roles of technological innovation on basic metal industries and then developed technological innovation framework for enhancing sustainable competitive advantage in the basic metal industries. The previous research work indicates that technological innovation has critical impact in promoting local industries to improve their performance and achieve sustainable competitive environments. The filed observation, questioner and expert interview result from basic metal industries indicate that the technological capability of local industries to invention, adoption, modification, improving and use a given innovative technology is very poor. As the result, this poor technological innovation was occurred due to improper innovation and technology transfer framework, non-collaborative operating environment between foreign and local industries, very weak national technology policies, problems research and innovation centers, the common miss points on basic metal industry innovation systems were investigated in this study. One of the conclusions of the article is that, through using the developed technological innovation framework in this study, basic metal industries improve innovation process and support an innovative culture for sector capabilities and achieve sustainable competitive advantage.

Keywords: technological innovation, competitive advantage, sustainable, basic metal industry, conceptual model, sustainability, supply chain integration

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Authors: Enoch F. Sam, Kris Brijs, Stijn Daniels, Tom Brijs, Geert Wets

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Notwithstanding the growing body of literature that recognises the importance of personal safety to public transport (PT) users, it remains unclear what PT users consider regarding their safety. In this study, we explore the criteria PT users in Ghana use to assess bus safety. This knowledge will afford a better understanding of PT users’ risk perceptions and assessments which may contribute to theoretical models of PT risk perceptions. We utilised phenomenological research methodology, with data drawn from 61 purposively sampled participants. Data collection (through focus group discussions and in-depth interviews) and analyses were done concurrently to the point of saturation. Our inductive data coding and analyses through the constant comparison and content analytic techniques resulted in 4 code categories (conceptual dimensions), 27 codes (safety items/criteria), and 100 quotations (data segments). Of the number of safety criteria participants use to assess bus safety, vehicle condition, driver’s marital status, and transport operator’s safety records were the most considered. With each criterion, participants rightly demonstrated its respective relevance to bus safety. These findings imply that investment in and maintenance of safer vehicles, and responsible and safety-conscious drivers, and prioritization of passengers’ safety are key-targets for public bus/minibus operators in Ghana.

Keywords: safety evaluations, public bus/minibus, passengers, phenomenology, Ghana

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In robotics literature, the simultaneous localization and mapping (SLAM) is commonly associated with a priori-posteriori problem. The autonomous vehicle needs a neutral map to spontaneously track its local position, i.e., “localization” while at the same time a precise path estimation of the environment state is required for effective route planning and obstacle avoidance. On the other hand, the environmental noise factors can significantly intensify the inherent uncertainties in using odometry information and measurements obtained from the robot’s exteroceptive sensor which in return directly affect the overall performance of the corresponding SLAM. Therefore, the current work is primarily dedicated to provide a diagnostic analysis of six SLAM algorithms including FastSLAM, L-SLAM, GraphSLAM, Grid SLAM and DP-SLAM. A SLAM simulated environment consisting of two sets of landmark locations and robot waypoints was set based on modified EKF and UKF in MATLAB using two separate maps for indoor and outdoor route planning subject to natural and artificial obstacles. The simulation results are expected to provide an unbiased platform to compare the estimation performances of the five SLAM models as well as on the reliability of each SLAM model for indoor and outdoor applications.

Keywords: route planning, obstacle, estimation performance, FastSLAM, L-SLAM, GraphSLAM, Grid SLAM, DP-SLAM

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Authors: Bruce G. Wilson

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The collection of municipal solid waste at the curbside is a complex operation that is repeated daily under varying circumstances around the world. There have been several attempts to develop Monte Carlo simulation models of the waste collection process dating back almost 50 years. Despite this long history, the use of simulation modeling as a planning or optimization tool for waste collection is still extremely limited in practice. Historically, simulation modeling of waste collection systems has been hampered by the limitations of computer hardware and software and by the availability of representative input data. This paper outlines the development of a Monte Carlo simulation model that overcomes many of the limitations contained in previous models. The model uses a general purpose simulation software program that is easily capable of modeling an entire waste collection network. The model treats the stops on a waste collection route as a queue of work to be processed by a collection vehicle (or server). Input data can be collected from a variety of sources including municipal geographic information systems, global positioning system recorders on collection vehicles, and weigh scales at transfer stations or treatment facilities. The result is a flexible model that is sufficiently robust that it can model the collection activities in a large municipality, while providing the flexibility to adapt to changing conditions on the collection route.

Keywords: modeling, queues, residential waste collection, Monte Carlo simulation

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Authors: Bruna P. De Souza, Ricardo C. De Almeida

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In some cities in the State of Parana – Brazil and in other countries atmospheric bromeliads (Tillandsia spp - Bromeliaceae) are considered weeds in trees, electric power lines, satellite dishes and other artificial supports. In this study, a numerical model was developed to simulate the seed dispersal of the Tillandsia recurvata species by wind with the objective of evaluating seeds displacement in the city of Ponta Grossa – PR, Brazil, since it is considered that the region is already infested. The model simulates the dispersal of each individual seed integrating parameters from the atmospheric boundary layer (ABL) and the local wind, simulated by the Weather Research Forecasting (WRF) mesoscale atmospheric model for the 2012 to 2015 period. The dispersal model also incorporates the approximate number of bromeliads and source height data collected from most infested electric power lines. The seeds terminal velocity, which is an important input data but was not available in the literature, was measured by an experiment with fifty-one seeds of Tillandsia recurvata. Wind is the main dispersal agent acting on plumed seeds whereas atmospheric turbulence is a determinant factor to transport the seeds to distances beyond 200 meters as well as to introduce random variability in the seed dispersal process. Such variability was added to the model through the application of an Inverse Fast Fourier Transform to wind velocity components energy spectra based on boundary-layer meteorology theory and estimated from micrometeorological parameters produced by the WRF model. Seasonal and annual wind means were obtained from the surface wind data simulated by WRF for Ponta Grossa. The mean wind direction is assumed to be the most probable direction of bromeliad seed trajectory. Moreover, the atmospheric turbulence effect and dispersal distances were analyzed in order to identify likely regions of infestation around Ponta Grossa urban area. It is important to mention that this model could be applied to any species and local as long as seed’s biological data and meteorological data for the region of interest are available.

Keywords: atmospheric turbulence, bromeliad, numerical model, seed dispersal, terminal velocity, wind

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Authors: Arpita Saha, Satish Chandra, Indrajit Ghosh

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Delay implicates the time loss of a traveler while crossing an intersection. Efficiency of traffic operation at signalized intersections is assessed in terms of delay caused to an individual vehicle. Highway Capacity Manual (HCM) method and Webster’s method are the most widely used in India for delay estimation purpose. However, in India, traffic is highly heterogeneous in nature with extremely poor lane discipline. Therefore, to explore best delay estimation technique for Indian condition, a comparison was made. In this study, seven signalized intersections from three different cities where chosen. Data was collected for both during morning and evening peak hours. Only under saturated cycles were considered for this study. Delay was estimated based on the field data. With the help of Simpson’s 1/3 rd rule, delay of under saturated cycles was estimated by measuring the area under the curve of queue length and cycle time. Moreover, the field observed delay was compared with the delay estimated using HCM, Webster, Probabilistic, Taylor’s expansion and Regression methods. The drawbacks of the existing delay estimation methods to be use in Indian heterogeneous traffic conditions were figured out, and best method was proposed. It was observed that direct estimation of delay using field measured data is more accurate than existing conventional and modified methods.

Keywords: delay estimation technique, field delay, heterogeneous traffic, signalised intersection

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Authors: Boumaraf Malak

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The development of intelligent transportation systems (ITS) and artificial intelligence (AI) are spurring us to pave the way for the widespread adoption of autonomous vehicles (AVs). This is open again opportunities for smart roads, smart traffic safety, and mobility comfort. A highly intelligent decision-making system is essential for autonomous driving around dense, dynamic objects. It must be able to handle complex road geometry and topology, as well as complex multiagent interactions, and closely follow higher-level commands such as routing information. Autonomous vehicles have become a very hot research topic in recent years due to their significant ability to reduce traffic accidents and personal injuries. Using new artificial intelligence-based technologies handles important functions in scene understanding, motion planning, decision making, vehicle control, social behavior, and communication for AV. This paper focuses only on deep reinforcement learning-based methods; it does not include traditional (flat) planar techniques, which have been the subject of extensive research in the past because reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in high dimensional environments. The DRL algorithm used so far found solutions to the four main problems of autonomous driving; in our paper, we highlight the challenges and point to possible future research directions.

Keywords: deep reinforcement learning, autonomous driving, deep deterministic policy gradient, deep Q-learning

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Authors: Ishani Das, Avinash Padhi, Sitabja Mukherjee, Santosh Kar, Avinash Sonawane

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Activation of cell mediated and humoral immune responses to Mycobacterium tuberculosis (Mtb) are critical for protection. Herein, we show that mice immunized with Mtb lipid bound chitosan nanoparticles(NPs) induce secretion of prominent Th1 and Th2 cytokines in lymph node and spleen cells, and also induced significantly higher levels of IgG, IgG1, IgG2 and IgM in comparison to control mice measured by ELISA. Furthermore, significantly enhanced γδ-T cell activation was observed in lymph node cells isolated from mice immunized with Mtb lipid coated chitosan-NPs as compared to mice immunized with chitosan-NPs alone or Mtb lipid liposomes through flow cytometric analysis. Also, it was observed that in comparison to CD8+ cells, significantly higher CD4+ cells were present in both the lymph node and spleen cells isolated from mice immunized with Mtb lipid coated chitosan NP. In conclusion, this study represents a promising new strategy for efficient delivery of Mtb lipids using chitosan NPs to trigger enhanced cell mediated and antibody response against Mtb lipids.

Keywords: antibody response, chitosan nanoparticles, cytokines, mycobacterium tuberculosis lipids

Procedia PDF Downloads 258